cola Report for recount2:TCGA_cervix

Date: 2019-12-26 01:26:58 CET, cola version: 1.3.2

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Summary

All available functions which can be applied to this res_list object:

res_list
#> A 'ConsensusPartitionList' object with 24 methods.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows are extracted by 'SD, CV, MAD, ATC' methods.
#>   Subgroups are detected by 'hclust, kmeans, skmeans, pam, mclust, NMF' method.
#>   Number of partitions are tried for k = 2, 3, 4, 5, 6.
#>   Performed in total 30000 partitions by row resampling.
#> 
#> Following methods can be applied to this 'ConsensusPartitionList' object:
#>  [1] "cola_report"           "collect_classes"       "collect_plots"         "collect_stats"        
#>  [5] "colnames"              "functional_enrichment" "get_anno_col"          "get_anno"             
#>  [9] "get_classes"           "get_matrix"            "get_membership"        "get_stats"            
#> [13] "is_best_k"             "is_stable_k"           "ncol"                  "nrow"                 
#> [17] "rownames"              "show"                  "suggest_best_k"        "test_to_known_factors"
#> [21] "top_rows_heatmap"      "top_rows_overlap"     
#> 
#> You can get result for a single method by, e.g. object["SD", "hclust"] or object["SD:hclust"]
#> or a subset of methods by object[c("SD", "CV")], c("hclust", "kmeans")]

The call of run_all_consensus_partition_methods() was:

#> run_all_consensus_partition_methods(data = mat, mc.cores = 4)

Dimension of the input matrix:

mat = get_matrix(res_list)
dim(mat)
#> [1] 17469   309

Density distribution

The density distribution for each sample is visualized as in one column in the following heatmap. The clustering is based on the distance which is the Kolmogorov-Smirnov statistic between two distributions.

library(ComplexHeatmap)
densityHeatmap(mat, ylab = "value", cluster_columns = TRUE, show_column_names = FALSE,
    mc.cores = 4)

plot of chunk density-heatmap

Suggest the best k

Folowing table shows the best k (number of partitions) for each combination of top-value methods and partition methods. Clicking on the method name in the table goes to the section for a single combination of methods.

The cola vignette explains the definition of the metrics used for determining the best number of partitions.

suggest_best_k(res_list)
The best k 1-PAC Mean silhouette Concordance Optional k
SD:kmeans 2 1.000 0.990 0.996 **
SD:pam 2 1.000 0.959 0.984 **
SD:mclust 2 1.000 0.989 0.995 **
MAD:kmeans 2 1.000 0.990 0.996 **
MAD:skmeans 2 1.000 0.971 0.988 **
MAD:pam 2 1.000 0.983 0.993 **
MAD:mclust 2 1.000 0.975 0.991 **
ATC:mclust 2 1.000 0.985 0.994 **
CV:NMF 2 1.000 0.963 0.985 **
CV:kmeans 2 0.986 0.957 0.982 **
ATC:kmeans 3 0.984 0.958 0.983 **
CV:pam 2 0.980 0.941 0.978 **
CV:mclust 2 0.979 0.949 0.979 **
ATC:skmeans 4 0.963 0.938 0.974 ** 2,3
ATC:NMF 2 0.946 0.943 0.976 *
MAD:NMF 2 0.946 0.948 0.979 *
SD:skmeans 2 0.933 0.948 0.978 *
SD:NMF 5 0.923 0.883 0.948 * 2
CV:skmeans 2 0.921 0.950 0.978 *
SD:hclust 3 0.649 0.811 0.897
ATC:pam 2 0.490 0.888 0.898
ATC:hclust 3 0.291 0.531 0.749
MAD:hclust 3 0.158 0.653 0.778
CV:hclust NA NA NA NA

**: 1-PAC > 0.95, *: 1-PAC > 0.9

CDF of consensus matrices

Cumulative distribution function curves of consensus matrix for all methods.

collect_plots(res_list, fun = plot_ecdf)

plot of chunk collect-plots

Consensus heatmap

Consensus heatmaps for all methods. (What is a consensus heatmap?)

collect_plots(res_list, k = 2, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-1

collect_plots(res_list, k = 3, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-2

collect_plots(res_list, k = 4, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-3

collect_plots(res_list, k = 5, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-4

collect_plots(res_list, k = 6, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-5

Membership heatmap

Membership heatmaps for all methods. (What is a membership heatmap?)

collect_plots(res_list, k = 2, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-1

collect_plots(res_list, k = 3, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-2

collect_plots(res_list, k = 4, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-3

collect_plots(res_list, k = 5, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-4

collect_plots(res_list, k = 6, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-5

Signature heatmap

Signature heatmaps for all methods. (What is a signature heatmap?)

Note in following heatmaps, rows are scaled.

collect_plots(res_list, k = 2, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-1

collect_plots(res_list, k = 3, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-2

collect_plots(res_list, k = 4, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-3

collect_plots(res_list, k = 5, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-4

collect_plots(res_list, k = 6, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-5

Statistics table

The statistics used for measuring the stability of consensus partitioning. (How are they defined?)

get_stats(res_list, k = 2)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      2 0.986           0.956       0.982          0.426 0.586   0.586
#> CV:NMF      2 1.000           0.963       0.985          0.423 0.575   0.575
#> MAD:NMF     2 0.946           0.948       0.979          0.459 0.542   0.542
#> ATC:NMF     2 0.946           0.943       0.976          0.442 0.565   0.565
#> SD:skmeans  2 0.933           0.948       0.978          0.482 0.515   0.515
#> CV:skmeans  2 0.921           0.950       0.978          0.450 0.542   0.542
#> MAD:skmeans 2 1.000           0.971       0.988          0.490 0.511   0.511
#> ATC:skmeans 2 1.000           0.988       0.995          0.501 0.499   0.499
#> SD:mclust   2 1.000           0.989       0.995          0.380 0.621   0.621
#> CV:mclust   2 0.979           0.949       0.979          0.421 0.583   0.583
#> MAD:mclust  2 1.000           0.975       0.991          0.383 0.625   0.625
#> ATC:mclust  2 1.000           0.985       0.994          0.381 0.621   0.621
#> SD:kmeans   2 1.000           0.990       0.996          0.393 0.609   0.609
#> CV:kmeans   2 0.986           0.957       0.982          0.381 0.612   0.612
#> MAD:kmeans  2 1.000           0.990       0.996          0.397 0.603   0.603
#> ATC:kmeans  2 0.734           0.924       0.962          0.467 0.526   0.526
#> SD:pam      2 1.000           0.959       0.984          0.349 0.648   0.648
#> CV:pam      2 0.980           0.941       0.978          0.252 0.755   0.755
#> MAD:pam     2 1.000           0.983       0.993          0.374 0.628   0.628
#> ATC:pam     2 0.490           0.888       0.898          0.442 0.544   0.544
#> SD:hclust   2 0.541           0.818       0.891          0.306 0.670   0.670
#> CV:hclust   2 0.579           0.818       0.889          0.254 0.663   0.663
#> MAD:hclust  2 0.306           0.590       0.838          0.289 0.760   0.760
#> ATC:hclust  2 0.407           0.742       0.867          0.364 0.667   0.667
get_stats(res_list, k = 3)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      3 0.868           0.888       0.953          0.502 0.734   0.562
#> CV:NMF      3 0.560           0.661       0.857          0.470 0.786   0.639
#> MAD:NMF     3 0.827           0.861       0.942          0.392 0.767   0.590
#> ATC:NMF     3 0.668           0.785       0.899          0.138 0.889   0.806
#> SD:skmeans  3 0.833           0.906       0.956          0.337 0.770   0.583
#> CV:skmeans  3 0.661           0.681       0.837          0.451 0.721   0.525
#> MAD:skmeans 3 0.742           0.804       0.905          0.330 0.765   0.573
#> ATC:skmeans 3 0.968           0.929       0.973          0.323 0.741   0.527
#> SD:mclust   3 0.700           0.873       0.922          0.670 0.721   0.555
#> CV:mclust   3 0.590           0.569       0.815          0.497 0.800   0.661
#> MAD:mclust  3 0.817           0.858       0.942          0.654 0.736   0.580
#> ATC:mclust  3 0.583           0.737       0.867          0.492 0.847   0.754
#> SD:kmeans   3 0.594           0.804       0.886          0.557 0.755   0.602
#> CV:kmeans   3 0.453           0.477       0.768          0.539 0.845   0.749
#> MAD:kmeans  3 0.602           0.750       0.875          0.580 0.750   0.592
#> ATC:kmeans  3 0.984           0.958       0.983          0.278 0.627   0.424
#> SD:pam      3 0.844           0.860       0.938          0.643 0.787   0.672
#> CV:pam      3 0.551           0.759       0.885          1.237 0.670   0.567
#> MAD:pam     3 0.674           0.669       0.854          0.631 0.797   0.676
#> ATC:pam     3 0.690           0.857       0.920          0.349 0.824   0.681
#> SD:hclust   3 0.649           0.811       0.897          0.411 0.925   0.889
#> CV:hclust   3 0.795           0.857       0.931          0.628 0.900   0.851
#> MAD:hclust  3 0.158           0.653       0.778          0.635 0.793   0.738
#> ATC:hclust  3 0.291           0.531       0.749          0.579 0.617   0.467
get_stats(res_list, k = 4)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      4 0.777           0.788       0.912         0.0907 0.885   0.703
#> CV:NMF      4 0.689           0.727       0.871         0.1522 0.817   0.581
#> MAD:NMF     4 0.777           0.813       0.912         0.0855 0.886   0.712
#> ATC:NMF     4 0.520           0.726       0.840         0.3757 0.750   0.507
#> SD:skmeans  4 0.846           0.851       0.934         0.1596 0.829   0.562
#> CV:skmeans  4 0.681           0.627       0.842         0.1368 0.837   0.578
#> MAD:skmeans 4 0.838           0.821       0.925         0.1473 0.822   0.546
#> ATC:skmeans 4 0.963           0.938       0.974         0.1280 0.809   0.511
#> SD:mclust   4 0.580           0.753       0.812         0.0599 0.967   0.911
#> CV:mclust   4 0.465           0.518       0.718         0.0905 0.748   0.465
#> MAD:mclust  4 0.671           0.700       0.792         0.1343 0.851   0.614
#> ATC:mclust  4 0.628           0.689       0.838         0.0804 0.859   0.722
#> SD:kmeans   4 0.611           0.690       0.773         0.1638 0.779   0.491
#> CV:kmeans   4 0.508           0.547       0.731         0.1683 0.795   0.595
#> MAD:kmeans  4 0.617           0.691       0.780         0.1441 0.800   0.519
#> ATC:kmeans  4 0.735           0.858       0.902         0.1988 0.768   0.484
#> SD:pam      4 0.625           0.339       0.674         0.1834 0.833   0.638
#> CV:pam      4 0.452           0.621       0.799         0.2114 0.808   0.597
#> MAD:pam     4 0.749           0.717       0.862         0.1611 0.807   0.570
#> ATC:pam     4 0.641           0.677       0.865         0.1741 0.815   0.570
#> SD:hclust   4 0.398           0.485       0.748         0.3227 0.967   0.946
#> CV:hclust   4 0.833           0.809       0.897         0.0428 0.986   0.976
#> MAD:hclust  4 0.359           0.500       0.744         0.2486 0.835   0.733
#> ATC:hclust  4 0.345           0.478       0.693         0.1365 0.772   0.522
get_stats(res_list, k = 5)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      5 0.923           0.883       0.948         0.0818 0.873   0.621
#> CV:NMF      5 0.715           0.740       0.833         0.0917 0.868   0.590
#> MAD:NMF     5 0.851           0.839       0.898         0.0860 0.856   0.594
#> ATC:NMF     5 0.676           0.729       0.856         0.1038 0.856   0.574
#> SD:skmeans  5 0.807           0.781       0.883         0.0611 0.906   0.660
#> CV:skmeans  5 0.688           0.713       0.831         0.0681 0.849   0.506
#> MAD:skmeans 5 0.827           0.784       0.896         0.0614 0.901   0.646
#> ATC:skmeans 5 0.892           0.877       0.930         0.0656 0.892   0.615
#> SD:mclust   5 0.561           0.565       0.729         0.0862 0.886   0.693
#> CV:mclust   5 0.500           0.338       0.634         0.0888 0.746   0.372
#> MAD:mclust  5 0.628           0.650       0.751         0.0370 0.907   0.678
#> ATC:mclust  5 0.694           0.785       0.868         0.1170 0.910   0.783
#> SD:kmeans   5 0.684           0.737       0.817         0.0900 0.931   0.757
#> CV:kmeans   5 0.607           0.667       0.801         0.1022 0.821   0.519
#> MAD:kmeans  5 0.729           0.730       0.796         0.0832 0.908   0.684
#> ATC:kmeans  5 0.812           0.831       0.902         0.0691 0.947   0.812
#> SD:pam      5 0.699           0.718       0.857         0.0824 0.754   0.397
#> CV:pam      5 0.498           0.560       0.738         0.1084 0.817   0.500
#> MAD:pam     5 0.667           0.603       0.787         0.0774 0.948   0.822
#> ATC:pam     5 0.688           0.707       0.840         0.1039 0.852   0.554
#> SD:hclust   5 0.382           0.413       0.646         0.1838 0.737   0.551
#> CV:hclust   5 0.683           0.778       0.861         0.0963 0.989   0.982
#> MAD:hclust  5 0.397           0.500       0.701         0.1585 0.831   0.653
#> ATC:hclust  5 0.452           0.473       0.674         0.0834 0.759   0.446
get_stats(res_list, k = 6)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      6 0.807           0.735       0.880         0.0566 0.931   0.737
#> CV:NMF      6 0.729           0.695       0.814         0.0399 0.910   0.636
#> MAD:NMF     6 0.827           0.724       0.882         0.0527 0.949   0.802
#> ATC:NMF     6 0.659           0.584       0.785         0.0518 0.927   0.712
#> SD:skmeans  6 0.774           0.760       0.858         0.0445 0.938   0.713
#> CV:skmeans  6 0.684           0.626       0.793         0.0431 0.911   0.617
#> MAD:skmeans 6 0.813           0.759       0.874         0.0461 0.933   0.694
#> ATC:skmeans 6 0.827           0.805       0.880         0.0351 0.952   0.772
#> SD:mclust   6 0.569           0.461       0.696         0.0577 0.928   0.755
#> CV:mclust   6 0.558           0.413       0.692         0.0584 0.804   0.390
#> MAD:mclust  6 0.609           0.495       0.702         0.0492 0.951   0.807
#> ATC:mclust  6 0.647           0.638       0.807         0.0741 0.924   0.781
#> SD:kmeans   6 0.681           0.601       0.761         0.0492 0.943   0.762
#> CV:kmeans   6 0.617           0.513       0.720         0.0569 0.894   0.603
#> MAD:kmeans  6 0.716           0.670       0.794         0.0505 0.933   0.723
#> ATC:kmeans  6 0.746           0.591       0.789         0.0471 0.984   0.936
#> SD:pam      6 0.674           0.657       0.793         0.1025 0.911   0.663
#> CV:pam      6 0.546           0.602       0.765         0.0357 0.954   0.805
#> MAD:pam     6 0.697           0.619       0.783         0.0699 0.877   0.556
#> ATC:pam     6 0.697           0.642       0.804         0.0274 0.972   0.877
#> SD:hclust   6 0.420           0.422       0.619         0.0986 0.752   0.431
#> CV:hclust   6 0.456           0.677       0.788         0.1223 0.992   0.985
#> MAD:hclust  6 0.454           0.478       0.659         0.0894 0.945   0.846
#> ATC:hclust  6 0.522           0.452       0.674         0.0455 0.882   0.684

Following heatmap plots the partition for each combination of methods and the lightness correspond to the silhouette scores for samples in each method. On top the consensus subgroup is inferred from all methods by taking the mean silhouette scores as weight.

collect_stats(res_list, k = 2)

plot of chunk tab-collect-stats-from-consensus-partition-list-1

collect_stats(res_list, k = 3)

plot of chunk tab-collect-stats-from-consensus-partition-list-2

collect_stats(res_list, k = 4)

plot of chunk tab-collect-stats-from-consensus-partition-list-3

collect_stats(res_list, k = 5)

plot of chunk tab-collect-stats-from-consensus-partition-list-4

collect_stats(res_list, k = 6)

plot of chunk tab-collect-stats-from-consensus-partition-list-5

Partition from all methods

Collect partitions from all methods:

collect_classes(res_list, k = 2)

plot of chunk tab-collect-classes-from-consensus-partition-list-1

collect_classes(res_list, k = 3)

plot of chunk tab-collect-classes-from-consensus-partition-list-2

collect_classes(res_list, k = 4)

plot of chunk tab-collect-classes-from-consensus-partition-list-3

collect_classes(res_list, k = 5)

plot of chunk tab-collect-classes-from-consensus-partition-list-4

collect_classes(res_list, k = 6)

plot of chunk tab-collect-classes-from-consensus-partition-list-5

Top rows overlap

Overlap of top rows from different top-row methods:

top_rows_overlap(res_list, top_n = 1000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-1

top_rows_overlap(res_list, top_n = 2000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-2

top_rows_overlap(res_list, top_n = 3000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-3

top_rows_overlap(res_list, top_n = 4000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-4

top_rows_overlap(res_list, top_n = 5000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-5

Also visualize the correspondance of rankings between different top-row methods:

top_rows_overlap(res_list, top_n = 1000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-1

top_rows_overlap(res_list, top_n = 2000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-2

top_rows_overlap(res_list, top_n = 3000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-3

top_rows_overlap(res_list, top_n = 4000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-4

top_rows_overlap(res_list, top_n = 5000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-5

Heatmaps of the top rows:

top_rows_heatmap(res_list, top_n = 1000)

plot of chunk tab-top-rows-heatmap-1

top_rows_heatmap(res_list, top_n = 2000)

plot of chunk tab-top-rows-heatmap-2

top_rows_heatmap(res_list, top_n = 3000)

plot of chunk tab-top-rows-heatmap-3

top_rows_heatmap(res_list, top_n = 4000)

plot of chunk tab-top-rows-heatmap-4

top_rows_heatmap(res_list, top_n = 5000)

plot of chunk tab-top-rows-heatmap-5

Results for each method


SD:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "hclust"]
# you can also extract it by
# res = res_list["SD:hclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.541           0.818       0.891         0.3058 0.670   0.670
#> 3 3 0.649           0.811       0.897         0.4107 0.925   0.889
#> 4 4 0.398           0.485       0.748         0.3227 0.967   0.946
#> 5 5 0.382           0.413       0.646         0.1838 0.737   0.551
#> 6 6 0.420           0.422       0.619         0.0986 0.752   0.431

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.3733     0.8844 0.928 0.072
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.2043     0.9131 0.968 0.032
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.4562     0.8693 0.904 0.096
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0672     0.9164 0.992 0.008
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0376     0.9164 0.996 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2236     0.9113 0.964 0.036
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.8661     0.4836 0.712 0.288
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.7528     0.8751 0.216 0.784
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4161     0.8661 0.916 0.084
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0376     0.9165 0.996 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0376     0.9164 0.996 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0376     0.9165 0.996 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.2948     0.9016 0.948 0.052
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.9393     0.7517 0.356 0.644
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3584     0.8965 0.932 0.068
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.2778     0.9046 0.952 0.048
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1843     0.9139 0.972 0.028
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0672     0.9170 0.992 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0376     0.9147 0.996 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.1414     0.9148 0.980 0.020
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.7528     0.8751 0.216 0.784
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0938     0.9167 0.988 0.012
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9155 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1184     0.9175 0.984 0.016
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.2043     0.9131 0.968 0.032
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2236     0.9125 0.964 0.036
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.2778     0.9046 0.952 0.048
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.1414     0.9167 0.980 0.020
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.7528     0.8751 0.216 0.784
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.8207     0.8592 0.256 0.744
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0376     0.9164 0.996 0.004
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3879     0.8758 0.924 0.076
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0376     0.9165 0.996 0.004
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9155 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.9491     0.2004 0.632 0.368
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.4815     0.8569 0.896 0.104
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.8555     0.5322 0.720 0.280
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.7528     0.8751 0.216 0.784
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0938     0.9167 0.988 0.012
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9155 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.9460     0.7421 0.364 0.636
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.1633     0.9145 0.976 0.024
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.2778     0.9046 0.952 0.048
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0376     0.9165 0.996 0.004
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9155 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2043     0.9145 0.968 0.032
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2778     0.8994 0.952 0.048
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.7528     0.8751 0.216 0.784
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.1633     0.9145 0.976 0.024
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     1  0.9970    -0.2549 0.532 0.468
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0938     0.9172 0.988 0.012
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.8386     0.8329 0.268 0.732
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.1633     0.9145 0.976 0.024
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2948     0.9047 0.948 0.052
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0938     0.9167 0.988 0.012
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.4161     0.8779 0.916 0.084
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.8499     0.5817 0.724 0.276
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.4022     0.8711 0.920 0.080
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.7528     0.8702 0.216 0.784
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.9155 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.1184     0.9174 0.984 0.016
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.1184     0.9179 0.984 0.016
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.2236     0.9116 0.964 0.036
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0672     0.9170 0.992 0.008
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.7528     0.8751 0.216 0.784
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.8081     0.6456 0.752 0.248
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0938     0.9172 0.988 0.012
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0672     0.9168 0.992 0.008
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.7602     0.6902 0.780 0.220
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.9393     0.7517 0.356 0.644
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0938     0.9171 0.988 0.012
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000     0.9155 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.1633     0.9152 0.976 0.024
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0376     0.9165 0.996 0.004
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0376     0.9165 0.996 0.004
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.9155 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0938     0.9180 0.988 0.012
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.7528     0.8751 0.216 0.784
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.7528     0.6961 0.784 0.216
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     1  0.9909    -0.1142 0.556 0.444
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.1843     0.9153 0.972 0.028
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.6801     0.7394 0.180 0.820
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0938     0.9171 0.988 0.012
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.9155 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.9155 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.1414     0.9166 0.980 0.020
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000     0.9155 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.9323     0.7633 0.348 0.652
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.7602     0.8748 0.220 0.780
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.3274     0.9008 0.940 0.060
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.2423     0.9103 0.960 0.040
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0938     0.9171 0.988 0.012
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.9983     0.4509 0.476 0.524
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.1633     0.9145 0.976 0.024
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.4022     0.8711 0.920 0.080
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0672     0.9169 0.992 0.008
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.4815     0.8569 0.896 0.104
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.2603     0.9051 0.956 0.044
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.2603     0.9034 0.956 0.044
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.2778     0.9046 0.952 0.048
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.4815     0.8617 0.896 0.104
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.7528     0.8751 0.216 0.784
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.7528     0.8751 0.216 0.784
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000     0.9155 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.4022     0.8711 0.920 0.080
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.7528     0.8751 0.216 0.784
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.8713     0.4055 0.708 0.292
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.2043     0.9131 0.968 0.032
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000     0.9155 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     1  0.9954    -0.2155 0.540 0.460
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.7528     0.8751 0.216 0.784
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.7602     0.6183 0.780 0.220
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.2423     0.9099 0.960 0.040
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.1633     0.9145 0.976 0.024
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.2603     0.9106 0.956 0.044
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0672     0.9171 0.992 0.008
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.2236     0.9131 0.964 0.036
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.7674     0.6052 0.776 0.224
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0672     0.9174 0.992 0.008
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0376     0.9165 0.996 0.004
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000     0.9155 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.1633     0.9122 0.976 0.024
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.2778     0.9077 0.952 0.048
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000     0.9155 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     1  0.3431     0.8916 0.936 0.064
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     1  0.9954    -0.2155 0.540 0.460
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.8763     0.7931 0.296 0.704
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000     0.9155 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     2  0.6887     0.7375 0.184 0.816
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.2778     0.9059 0.952 0.048
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.2043     0.9115 0.968 0.032
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0376     0.9164 0.996 0.004
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.7453     0.8720 0.212 0.788
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.0000     0.9155 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.7528     0.8751 0.216 0.784
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.7528     0.8751 0.216 0.784
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0376     0.9165 0.996 0.004
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.7528     0.8751 0.216 0.784
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.9993     0.4245 0.484 0.516
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0376     0.9164 0.996 0.004
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.2603     0.9059 0.956 0.044
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.9710     0.6777 0.400 0.600
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.1184     0.9177 0.984 0.016
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     1  0.9954    -0.2155 0.540 0.460
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.9552     0.7234 0.376 0.624
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.2778     0.9059 0.952 0.048
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.2603     0.9051 0.956 0.044
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.1184     0.7085 0.016 0.984
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.6438     0.7804 0.836 0.164
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.1843     0.9121 0.972 0.028
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000     0.9155 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0672     0.9168 0.992 0.008
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.9427     0.7466 0.360 0.640
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0672     0.9168 0.992 0.008
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     1  0.1633     0.9157 0.976 0.024
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.8555     0.7993 0.280 0.720
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.1184     0.9169 0.984 0.016
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.1184     0.9170 0.984 0.016
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.9710     0.6449 0.400 0.600
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.7528     0.8723 0.216 0.784
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.1184     0.9163 0.984 0.016
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1  0.2423     0.9110 0.960 0.040
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.7883     0.8701 0.236 0.764
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000     0.9155 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.9944     0.5447 0.456 0.544
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.9896     0.5881 0.440 0.560
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.3879     0.8703 0.924 0.076
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.9710     0.6882 0.400 0.600
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000     0.9155 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     1  0.9970    -0.2489 0.532 0.468
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.3114     0.8956 0.944 0.056
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.2043     0.9141 0.968 0.032
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.2948     0.8997 0.948 0.052
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.2603     0.9106 0.956 0.044
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.0000     0.9155 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0376     0.9164 0.996 0.004
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.1184     0.9157 0.984 0.016
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000     0.9155 1.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.3584     0.8965 0.932 0.068
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     1  0.9970    -0.2549 0.532 0.468
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.7528     0.8751 0.216 0.784
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.4161     0.8661 0.916 0.084
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.1633     0.7137 0.024 0.976
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0938     0.9167 0.988 0.012
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0376     0.9165 0.996 0.004
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.8144     0.8627 0.252 0.748
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000     0.9155 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0672     0.9168 0.992 0.008
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.9866     0.6005 0.432 0.568
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.7528     0.8751 0.216 0.784
#> B3F746DC-E487-4305-9F30-825D1520E8FD     1  0.9909    -0.1192 0.556 0.444
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.1184     0.9174 0.984 0.016
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.2778     0.9070 0.952 0.048
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000     0.9155 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.1843     0.9152 0.972 0.028
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000     0.9155 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.8144     0.8618 0.252 0.748
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.1633     0.9152 0.976 0.024
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.1184     0.9170 0.984 0.016
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.4161     0.8661 0.916 0.084
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0672     0.9169 0.992 0.008
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.9710     0.0846 0.600 0.400
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.1414     0.9161 0.980 0.020
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000     0.9155 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0672     0.9170 0.992 0.008
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0938     0.9171 0.988 0.012
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0376     0.9164 0.996 0.004
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.3431     0.8945 0.936 0.064
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.2043     0.9147 0.968 0.032
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.1633     0.7137 0.024 0.976
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     1  0.9909    -0.1142 0.556 0.444
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.3733     0.8914 0.928 0.072
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.1414     0.9148 0.980 0.020
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0672     0.9174 0.992 0.008
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.6438     0.7804 0.836 0.164
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000     0.9155 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.9209     0.3264 0.664 0.336
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.8016     0.6151 0.756 0.244
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.4562     0.8673 0.904 0.096
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.9155 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.4022     0.8711 0.920 0.080
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.9044     0.8056 0.320 0.680
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.8327     0.6023 0.736 0.264
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.7528     0.8751 0.216 0.784
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.7528     0.8751 0.216 0.784
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.7815     0.8717 0.232 0.768
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.1414     0.9161 0.980 0.020
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.5737     0.8112 0.864 0.136
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.2236     0.9146 0.964 0.036
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.9155 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0672     0.9169 0.992 0.008
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.2423     0.9099 0.960 0.040
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.2948     0.9016 0.948 0.052
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1414     0.9166 0.980 0.020
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0376     0.9164 0.996 0.004
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.7528     0.8751 0.216 0.784
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1843     0.9107 0.972 0.028
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.4690     0.8641 0.900 0.100
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.7950     0.6475 0.760 0.240
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     1  0.9970    -0.2398 0.532 0.468
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.8909     0.8137 0.308 0.692
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9155 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.9710     0.6777 0.400 0.600
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.8144     0.8627 0.252 0.748
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0938     0.9167 0.988 0.012
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0938     0.9167 0.988 0.012
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.7745     0.8640 0.228 0.772
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.7528     0.8751 0.216 0.784
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.4161     0.8804 0.916 0.084
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.9155 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000     0.9155 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.9393     0.7549 0.356 0.644
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0938     0.9175 0.988 0.012
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.9710     0.6777 0.400 0.600
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0938     0.9165 0.988 0.012
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000     0.9155 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.3733     0.8933 0.928 0.072
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1633     0.9152 0.976 0.024
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9155 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.7602     0.8748 0.220 0.780
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000     0.9155 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1633     0.9171 0.976 0.024
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9155 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.2043     0.9142 0.968 0.032
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1184     0.9174 0.984 0.016
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9155 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000     0.9155 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.2043     0.9099 0.968 0.032
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1184     0.9174 0.984 0.016
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1184     0.9170 0.984 0.016
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4690     0.8658 0.900 0.100
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2043     0.9145 0.968 0.032
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.7602     0.8748 0.220 0.780
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1843     0.9103 0.972 0.028
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.2948     0.9013 0.948 0.052
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9155 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.9155 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9155 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.7453     0.8720 0.212 0.788
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3431     0.8945 0.936 0.064
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.9815     0.1927 0.580 0.420
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3274     0.8985 0.940 0.060
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  1.0000    -0.4546 0.500 0.500
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.3114     0.8978 0.944 0.056
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.1843     0.9155 0.972 0.028
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0376     0.9165 0.996 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9155 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.9427     0.7489 0.360 0.640
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9155 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.9909    -0.1142 0.556 0.444
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1633     0.9156 0.976 0.024
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.9286     0.4235 0.656 0.344
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4161     0.8779 0.916 0.084
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2603     0.9019 0.956 0.044
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.3584     0.8965 0.932 0.068
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.2603     0.9036 0.956 0.044
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1184     0.9169 0.984 0.016
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.1843     0.9139 0.972 0.028
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.2236     0.9133 0.964 0.036
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.3584     0.8965 0.932 0.068
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0672     0.9170 0.992 0.008
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0376     0.9165 0.996 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0376     0.9164 0.996 0.004
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.7528     0.8751 0.216 0.784
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.7528     0.8751 0.216 0.784
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.2043     0.9131 0.968 0.032
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1414     0.9178 0.980 0.020
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0672     0.9164 0.992 0.008
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9155 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.6685     0.6272 0.708 0.048 0.244
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.1711     0.9294 0.960 0.008 0.032
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.3791     0.8917 0.892 0.048 0.060
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0592     0.9344 0.988 0.000 0.012
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0661     0.9345 0.988 0.004 0.008
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1399     0.9327 0.968 0.004 0.028
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.7298     0.5932 0.692 0.220 0.088
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.1129     0.7872 0.020 0.976 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4092     0.8695 0.876 0.036 0.088
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0592     0.9333 0.988 0.000 0.012
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1015     0.9335 0.980 0.008 0.012
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1529     0.9308 0.960 0.000 0.040
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.2229     0.9242 0.944 0.012 0.044
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.6950     0.0703 0.020 0.572 0.408
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.2651     0.9170 0.928 0.012 0.060
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.2492     0.9206 0.936 0.016 0.048
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1711     0.9289 0.960 0.008 0.032
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0424     0.9335 0.992 0.000 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0747     0.9336 0.984 0.000 0.016
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0983     0.9319 0.980 0.004 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0892     0.7876 0.020 0.980 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0747     0.9330 0.984 0.000 0.016
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0592     0.9329 0.988 0.000 0.012
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0747     0.9345 0.984 0.000 0.016
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#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0592     0.9333 0.988 0.000 0.012
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.2590     0.7106 0.072 0.924 0.004
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0424     0.9327 0.992 0.000 0.008
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0592     0.9338 0.988 0.000 0.012
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     3  0.8665     0.5066 0.104 0.412 0.484
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0892     0.7876 0.020 0.980 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     3  0.5974     0.6926 0.148 0.068 0.784
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0747     0.9348 0.984 0.000 0.016
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.1765     0.9290 0.956 0.004 0.040
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0424     0.9327 0.992 0.000 0.008
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.1170     0.9333 0.976 0.008 0.016
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0592     0.9329 0.988 0.000 0.012
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.2846     0.7336 0.056 0.924 0.020
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.1129     0.9335 0.976 0.004 0.020
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.1878     0.9264 0.952 0.004 0.044
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.4527     0.8536 0.860 0.052 0.088
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0475     0.9345 0.992 0.004 0.004
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.8962     0.1442 0.540 0.304 0.156
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0983     0.9332 0.980 0.004 0.016
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0424     0.9327 0.992 0.000 0.008
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.1411     0.9316 0.964 0.000 0.036
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0424     0.9346 0.992 0.000 0.008
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.1163     0.9329 0.972 0.000 0.028
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.3550     0.8925 0.896 0.024 0.080
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.1491     0.9328 0.968 0.016 0.016
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.5443     0.5218 0.004 0.736 0.260
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     3  0.5473     0.6942 0.140 0.052 0.808
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.3406     0.9023 0.904 0.028 0.068
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0592     0.9325 0.988 0.000 0.012
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0424     0.9341 0.992 0.000 0.008
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.4915     0.8263 0.832 0.036 0.132
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0424     0.9327 0.992 0.000 0.008
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.7742     0.4472 0.632 0.288 0.080
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.6447     0.6982 0.744 0.060 0.196
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.3921     0.8865 0.884 0.036 0.080
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0424     0.9327 0.992 0.000 0.008
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.4357     0.8621 0.868 0.052 0.080
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.7317     0.4107 0.096 0.696 0.208
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.6481     0.6843 0.728 0.048 0.224
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.1129     0.7875 0.020 0.976 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0892     0.7876 0.020 0.980 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.2313     0.7680 0.032 0.944 0.024
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0983     0.9332 0.980 0.004 0.016
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.4925     0.8439 0.844 0.080 0.076
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1289     0.9339 0.968 0.000 0.032
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0829     0.9337 0.984 0.004 0.012
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0475     0.9345 0.992 0.004 0.004
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.2063     0.9258 0.948 0.008 0.044
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.2229     0.9242 0.944 0.012 0.044
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1399     0.9299 0.968 0.028 0.004
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0592     0.9338 0.988 0.000 0.012
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.1129     0.7875 0.020 0.976 0.004
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1774     0.9305 0.960 0.024 0.016
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.4007     0.8830 0.880 0.036 0.084
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5756     0.7293 0.764 0.028 0.208
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     3  0.6393     0.7271 0.112 0.120 0.768
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.4818     0.5924 0.108 0.844 0.048
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0592     0.9329 0.988 0.000 0.012
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     3  0.7366     0.3521 0.032 0.444 0.524
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.2590     0.7106 0.072 0.924 0.004
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0747     0.9330 0.984 0.000 0.016
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0747     0.9330 0.984 0.000 0.016
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.4602     0.6617 0.016 0.832 0.152
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0892     0.7876 0.020 0.980 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.3649     0.8956 0.896 0.036 0.068
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0592     0.9329 0.988 0.000 0.012
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0592     0.9329 0.988 0.000 0.012
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.6818     0.2396 0.024 0.628 0.348
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0592     0.9342 0.988 0.000 0.012
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     3  0.7366     0.3521 0.032 0.444 0.524
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0661     0.9347 0.988 0.008 0.004
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0592     0.9329 0.988 0.000 0.012
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.2749     0.9149 0.924 0.012 0.064
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1315     0.9329 0.972 0.008 0.020
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0592     0.9329 0.988 0.000 0.012
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.1315     0.7862 0.020 0.972 0.008
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0592     0.9329 0.988 0.000 0.012
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1267     0.9353 0.972 0.004 0.024
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0424     0.9327 0.992 0.000 0.008
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.1482     0.9320 0.968 0.012 0.020
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1399     0.9326 0.968 0.004 0.028
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0424     0.9327 0.992 0.000 0.008
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0592     0.9337 0.988 0.000 0.012
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.2176     0.9295 0.948 0.020 0.032
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1399     0.9326 0.968 0.004 0.028
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1170     0.9347 0.976 0.008 0.016
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.3649     0.8958 0.896 0.036 0.068
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1267     0.9329 0.972 0.004 0.024
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.1482     0.7858 0.020 0.968 0.012
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1751     0.9310 0.960 0.012 0.028
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.6380     0.6585 0.732 0.044 0.224
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0592     0.9329 0.988 0.000 0.012
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0424     0.9327 0.992 0.000 0.008
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0424     0.9327 0.992 0.000 0.008
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.1781     0.7819 0.020 0.960 0.020
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3550     0.8925 0.896 0.024 0.080
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.8597     0.3591 0.576 0.132 0.292
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3112     0.9100 0.916 0.028 0.056
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.7620    -0.0199 0.348 0.596 0.056
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.2689     0.9189 0.932 0.032 0.036
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.4692     0.8013 0.820 0.012 0.168
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0592     0.9333 0.988 0.000 0.012
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0592     0.9329 0.988 0.000 0.012
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.7169     0.0444 0.028 0.568 0.404
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0424     0.9327 0.992 0.000 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.5473     0.6942 0.140 0.052 0.808
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2860     0.9068 0.912 0.004 0.084
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.7523     0.5429 0.660 0.080 0.260
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4712     0.8494 0.848 0.044 0.108
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2434     0.9236 0.940 0.036 0.024
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2651     0.9170 0.928 0.012 0.060
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1832     0.9284 0.956 0.008 0.036
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1525     0.9349 0.964 0.004 0.032
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.1585     0.9298 0.964 0.008 0.028
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.1905     0.9292 0.956 0.028 0.016
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2651     0.9170 0.928 0.012 0.060
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0747     0.9340 0.984 0.000 0.016
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0592     0.9333 0.988 0.000 0.012
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0424     0.9335 0.992 0.000 0.008
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0892     0.7876 0.020 0.980 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1315     0.7866 0.020 0.972 0.008
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.1711     0.9294 0.960 0.008 0.032
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1031     0.9348 0.976 0.000 0.024
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0829     0.9348 0.984 0.004 0.012
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0424     0.9327 0.992 0.000 0.008

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.7706    -0.2735 0.464 0.008 0.176 0.352
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.4655     0.5686 0.760 0.000 0.208 0.032
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5633     0.4686 0.704 0.024 0.244 0.028
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2408     0.6464 0.896 0.000 0.104 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2466     0.6517 0.900 0.004 0.096 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.5154     0.3573 0.660 0.004 0.324 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.8070    -0.0104 0.568 0.200 0.168 0.064
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0188     0.7553 0.000 0.996 0.000 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6988    -0.2636 0.496 0.044 0.424 0.036
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1940     0.6399 0.924 0.000 0.076 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3768     0.5748 0.808 0.008 0.184 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3279     0.6294 0.872 0.000 0.096 0.032
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.5067     0.5171 0.736 0.004 0.224 0.036
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.5698     0.0397 0.004 0.560 0.020 0.416
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.4675     0.4834 0.736 0.000 0.244 0.020
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.5201     0.5328 0.732 0.004 0.220 0.044
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4238     0.6056 0.796 0.000 0.176 0.028
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2011     0.6417 0.920 0.000 0.080 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.3528     0.5655 0.808 0.000 0.192 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.4194     0.5875 0.764 0.000 0.228 0.008
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3074     0.6105 0.848 0.000 0.152 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3266     0.5871 0.832 0.000 0.168 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2345     0.6309 0.900 0.000 0.100 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.4524     0.5839 0.768 0.000 0.204 0.028
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.3688     0.6029 0.792 0.000 0.208 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.5047     0.5346 0.744 0.004 0.212 0.040
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.3300     0.6428 0.848 0.000 0.144 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.2432     0.7209 0.024 0.928 0.028 0.020
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4122     0.4961 0.760 0.004 0.236 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.7228    -0.2651 0.496 0.060 0.408 0.036
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2149     0.6357 0.912 0.000 0.088 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2530     0.6222 0.888 0.000 0.112 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.8266    -0.2945 0.480 0.324 0.148 0.048
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#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.1863     0.7082 0.040 0.944 0.012 0.004
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.2081     0.6367 0.916 0.000 0.084 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.3831     0.5800 0.792 0.000 0.204 0.004
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     4  0.4746     0.5224 0.000 0.368 0.000 0.632
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.1516     0.7254 0.008 0.016 0.016 0.960
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.2048     0.6459 0.928 0.000 0.064 0.008
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.4252     0.5446 0.744 0.000 0.252 0.004
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.3172     0.6002 0.840 0.000 0.160 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.3751     0.5816 0.800 0.000 0.196 0.004
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.3266     0.5871 0.832 0.000 0.168 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.2210     0.7261 0.020 0.936 0.028 0.016
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.4429     0.5873 0.764 0.004 0.220 0.012
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.4227     0.5954 0.820 0.000 0.120 0.060
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.7250    -0.3139 0.476 0.060 0.428 0.036
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.4053     0.5102 0.768 0.004 0.228 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.8835     0.3651 0.296 0.264 0.392 0.048
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.3972     0.6127 0.788 0.000 0.204 0.008
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.2266     0.6373 0.912 0.000 0.084 0.004
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.2670     0.6403 0.904 0.000 0.072 0.024
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.3649     0.5679 0.796 0.000 0.204 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.2563     0.6429 0.908 0.000 0.072 0.020
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.6084     0.4359 0.696 0.012 0.204 0.088
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.4240     0.5826 0.784 0.004 0.200 0.012
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.5138     0.3890 0.000 0.600 0.392 0.008
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0188     0.7245 0.000 0.000 0.004 0.996
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.6000     0.4127 0.688 0.020 0.240 0.052
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.2773     0.6350 0.880 0.000 0.116 0.004
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.2675     0.6494 0.892 0.000 0.100 0.008
#> C86EBD08-53F2-4972-801A-74970FDD6A62     3  0.6105     0.2834 0.476 0.004 0.484 0.036
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.2647     0.6435 0.880 0.000 0.120 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.8182    -0.1793 0.528 0.268 0.148 0.056
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.5324    -0.0348 0.644 0.004 0.336 0.016
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.6156     0.4329 0.688 0.020 0.224 0.068
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.2408     0.6461 0.896 0.000 0.104 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.7247    -0.2911 0.480 0.060 0.424 0.036
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.6268     0.4498 0.048 0.692 0.044 0.216
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.5702    -0.1432 0.572 0.008 0.404 0.016
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0188     0.7555 0.000 0.996 0.000 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.1516     0.7440 0.008 0.960 0.016 0.016
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.3972     0.6127 0.788 0.000 0.204 0.008
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.6753     0.3937 0.672 0.064 0.204 0.060
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.4074     0.5975 0.792 0.004 0.196 0.008
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.4155     0.4884 0.756 0.004 0.240 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.4053     0.5102 0.768 0.004 0.228 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.4755     0.5699 0.760 0.000 0.200 0.040
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.5067     0.5171 0.736 0.004 0.224 0.036
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4775     0.4788 0.740 0.028 0.232 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.3649     0.6089 0.796 0.000 0.204 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0188     0.7555 0.000 0.996 0.000 0.004
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.3712     0.6004 0.832 0.012 0.152 0.004
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.6121     0.4310 0.688 0.020 0.228 0.064
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5229    -0.1422 0.564 0.000 0.428 0.008
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1978     0.7604 0.000 0.068 0.004 0.928
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.4003     0.6575 0.036 0.856 0.080 0.028
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.3486     0.5808 0.812 0.000 0.188 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.4933     0.3952 0.000 0.432 0.000 0.568
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.1863     0.7082 0.040 0.944 0.012 0.004
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.3306     0.6445 0.840 0.000 0.156 0.004
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3172     0.6057 0.840 0.000 0.160 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3355     0.6276 0.000 0.836 0.004 0.160
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.6019     0.4475 0.696 0.020 0.224 0.060
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.3975     0.4931 0.760 0.000 0.240 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.3945     0.5323 0.780 0.000 0.216 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.5598     0.2492 0.008 0.628 0.020 0.344
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.3636     0.6232 0.820 0.000 0.172 0.008
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.4933     0.3952 0.000 0.432 0.000 0.568
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.3893     0.6112 0.796 0.008 0.196 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.3873     0.5089 0.772 0.000 0.228 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.4797     0.4629 0.720 0.000 0.260 0.020
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.4429     0.5842 0.764 0.004 0.220 0.012
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.3486     0.5863 0.812 0.000 0.188 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0336     0.7544 0.000 0.992 0.000 0.008
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.3870     0.5425 0.788 0.000 0.208 0.004
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.3450     0.6478 0.836 0.000 0.156 0.008
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.3486     0.5799 0.812 0.000 0.188 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.3982     0.5419 0.776 0.000 0.220 0.004
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.3439     0.6254 0.868 0.000 0.084 0.048
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2011     0.6404 0.920 0.000 0.080 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.2704     0.6458 0.876 0.000 0.124 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.3983     0.6213 0.828 0.008 0.144 0.020
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.3439     0.6244 0.868 0.000 0.084 0.048
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3591     0.6413 0.824 0.000 0.168 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4883     0.4140 0.696 0.000 0.288 0.016
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3907     0.5588 0.768 0.000 0.232 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0524     0.7542 0.000 0.988 0.004 0.008
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3105     0.6070 0.868 0.000 0.120 0.012
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.7427    -0.2121 0.504 0.004 0.164 0.328
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.3444     0.5717 0.816 0.000 0.184 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2704     0.6290 0.876 0.000 0.124 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.3219     0.5779 0.836 0.000 0.164 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0895     0.7495 0.000 0.976 0.020 0.004
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.6084     0.4359 0.696 0.012 0.204 0.088
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.7316     0.3804 0.408 0.052 0.492 0.048
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5980     0.4350 0.696 0.020 0.228 0.056
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.7429     0.2682 0.176 0.608 0.184 0.032
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.4470     0.6197 0.824 0.032 0.116 0.028
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.6555     0.1800 0.632 0.000 0.156 0.212
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2011     0.6434 0.920 0.000 0.080 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.3528     0.5628 0.808 0.000 0.192 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.5928     0.0583 0.004 0.564 0.032 0.400
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2281     0.6438 0.904 0.000 0.096 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0188     0.7245 0.000 0.000 0.004 0.996
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4827     0.5587 0.784 0.000 0.124 0.092
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5503     0.3360 0.468 0.000 0.516 0.016
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.7265     0.1126 0.588 0.012 0.220 0.180
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4044     0.5886 0.820 0.024 0.152 0.004
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4964     0.4585 0.716 0.000 0.256 0.028
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3219     0.5970 0.836 0.000 0.164 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2676     0.6366 0.896 0.000 0.092 0.012
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.4004     0.6211 0.812 0.000 0.164 0.024
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.4947     0.5882 0.752 0.024 0.212 0.012
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4964     0.4585 0.716 0.000 0.256 0.028
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3925     0.6339 0.808 0.000 0.176 0.016
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1792     0.6418 0.932 0.000 0.068 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.3444     0.5738 0.816 0.000 0.184 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.7557 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0336     0.7547 0.000 0.992 0.000 0.008
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.4406     0.6050 0.780 0.000 0.192 0.028
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2530     0.6333 0.896 0.000 0.100 0.004
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4088     0.5201 0.764 0.004 0.232 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2281     0.6335 0.904 0.000 0.096 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.7631     0.2216 0.456 0.008 0.108 0.332 0.096
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.5197     0.4872 0.712 0.000 0.080 0.020 0.188
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.3759     0.5176 0.828 0.008 0.084 0.000 0.080
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4538     0.3416 0.620 0.000 0.016 0.000 0.364
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4945     0.1191 0.536 0.004 0.020 0.000 0.440
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.6084     0.4819 0.208 0.000 0.220 0.000 0.572
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.5625     0.3735 0.692 0.188 0.092 0.020 0.008
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0162     0.8049 0.000 0.996 0.000 0.004 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.5559    -0.2753 0.052 0.004 0.392 0.004 0.548
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4269     0.4383 0.684 0.000 0.016 0.000 0.300
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.4503     0.5396 0.268 0.000 0.036 0.000 0.696
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.5427     0.3057 0.580 0.000 0.024 0.028 0.368
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.3942     0.5377 0.824 0.000 0.068 0.020 0.088
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.5603     0.0239 0.000 0.528 0.024 0.416 0.032
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.2514     0.5350 0.896 0.000 0.060 0.000 0.044
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.4129     0.5338 0.808 0.000 0.060 0.020 0.112
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5322     0.4388 0.664 0.000 0.068 0.012 0.256
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4494     0.3416 0.608 0.000 0.012 0.000 0.380
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.4014     0.5371 0.256 0.000 0.016 0.000 0.728
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.5485     0.3192 0.400 0.000 0.056 0.004 0.540
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3689     0.4849 0.740 0.000 0.004 0.000 0.256
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.4283     0.4509 0.348 0.000 0.008 0.000 0.644
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4040     0.4709 0.712 0.000 0.012 0.000 0.276
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.5293     0.4585 0.692 0.000 0.080 0.016 0.212
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4763     0.4331 0.632 0.000 0.032 0.000 0.336
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.4111     0.5299 0.808 0.000 0.068 0.016 0.108
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5132     0.3623 0.612 0.000 0.036 0.008 0.344
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#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.7965     0.2012 0.412 0.008 0.076 0.308 0.196
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.2376     0.5445 0.904 0.000 0.044 0.000 0.052
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     5  0.4479     0.5263 0.264 0.000 0.036 0.000 0.700
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     5  0.4252     0.5436 0.280 0.000 0.020 0.000 0.700
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.3582     0.5083 0.768 0.000 0.008 0.000 0.224
#> 31B54613-A20E-4039-BB8B-9B52104CE418     5  0.4168     0.5680 0.200 0.000 0.044 0.000 0.756
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.2597     0.5351 0.896 0.000 0.060 0.004 0.040
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     4  0.2674     0.7480 0.000 0.140 0.004 0.856 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     5  0.5358    -0.3080 0.032 0.008 0.396 0.004 0.560
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.4546     0.0545 0.008 0.532 0.460 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.3662     0.4887 0.744 0.000 0.004 0.000 0.252
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.4029     0.4333 0.680 0.000 0.004 0.000 0.316
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.1502     0.7440 0.056 0.940 0.004 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.4436     0.3095 0.596 0.000 0.008 0.000 0.396
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     5  0.4733     0.4531 0.348 0.000 0.028 0.000 0.624
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     4  0.4074     0.5248 0.000 0.364 0.000 0.636 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.1533     0.6725 0.024 0.016 0.004 0.952 0.004
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.4859     0.3575 0.608 0.000 0.024 0.004 0.364
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.4444     0.4910 0.756 0.000 0.088 0.000 0.156
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     5  0.4437     0.5080 0.316 0.000 0.020 0.000 0.664
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.3621     0.5359 0.788 0.000 0.020 0.000 0.192
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     5  0.4283     0.4509 0.348 0.000 0.008 0.000 0.644
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.2881     0.7535 0.020 0.896 0.040 0.008 0.036
#> 344B9631-AAA5-4302-8747-D584345D9131     5  0.5590     0.3218 0.396 0.000 0.056 0.008 0.540
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.6413     0.0797 0.472 0.000 0.064 0.044 0.420
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.5358    -0.3080 0.032 0.008 0.396 0.004 0.560
#> 297611E9-9555-4BCA-A723-02E846ACC23A     5  0.4773     0.5680 0.216 0.004 0.064 0.000 0.716
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.8140     0.3571 0.068 0.172 0.384 0.024 0.352
#> FD544083-9BD5-4036-BD81-0352B67CC45C     5  0.5405     0.1629 0.460 0.000 0.056 0.000 0.484
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.4655     0.0782 0.512 0.000 0.012 0.000 0.476
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.5154     0.3052 0.576 0.000 0.020 0.016 0.388
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.4794     0.4715 0.344 0.000 0.032 0.000 0.624
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.5106     0.2587 0.560 0.000 0.020 0.012 0.408
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.4445     0.5191 0.812 0.012 0.052 0.080 0.044
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.3885     0.5355 0.784 0.000 0.040 0.000 0.176
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.4546     0.0545 0.008 0.532 0.460 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0324     0.6754 0.000 0.000 0.004 0.992 0.004
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.3767     0.5291 0.856 0.020 0.040 0.044 0.040
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.4295     0.5067 0.724 0.000 0.024 0.004 0.248
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.5046     0.0581 0.500 0.000 0.032 0.000 0.468
#> C86EBD08-53F2-4972-801A-74970FDD6A62     3  0.6099     0.1757 0.124 0.000 0.452 0.000 0.424
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.4597     0.2305 0.564 0.000 0.012 0.000 0.424
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.5900     0.2622 0.636 0.256 0.084 0.016 0.008
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.6510     0.3921 0.568 0.004 0.228 0.012 0.188
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.3403     0.5145 0.864 0.012 0.080 0.028 0.016
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.4666     0.2704 0.572 0.000 0.016 0.000 0.412
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.5585    -0.2613 0.048 0.008 0.380 0.004 0.560
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.5843     0.4933 0.040 0.684 0.056 0.204 0.016
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.6139     0.3484 0.560 0.000 0.288 0.004 0.148
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0324     0.8047 0.000 0.992 0.004 0.004 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.1997     0.7856 0.008 0.936 0.024 0.012 0.020
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     5  0.5405     0.1629 0.460 0.000 0.056 0.000 0.484
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.4068     0.5042 0.832 0.056 0.076 0.020 0.016
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.5385     0.4203 0.288 0.000 0.088 0.000 0.624
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.4221     0.5667 0.188 0.004 0.044 0.000 0.764
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.4773     0.5680 0.216 0.004 0.064 0.000 0.716
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.5186     0.4724 0.704 0.000 0.068 0.020 0.208
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.3942     0.5377 0.824 0.000 0.068 0.020 0.088
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.5389     0.5572 0.216 0.024 0.072 0.000 0.688
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.4822     0.4626 0.352 0.000 0.032 0.000 0.616
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0324     0.8047 0.000 0.992 0.004 0.004 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4573     0.4986 0.704 0.008 0.028 0.000 0.260
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.3375     0.5117 0.864 0.012 0.084 0.024 0.016
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.4873     0.3952 0.688 0.000 0.244 0.000 0.068
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1864     0.7293 0.000 0.068 0.004 0.924 0.004
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.4233     0.6780 0.024 0.816 0.104 0.012 0.044
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.4524     0.4855 0.336 0.000 0.020 0.000 0.644
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.5033     0.4198 0.000 0.400 0.004 0.568 0.028
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.1502     0.7440 0.056 0.940 0.004 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.4588     0.2913 0.604 0.000 0.016 0.000 0.380
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3579     0.4967 0.756 0.000 0.004 0.000 0.240
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3210     0.6803 0.000 0.832 0.008 0.152 0.008
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.3352     0.5220 0.868 0.012 0.076 0.024 0.020
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.4168     0.5680 0.200 0.000 0.044 0.000 0.756
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.4479     0.5263 0.264 0.000 0.036 0.000 0.700
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.5710     0.2443 0.004 0.592 0.028 0.340 0.036
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.5513     0.2780 0.408 0.000 0.068 0.000 0.524
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.5033     0.4198 0.000 0.400 0.004 0.568 0.028
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.5199     0.3378 0.412 0.004 0.036 0.000 0.548
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.3977     0.5716 0.204 0.000 0.032 0.000 0.764
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.2046     0.5240 0.916 0.000 0.068 0.000 0.016
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.5604     0.3059 0.404 0.000 0.056 0.008 0.532
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.4524     0.4765 0.336 0.000 0.020 0.000 0.644
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0324     0.8043 0.000 0.992 0.004 0.004 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.4520     0.5122 0.284 0.000 0.032 0.000 0.684
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4752     0.2984 0.568 0.000 0.020 0.000 0.412
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.4165     0.4945 0.320 0.000 0.008 0.000 0.672
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.3262     0.5376 0.840 0.000 0.036 0.000 0.124
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5873     0.2053 0.520 0.000 0.036 0.036 0.408
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.4533     0.1737 0.544 0.000 0.008 0.000 0.448
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4717     0.3174 0.584 0.000 0.020 0.000 0.396
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5209     0.4037 0.628 0.004 0.044 0.004 0.320
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5943     0.1845 0.512 0.000 0.040 0.036 0.412
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5250     0.1466 0.536 0.000 0.048 0.000 0.416
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.2813     0.5157 0.868 0.000 0.108 0.000 0.024
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3804     0.5200 0.796 0.000 0.044 0.000 0.160
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0451     0.8035 0.000 0.988 0.008 0.004 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3958     0.5333 0.776 0.000 0.040 0.000 0.184
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.8035     0.1749 0.400 0.004 0.096 0.308 0.192
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.4270     0.4952 0.320 0.000 0.012 0.000 0.668
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     5  0.4811     0.1530 0.452 0.000 0.020 0.000 0.528
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.4306     0.4676 0.328 0.000 0.012 0.000 0.660
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.1455     0.7907 0.000 0.952 0.032 0.008 0.008
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.4445     0.5191 0.812 0.012 0.052 0.080 0.044
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.5527     0.0830 0.576 0.040 0.368 0.012 0.004
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3601     0.5334 0.864 0.020 0.028 0.044 0.044
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.7006     0.1530 0.036 0.568 0.188 0.012 0.196
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6721     0.2682 0.516 0.028 0.068 0.024 0.364
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.7751     0.1033 0.400 0.000 0.076 0.196 0.328
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4416     0.3673 0.632 0.000 0.012 0.000 0.356
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.4297     0.5249 0.288 0.000 0.020 0.000 0.692
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.5860     0.0347 0.000 0.528 0.036 0.400 0.036
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.4897     0.1024 0.516 0.000 0.024 0.000 0.460
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0324     0.6754 0.000 0.000 0.004 0.992 0.004
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6691     0.3204 0.548 0.000 0.072 0.076 0.304
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.5030     0.2079 0.604 0.000 0.352 0.000 0.044
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4769     0.4459 0.768 0.008 0.060 0.144 0.020
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4818     0.4993 0.700 0.020 0.028 0.000 0.252
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2141     0.5247 0.916 0.000 0.064 0.004 0.016
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4890     0.4362 0.628 0.000 0.040 0.000 0.332
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4754     0.4391 0.660 0.000 0.024 0.008 0.308
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.5770     0.3255 0.584 0.000 0.076 0.012 0.328
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5930    -0.0544 0.500 0.012 0.060 0.004 0.424
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2141     0.5247 0.916 0.000 0.064 0.004 0.016
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4622     0.5066 0.700 0.000 0.024 0.012 0.264
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4457     0.3495 0.620 0.000 0.012 0.000 0.368
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.4584     0.5079 0.312 0.000 0.028 0.000 0.660
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8050 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0451     0.8044 0.000 0.988 0.004 0.008 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.5817     0.3676 0.608 0.000 0.084 0.016 0.292
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3934     0.5041 0.740 0.000 0.016 0.000 0.244
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.5042     0.5634 0.256 0.004 0.064 0.000 0.676
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     5  0.4740     0.0881 0.468 0.000 0.016 0.000 0.516

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.8621    0.12879 0.120 0.004 0.304 0.296 0.148 0.128
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.7033    0.23618 0.332 0.000 0.420 0.004 0.096 0.148
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4704    0.58289 0.120 0.000 0.732 0.000 0.032 0.116
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4890    0.20878 0.516 0.000 0.436 0.000 0.036 0.012
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4832    0.42389 0.608 0.000 0.324 0.000 0.064 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4727    0.13399 0.560 0.000 0.024 0.000 0.400 0.016
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#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.3594    0.57047 0.820 0.000 0.100 0.000 0.056 0.024
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2507    0.72424 0.000 0.892 0.000 0.020 0.028 0.060
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.5756    0.54213 0.096 0.000 0.696 0.060 0.076 0.072
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4488    0.17767 0.004 0.016 0.544 0.000 0.004 0.432
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.4448    0.57854 0.072 0.000 0.788 0.024 0.056 0.060
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.7369    0.07448 0.080 0.476 0.028 0.028 0.308 0.080
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6895    0.33331 0.532 0.016 0.268 0.016 0.096 0.072
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.8402    0.10914 0.388 0.000 0.180 0.172 0.152 0.108
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4623    0.25532 0.540 0.000 0.428 0.000 0.016 0.016
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.3613    0.54575 0.816 0.000 0.076 0.000 0.092 0.016
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.6155   -0.02539 0.000 0.440 0.004 0.424 0.080 0.052
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.4884    0.43484 0.608 0.000 0.324 0.000 0.060 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1092    0.52515 0.000 0.000 0.000 0.960 0.020 0.020
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.7275    0.24253 0.480 0.000 0.280 0.052 0.112 0.076
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5029    0.32659 0.048 0.000 0.592 0.000 0.020 0.340
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5793    0.53289 0.040 0.000 0.664 0.120 0.028 0.148
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.5005    0.06133 0.460 0.008 0.488 0.000 0.004 0.040
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.2569    0.58395 0.044 0.000 0.892 0.004 0.012 0.048
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.5640    0.06847 0.428 0.000 0.472 0.000 0.068 0.032
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5252    0.13380 0.488 0.000 0.448 0.004 0.036 0.024
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.6781    0.21663 0.504 0.000 0.236 0.000 0.116 0.144
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.7054    0.29707 0.484 0.012 0.260 0.000 0.144 0.100
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.2569    0.58395 0.044 0.000 0.892 0.004 0.012 0.048
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5429    0.40449 0.288 0.000 0.608 0.004 0.028 0.072
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4682    0.27397 0.548 0.000 0.416 0.000 0.016 0.020
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4396    0.52784 0.748 0.000 0.116 0.000 0.120 0.016
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0146    0.77159 0.000 0.996 0.000 0.000 0.000 0.004
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0696    0.76830 0.000 0.980 0.004 0.008 0.004 0.004
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6992    0.13031 0.464 0.000 0.256 0.000 0.120 0.160
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.4646    0.18201 0.396 0.000 0.568 0.000 0.016 0.020
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.5113    0.42075 0.656 0.000 0.108 0.000 0.220 0.016
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4722    0.49704 0.656 0.000 0.264 0.000 0.076 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-hclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


SD:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "kmeans"]
# you can also extract it by
# res = res_list["SD:kmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.990       0.996         0.3928 0.609   0.609
#> 3 3 0.594           0.804       0.886         0.5567 0.755   0.602
#> 4 4 0.611           0.690       0.773         0.1638 0.779   0.491
#> 5 5 0.684           0.737       0.817         0.0900 0.931   0.757
#> 6 6 0.681           0.601       0.761         0.0492 0.943   0.762

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0672      0.989 0.992 0.008
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.996 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.996 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.996 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.996 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.996 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.995 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.995 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.996 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.996 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.996 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.996 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.996 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.995 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.996 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.996 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.996 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.996 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.996 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.996 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.995 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.996 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.996 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.996 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.996 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.996 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.996 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.996 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.995 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.995 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.996 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.996 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.996 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.996 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.995 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.996 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.996 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.995 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.996 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.996 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.995 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.996 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.996 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.996 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.996 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.996 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.996 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.995 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.996 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.995 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.996 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.995 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.996 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.996 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.996 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000      0.996 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.996 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000      0.996 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.995 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.996 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.996 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000      0.996 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.996 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.996 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.995 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.996 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.996 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.996 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.996 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.995 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.996 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.996 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.996 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.996 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000      0.996 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.996 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.996 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.995 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000      0.996 1.000 0.000
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#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.996 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.996 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.996 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.996 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.996 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.996 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.996 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.996 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.996 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.996 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.996 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.995 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.996 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000      0.996 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.996 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.996 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.996 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.995 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000      0.996 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0938      0.984 0.012 0.988
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000      0.996 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.4562      0.895 0.096 0.904
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.996 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000      0.996 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.996 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.996 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.995 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.996 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.995 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.996 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.996 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.996 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.2948      0.945 0.052 0.948
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.996 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.996 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000      0.996 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.996 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000      0.996 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.996 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.996 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.996 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.996 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.995 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.995 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.996 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.996 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.996 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.996 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.4256     0.7490 0.096 0.036 0.868
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.3192     0.8401 0.112 0.000 0.888
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2878     0.8385 0.096 0.000 0.904
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3816     0.8183 0.852 0.000 0.148
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0892     0.8619 0.980 0.000 0.020
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.8624 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5754     0.4577 0.004 0.296 0.700
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9521 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.1860     0.8380 0.948 0.000 0.052
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3816     0.8183 0.852 0.000 0.148
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.8624 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3816     0.8183 0.852 0.000 0.148
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3192     0.8401 0.112 0.000 0.888
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.2796     0.9439 0.000 0.908 0.092
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.3038     0.8360 0.104 0.000 0.896
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3192     0.8401 0.112 0.000 0.888
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.5216     0.7415 0.260 0.000 0.740
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3752     0.8208 0.856 0.000 0.144
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.8624 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.6244     0.5047 0.440 0.000 0.560
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9521 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0892     0.8619 0.980 0.000 0.020
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3267     0.8355 0.884 0.000 0.116
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3816     0.8183 0.852 0.000 0.148
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3192     0.8401 0.112 0.000 0.888
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.3038     0.8047 0.896 0.000 0.104
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2796     0.8372 0.092 0.000 0.908
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3412     0.8344 0.124 0.000 0.876
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9521 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9521 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.8624 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.8624 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3816     0.8183 0.852 0.000 0.148
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.8624 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9521 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6225     0.3143 0.432 0.000 0.568
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5882     0.2782 0.652 0.000 0.348
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9521 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3816     0.8183 0.852 0.000 0.148
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0892     0.8619 0.980 0.000 0.020
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.2711     0.9445 0.000 0.912 0.088
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.3619     0.8347 0.136 0.000 0.864
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1860     0.8025 0.052 0.000 0.948
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3816     0.8183 0.852 0.000 0.148
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.5785     0.2793 0.668 0.000 0.332
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2796     0.8159 0.908 0.000 0.092
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.8624 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9521 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.3192     0.8401 0.112 0.000 0.888
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.2796     0.9439 0.000 0.908 0.092
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3752     0.8208 0.856 0.000 0.144
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.2796     0.9439 0.000 0.908 0.092
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.2959     0.8394 0.100 0.000 0.900
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5529     0.6577 0.296 0.000 0.704
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.4178     0.7986 0.828 0.000 0.172
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2261     0.8280 0.068 0.000 0.932
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2878     0.8385 0.096 0.000 0.904
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1031     0.8477 0.976 0.000 0.024
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0747     0.9516 0.000 0.984 0.016
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3816     0.8183 0.852 0.000 0.148
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.8624 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.2625     0.8449 0.916 0.000 0.084
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.6295    -0.3004 0.528 0.000 0.472
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3816     0.8183 0.852 0.000 0.148
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9521 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2796     0.8380 0.092 0.000 0.908
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3686     0.8232 0.860 0.000 0.140
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.3340     0.7527 0.880 0.000 0.120
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.3192     0.8401 0.112 0.000 0.888
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.2796     0.9439 0.000 0.908 0.092
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.8624 1.000 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0747     0.8560 0.984 0.000 0.016
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.6225     0.5155 0.432 0.000 0.568
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3816     0.8183 0.852 0.000 0.148
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4002     0.8089 0.840 0.000 0.160
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.8624 1.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000     0.8624 1.000 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9521 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.2711     0.8294 0.088 0.000 0.912
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.2959     0.9402 0.000 0.900 0.100
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0892     0.8619 0.980 0.000 0.020
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.4128     0.6490 0.012 0.132 0.856
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0424     0.8597 0.992 0.000 0.008
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.8624 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0892     0.8619 0.980 0.000 0.020
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0237     0.8631 0.996 0.000 0.004
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3412     0.8251 0.876 0.000 0.124
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.2796     0.9439 0.000 0.908 0.092
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.1860     0.9492 0.000 0.948 0.052
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.4974     0.7515 0.236 0.000 0.764
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000     0.8624 1.000 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.5363     0.4525 0.724 0.000 0.276
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.2796     0.9439 0.000 0.908 0.092
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.5621     0.7008 0.308 0.000 0.692
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.8624 1.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.8624 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.5621     0.6265 0.308 0.000 0.692
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.4291     0.8008 0.820 0.000 0.180
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000     0.8624 1.000 0.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.3192     0.8401 0.112 0.000 0.888
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.4399     0.7851 0.188 0.000 0.812
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9521 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9521 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000     0.8624 1.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000     0.8624 1.000 0.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9521 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.1905     0.8355 0.956 0.016 0.028
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.3192     0.8401 0.112 0.000 0.888
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000     0.8624 1.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.2796     0.9439 0.000 0.908 0.092
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9521 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000     0.8624 1.000 0.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.3038     0.8399 0.104 0.000 0.896
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.2796     0.8372 0.092 0.000 0.908
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.5733     0.5560 0.676 0.000 0.324
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000     0.8624 1.000 0.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0424     0.8597 0.992 0.000 0.008
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000     0.8624 1.000 0.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.3816     0.8183 0.852 0.000 0.148
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#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0829     0.7751 0.012 0.004 0.984
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.4504     0.7718 0.196 0.000 0.804
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.6852     0.5477 0.300 0.664 0.036
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.3879     0.8273 0.152 0.000 0.848
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4062     0.7884 0.164 0.000 0.836
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2165     0.8548 0.936 0.000 0.064
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.8624 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.2796     0.9439 0.000 0.908 0.092
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3816     0.8183 0.852 0.000 0.148
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.3482     0.9224 0.000 0.872 0.128
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4062     0.8056 0.836 0.000 0.164
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.2796     0.8372 0.092 0.000 0.908
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.2261     0.8280 0.068 0.000 0.932
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.7216     0.6011 0.112 0.712 0.176
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5760     0.5472 0.672 0.000 0.328
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5465     0.6514 0.712 0.000 0.288
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4062     0.8056 0.836 0.000 0.164
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3192     0.8401 0.112 0.000 0.888
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.6126     0.5717 0.400 0.000 0.600
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4291     0.7885 0.180 0.000 0.820
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5291     0.6697 0.268 0.000 0.732
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3752     0.8208 0.856 0.000 0.144
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1163     0.8535 0.972 0.000 0.028
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9521 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9521 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3192     0.8401 0.112 0.000 0.888
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.6309     0.0815 0.496 0.000 0.504
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.8624 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0892     0.8619 0.980 0.000 0.020

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.9211     0.1473 0.448 0.244 0.132 0.176
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.5524     0.9089 0.048 0.000 0.676 0.276
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.6602     0.8457 0.092 0.000 0.552 0.356
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0817     0.7451 0.976 0.000 0.000 0.024
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3266     0.5615 0.832 0.000 0.000 0.168
#> 03E81178-E971-4E91-8BED-D8273EA1425C     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.7651     0.8336 0.048 0.096 0.552 0.304
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.6196     0.6969 0.228 0.100 0.004 0.668
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1022     0.7452 0.968 0.000 0.000 0.032
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.4804     0.7921 0.384 0.000 0.000 0.616
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1118     0.7352 0.964 0.000 0.000 0.036
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.5599     0.9091 0.052 0.000 0.672 0.276
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.8256 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.6824     0.1771 0.548 0.000 0.116 0.336
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.5672     0.9087 0.056 0.000 0.668 0.276
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.4978     0.8541 0.012 0.000 0.664 0.324
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1118     0.7320 0.964 0.000 0.000 0.036
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     4  0.4761     0.7924 0.372 0.000 0.000 0.628
#> C204D355-B876-4341-A111-36D48CBDD2A8     4  0.6310    -0.3724 0.060 0.000 0.428 0.512
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3074     0.5910 0.848 0.000 0.000 0.152
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1022     0.7360 0.968 0.000 0.000 0.032
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0921     0.7451 0.972 0.000 0.000 0.028
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.5524     0.9089 0.048 0.000 0.676 0.276
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     4  0.4907     0.4560 0.420 0.000 0.000 0.580
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.5716     0.9077 0.060 0.000 0.668 0.272
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.7846     0.6019 0.300 0.000 0.404 0.296
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.4713     0.7894 0.360 0.000 0.000 0.640
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0592     0.7433 0.984 0.000 0.000 0.016
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     4  0.4817     0.7923 0.388 0.000 0.000 0.612
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3870     0.6472 0.788 0.000 0.004 0.208
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.5303     0.5494 0.136 0.084 0.012 0.768
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1022     0.7451 0.968 0.000 0.000 0.032
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.3688     0.4896 0.792 0.000 0.000 0.208
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.8256 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.5697     0.9078 0.056 0.000 0.664 0.280
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.5750     0.9088 0.052 0.004 0.672 0.272
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0921     0.7391 0.972 0.000 0.000 0.028
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     4  0.7031     0.3266 0.156 0.000 0.288 0.556
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4866     0.2633 0.596 0.000 0.000 0.404
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5549     0.9080 0.048 0.000 0.672 0.280
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0188     0.8245 0.000 0.996 0.004 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1118     0.7351 0.964 0.000 0.000 0.036
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0376     0.8230 0.000 0.992 0.004 0.004
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5716     0.9077 0.060 0.000 0.668 0.272
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4353     0.6064 0.756 0.000 0.012 0.232
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0921     0.7451 0.972 0.000 0.000 0.028
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.5750     0.9088 0.052 0.004 0.672 0.272
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.5857     0.8951 0.056 0.000 0.636 0.308
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.4713     0.7894 0.360 0.000 0.000 0.640
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.4193     0.8612 0.000 0.732 0.268 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0817     0.7391 0.976 0.000 0.000 0.024
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.4624     0.0286 0.660 0.000 0.000 0.340
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.5248     0.6001 0.164 0.000 0.088 0.748
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0592     0.7459 0.984 0.000 0.000 0.016
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.5888     0.8961 0.048 0.004 0.640 0.308
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1302     0.7290 0.956 0.000 0.000 0.044
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     4  0.5817     0.7050 0.248 0.000 0.076 0.676
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.5675     0.9085 0.048 0.004 0.676 0.272
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0188     0.8245 0.000 0.996 0.004 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     4  0.4730     0.7898 0.364 0.000 0.000 0.636
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     4  0.5204     0.7934 0.376 0.000 0.012 0.612
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     4  0.6013    -0.0165 0.064 0.000 0.312 0.624
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0817     0.7391 0.976 0.000 0.000 0.024
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0921     0.7391 0.972 0.000 0.000 0.028
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     4  0.4804     0.7921 0.384 0.000 0.000 0.616
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5675     0.9085 0.048 0.004 0.676 0.272
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0657     0.8193 0.000 0.984 0.004 0.012
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4454     0.2629 0.692 0.000 0.000 0.308
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.8733     0.6433 0.048 0.220 0.404 0.328
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     4  0.4713     0.7878 0.360 0.000 0.000 0.640
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     4  0.4817     0.7923 0.388 0.000 0.000 0.612
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.1792     0.7021 0.932 0.000 0.000 0.068
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4933    -0.4086 0.568 0.000 0.000 0.432
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.2011     0.7067 0.920 0.000 0.000 0.080
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0376     0.8229 0.000 0.992 0.004 0.004
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.3444     0.8530 0.000 0.816 0.184 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.4957     0.8721 0.012 0.000 0.668 0.320
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     4  0.4877     0.7634 0.408 0.000 0.000 0.592
#> D47D0936-826F-4D54-9225-F71B95357438     4  0.6907     0.4480 0.172 0.000 0.240 0.588
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0188     0.8245 0.000 0.996 0.004 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.5355     0.7888 0.020 0.000 0.620 0.360
#> D587A993-3C47-4D4C-B744-59169D4F7451     4  0.4697     0.7900 0.356 0.000 0.000 0.644
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.5642     0.5510 0.704 0.004 0.064 0.228
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.1389     0.7405 0.952 0.000 0.000 0.048
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     4  0.4713     0.7894 0.360 0.000 0.000 0.640
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.5672     0.9087 0.056 0.000 0.668 0.276
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.7031     0.1988 0.536 0.000 0.140 0.324
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     4  0.4855     0.7754 0.400 0.000 0.000 0.600
#> 7822EA86-35A1-4285-9429-2B63111B9885     4  0.4697     0.7900 0.356 0.000 0.000 0.644
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     4  0.5821     0.7541 0.368 0.040 0.000 0.592
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.5599     0.9091 0.052 0.000 0.672 0.276
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     4  0.4817     0.7923 0.388 0.000 0.000 0.612
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.1109     0.8107 0.000 0.968 0.004 0.028
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     4  0.4697     0.7900 0.356 0.000 0.000 0.644
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.5524     0.9089 0.048 0.000 0.676 0.276
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.5972     0.8927 0.064 0.000 0.632 0.304
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.2814     0.7110 0.868 0.000 0.000 0.132
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     4  0.4804     0.7921 0.384 0.000 0.000 0.616
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     4  0.4746     0.7914 0.368 0.000 0.000 0.632
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     4  0.4697     0.7900 0.356 0.000 0.000 0.644
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0921     0.7451 0.972 0.000 0.000 0.028
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.1867     0.6996 0.928 0.000 0.000 0.072
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.2596     0.7343 0.908 0.000 0.024 0.068
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.2593     0.7228 0.892 0.000 0.004 0.104
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.6136     0.3721 0.632 0.000 0.080 0.288
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0707     0.7407 0.980 0.000 0.000 0.020
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.9262     0.5479 0.196 0.208 0.452 0.144
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.1209     0.8082 0.000 0.964 0.004 0.032
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#> EFE5A302-D138-4044-A301-5C5FD1C24836     4  0.4817     0.7923 0.388 0.000 0.000 0.612
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.7952     0.3459 0.584 0.100 0.096 0.220
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6227     0.8689 0.056 0.004 0.588 0.352
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6078     0.3879 0.620 0.000 0.068 0.312
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.7746     0.5736 0.140 0.120 0.116 0.624
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.7283     0.7731 0.208 0.000 0.536 0.256
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.7710     0.6793 0.028 0.180 0.564 0.228
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1867     0.6964 0.928 0.000 0.000 0.072
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     4  0.4804     0.7927 0.384 0.000 0.000 0.616
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0188     0.8245 0.000 0.996 0.004 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0336     0.7442 0.992 0.000 0.000 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.1771     0.7978 0.004 0.948 0.012 0.036
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1022     0.7428 0.968 0.000 0.000 0.032
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.7710     0.6704 0.224 0.000 0.408 0.368
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6758     0.8611 0.104 0.004 0.580 0.312
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.3860     0.6705 0.852 0.104 0.032 0.012
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2921     0.7076 0.860 0.000 0.000 0.140
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4562     0.6734 0.792 0.000 0.056 0.152
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1302     0.7442 0.956 0.000 0.000 0.044
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.5599     0.9091 0.052 0.000 0.672 0.276
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     4  0.5773    -0.1698 0.044 0.000 0.336 0.620
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6682     0.3026 0.576 0.000 0.112 0.312
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.7309     0.1519 0.528 0.000 0.200 0.272
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1118     0.7351 0.964 0.000 0.000 0.036
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.4713     0.7722 0.360 0.000 0.000 0.640
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.4543     0.8648 0.000 0.676 0.324 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.5599     0.9091 0.052 0.000 0.672 0.276
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3444     0.6765 0.816 0.000 0.000 0.184
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.4761     0.7924 0.372 0.000 0.000 0.628
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2345     0.6703 0.900 0.000 0.000 0.100

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4452    0.33748 0.164 0.000 0.072 0.760 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.6107    0.58969 0.132 0.000 0.616 0.232 0.020
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2962    0.79936 0.868 0.000 0.000 0.084 0.048
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4349    0.76963 0.756 0.000 0.000 0.068 0.176
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0771    0.87425 0.020 0.000 0.000 0.004 0.976
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2790    0.77067 0.000 0.068 0.880 0.052 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1364    0.85542 0.012 0.000 0.000 0.036 0.952
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1697    0.79909 0.932 0.000 0.000 0.060 0.008
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.1469    0.87327 0.036 0.000 0.000 0.016 0.948
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4269    0.76972 0.776 0.000 0.000 0.108 0.116
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.4288    0.83127 0.004 0.384 0.000 0.612 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.5989    0.57322 0.620 0.000 0.124 0.240 0.016
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0162    0.82955 0.000 0.000 0.996 0.004 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0609    0.82506 0.000 0.000 0.980 0.020 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2824    0.80213 0.872 0.000 0.000 0.032 0.096
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0510    0.87367 0.016 0.000 0.000 0.000 0.984
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4558    0.43415 0.000 0.000 0.652 0.024 0.324
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4297    0.77630 0.764 0.000 0.000 0.072 0.164
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2879    0.80431 0.868 0.000 0.000 0.032 0.100
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2193    0.78620 0.900 0.000 0.000 0.092 0.008
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.5661    0.39681 0.272 0.000 0.000 0.120 0.608
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0290    0.82888 0.000 0.000 0.992 0.008 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.6062    0.30733 0.336 0.000 0.540 0.120 0.004
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0162    0.93098 0.004 0.996 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.1041    0.87496 0.032 0.000 0.000 0.004 0.964
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.1750    0.87199 0.028 0.000 0.000 0.036 0.936
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2130    0.80758 0.908 0.000 0.000 0.012 0.080
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.2793    0.84867 0.088 0.000 0.000 0.036 0.876
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2707    0.76958 0.860 0.000 0.008 0.132 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.5321    0.63250 0.108 0.000 0.016 0.172 0.704
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2522    0.78248 0.880 0.000 0.000 0.108 0.012
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.4384    0.71416 0.728 0.000 0.000 0.044 0.228
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.4138    0.83093 0.000 0.384 0.000 0.616 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0162    0.82955 0.000 0.000 0.996 0.004 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4221    0.77193 0.780 0.000 0.000 0.108 0.112
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.5083    0.19233 0.000 0.000 0.432 0.036 0.532
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.6066    0.36556 0.516 0.000 0.000 0.132 0.352
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.0955    0.87459 0.028 0.000 0.000 0.004 0.968
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.4138    0.83093 0.000 0.384 0.000 0.616 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4317    0.76763 0.772 0.000 0.000 0.116 0.112
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.4403    0.82993 0.008 0.384 0.000 0.608 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2707    0.77242 0.860 0.000 0.008 0.132 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2408    0.78299 0.892 0.000 0.004 0.096 0.008
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0609    0.82567 0.000 0.000 0.980 0.020 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1942    0.80270 0.000 0.000 0.920 0.068 0.012
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.2616    0.85118 0.036 0.000 0.000 0.076 0.888
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2439    0.74887 0.004 0.876 0.000 0.120 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2361    0.80341 0.892 0.000 0.000 0.012 0.096
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.0865    0.87425 0.024 0.000 0.000 0.004 0.972
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.6133   -0.06300 0.436 0.000 0.000 0.128 0.436
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.4827    0.73956 0.016 0.000 0.136 0.096 0.752
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2104    0.80798 0.916 0.000 0.000 0.024 0.060
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2069    0.79899 0.000 0.000 0.912 0.076 0.012
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4365    0.76509 0.768 0.000 0.000 0.116 0.116
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.3064    0.80394 0.000 0.000 0.108 0.036 0.856
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.4288    0.83127 0.004 0.384 0.000 0.612 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.0290    0.87153 0.008 0.000 0.000 0.000 0.992
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.2234    0.86665 0.044 0.000 0.004 0.036 0.916
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4907   -0.03962 0.000 0.000 0.488 0.024 0.488
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.2983    0.80136 0.864 0.000 0.000 0.040 0.096
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4221    0.77193 0.780 0.000 0.000 0.108 0.112
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.0992    0.87431 0.024 0.000 0.000 0.008 0.968
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.1216    0.87491 0.020 0.000 0.000 0.020 0.960
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.4088    0.82135 0.000 0.368 0.000 0.632 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.5773    0.30454 0.512 0.000 0.000 0.092 0.396
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.7425    0.37169 0.048 0.120 0.508 0.300 0.024
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.0162    0.86988 0.004 0.000 0.000 0.000 0.996
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.1965    0.86749 0.052 0.000 0.000 0.024 0.924
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2983    0.80559 0.864 0.000 0.000 0.040 0.096
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     5  0.6194    0.12495 0.388 0.000 0.000 0.140 0.472
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.5113    0.71915 0.708 0.000 0.004 0.128 0.160
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.4288    0.83127 0.004 0.384 0.000 0.612 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.4201   -0.32256 0.000 0.592 0.000 0.408 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0865    0.82279 0.000 0.000 0.972 0.004 0.024
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.2616    0.83977 0.100 0.000 0.000 0.020 0.880
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.5132    0.42025 0.008 0.000 0.344 0.036 0.612
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.4288    0.82997 0.004 0.384 0.000 0.612 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.1522    0.80492 0.000 0.000 0.944 0.012 0.044
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.1195    0.87119 0.028 0.000 0.000 0.012 0.960
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.1469    0.87315 0.036 0.000 0.000 0.016 0.948
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.4039    0.75762 0.784 0.000 0.044 0.168 0.004
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.3601    0.78368 0.820 0.000 0.000 0.128 0.052
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.3517    0.81352 0.068 0.000 0.000 0.100 0.832
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0162    0.82955 0.000 0.000 0.996 0.004 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.6155    0.55584 0.608 0.000 0.132 0.240 0.020
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.2464    0.84798 0.096 0.000 0.000 0.016 0.888
#> 7822EA86-35A1-4285-9429-2B63111B9885     5  0.1836    0.86769 0.032 0.000 0.000 0.036 0.932
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     5  0.3805    0.80119 0.084 0.004 0.000 0.092 0.820
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.1836    0.86975 0.032 0.000 0.000 0.036 0.932
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.4276    0.83008 0.004 0.380 0.000 0.616 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.1741    0.86930 0.040 0.000 0.000 0.024 0.936
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.2554    0.78392 0.036 0.000 0.892 0.072 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.2411    0.77597 0.884 0.000 0.008 0.108 0.000
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#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.3583    0.74394 0.808 0.000 0.008 0.168 0.016
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.4774    0.20147 0.000 0.000 0.556 0.020 0.424
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.2669    0.84591 0.104 0.000 0.000 0.020 0.876
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.5895    0.28574 0.040 0.000 0.384 0.036 0.540
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.6653    0.42773 0.484 0.000 0.008 0.192 0.316
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0703    0.87427 0.024 0.000 0.000 0.000 0.976
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.6992    0.28742 0.304 0.000 0.464 0.212 0.020
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4022    0.77986 0.796 0.000 0.000 0.104 0.100
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3327    0.78562 0.828 0.000 0.000 0.028 0.144
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5275    0.74206 0.740 0.000 0.076 0.120 0.064
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.5161    0.64418 0.160 0.000 0.732 0.036 0.072
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4266    0.76979 0.776 0.000 0.000 0.120 0.104
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.2729    0.80499 0.884 0.000 0.000 0.060 0.056
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.6265    0.53733 0.596 0.000 0.144 0.240 0.020
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3794    0.75773 0.800 0.000 0.000 0.152 0.048
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2295    0.78347 0.900 0.000 0.008 0.088 0.004
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.5296   -0.25212 0.472 0.000 0.000 0.480 0.048
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0703    0.87418 0.024 0.000 0.000 0.000 0.976
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4462    0.73256 0.740 0.000 0.000 0.064 0.196
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2712    0.84991 0.088 0.000 0.000 0.032 0.880
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5414    0.67326 0.656 0.000 0.100 0.240 0.004
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4400    0.71068 0.048 0.000 0.772 0.164 0.016
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4902    0.72778 0.712 0.000 0.048 0.224 0.016
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.1996    0.84477 0.012 0.048 0.000 0.012 0.928
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5109    0.62451 0.188 0.000 0.708 0.096 0.008
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.6051    0.29992 0.000 0.000 0.476 0.404 0.120
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3192    0.79303 0.848 0.000 0.000 0.040 0.112
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1168    0.87374 0.032 0.000 0.000 0.008 0.960
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.4288    0.83127 0.004 0.384 0.000 0.612 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2505    0.80505 0.888 0.000 0.000 0.020 0.092
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.4193    0.75806 0.000 0.304 0.012 0.684 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3608    0.78442 0.824 0.000 0.000 0.112 0.064
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.7215    0.17555 0.328 0.000 0.412 0.236 0.024
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4617    0.67590 0.148 0.000 0.744 0.108 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.3647    0.78340 0.840 0.028 0.000 0.100 0.032
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2563    0.77399 0.872 0.000 0.008 0.120 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5432    0.69286 0.712 0.000 0.064 0.172 0.052
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2818    0.78550 0.856 0.000 0.000 0.132 0.012
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4829   -0.00144 0.000 0.000 0.496 0.020 0.484
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.5755    0.60627 0.640 0.000 0.100 0.244 0.016
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6687    0.54332 0.584 0.000 0.228 0.136 0.052
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4221    0.77193 0.780 0.000 0.000 0.108 0.112
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.1943    0.85004 0.020 0.000 0.000 0.056 0.924
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.93446 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.83040 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2513    0.77513 0.876 0.000 0.008 0.116 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0510    0.87367 0.016 0.000 0.000 0.000 0.984
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3182    0.79315 0.844 0.000 0.000 0.032 0.124

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.6671    0.06994 0.152 0.000 0.032 0.412 0.016 0.388
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0146    0.76684 0.000 0.000 0.996 0.004 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.4998    0.34048 0.036 0.000 0.336 0.016 0.008 0.604
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3717    0.36061 0.708 0.000 0.000 0.000 0.016 0.276
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4941    0.33160 0.660 0.000 0.000 0.008 0.104 0.228
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1798    0.81059 0.020 0.000 0.000 0.028 0.932 0.020
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.3433    0.67402 0.004 0.032 0.832 0.024 0.000 0.108
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0508    0.94287 0.004 0.984 0.000 0.000 0.000 0.012
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1970    0.79947 0.008 0.000 0.000 0.044 0.920 0.028
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2592    0.53847 0.864 0.000 0.000 0.004 0.016 0.116
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.3044    0.81460 0.048 0.000 0.000 0.036 0.864 0.052
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3603    0.55022 0.816 0.000 0.000 0.036 0.032 0.116
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0146    0.76684 0.000 0.000 0.996 0.004 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.4117    0.87166 0.000 0.192 0.000 0.740 0.004 0.064
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.5162    0.61619 0.268 0.000 0.076 0.016 0.004 0.636
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0405    0.76603 0.000 0.000 0.988 0.008 0.000 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.2860    0.72297 0.000 0.000 0.868 0.068 0.012 0.052
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0914    0.57959 0.968 0.000 0.000 0.000 0.016 0.016
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1138    0.81423 0.012 0.000 0.000 0.004 0.960 0.024
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5218    0.58437 0.000 0.000 0.668 0.068 0.212 0.052
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0146    0.94488 0.000 0.996 0.000 0.000 0.000 0.004
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4886    0.33115 0.664 0.000 0.000 0.012 0.084 0.240
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3517    0.52153 0.804 0.000 0.000 0.004 0.056 0.136
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3628    0.35658 0.720 0.000 0.000 0.004 0.008 0.268
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.76711 0.000 0.000 1.000 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.6231   -0.02493 0.240 0.000 0.000 0.012 0.448 0.300
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0717    0.76115 0.000 0.000 0.976 0.008 0.000 0.016
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.6883   -0.13853 0.172 0.000 0.440 0.044 0.016 0.328
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.94479 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.2145    0.87161 0.000 0.900 0.000 0.028 0.000 0.072
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.2565    0.81372 0.040 0.000 0.000 0.040 0.892 0.028
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.3074    0.79569 0.016 0.000 0.000 0.068 0.856 0.060
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1624    0.57126 0.936 0.000 0.000 0.004 0.020 0.040
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.5721    0.68543 0.176 0.000 0.008 0.080 0.656 0.080
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0653    0.94144 0.004 0.980 0.000 0.004 0.000 0.012
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.4151    0.06131 0.576 0.000 0.004 0.008 0.000 0.412
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4433    0.52685 0.016 0.000 0.000 0.024 0.656 0.304
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0405    0.94390 0.004 0.988 0.000 0.000 0.000 0.008
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.4115    0.19551 0.624 0.000 0.000 0.004 0.012 0.360
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.5593    0.32738 0.616 0.000 0.000 0.024 0.204 0.156
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.3284    0.87824 0.000 0.196 0.000 0.784 0.000 0.020
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0767    0.76397 0.000 0.000 0.976 0.008 0.004 0.012
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0405    0.76580 0.000 0.000 0.988 0.008 0.000 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3603    0.54885 0.816 0.000 0.000 0.036 0.032 0.116
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.6558    0.29762 0.016 0.000 0.488 0.076 0.344 0.076
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     6  0.6269    0.31620 0.288 0.000 0.000 0.008 0.296 0.408
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.2602    0.80446 0.020 0.000 0.000 0.052 0.888 0.040
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0146    0.94488 0.000 0.996 0.000 0.000 0.000 0.004
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0405    0.76596 0.000 0.000 0.988 0.008 0.000 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.3253    0.87790 0.000 0.192 0.000 0.788 0.000 0.020
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3869    0.53722 0.796 0.000 0.000 0.040 0.036 0.128
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.3978    0.87374 0.000 0.192 0.000 0.744 0.000 0.064
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000    0.76711 0.000 0.000 1.000 0.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.5112   -0.02313 0.540 0.000 0.020 0.028 0.008 0.404
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3774    0.26208 0.664 0.000 0.000 0.000 0.008 0.328
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1245    0.74965 0.000 0.000 0.952 0.016 0.000 0.032
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2302    0.69515 0.000 0.000 0.872 0.008 0.000 0.120
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.4134    0.73957 0.040 0.000 0.000 0.064 0.784 0.112
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3626    0.70891 0.000 0.788 0.000 0.144 0.000 0.068
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2065    0.57529 0.912 0.000 0.000 0.004 0.032 0.052
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.1959    0.81050 0.024 0.000 0.000 0.032 0.924 0.020
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.6295    0.34384 0.568 0.000 0.000 0.072 0.176 0.184
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.7268    0.52291 0.040 0.000 0.132 0.124 0.524 0.180
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1297    0.56967 0.948 0.000 0.000 0.000 0.012 0.040
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0146    0.94488 0.000 0.996 0.000 0.000 0.000 0.004
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2446    0.68726 0.000 0.000 0.864 0.012 0.000 0.124
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3730    0.54144 0.804 0.000 0.000 0.032 0.036 0.128
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.5363    0.66463 0.016 0.000 0.124 0.072 0.708 0.080
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0405    0.76550 0.000 0.000 0.988 0.008 0.000 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.4117    0.87166 0.000 0.192 0.000 0.740 0.004 0.064
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.1148    0.81314 0.016 0.000 0.000 0.004 0.960 0.020
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.5041    0.74478 0.080 0.000 0.024 0.076 0.744 0.076
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.5943    0.30518 0.000 0.000 0.504 0.068 0.368 0.060
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1341    0.58184 0.948 0.000 0.000 0.000 0.028 0.024
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3689    0.54635 0.808 0.000 0.000 0.036 0.032 0.124
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.1944    0.81359 0.024 0.000 0.000 0.016 0.924 0.036
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.2195    0.81623 0.024 0.000 0.000 0.028 0.912 0.036
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.94479 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0405    0.76550 0.000 0.000 0.988 0.008 0.000 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.3831    0.85766 0.004 0.168 0.004 0.776 0.000 0.048
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.6338   -0.23166 0.340 0.000 0.000 0.008 0.312 0.340
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.6448    0.01422 0.004 0.040 0.368 0.100 0.012 0.476
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.1148    0.81314 0.016 0.000 0.000 0.004 0.960 0.020
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.4082    0.77511 0.096 0.000 0.000 0.048 0.792 0.064
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3980    0.47110 0.760 0.000 0.000 0.004 0.068 0.168
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5895    0.37379 0.612 0.000 0.000 0.056 0.148 0.184
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.5157    0.48332 0.692 0.000 0.000 0.048 0.100 0.160
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.3946    0.87496 0.000 0.192 0.000 0.752 0.004 0.052
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#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0146    0.94488 0.000 0.996 0.000 0.000 0.000 0.004
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0692    0.93379 0.000 0.976 0.000 0.004 0.000 0.020
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.5549    0.55302 0.000 0.000 0.632 0.072 0.232 0.064
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0405    0.76550 0.000 0.000 0.988 0.008 0.000 0.004
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.2755    0.80999 0.016 0.000 0.000 0.068 0.876 0.040
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.1230    0.81464 0.028 0.000 0.000 0.008 0.956 0.008
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.1116    0.81426 0.028 0.000 0.000 0.004 0.960 0.008
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000    0.76711 0.000 0.000 1.000 0.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0806    0.75950 0.000 0.000 0.972 0.008 0.000 0.020
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.1871    0.81640 0.032 0.000 0.000 0.016 0.928 0.024
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.3303    0.79616 0.048 0.000 0.000 0.044 0.848 0.060
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0508    0.94244 0.004 0.984 0.000 0.000 0.000 0.012
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1826    0.56660 0.924 0.000 0.000 0.004 0.020 0.052
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0806    0.75960 0.000 0.000 0.972 0.008 0.000 0.020
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     6  0.5447    0.62089 0.236 0.000 0.108 0.008 0.016 0.632
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.3691    0.87246 0.004 0.192 0.000 0.768 0.000 0.036
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2696    0.84267 0.000 0.872 0.000 0.048 0.004 0.076
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.4542    0.62654 0.176 0.000 0.000 0.008 0.716 0.100
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.3946    0.87496 0.000 0.192 0.000 0.752 0.004 0.052
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0458    0.93908 0.000 0.984 0.000 0.000 0.000 0.016
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.6437    0.41462 0.116 0.000 0.592 0.060 0.028 0.204
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4446    0.11833 0.588 0.000 0.000 0.008 0.020 0.384
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3091    0.76016 0.004 0.824 0.000 0.148 0.000 0.024
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0260    0.94463 0.000 0.992 0.000 0.000 0.000 0.008
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0260    0.76625 0.000 0.000 0.992 0.008 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.4642    0.75691 0.092 0.000 0.000 0.076 0.752 0.080
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.5927    0.66575 0.056 0.000 0.108 0.076 0.680 0.080
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.5096   -0.11660 0.000 0.536 0.000 0.388 0.004 0.072
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.3652    0.80037 0.028 0.000 0.000 0.080 0.820 0.072
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.3758    0.87786 0.000 0.192 0.000 0.764 0.004 0.040
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.2351    0.81174 0.036 0.000 0.000 0.028 0.904 0.032
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0909    0.81367 0.012 0.000 0.000 0.000 0.968 0.020
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     6  0.4621    0.21902 0.476 0.000 0.004 0.016 0.008 0.496
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.5894    0.31394 0.000 0.000 0.508 0.068 0.368 0.056
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.3847    0.75906 0.136 0.000 0.000 0.004 0.780 0.080
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0508    0.94287 0.004 0.984 0.000 0.000 0.000 0.012
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.7409    0.20045 0.076 0.000 0.436 0.080 0.328 0.080
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.5729    0.44859 0.324 0.000 0.000 0.008 0.148 0.520
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.1180    0.81545 0.016 0.000 0.000 0.012 0.960 0.012
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     6  0.6241    0.55969 0.208 0.000 0.232 0.008 0.020 0.532
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.3292    0.55338 0.836 0.000 0.000 0.032 0.024 0.108
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2076    0.57846 0.912 0.000 0.000 0.012 0.060 0.016
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5416    0.06311 0.556 0.000 0.020 0.020 0.036 0.368
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.6506    0.49628 0.184 0.000 0.608 0.076 0.052 0.080
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4069    0.52761 0.780 0.000 0.000 0.052 0.032 0.136
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3813    0.43958 0.744 0.000 0.000 0.008 0.024 0.224
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.5233    0.62097 0.252 0.000 0.080 0.016 0.008 0.644
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4962   -0.10088 0.516 0.000 0.000 0.008 0.048 0.428
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0508    0.94287 0.004 0.984 0.000 0.000 0.000 0.012
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3867    0.28478 0.688 0.000 0.004 0.012 0.000 0.296
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.6856    0.11203 0.416 0.000 0.000 0.248 0.056 0.280
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.1232    0.81560 0.024 0.000 0.000 0.004 0.956 0.016
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.6618    0.28140 0.572 0.000 0.020 0.072 0.180 0.156
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.4835    0.72723 0.160 0.000 0.000 0.052 0.720 0.068
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.94479 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     6  0.6037    0.00234 0.432 0.000 0.048 0.056 0.012 0.452
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4481    0.22514 0.000 0.000 0.556 0.024 0.004 0.416
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     6  0.5622    0.03240 0.456 0.000 0.040 0.032 0.012 0.460
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.4165    0.74179 0.012 0.012 0.000 0.088 0.784 0.104
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6301    0.42611 0.232 0.000 0.572 0.060 0.008 0.128
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.7668    0.23167 0.028 0.000 0.360 0.320 0.092 0.200
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2144    0.57660 0.908 0.000 0.000 0.004 0.048 0.040
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.2763    0.80536 0.052 0.000 0.000 0.028 0.880 0.040
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.4117    0.87166 0.000 0.192 0.000 0.740 0.004 0.064
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.1334    0.57389 0.948 0.000 0.000 0.000 0.020 0.032
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.3517    0.82947 0.004 0.128 0.004 0.812 0.000 0.052
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3986    0.52389 0.780 0.000 0.000 0.044 0.028 0.148
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.5779    0.59365 0.160 0.000 0.176 0.020 0.016 0.628
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5249    0.36131 0.068 0.000 0.636 0.036 0.000 0.260
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4313    0.46629 0.712 0.004 0.000 0.028 0.016 0.240
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4418    0.07251 0.584 0.000 0.004 0.016 0.004 0.392
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4852   -0.33783 0.480 0.000 0.012 0.004 0.024 0.480
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3991    0.48326 0.744 0.000 0.000 0.028 0.016 0.212
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0291    0.76714 0.000 0.000 0.992 0.004 0.000 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5919    0.23987 0.000 0.000 0.488 0.072 0.388 0.052
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.5105    0.59931 0.288 0.000 0.056 0.016 0.008 0.632
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.7189    0.34285 0.348 0.000 0.176 0.036 0.040 0.400
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3300    0.55328 0.832 0.000 0.000 0.020 0.032 0.116
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3286    0.77038 0.044 0.000 0.000 0.012 0.832 0.112
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0146    0.94488 0.000 0.996 0.000 0.000 0.000 0.004
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0603    0.94201 0.004 0.980 0.000 0.000 0.000 0.016
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0260    0.76625 0.000 0.000 0.992 0.008 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4315    0.10466 0.596 0.000 0.004 0.012 0.004 0.384
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.1773    0.81158 0.016 0.000 0.000 0.036 0.932 0.016
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1909    0.58133 0.920 0.000 0.000 0.004 0.052 0.024

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-kmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-kmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


SD:skmeans*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "skmeans"]
# you can also extract it by
# res = res_list["SD:skmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.933           0.948       0.978         0.4825 0.515   0.515
#> 3 3 0.833           0.906       0.956         0.3365 0.770   0.583
#> 4 4 0.846           0.851       0.934         0.1596 0.829   0.562
#> 5 5 0.807           0.781       0.883         0.0611 0.906   0.660
#> 6 6 0.774           0.760       0.858         0.0445 0.938   0.713

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000      0.965 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.9732      0.305 0.596 0.404
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     2  0.0000      0.965 0.000 1.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.985 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.985 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.985 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.965 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.965 0.000 1.000
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#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000      0.985 1.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000      0.965 0.000 1.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000      0.985 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0000      0.985 1.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000      0.965 0.000 1.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000      0.965 0.000 1.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000      0.965 0.000 1.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000      0.985 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000      0.985 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000      0.985 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000      0.985 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000      0.985 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000      0.965 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.0000      0.985 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000      0.985 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     2  0.8555      0.629 0.280 0.720
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000      0.985 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.0000      0.965 0.000 1.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000      0.985 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000      0.985 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000      0.985 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000      0.985 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000      0.985 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.0000      0.965 0.000 1.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000      0.985 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000      0.965 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000      0.965 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     2  0.0000      0.965 0.000 1.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000      0.985 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000      0.985 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000      0.985 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000      0.985 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000      0.965 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     2  0.0000      0.965 0.000 1.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     2  0.0000      0.965 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.985 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.985 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000      0.965 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     2  0.9323      0.489 0.348 0.652
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000      0.965 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.965 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.965 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000      0.985 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     2  0.0000      0.965 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000      0.985 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.985 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.985 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     2  0.9933      0.202 0.452 0.548
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     2  0.0000      0.965 0.000 1.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.985 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.985 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.965 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000      0.985 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     2  0.0000      0.965 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000      0.985 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.965 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.965 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.985 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.965 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.965 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.985 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.985 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.965 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.965 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     2  0.0000      0.965 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.985 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.985 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.965 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.985 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.965 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.985 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.985 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.985 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.985 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.985 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.965 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.985 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.985 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.985 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.985 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.985 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.985 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.985 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.985 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.985 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.985 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.985 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.985 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.965 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.985 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.3274      0.916 0.060 0.940
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.985 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.985 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.985 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.965 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.0000      0.965 0.000 1.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000      0.965 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000      0.965 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.965 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.985 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.7950      0.701 0.240 0.760
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.985 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.985 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.965 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.985 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.965 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.985 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0672      0.978 0.992 0.008
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     2  0.0000      0.965 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.965 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.985 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.985 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.3733      0.905 0.072 0.928
#> CE6B6871-3ED3-44DE-A777-7558D4429057     2  0.6438      0.805 0.164 0.836
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.0000      0.965 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     2  0.0672      0.959 0.008 0.992
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.985 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.985 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.985 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.965 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.965 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     2  0.6438      0.805 0.164 0.836
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.985 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.985 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.985 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.4555    0.73969 0.000 0.800 0.200
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.93014 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000    0.93014 0.000 0.000 1.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.95170 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.95170 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000    0.95170 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6168    0.31530 0.000 0.412 0.588
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.97140 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5635    0.76231 0.784 0.036 0.180
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000    0.95170 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.95170 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000    0.95170 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.93014 0.000 0.000 1.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.97140 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0000    0.93014 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.93014 0.000 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000    0.93014 0.000 0.000 1.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000    0.95170 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000    0.95170 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0592    0.92448 0.012 0.000 0.988
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.97140 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.95170 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000    0.95170 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.95170 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.93014 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4555    0.77278 0.800 0.000 0.200
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000    0.93014 0.000 0.000 1.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0000    0.93014 0.000 0.000 1.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.97140 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.97140 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000    0.95170 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000    0.95170 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.95170 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000    0.95170 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.97140 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.7543    0.58985 0.216 0.680 0.104
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     2  0.4555    0.72411 0.000 0.800 0.200
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.97140 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000    0.95170 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000    0.95170 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.97140 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000    0.93014 0.000 0.000 1.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000    0.93014 0.000 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000    0.95170 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4504    0.76328 0.196 0.000 0.804
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.5254    0.69104 0.736 0.000 0.264
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#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.5098    0.68715 0.752 0.000 0.248
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000    0.95170 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.4555    0.77278 0.800 0.000 0.200
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000    0.95170 1.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000    0.97140 0.000 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0747    0.92106 0.000 0.016 0.984
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000    0.93014 0.000 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.95170 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000    0.95170 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000    0.97140 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000    0.93014 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.97140 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.97140 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.97140 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0000    0.93014 0.000 0.000 1.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000    0.93014 0.000 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.3551    0.84408 0.868 0.000 0.132
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.95170 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000    0.95170 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000    0.93014 0.000 0.000 1.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000    0.93014 0.000 0.000 1.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000    0.95170 1.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000    0.95170 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.97140 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000    0.95170 1.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000    0.93014 0.000 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0000    0.93014 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.97140 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.97140 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000    0.95170 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.97140 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.97140 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.0892    0.92025 0.020 0.000 0.980
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.2261    0.90582 0.932 0.000 0.068
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.97140 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.97140 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000    0.93014 0.000 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000    0.95170 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.6045    0.43078 0.380 0.000 0.620
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.97140 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000    0.95170 1.000 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.97140 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.95170 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0237    0.94963 0.996 0.000 0.004
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.3482    0.85696 0.872 0.000 0.128
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0237    0.92840 0.004 0.000 0.996
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000    0.95170 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.97140 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.5058    0.69347 0.244 0.000 0.756
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4702    0.75834 0.788 0.000 0.212
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0424    0.94733 0.992 0.000 0.008
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000    0.93014 0.000 0.000 1.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000    0.95170 1.000 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.95170 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.5968    0.43269 0.364 0.000 0.636
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.4796    0.72301 0.220 0.000 0.780
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000    0.95170 1.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.2625    0.88998 0.916 0.000 0.084
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000    0.93014 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1860    0.91927 0.948 0.000 0.052
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.97140 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0892    0.94020 0.980 0.000 0.020
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.2066    0.90382 0.060 0.940 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000    0.95170 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000    0.95170 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.95170 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.97140 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.5573    0.75087 0.044 0.160 0.796
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0592    0.92351 0.000 0.012 0.988
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.4099    0.79699 0.008 0.140 0.852
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000    0.97140 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000    0.93014 0.000 0.000 1.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4750    0.70052 0.000 0.216 0.784
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.95170 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.95170 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.97140 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.95170 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000    0.97140 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0237    0.94951 0.996 0.000 0.004
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000    0.93014 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000    0.93014 0.000 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000    0.97140 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.1643    0.92465 0.956 0.000 0.044
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4605    0.76846 0.796 0.000 0.204
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5058    0.67409 0.756 0.244 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.93014 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3879    0.80013 0.000 0.152 0.848
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0237    0.92821 0.000 0.004 0.996
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.3116    0.85568 0.108 0.000 0.892
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.95170 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4121    0.80721 0.832 0.000 0.168
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.97140 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.97140 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.93014 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4974    0.70298 0.764 0.000 0.236
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000    0.95170 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000    0.95170 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.3768     0.7561 0.008 0.808 0.184 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0188     0.8839 0.004 0.000 0.996 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4713     0.4160 0.640 0.000 0.000 0.360
#> 03E81178-E971-4E91-8BED-D8273EA1425C     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4941     0.2338 0.000 0.436 0.564 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.4454     0.6063 0.692 0.000 0.308 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.3569     0.7294 0.000 0.000 0.804 0.196
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4431     0.5415 0.696 0.000 0.000 0.304
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     4  0.2760     0.8112 0.128 0.000 0.000 0.872
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3400     0.7404 0.820 0.180 0.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.4313     0.6193 0.004 0.260 0.000 0.736
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     4  0.4697     0.4490 0.356 0.000 0.000 0.644
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4730     0.5032 0.000 0.000 0.636 0.364
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     4  0.4123     0.7001 0.220 0.000 0.008 0.772
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2814     0.8081 0.868 0.000 0.132 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.5645     0.3791 0.364 0.032 0.000 0.604
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.4985    -0.0392 0.000 0.000 0.468 0.532
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#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     4  0.4888     0.3138 0.412 0.000 0.000 0.588
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0592     0.8789 0.000 0.000 0.984 0.016
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.4585     0.4051 0.332 0.000 0.668 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     4  0.1302     0.8881 0.044 0.000 0.000 0.956
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.2563     0.8344 0.020 0.000 0.908 0.072
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     4  0.0188     0.9191 0.000 0.000 0.004 0.996
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.4103     0.6610 0.000 0.000 0.744 0.256
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.4643     0.5406 0.000 0.000 0.656 0.344
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     4  0.5130     0.5222 0.312 0.000 0.020 0.668
#> D365A238-4739-4B54-9608-DC548F21C04E     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0188     0.8839 0.004 0.000 0.996 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.1211     0.8806 0.960 0.000 0.000 0.040
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.3751     0.7449 0.800 0.000 0.196 0.004
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.4525     0.7599 0.116 0.000 0.804 0.080
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0336     0.9006 0.992 0.000 0.000 0.008
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.2469     0.8263 0.892 0.000 0.108 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4730     0.5121 0.636 0.000 0.364 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4543     0.5025 0.676 0.000 0.000 0.324
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.6262     0.4993 0.280 0.628 0.000 0.092
#> 9AF0E82E-E621-437A-8D19-700532B95090     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     4  0.7506     0.1921 0.208 0.000 0.308 0.484
#> EFE5A302-D138-4044-A301-5C5FD1C24836     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3764     0.7183 0.784 0.000 0.216 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.3907     0.6492 0.000 0.232 0.768 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3311     0.7685 0.828 0.000 0.172 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0336     0.8814 0.008 0.000 0.992 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.5454     0.7077 0.000 0.096 0.732 0.172
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0188     0.8839 0.004 0.000 0.996 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1302     0.8552 0.044 0.000 0.956 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4079     0.7532 0.800 0.000 0.180 0.020
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5257     0.6844 0.000 0.060 0.728 0.212
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.3975     0.7031 0.760 0.000 0.240 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4610     0.6330 0.236 0.000 0.744 0.020
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0188     0.9022 0.996 0.000 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.0188     0.9194 0.004 0.000 0.000 0.996
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9831 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8859 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.9018 1.000 0.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.0000     0.9221 0.000 0.000 0.000 1.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0921     0.8886 0.972 0.000 0.000 0.028

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.7289     0.2519 0.152 0.448 0.044 0.352 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.3966     0.3550 0.664 0.000 0.336 0.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3143     0.6412 0.796 0.000 0.000 0.204 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.5505     0.4736 0.604 0.000 0.000 0.092 0.304
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0000     0.9098 0.000 0.000 0.000 0.000 1.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4978     0.0464 0.028 0.476 0.496 0.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.0000     0.9098 0.000 0.000 0.000 0.000 1.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     4  0.3752     0.6783 0.292 0.000 0.000 0.708 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.1043     0.9050 0.000 0.000 0.000 0.040 0.960
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0609     0.7402 0.980 0.000 0.020 0.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     4  0.3336     0.7376 0.228 0.000 0.000 0.772 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0794     0.8930 0.000 0.000 0.972 0.000 0.028
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.5303     0.5515 0.660 0.000 0.000 0.108 0.232
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4731     0.0702 0.528 0.000 0.000 0.456 0.016
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3895     0.4568 0.680 0.000 0.000 0.320 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4526     0.5076 0.672 0.000 0.000 0.028 0.300
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.2424     0.8099 0.132 0.000 0.868 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.1270     0.8916 0.000 0.000 0.000 0.052 0.948
#> 904EDF2E-411E-43BD-901D-46129AFA283A     4  0.3684     0.6789 0.280 0.000 0.000 0.720 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.2329     0.8544 0.000 0.000 0.000 0.124 0.876
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1818     0.7345 0.932 0.044 0.000 0.024 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.5375     0.1054 0.452 0.004 0.000 0.044 0.500
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1478     0.7349 0.936 0.000 0.000 0.064 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.6075     0.2875 0.512 0.000 0.000 0.132 0.356
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2488     0.8322 0.000 0.000 0.872 0.004 0.124
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2672     0.6993 0.872 0.000 0.004 0.008 0.116
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.0162     0.9101 0.000 0.000 0.000 0.004 0.996
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.1270     0.9319 0.000 0.948 0.000 0.052 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.3274     0.6096 0.780 0.000 0.000 0.220 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3336     0.6053 0.772 0.000 0.000 0.228 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1792     0.8537 0.084 0.000 0.916 0.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.2852     0.7899 0.000 0.000 0.000 0.172 0.828
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
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#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.4402     0.7289 0.000 0.740 0.000 0.056 0.204
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0162     0.9014 0.000 0.000 0.996 0.000 0.004
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     4  0.4467     0.7322 0.164 0.000 0.000 0.752 0.084
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.3333     0.7221 0.208 0.000 0.000 0.004 0.788
#> 331A9160-D730-45DD-A985-C6CAC03035ED     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.7345     0.2936 0.224 0.480 0.020 0.260 0.016
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.3932     0.5201 0.328 0.000 0.672 0.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.2127     0.9014 0.000 0.892 0.000 0.108 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.1364     0.7273 0.952 0.000 0.012 0.036 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.4273     0.1240 0.552 0.000 0.000 0.448 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     5  0.3210     0.7604 0.000 0.000 0.000 0.212 0.788
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.1410     0.8787 0.060 0.000 0.000 0.000 0.940
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     4  0.5490     0.6062 0.248 0.000 0.000 0.636 0.116
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.4437     0.4083 0.664 0.000 0.020 0.316 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     5  0.5301     0.5866 0.148 0.000 0.000 0.176 0.676
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.0162     0.9094 0.000 0.000 0.000 0.004 0.996
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.1341     0.9313 0.000 0.944 0.000 0.056 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.1608     0.8625 0.072 0.000 0.928 0.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0880     0.8920 0.000 0.000 0.968 0.000 0.032
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.1197     0.8970 0.000 0.000 0.000 0.048 0.952
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.0510     0.9092 0.000 0.000 0.000 0.016 0.984
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     4  0.4060     0.5245 0.360 0.000 0.000 0.640 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0880     0.7360 0.968 0.000 0.032 0.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.1774     0.8866 0.052 0.000 0.000 0.016 0.932
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.1410     0.8748 0.060 0.000 0.940 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0880     0.7434 0.968 0.000 0.000 0.032 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.1908     0.8765 0.000 0.000 0.000 0.092 0.908
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.3644     0.8232 0.000 0.000 0.096 0.080 0.824
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.0000     0.9098 0.000 0.000 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000     0.7437 1.000 0.000 0.000 0.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1851     0.8630 0.000 0.000 0.912 0.000 0.088
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.0880     0.9052 0.000 0.000 0.000 0.032 0.968
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3962     0.7772 0.000 0.000 0.800 0.088 0.112
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.2304     0.7263 0.908 0.000 0.004 0.020 0.068
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0000     0.9098 0.000 0.000 0.000 0.000 1.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.1608     0.7137 0.928 0.000 0.072 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     4  0.4714     0.7142 0.192 0.000 0.000 0.724 0.084
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.2439     0.6997 0.876 0.000 0.004 0.120 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3843     0.7220 0.012 0.000 0.788 0.184 0.016
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     4  0.1571     0.7947 0.060 0.000 0.000 0.936 0.004
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5554     0.3674 0.592 0.000 0.076 0.328 0.004
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0703     0.7390 0.976 0.000 0.024 0.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0290     0.7443 0.992 0.000 0.000 0.008 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3857     0.4859 0.688 0.000 0.000 0.312 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.2278     0.7009 0.032 0.000 0.000 0.908 0.060
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0162     0.9103 0.000 0.000 0.000 0.004 0.996
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     3  0.8419    -0.1219 0.272 0.000 0.324 0.156 0.248
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2280     0.8566 0.000 0.000 0.000 0.120 0.880
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.5057     0.1395 0.356 0.000 0.036 0.604 0.004
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.7464    -0.0158 0.332 0.352 0.284 0.032 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4310     0.3910 0.604 0.000 0.004 0.392 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.2230     0.8447 0.000 0.884 0.000 0.000 0.116
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1121     0.8827 0.000 0.000 0.956 0.044 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.3456     0.7674 0.000 0.000 0.800 0.184 0.016
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     4  0.3242     0.7465 0.216 0.000 0.000 0.784 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0404     0.9094 0.000 0.000 0.000 0.012 0.988
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.1478     0.9292 0.000 0.936 0.000 0.064 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     4  0.3612     0.6955 0.268 0.000 0.000 0.732 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.2966     0.8295 0.000 0.816 0.000 0.184 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.2424     0.6643 0.868 0.000 0.132 0.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5537     0.5591 0.192 0.000 0.648 0.160 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.3366     0.5940 0.768 0.000 0.000 0.232 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.2719     0.6823 0.852 0.000 0.004 0.144 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     4  0.3534     0.6800 0.256 0.000 0.000 0.744 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1557     0.8813 0.000 0.008 0.940 0.000 0.052
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0771     0.7384 0.976 0.000 0.004 0.020 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3593     0.6869 0.828 0.000 0.084 0.088 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     4  0.1478     0.7962 0.064 0.000 0.000 0.936 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3224     0.7798 0.160 0.000 0.000 0.016 0.824
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9404 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.9027 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3395     0.5883 0.764 0.000 0.000 0.236 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0324     0.9100 0.004 0.000 0.000 0.004 0.992
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     4  0.4303     0.7367 0.192 0.000 0.000 0.752 0.056

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1684     0.7553 0.028 0.008 0.008 0.940 0.000 0.016
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.4236     0.3919 0.000 0.000 0.308 0.036 0.000 0.656
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     6  0.3850     0.5249 0.340 0.000 0.000 0.004 0.004 0.652
#> 78F79407-D49F-4FA2-B09F-0665C502827C     6  0.5367     0.4592 0.300 0.000 0.000 0.004 0.124 0.572
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0363     0.8840 0.000 0.000 0.000 0.012 0.988 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5169     0.1772 0.000 0.432 0.504 0.024 0.000 0.040
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1267     0.8720 0.000 0.000 0.000 0.060 0.940 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2669     0.7284 0.836 0.000 0.000 0.008 0.000 0.156
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.1297     0.8862 0.040 0.000 0.000 0.012 0.948 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0632     0.7630 0.976 0.000 0.000 0.024 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.2823     0.8449 0.000 0.204 0.000 0.796 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.1194     0.7346 0.008 0.000 0.004 0.032 0.000 0.956
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0405     0.9073 0.000 0.000 0.988 0.008 0.000 0.004
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2135     0.7453 0.872 0.000 0.000 0.000 0.000 0.128
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0405     0.8863 0.008 0.000 0.000 0.000 0.988 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0748     0.9043 0.000 0.000 0.976 0.004 0.016 0.004
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     6  0.5146     0.4895 0.300 0.000 0.000 0.004 0.100 0.596
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4836     0.1987 0.564 0.000 0.000 0.004 0.052 0.380
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     6  0.4116     0.3770 0.416 0.000 0.000 0.012 0.000 0.572
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     6  0.3781     0.6014 0.036 0.000 0.000 0.004 0.204 0.756
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0260     0.9096 0.000 0.000 0.992 0.008 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3290     0.6597 0.000 0.000 0.744 0.004 0.000 0.252
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.0508     0.8850 0.004 0.000 0.000 0.012 0.984 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.2527     0.8528 0.064 0.000 0.000 0.048 0.884 0.004
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2982     0.7138 0.820 0.000 0.000 0.004 0.012 0.164
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.3437     0.7768 0.188 0.000 0.004 0.012 0.788 0.008
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     6  0.5240     0.6087 0.156 0.164 0.000 0.020 0.000 0.660
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#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.3124     0.6868 0.828 0.000 0.000 0.140 0.008 0.024
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     6  0.2946     0.6972 0.176 0.000 0.000 0.012 0.000 0.812
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     5  0.2058     0.8738 0.056 0.000 0.016 0.008 0.916 0.004
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     5  0.0520     0.8867 0.008 0.000 0.000 0.000 0.984 0.008
#> 627BC251-D217-4955-B718-6B9D6DEA1756     6  0.4821     0.5826 0.240 0.000 0.000 0.004 0.096 0.660
#> 31B54613-A20E-4039-BB8B-9B52104CE418     5  0.3096     0.7964 0.172 0.000 0.004 0.008 0.812 0.004
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     6  0.1720     0.7365 0.032 0.000 0.000 0.040 0.000 0.928
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     4  0.2416     0.8505 0.000 0.156 0.000 0.844 0.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     5  0.2416     0.7992 0.000 0.000 0.000 0.156 0.844 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     6  0.5473     0.3889 0.348 0.000 0.000 0.008 0.108 0.536
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.2362     0.7407 0.860 0.000 0.000 0.000 0.004 0.136
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.2794     0.7250 0.840 0.000 0.000 0.004 0.012 0.144
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.2113     0.8792 0.028 0.000 0.916 0.008 0.044 0.004
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     4  0.3866     0.3761 0.000 0.484 0.000 0.516 0.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.1444     0.8212 0.000 0.072 0.000 0.928 0.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.1663     0.7600 0.912 0.000 0.000 0.000 0.000 0.088
#> A9022D9E-1D30-49EE-8552-1364A8027F34     6  0.0717     0.7388 0.008 0.000 0.000 0.000 0.016 0.976
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     5  0.3388     0.7667 0.172 0.000 0.000 0.000 0.792 0.036
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     6  0.1204     0.7437 0.056 0.000 0.000 0.000 0.000 0.944
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     5  0.4983     0.3994 0.356 0.000 0.000 0.008 0.576 0.060
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.2588     0.8354 0.000 0.000 0.860 0.012 0.124 0.004
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     5  0.5035     0.3800 0.380 0.000 0.000 0.068 0.548 0.004
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.1387     0.8684 0.000 0.000 0.000 0.068 0.932 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     5  0.2149     0.8526 0.104 0.000 0.000 0.004 0.888 0.004
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     4  0.4566     0.7234 0.000 0.120 0.000 0.696 0.184 0.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0767     0.9045 0.000 0.000 0.976 0.008 0.012 0.004
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.2767     0.7476 0.868 0.000 0.000 0.004 0.056 0.072
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0603     0.7647 0.980 0.000 0.000 0.016 0.000 0.004
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.3426     0.7120 0.012 0.000 0.000 0.004 0.764 0.220
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0405     0.7651 0.988 0.000 0.000 0.008 0.000 0.004
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.0951     0.7599 0.008 0.000 0.000 0.968 0.004 0.020
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.3448     0.6198 0.000 0.000 0.716 0.004 0.000 0.280
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.1471     0.8150 0.004 0.064 0.000 0.932 0.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     6  0.1364     0.7294 0.004 0.000 0.004 0.048 0.000 0.944
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     6  0.4524     0.3937 0.404 0.000 0.000 0.036 0.000 0.560
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     5  0.4128     0.6302 0.300 0.000 0.004 0.012 0.676 0.008
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.2462     0.8339 0.000 0.000 0.000 0.028 0.876 0.096
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.3506     0.7094 0.792 0.000 0.000 0.000 0.052 0.156
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0260     0.9552 0.000 0.992 0.000 0.008 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     6  0.4678     0.4136 0.304 0.000 0.012 0.044 0.000 0.640
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0260     0.9096 0.000 0.000 0.992 0.008 0.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     5  0.5377     0.3089 0.336 0.000 0.000 0.004 0.548 0.112
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.1461     0.8735 0.016 0.000 0.000 0.044 0.940 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.3221     0.7939 0.000 0.264 0.000 0.736 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.1588     0.8718 0.000 0.000 0.924 0.004 0.000 0.072
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.1036     0.9002 0.000 0.000 0.964 0.008 0.024 0.004
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.2433     0.8565 0.072 0.000 0.000 0.044 0.884 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.0260     0.8864 0.008 0.000 0.000 0.000 0.992 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.0405     0.8863 0.008 0.000 0.000 0.000 0.988 0.004
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0363     0.9085 0.000 0.000 0.988 0.012 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.0551     0.8866 0.008 0.000 0.000 0.004 0.984 0.004
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.1296     0.8836 0.032 0.000 0.000 0.012 0.952 0.004
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.3463     0.6137 0.748 0.000 0.000 0.004 0.008 0.240
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0260     0.9096 0.000 0.000 0.992 0.008 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     6  0.0806     0.7342 0.000 0.000 0.008 0.020 0.000 0.972
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.2135     0.8449 0.000 0.128 0.000 0.872 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.2575     0.8500 0.044 0.000 0.000 0.004 0.880 0.072
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.2823     0.8449 0.000 0.204 0.000 0.796 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.1908     0.8558 0.000 0.000 0.900 0.004 0.000 0.096
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     6  0.3104     0.6767 0.204 0.000 0.000 0.004 0.004 0.788
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0146     0.9596 0.000 0.996 0.000 0.004 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.2044     0.8678 0.076 0.000 0.004 0.008 0.908 0.004
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.3485     0.8183 0.060 0.000 0.104 0.008 0.824 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.0837     0.8860 0.000 0.000 0.004 0.020 0.972 0.004
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.2823     0.8449 0.000 0.204 0.000 0.796 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.0665     0.8865 0.008 0.000 0.000 0.008 0.980 0.004
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0260     0.8864 0.008 0.000 0.000 0.000 0.992 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     6  0.1418     0.7386 0.024 0.000 0.000 0.032 0.000 0.944
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.2420     0.8510 0.000 0.000 0.876 0.008 0.108 0.008
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.1464     0.8852 0.036 0.000 0.000 0.016 0.944 0.004
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.4044     0.7707 0.096 0.000 0.780 0.008 0.112 0.004
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.1408     0.7353 0.020 0.000 0.000 0.000 0.036 0.944
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0767     0.8874 0.008 0.000 0.000 0.012 0.976 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     6  0.1152     0.7282 0.000 0.000 0.044 0.004 0.000 0.952
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0603     0.7647 0.980 0.000 0.000 0.016 0.000 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3096     0.7465 0.840 0.000 0.000 0.004 0.048 0.108
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     6  0.2723     0.7088 0.128 0.000 0.000 0.004 0.016 0.852
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3611     0.7379 0.188 0.000 0.780 0.008 0.020 0.004
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1578     0.7522 0.936 0.000 0.000 0.048 0.012 0.004
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     6  0.5358     0.2861 0.408 0.000 0.072 0.008 0.004 0.508
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.1116     0.7331 0.004 0.000 0.008 0.028 0.000 0.960
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     6  0.1296     0.7420 0.032 0.000 0.000 0.004 0.012 0.952
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     6  0.4150     0.4280 0.392 0.000 0.000 0.016 0.000 0.592
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.3121     0.6141 0.192 0.000 0.000 0.796 0.008 0.004
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0551     0.8863 0.008 0.000 0.000 0.004 0.984 0.004
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.7661     0.0682 0.392 0.000 0.156 0.012 0.192 0.248
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.3231     0.7869 0.180 0.000 0.000 0.012 0.800 0.008
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.2617     0.7051 0.080 0.000 0.004 0.876 0.000 0.040
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.6232    -0.1163 0.000 0.012 0.212 0.388 0.000 0.388
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     6  0.5456     0.5123 0.188 0.000 0.004 0.216 0.000 0.592
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.1745     0.8738 0.000 0.920 0.000 0.012 0.068 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1267     0.8838 0.060 0.000 0.940 0.000 0.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.5610     0.2959 0.104 0.000 0.304 0.572 0.016 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2454     0.7529 0.876 0.000 0.000 0.004 0.016 0.104
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0951     0.8855 0.020 0.000 0.000 0.008 0.968 0.004
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2823     0.8449 0.000 0.204 0.000 0.796 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2454     0.7213 0.840 0.000 0.000 0.000 0.000 0.160
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1434     0.8029 0.012 0.048 0.000 0.940 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1625     0.7500 0.928 0.000 0.000 0.060 0.000 0.012
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.1713     0.7162 0.000 0.000 0.044 0.028 0.000 0.928
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5580     0.5454 0.024 0.000 0.620 0.168 0.000 0.188
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     6  0.3812     0.6205 0.264 0.000 0.000 0.024 0.000 0.712
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.2234     0.7068 0.124 0.000 0.000 0.004 0.000 0.872
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4117     0.5882 0.716 0.000 0.000 0.056 0.000 0.228
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1484     0.8932 0.000 0.008 0.944 0.004 0.040 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.1226     0.7312 0.004 0.000 0.004 0.040 0.000 0.952
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.3020     0.6996 0.100 0.000 0.024 0.004 0.016 0.856
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0508     0.7650 0.984 0.000 0.000 0.012 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3187     0.7523 0.012 0.000 0.000 0.004 0.796 0.188
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9635 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0146     0.9104 0.000 0.000 0.996 0.004 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.3799     0.6051 0.276 0.000 0.000 0.020 0.000 0.704
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0767     0.8860 0.008 0.000 0.000 0.012 0.976 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2527     0.7552 0.868 0.000 0.000 0.000 0.024 0.108

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-skmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


SD:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "pam"]
# you can also extract it by
# res = res_list["SD:pam"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.959       0.984         0.3493 0.648   0.648
#> 3 3 0.844           0.860       0.938         0.6432 0.787   0.672
#> 4 4 0.625           0.339       0.674         0.1834 0.833   0.638
#> 5 5 0.699           0.718       0.857         0.0824 0.754   0.397
#> 6 6 0.674           0.657       0.793         0.1025 0.911   0.663

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1   0.000     0.9907 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1   0.000     0.9907 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1   0.000     0.9907 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1   0.000     0.9907 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1   0.000     0.9907 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1   0.000     0.9907 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1   0.767     0.6928 0.776 0.224
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2   0.000     0.9591 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1   0.000     0.9907 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1   0.000     0.9907 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1   0.000     0.9907 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1   0.000     0.9907 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1   0.000     0.9907 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2   0.000     0.9591 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1   0.000     0.9907 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1   0.000     0.9907 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1   0.000     0.9907 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1   0.000     0.9907 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1   0.000     0.9907 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1   0.000     0.9907 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2   0.000     0.9591 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1   0.000     0.9907 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1   0.000     0.9907 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1   0.000     0.9907 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1   0.000     0.9907 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1   0.000     0.9907 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1   0.000     0.9907 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1   0.000     0.9907 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2   0.000     0.9591 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2   0.000     0.9591 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1   0.000     0.9907 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1   0.000     0.9907 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1   0.000     0.9907 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1   0.000     0.9907 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2   0.000     0.9591 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1   0.000     0.9907 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1   0.000     0.9907 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2   0.000     0.9591 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1   0.000     0.9907 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1   0.000     0.9907 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2   0.000     0.9591 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1   0.000     0.9907 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1   0.000     0.9907 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1   0.000     0.9907 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1   0.000     0.9907 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1   0.000     0.9907 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1   0.000     0.9907 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2   0.000     0.9591 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1   0.000     0.9907 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2   0.000     0.9591 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1   0.000     0.9907 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2   0.000     0.9591 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1   0.000     0.9907 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1   0.000     0.9907 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1   0.000     0.9907 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1   0.000     0.9907 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1   0.000     0.9907 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1   0.000     0.9907 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2   0.000     0.9591 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1   0.000     0.9907 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1   0.000     0.9907 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1   0.000     0.9907 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1   0.000     0.9907 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1   0.000     0.9907 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2   0.000     0.9591 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1   0.000     0.9907 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1   0.000     0.9907 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1   0.000     0.9907 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1   0.000     0.9907 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2   0.722     0.7509 0.200 0.800
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1   0.000     0.9907 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1   0.000     0.9907 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1   0.000     0.9907 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1   0.000     0.9907 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1   0.000     0.9907 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1   0.000     0.9907 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1   0.000     0.9907 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2   0.000     0.9591 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1   0.000     0.9907 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2   0.000     0.9591 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1   0.000     0.9907 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1   0.000     0.9907 1.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1   0.000     0.9907 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1   0.000     0.9907 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1   0.000     0.9907 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1   0.000     0.9907 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1   0.000     0.9907 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2   0.416     0.8842 0.084 0.916
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2   0.000     0.9591 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1   0.000     0.9907 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1   0.000     0.9907 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1   0.000     0.9907 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2   0.000     0.9591 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1   0.000     0.9907 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1   0.000     0.9907 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1   0.000     0.9907 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1   0.000     0.9907 1.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1   0.000     0.9907 1.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1   0.000     0.9907 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1   0.000     0.9907 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1   0.000     0.9907 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2   0.000     0.9591 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2   0.000     0.9591 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1   0.000     0.9907 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1   0.000     0.9907 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2   0.000     0.9591 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1   0.000     0.9907 1.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1   0.000     0.9907 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1   0.000     0.9907 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     1   0.932     0.4336 0.652 0.348
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2   0.000     0.9591 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1   0.000     0.9907 1.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1   0.000     0.9907 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1   0.000     0.9907 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1   0.000     0.9907 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1   0.000     0.9907 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1   0.000     0.9907 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1   0.000     0.9907 1.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1   0.000     0.9907 1.000 0.000
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#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1   0.000     0.9907 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1   0.000     0.9907 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1   0.000     0.9907 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1   0.000     0.9907 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1   0.000     0.9907 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2   0.000     0.9591 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2   0.000     0.9591 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1   0.000     0.9907 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1   0.000     0.9907 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1   0.000     0.9907 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1   0.000     0.9907 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0592    0.93083 0.988 0.000 0.012
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.90016 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.4062    0.82703 0.836 0.000 0.164
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.93033 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.93033 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2165    0.91260 0.936 0.000 0.064
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.8727    0.39139 0.588 0.176 0.236
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.93803 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.4974    0.69359 0.236 0.000 0.764
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0424    0.93120 0.992 0.000 0.008
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0747    0.93051 0.984 0.000 0.016
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1529    0.92284 0.960 0.000 0.040
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2066    0.87546 0.060 0.000 0.940
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.93803 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000    0.93033 1.000 0.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.90016 0.000 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000    0.90016 0.000 0.000 1.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000    0.93033 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.2066    0.91273 0.940 0.000 0.060
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0592    0.89882 0.012 0.000 0.988
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.93803 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.93033 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2066    0.91273 0.940 0.000 0.060
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.93033 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.90016 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0747    0.92958 0.984 0.000 0.016
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.6225    0.20702 0.568 0.000 0.432
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0424    0.93063 0.992 0.000 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.93803 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.93803 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0237    0.93060 0.996 0.000 0.004
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.4654    0.77473 0.792 0.000 0.208
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.93033 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1289    0.92533 0.968 0.000 0.032
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.93803 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000    0.93033 1.000 0.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.2066    0.91273 0.940 0.000 0.060
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.93803 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000    0.93033 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.2356    0.90776 0.928 0.000 0.072
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.93803 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0237    0.90005 0.004 0.000 0.996
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000    0.90016 0.000 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0424    0.93063 0.992 0.000 0.008
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.0892    0.89447 0.020 0.000 0.980
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2066    0.91273 0.940 0.000 0.060
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0424    0.93063 0.992 0.000 0.008
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.93803 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000    0.90016 0.000 0.000 1.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.93803 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0424    0.93063 0.992 0.000 0.008
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000    0.93803 0.000 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.2066    0.87546 0.060 0.000 0.940
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0237    0.93053 0.996 0.000 0.004
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0237    0.93053 0.996 0.000 0.004
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1529    0.88940 0.040 0.000 0.960
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2066    0.87546 0.060 0.000 0.940
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.2261    0.91233 0.932 0.000 0.068
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000    0.93803 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0237    0.93060 0.996 0.000 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2796    0.89897 0.908 0.000 0.092
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0424    0.93063 0.992 0.000 0.008
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.4605    0.78018 0.796 0.000 0.204
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0424    0.93063 0.992 0.000 0.008
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.93803 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.1753    0.88523 0.048 0.000 0.952
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0424    0.93063 0.992 0.000 0.008
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.0000    0.90016 0.000 0.000 1.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000    0.90016 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.4452    0.69426 0.192 0.808 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.2066    0.91273 0.940 0.000 0.060
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.1411    0.88764 0.036 0.000 0.964
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0000    0.90016 0.000 0.000 1.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000    0.93033 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0424    0.93063 0.992 0.000 0.008
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     3  0.6274    0.13683 0.456 0.000 0.544
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.2261    0.91233 0.932 0.000 0.068
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.93803 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000    0.90016 0.000 0.000 1.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000    0.93803 0.000 1.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.1031    0.92686 0.976 0.000 0.024
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6180    0.23823 0.416 0.000 0.584
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.2261    0.90961 0.932 0.000 0.068
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.2165    0.91260 0.936 0.000 0.064
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0592    0.92983 0.988 0.000 0.012
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0892    0.92995 0.980 0.000 0.020
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3192    0.88311 0.888 0.000 0.112
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.2625    0.83860 0.084 0.916 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000    0.93803 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0424    0.89694 0.008 0.000 0.992
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.2165    0.91565 0.936 0.000 0.064
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.5058    0.68924 0.244 0.000 0.756
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000    0.93803 0.000 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000    0.90016 0.000 0.000 1.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.2261    0.91233 0.932 0.000 0.068
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.2066    0.91273 0.940 0.000 0.060
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0592    0.93083 0.988 0.000 0.012
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0424    0.93063 0.992 0.000 0.008
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0424    0.93063 0.992 0.000 0.008
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0747    0.89764 0.016 0.000 0.984
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000    0.93033 1.000 0.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000    0.93803 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000    0.93803 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.2165    0.91260 0.936 0.000 0.064
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.2066    0.91658 0.940 0.000 0.060
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000    0.93803 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.0424    0.93063 0.992 0.000 0.008
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0592    0.89873 0.012 0.000 0.988
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     3  0.4974    0.69359 0.236 0.000 0.764
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     3  0.6191    0.72487 0.140 0.084 0.776
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000    0.93803 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.2261    0.91233 0.932 0.000 0.068
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.1964    0.87831 0.056 0.000 0.944
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.4002    0.79852 0.840 0.000 0.160
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0237    0.93053 0.996 0.000 0.004
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.2448    0.90879 0.924 0.000 0.076
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0424    0.93063 0.992 0.000 0.008
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0424    0.93063 0.992 0.000 0.008
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.1529    0.92137 0.960 0.000 0.040
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000    0.93033 1.000 0.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000    0.93033 1.000 0.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000    0.93033 1.000 0.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0237    0.93053 0.996 0.000 0.004
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0237    0.93053 0.996 0.000 0.004
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     1  0.6274    0.25867 0.544 0.000 0.456
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     1  0.4652    0.85364 0.856 0.064 0.080
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     1  0.6126    0.33913 0.600 0.400 0.000
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0424    0.93063 0.992 0.000 0.008
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.6140    0.22403 0.596 0.000 0.404
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0000    0.93033 1.000 0.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.0424    0.93063 0.992 0.000 0.008
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.2165    0.91260 0.936 0.000 0.064
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000    0.93803 0.000 1.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     3  0.0000    0.90016 0.000 0.000 1.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000    0.93803 0.000 1.000 0.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000    0.93803 0.000 1.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000    0.93033 1.000 0.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000    0.93803 0.000 1.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000    0.93803 0.000 1.000 0.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0424    0.93063 0.992 0.000 0.008
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.0424    0.93063 0.992 0.000 0.008
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000    0.93803 0.000 1.000 0.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     3  0.5216    0.67124 0.260 0.000 0.740
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.7043    0.15003 0.448 0.532 0.020
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000    0.93803 0.000 1.000 0.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.0000    0.93033 1.000 0.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.0747    0.93046 0.984 0.000 0.016
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000    0.93803 0.000 1.000 0.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.5216    0.65807 0.740 0.000 0.260
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0000    0.93033 1.000 0.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000    0.93033 1.000 0.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     3  0.5058    0.69132 0.244 0.000 0.756
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000    0.93803 0.000 1.000 0.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     3  0.3116    0.83000 0.108 0.000 0.892
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     1  0.1289    0.92689 0.968 0.000 0.032
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     1  0.6309    0.00845 0.504 0.496 0.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0424    0.93063 0.992 0.000 0.008
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.2261    0.91233 0.932 0.000 0.068
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.7890    0.24996 0.396 0.544 0.060
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000    0.93803 0.000 1.000 0.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     3  0.0000    0.90016 0.000 0.000 1.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     3  0.0000    0.90016 0.000 0.000 1.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000    0.93803 0.000 1.000 0.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.1163    0.92692 0.972 0.000 0.028
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000    0.93803 0.000 1.000 0.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000    0.93803 0.000 1.000 0.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.0424    0.93063 0.992 0.000 0.008
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.5678    0.51570 0.316 0.684 0.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0424    0.93063 0.992 0.000 0.008
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000    0.93803 0.000 1.000 0.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.2165    0.91464 0.936 0.000 0.064
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000    0.93033 1.000 0.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.0424    0.93063 0.992 0.000 0.008
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000    0.93033 1.000 0.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     3  0.1643    0.88101 0.044 0.000 0.956
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.2066    0.91273 0.940 0.000 0.060
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0424    0.93042 0.992 0.000 0.008
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0424    0.93063 0.992 0.000 0.008
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0237    0.93053 0.996 0.000 0.004
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000    0.93803 0.000 1.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000    0.93803 0.000 1.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.2356    0.91079 0.928 0.000 0.072
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000    0.93803 0.000 1.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.1031    0.92693 0.976 0.000 0.024
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0237    0.93060 0.996 0.000 0.004
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.4346    0.73342 0.000 0.816 0.184
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000    0.93033 1.000 0.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.0000    0.90016 0.000 0.000 1.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000    0.93803 0.000 1.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000    0.93803 0.000 1.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.6286    0.13111 0.464 0.536 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0424    0.93063 0.992 0.000 0.008
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000    0.93033 1.000 0.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000    0.93033 1.000 0.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000    0.93033 1.000 0.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.2066    0.91273 0.940 0.000 0.060
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.93803 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.0000    0.90016 0.000 0.000 1.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.2261    0.91233 0.932 0.000 0.068
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.6095    0.40290 0.608 0.000 0.392
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0592    0.92987 0.988 0.000 0.012
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.5810    0.49701 0.336 0.000 0.664
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0237    0.89865 0.004 0.000 0.996
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000    0.93033 1.000 0.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0424    0.93063 0.992 0.000 0.008
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.2625    0.90009 0.916 0.000 0.084
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.2165    0.91457 0.936 0.000 0.064
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.1031    0.92828 0.976 0.000 0.024
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000    0.93033 1.000 0.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000    0.93803 0.000 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.5708    0.65082 0.204 0.768 0.028
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0424    0.93063 0.992 0.000 0.008
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0424    0.93063 0.992 0.000 0.008
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.2261    0.91233 0.932 0.000 0.068
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.3340    0.87645 0.880 0.000 0.120
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0237    0.93060 0.996 0.000 0.004
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000    0.93803 0.000 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.0000    0.93033 1.000 0.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0747    0.89706 0.016 0.000 0.984
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.93033 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.2261    0.91233 0.932 0.000 0.068
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.6314    0.34645 0.392 0.604 0.004
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.2066    0.87546 0.060 0.000 0.940
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.93803 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.93803 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.93803 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0424    0.89694 0.008 0.000 0.992
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.2280    0.87817 0.052 0.008 0.940
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.2261    0.91233 0.932 0.000 0.068
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.2165    0.91260 0.936 0.000 0.064
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.2165    0.91260 0.936 0.000 0.064
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.2066    0.87546 0.060 0.000 0.940
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.6305    0.01008 0.516 0.000 0.484
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1860    0.91670 0.948 0.000 0.052
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.2796    0.89899 0.908 0.000 0.092
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.93803 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000    0.93033 1.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.5905    0.42951 0.648 0.000 0.352
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.1289    0.92435 0.968 0.000 0.032
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.93803 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.93803 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.2066    0.91273 0.940 0.000 0.060
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.93803 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.5178    0.59727 0.256 0.744 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.5733    0.50646 0.676 0.000 0.324
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000    0.93033 1.000 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.93803 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.93803 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000    0.90016 0.000 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.6302   -0.06742 0.520 0.000 0.480
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.4974    0.69359 0.236 0.000 0.764
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.93803 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4555    0.78615 0.800 0.000 0.200
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.93803 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.3752    0.84061 0.856 0.000 0.144
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.2261    0.91140 0.932 0.000 0.068
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000    0.93033 1.000 0.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0237    0.89865 0.004 0.000 0.996
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.2165    0.91260 0.936 0.000 0.064
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.93803 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2959    0.85906 0.100 0.000 0.900
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000    0.93033 1.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.2066    0.91273 0.940 0.000 0.060
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0747    0.92561 0.984 0.000 0.016
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0424    0.93063 0.992 0.000 0.008
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0424    0.93063 0.992 0.000 0.008
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6045    0.40315 0.620 0.000 0.380
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.2537    0.87001 0.080 0.000 0.920
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0424    0.93063 0.992 0.000 0.008
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0424    0.93063 0.992 0.000 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000    0.93033 1.000 0.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000    0.93033 1.000 0.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.93803 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000    0.93033 1.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.2165    0.91462 0.936 0.000 0.064
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2165    0.91260 0.936 0.000 0.064
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2356    0.89048 0.928 0.000 0.072
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2165    0.91260 0.936 0.000 0.064
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.93803 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.1643    0.92269 0.956 0.000 0.044
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.6189    0.37323 0.632 0.004 0.364
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0424    0.93063 0.992 0.000 0.008
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.0237    0.93060 0.996 0.000 0.004
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0424    0.93063 0.992 0.000 0.008
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.0000    0.90016 0.000 0.000 1.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2066    0.91273 0.940 0.000 0.060
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.3686    0.84629 0.860 0.000 0.140
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.93803 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0237    0.93053 0.996 0.000 0.004
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.9624    0.17664 0.472 0.256 0.272
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0424    0.93063 0.992 0.000 0.008
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.6126    0.35783 0.600 0.000 0.400
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.1031    0.92413 0.976 0.000 0.024
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0000    0.93033 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.93033 1.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000    0.93033 1.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0424    0.93063 0.992 0.000 0.008
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2066    0.87546 0.060 0.000 0.940
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0000    0.90016 0.000 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0237    0.93053 0.996 0.000 0.004
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4121    0.81266 0.832 0.000 0.168
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0424    0.93063 0.992 0.000 0.008
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.2878    0.89006 0.904 0.000 0.096
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.93803 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.93803 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1643    0.88548 0.044 0.000 0.956
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0237    0.93053 0.996 0.000 0.004
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0237    0.93060 0.996 0.000 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0237    0.93060 0.996 0.000 0.004

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5126    0.19276 0.444 0.000 0.004 0.552
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.6336    0.09338 0.608 0.000 0.088 0.304
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
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#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     4  0.6102   -0.27938 0.472 0.012 0.024 0.492
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     3  0.3873    0.71109 0.228 0.000 0.772 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.4933   -0.09227 0.568 0.000 0.000 0.432
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.4661    0.81962 0.000 0.728 0.016 0.256
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.4103    0.82882 0.000 0.744 0.000 0.256
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.7670    0.47416 0.212 0.484 0.004 0.300
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.4103    0.82882 0.000 0.744 0.000 0.256
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.1940    0.26941 0.924 0.000 0.000 0.076
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.5000   -0.13665 0.500 0.000 0.000 0.500
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     3  0.5000    0.58828 0.496 0.000 0.504 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.4072    0.15577 0.748 0.000 0.000 0.252
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.4994   -0.12456 0.520 0.000 0.000 0.480
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.4998   -0.12665 0.512 0.000 0.000 0.488
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.4103    0.82882 0.000 0.744 0.000 0.256
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.0336    0.29734 0.992 0.000 0.000 0.008
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.4898   -0.07879 0.584 0.000 0.000 0.416
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     4  0.4961    0.21726 0.448 0.000 0.000 0.552
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.2647    0.80616 0.000 0.880 0.120 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.4817    0.64685 0.388 0.000 0.612 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.2921    0.87416 0.000 0.860 0.000 0.140
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.8405   -0.19717 0.236 0.352 0.024 0.388
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> A9022D9E-1D30-49EE-8552-1364A8027F34     4  0.4103    0.46824 0.256 0.000 0.000 0.744
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     4  0.5000    0.10949 0.500 0.000 0.000 0.500
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     4  0.5000    0.10949 0.500 0.000 0.000 0.500
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.1022    0.28776 0.968 0.000 0.000 0.032
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.1557    0.89142 0.000 0.944 0.000 0.056
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.5000    0.58828 0.496 0.000 0.504 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0188    0.29785 0.996 0.000 0.000 0.004
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.5495    0.06394 0.728 0.000 0.096 0.176
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.4994   -0.12418 0.520 0.000 0.000 0.480
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.5409   -0.22147 0.496 0.000 0.012 0.492
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0921    0.77188 0.028 0.000 0.972 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     4  0.5000    0.10949 0.500 0.000 0.000 0.500
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.4391    0.15432 0.740 0.000 0.008 0.252
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.2589    0.23780 0.884 0.000 0.000 0.116
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.5126   -0.10254 0.552 0.000 0.004 0.444
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     4  0.5000    0.10949 0.500 0.000 0.000 0.500
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     1  0.8041   -0.13769 0.504 0.216 0.024 0.256
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     4  0.4422    0.46641 0.256 0.000 0.008 0.736
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0188    0.29785 0.996 0.000 0.000 0.004
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.4807    0.15038 0.728 0.000 0.024 0.248
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     4  0.4134    0.46746 0.260 0.000 0.000 0.740
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0188    0.29785 0.996 0.000 0.000 0.004
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.7323    0.42157 0.156 0.456 0.000 0.388
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.1004    0.77208 0.024 0.000 0.972 0.004
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1716    0.27590 0.936 0.000 0.000 0.064
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0469    0.29678 0.988 0.000 0.000 0.012
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0469    0.29677 0.988 0.000 0.000 0.012
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4679    0.30642 0.352 0.000 0.648 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4543    0.01383 0.676 0.000 0.000 0.324
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0592    0.29337 0.984 0.000 0.016 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.4925    0.07714 0.428 0.000 0.572 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     4  0.4713    0.33171 0.360 0.000 0.000 0.640
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.4103    0.82882 0.000 0.744 0.000 0.256
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.1302    0.89296 0.000 0.956 0.000 0.044
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.4072    0.15577 0.748 0.000 0.000 0.252
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4040    0.83303 0.000 0.752 0.000 0.248
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.4245    0.70529 0.064 0.820 0.000 0.116
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.7073   -0.07117 0.464 0.000 0.412 0.124
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.5000   -0.13580 0.504 0.000 0.000 0.496
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.2814    0.87463 0.000 0.868 0.000 0.132
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     4  0.7416    0.21736 0.192 0.000 0.312 0.496
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.5000    0.58828 0.496 0.000 0.504 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.2814    0.87463 0.000 0.868 0.000 0.132
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4100    0.24853 0.832 0.000 0.076 0.092
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4072    0.83096 0.000 0.748 0.000 0.252
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.2399    0.27642 0.920 0.000 0.048 0.032
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.4252    0.15500 0.744 0.000 0.004 0.252
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.5000   -0.13665 0.500 0.000 0.000 0.500
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.5000    0.58828 0.496 0.000 0.504 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0336    0.29775 0.992 0.000 0.000 0.008
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2611    0.72205 0.008 0.000 0.896 0.096
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     4  0.5000    0.10949 0.500 0.000 0.000 0.500
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.1474    0.27737 0.948 0.000 0.000 0.052
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5511   -0.13942 0.500 0.000 0.016 0.484
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     4  0.6528    0.20144 0.300 0.000 0.104 0.596
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1890    0.74733 0.008 0.000 0.936 0.056
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> CCDB0290-91DA-4089-84A6-4434BA028D30     4  0.4103    0.46824 0.256 0.000 0.000 0.744
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     4  0.4967    0.21887 0.452 0.000 0.000 0.548
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.5000   -0.13665 0.500 0.000 0.000 0.500
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.2011    0.26874 0.920 0.000 0.000 0.080
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1637    0.27257 0.940 0.000 0.000 0.060
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     4  0.5781    0.13657 0.480 0.000 0.028 0.492
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2345    0.25612 0.900 0.000 0.000 0.100
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5560   -0.07762 0.584 0.000 0.024 0.392
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.7221    0.15698 0.168 0.000 0.308 0.524
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5296   -0.13420 0.500 0.000 0.008 0.492
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.5147    0.17454 0.460 0.004 0.000 0.536
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     4  0.4250    0.46219 0.276 0.000 0.000 0.724
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4999    0.59105 0.492 0.000 0.508 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0336    0.29699 0.992 0.000 0.000 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4516    0.15176 0.736 0.000 0.012 0.252
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.4103    0.82882 0.000 0.744 0.000 0.256
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.5627    0.07685 0.696 0.024 0.024 0.256
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.5879    0.05015 0.672 0.000 0.080 0.248
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6380   -0.16182 0.500 0.000 0.064 0.436
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.5000   -0.13665 0.500 0.000 0.000 0.500
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5000   -0.13665 0.500 0.000 0.000 0.500
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.4103    0.46824 0.256 0.000 0.000 0.744
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4040    0.69932 0.248 0.000 0.752 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.5296   -0.13420 0.500 0.000 0.008 0.492
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6554   -0.09259 0.540 0.000 0.084 0.376
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4072    0.15577 0.748 0.000 0.000 0.252
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.89843 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.77490 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4999   -0.12196 0.508 0.000 0.000 0.492
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.4356    0.43408 0.292 0.000 0.000 0.708
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.5000   -0.13665 0.500 0.000 0.000 0.500

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.3010    0.72213 0.824 0.000 0.000 0.172 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.3649    0.48521 0.088 0.000 0.088 0.000 0.824
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1043    0.85644 0.960 0.000 0.000 0.000 0.040
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1121    0.85470 0.956 0.000 0.000 0.000 0.044
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.3452    0.70430 0.244 0.000 0.000 0.000 0.756
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4731    0.35570 0.328 0.032 0.640 0.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0290    0.92596 0.000 0.992 0.000 0.008 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4430    0.40275 0.012 0.000 0.360 0.000 0.628
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1638    0.82033 0.932 0.000 0.000 0.004 0.064
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0703    0.85721 0.976 0.000 0.000 0.000 0.024
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3010    0.71277 0.824 0.000 0.000 0.004 0.172
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.3636    0.64870 0.000 0.272 0.000 0.728 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3452    0.63587 0.756 0.000 0.000 0.000 0.244
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0290    0.86754 0.992 0.000 0.000 0.000 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0000    0.56839 0.000 0.000 0.000 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1270    0.84966 0.948 0.000 0.000 0.000 0.052
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.4151    0.63574 0.344 0.000 0.000 0.004 0.652
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0290    0.86754 0.992 0.000 0.000 0.000 0.008
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4201    0.46397 0.592 0.000 0.000 0.000 0.408
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3913    0.38134 0.324 0.000 0.676 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.2966    0.72862 0.000 0.816 0.000 0.184 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1270    0.84966 0.948 0.000 0.000 0.000 0.052
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.4718    0.68045 0.344 0.000 0.028 0.000 0.628
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1270    0.84966 0.948 0.000 0.000 0.000 0.052
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1502    0.83496 0.940 0.000 0.004 0.000 0.056
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0404    0.86732 0.988 0.000 0.000 0.000 0.012
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4639    0.67407 0.344 0.000 0.000 0.024 0.632
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0290    0.86754 0.992 0.000 0.000 0.000 0.008
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.3561    0.67936 0.260 0.000 0.000 0.000 0.740
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.4262    0.25521 0.000 0.440 0.000 0.560 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2953    0.69733 0.012 0.000 0.844 0.000 0.144
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.3913    0.68220 0.324 0.000 0.000 0.000 0.676
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.0162    0.86283 0.000 0.004 0.000 0.996 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.4434    0.22546 0.000 0.460 0.000 0.536 0.004
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.4101    0.66552 0.372 0.000 0.000 0.000 0.628
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2732    0.76866 0.000 0.840 0.000 0.160 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0671    0.86667 0.980 0.000 0.000 0.004 0.016
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.3932    0.68303 0.328 0.000 0.000 0.000 0.672
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.4654    0.67873 0.348 0.000 0.024 0.000 0.628
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3895    0.50870 0.000 0.000 0.680 0.000 0.320
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.4341    0.39738 0.008 0.000 0.364 0.000 0.628
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.1792    0.82991 0.000 0.084 0.000 0.916 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.0000    0.56839 0.000 0.000 0.000 0.000 1.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.3895    0.44384 0.000 0.000 0.320 0.000 0.680
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.4238    0.39221 0.004 0.000 0.368 0.000 0.628
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0451    0.86782 0.988 0.000 0.000 0.004 0.008
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0324    0.86701 0.992 0.000 0.000 0.004 0.004
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.5271    0.62812 0.152 0.000 0.168 0.000 0.680
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.4088    0.66813 0.368 0.000 0.000 0.000 0.632
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.3508    0.65200 0.000 0.252 0.000 0.748 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.2127    0.80310 0.892 0.000 0.000 0.000 0.108
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.4011    0.41245 0.012 0.000 0.124 0.056 0.808
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.0000    0.56839 0.000 0.000 0.000 0.000 1.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.3895    0.68240 0.320 0.000 0.000 0.000 0.680
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3876    0.59170 0.684 0.000 0.000 0.000 0.316
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0671    0.86138 0.980 0.000 0.000 0.004 0.016
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     5  0.4389    0.66665 0.368 0.000 0.004 0.004 0.624
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.1043    0.85190 0.000 0.040 0.000 0.960 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.4278    0.08090 0.000 0.548 0.000 0.452 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.1121    0.81358 0.000 0.000 0.956 0.000 0.044
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3796    0.35094 0.700 0.000 0.000 0.000 0.300
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.6585    0.27660 0.212 0.000 0.360 0.000 0.428
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.0162    0.86283 0.000 0.004 0.000 0.996 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.4227    0.60648 0.420 0.000 0.000 0.000 0.580
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.3913    0.68092 0.324 0.000 0.000 0.000 0.676
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0486    0.86742 0.988 0.000 0.004 0.004 0.004
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0324    0.86692 0.992 0.000 0.000 0.004 0.004
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.3932    0.53867 0.672 0.000 0.000 0.000 0.328
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.4425    0.46669 0.452 0.000 0.000 0.004 0.544
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.3210    0.57839 0.788 0.000 0.000 0.000 0.212
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.4825    0.27972 0.568 0.000 0.000 0.408 0.024
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.4890    0.42540 0.040 0.000 0.332 0.000 0.628
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.0162    0.86102 0.000 0.000 0.000 0.996 0.004
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.4101    0.66552 0.372 0.000 0.000 0.000 0.628
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.4901    0.60436 0.708 0.000 0.196 0.000 0.096
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     5  0.4101    0.66552 0.372 0.000 0.000 0.000 0.628
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0162    0.86828 0.996 0.000 0.000 0.000 0.004
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.3003    0.65053 0.812 0.000 0.000 0.000 0.188
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0880    0.86088 0.968 0.000 0.000 0.000 0.032
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.1043    0.85644 0.960 0.000 0.000 0.000 0.040
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.4101    0.50672 0.628 0.000 0.000 0.000 0.372
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0290    0.86720 0.992 0.000 0.008 0.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     5  0.6410    0.57704 0.132 0.000 0.040 0.220 0.608
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     4  0.0162    0.86102 0.000 0.000 0.000 0.996 0.004
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     5  0.7903   -0.20338 0.312 0.068 0.000 0.300 0.320
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.4219    0.40964 0.584 0.000 0.000 0.000 0.416
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.4101    0.50672 0.628 0.000 0.000 0.000 0.372
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     5  0.3983    0.66842 0.340 0.000 0.000 0.000 0.660
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     5  0.4341    0.39738 0.008 0.000 0.364 0.000 0.628
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0510    0.92036 0.000 0.984 0.000 0.016 0.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0451    0.86782 0.988 0.000 0.000 0.004 0.008
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     4  0.0162    0.86283 0.000 0.004 0.000 0.996 0.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.3895    0.53975 0.680 0.000 0.000 0.000 0.320
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     4  0.0162    0.86283 0.000 0.004 0.000 0.996 0.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.6582    0.01699 0.456 0.000 0.356 0.004 0.184
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     4  0.0162    0.86102 0.000 0.000 0.000 0.996 0.004
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#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0000    0.86103 0.000 0.000 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.1270    0.57265 0.052 0.000 0.000 0.000 0.948
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.1544    0.82835 0.932 0.000 0.068 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0451    0.86782 0.988 0.000 0.000 0.004 0.008
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0290    0.86754 0.992 0.000 0.000 0.000 0.008
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3932    0.53867 0.672 0.000 0.000 0.000 0.328
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3707    0.48124 0.000 0.000 0.716 0.000 0.284
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3535    0.65556 0.808 0.000 0.028 0.000 0.164
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0162    0.86767 0.996 0.000 0.000 0.004 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.0000    0.56839 0.000 0.000 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.93117 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.84737 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000    0.86782 1.000 0.000 0.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4201    0.45684 0.592 0.000 0.000 0.000 0.408
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0451    0.86782 0.988 0.000 0.000 0.004 0.008

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     6  0.4081     0.7621 0.120 0.000 0.000 0.088 0.016 0.776
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.3522     0.5129 0.072 0.000 0.076 0.000 0.828 0.024
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3017     0.6436 0.816 0.000 0.000 0.000 0.020 0.164
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3025     0.6474 0.820 0.000 0.000 0.000 0.024 0.156
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.5495     0.5694 0.288 0.000 0.000 0.000 0.548 0.164
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5199     0.4861 0.216 0.000 0.628 0.000 0.004 0.152
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.3983     0.4269 0.000 0.000 0.348 0.004 0.640 0.008
#> 53062969-D209-490B-9C9B-5D297625E2AE     6  0.3588     0.7909 0.152 0.000 0.000 0.000 0.060 0.788
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1926     0.7103 0.912 0.000 0.000 0.000 0.020 0.068
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     6  0.1720     0.7075 0.032 0.000 0.000 0.000 0.040 0.928
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0937     0.8553 0.000 0.000 0.960 0.000 0.000 0.040
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.1957     0.8125 0.000 0.112 0.000 0.888 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3595     0.5994 0.704 0.000 0.000 0.000 0.288 0.008
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0146     0.8524 0.000 0.000 0.996 0.000 0.004 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1957     0.6928 0.888 0.000 0.000 0.000 0.000 0.112
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.2003     0.6487 0.116 0.000 0.000 0.000 0.884 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0000     0.8538 0.000 0.000 1.000 0.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3248     0.6340 0.804 0.000 0.000 0.000 0.032 0.164
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     6  0.1333     0.6805 0.008 0.000 0.000 0.000 0.048 0.944
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2003     0.6897 0.884 0.000 0.000 0.000 0.000 0.116
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8538 0.000 0.000 1.000 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.5584     0.4650 0.520 0.000 0.000 0.000 0.316 0.164
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4112     0.5823 0.224 0.000 0.724 0.000 0.004 0.048
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.2517     0.6966 0.876 0.000 0.100 0.000 0.016 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.3563     0.4285 0.000 0.664 0.000 0.336 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.3248     0.6340 0.804 0.000 0.000 0.000 0.032 0.164
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.5539     0.6218 0.232 0.000 0.080 0.000 0.632 0.056
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3248     0.6340 0.804 0.000 0.000 0.000 0.032 0.164
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2699     0.6994 0.884 0.000 0.028 0.000 0.048 0.040
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0146     0.9404 0.000 0.996 0.000 0.000 0.004 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0603     0.7222 0.980 0.000 0.000 0.000 0.004 0.016
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4139     0.6282 0.336 0.000 0.000 0.024 0.640 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.7211 1.000 0.000 0.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.5487     0.5280 0.320 0.000 0.000 0.000 0.532 0.148
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.3838     0.2589 0.000 0.448 0.000 0.552 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1285     0.8517 0.000 0.000 0.944 0.000 0.004 0.052
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2773     0.6959 0.004 0.000 0.836 0.000 0.152 0.008
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.3578     0.6331 0.340 0.000 0.000 0.000 0.660 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0260     0.7209 0.992 0.000 0.000 0.000 0.000 0.008
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.0000     0.8559 0.000 0.000 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.4057     0.2834 0.000 0.436 0.000 0.556 0.008 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0146     0.8527 0.004 0.000 0.996 0.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2312     0.6891 0.876 0.000 0.000 0.000 0.012 0.112
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2191     0.6873 0.876 0.000 0.000 0.000 0.004 0.120
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1219     0.8532 0.000 0.000 0.948 0.000 0.004 0.048
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0260     0.8525 0.000 0.000 0.992 0.000 0.008 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.4224     0.3406 0.028 0.000 0.000 0.000 0.632 0.340
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2664     0.7381 0.000 0.816 0.000 0.184 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     6  0.3867     0.1508 0.488 0.000 0.000 0.000 0.000 0.512
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.5529     0.5632 0.336 0.000 0.000 0.000 0.516 0.148
#> 09758B6F-1B2D-4AED-8913-696097069409     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.5268     0.5857 0.240 0.000 0.016 0.000 0.632 0.112
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2092     0.6857 0.876 0.000 0.000 0.000 0.000 0.124
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.4467     0.5367 0.000 0.000 0.632 0.000 0.320 0.048
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     6  0.3847     0.3866 0.456 0.000 0.000 0.000 0.000 0.544
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.4101     0.4298 0.008 0.000 0.352 0.000 0.632 0.008
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.1444     0.8338 0.000 0.072 0.000 0.928 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.4449     0.5848 0.124 0.000 0.000 0.000 0.712 0.164
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.7096     0.5198 0.124 0.000 0.224 0.000 0.456 0.196
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.3852     0.3885 0.000 0.000 0.384 0.000 0.612 0.004
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     6  0.3857     0.3728 0.468 0.000 0.000 0.000 0.000 0.532
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     6  0.2994     0.7982 0.208 0.000 0.000 0.000 0.004 0.788
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.6618     0.6232 0.244 0.000 0.100 0.000 0.520 0.136
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.3887     0.6228 0.360 0.000 0.000 0.000 0.632 0.008
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.1219     0.8532 0.000 0.000 0.948 0.000 0.004 0.048
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     6  0.5276     0.2650 0.000 0.112 0.000 0.348 0.000 0.540
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.3102     0.6439 0.816 0.000 0.000 0.000 0.028 0.156
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.3712     0.4537 0.004 0.000 0.124 0.016 0.808 0.048
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.4449     0.5848 0.124 0.000 0.000 0.000 0.712 0.164
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.5054     0.6002 0.336 0.000 0.000 0.000 0.572 0.092
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.5726     0.3745 0.504 0.000 0.000 0.000 0.196 0.300
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     6  0.3200     0.7990 0.196 0.000 0.000 0.000 0.016 0.788
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     5  0.4466     0.3160 0.032 0.000 0.004 0.000 0.612 0.352
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.0858     0.8510 0.000 0.028 0.000 0.968 0.000 0.004
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.3869    -0.1449 0.000 0.500 0.000 0.500 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.1934     0.8335 0.000 0.000 0.916 0.000 0.044 0.040
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3725     0.2599 0.676 0.000 0.000 0.000 0.316 0.008
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.6067     0.2687 0.192 0.000 0.376 0.000 0.424 0.008
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.0000     0.8559 0.000 0.000 0.000 1.000 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.8538 0.000 0.000 1.000 0.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.4002     0.5784 0.404 0.000 0.000 0.000 0.588 0.008
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.4319     0.6220 0.348 0.000 0.000 0.000 0.620 0.032
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     6  0.3309     0.7941 0.192 0.000 0.004 0.000 0.016 0.788
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3819     0.2077 0.624 0.000 0.000 0.000 0.004 0.372
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0000     0.8538 0.000 0.000 1.000 0.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.3563     0.5583 0.664 0.000 0.000 0.000 0.336 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     6  0.2934     0.5551 0.112 0.000 0.000 0.000 0.044 0.844
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.4684     0.5107 0.656 0.000 0.000 0.000 0.256 0.088
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     6  0.2164     0.7413 0.060 0.000 0.000 0.020 0.012 0.908
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0865     0.8554 0.000 0.000 0.964 0.000 0.000 0.036
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.6999     0.5132 0.112 0.000 0.256 0.000 0.460 0.172
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.0000     0.8559 0.000 0.000 0.000 1.000 0.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.3967     0.6226 0.356 0.000 0.000 0.000 0.632 0.012
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0363     0.8549 0.000 0.000 0.988 0.000 0.000 0.012
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.5853     0.5439 0.612 0.000 0.168 0.000 0.172 0.048
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.3706     0.1848 0.620 0.000 0.000 0.000 0.000 0.380
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     5  0.4968     0.5733 0.248 0.000 0.000 0.000 0.632 0.120
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0508     0.7213 0.984 0.000 0.000 0.000 0.004 0.012
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.1633     0.7269 0.932 0.000 0.000 0.000 0.024 0.044
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#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.0865     0.8493 0.000 0.036 0.000 0.964 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.6137     0.5598 0.320 0.000 0.024 0.000 0.492 0.164
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.3637     0.5726 0.056 0.000 0.000 0.000 0.780 0.164
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.2257     0.7161 0.876 0.000 0.000 0.000 0.116 0.008
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.3695     0.3992 0.000 0.000 0.376 0.000 0.624 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.4508     0.6117 0.316 0.000 0.000 0.000 0.632 0.052
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3522     0.6520 0.044 0.000 0.784 0.000 0.000 0.172
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1863     0.7201 0.896 0.000 0.000 0.000 0.104 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3512     0.6619 0.272 0.000 0.000 0.000 0.720 0.008
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.2747     0.7163 0.860 0.000 0.044 0.000 0.096 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0260     0.7209 0.992 0.000 0.000 0.000 0.000 0.008
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.4930    -0.2594 0.404 0.000 0.008 0.000 0.540 0.048
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1918     0.7800 0.088 0.000 0.904 0.000 0.000 0.008
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0260     0.7209 0.992 0.000 0.000 0.000 0.000 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.3563     0.5583 0.664 0.000 0.000 0.000 0.336 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4243     0.5989 0.732 0.000 0.000 0.000 0.104 0.164
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     6  0.3371     0.7267 0.292 0.000 0.000 0.000 0.000 0.708
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     6  0.3422     0.7049 0.036 0.000 0.000 0.000 0.176 0.788
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.3198     0.6646 0.260 0.000 0.000 0.000 0.740 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.1866     0.7097 0.908 0.000 0.084 0.000 0.000 0.008
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.4325     0.4673 0.456 0.000 0.000 0.000 0.524 0.020
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     6  0.5732     0.1641 0.376 0.000 0.004 0.000 0.148 0.472
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.7039     0.1216 0.240 0.000 0.368 0.008 0.336 0.048
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.2653     0.6632 0.844 0.000 0.000 0.000 0.012 0.144
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.5497     0.5023 0.656 0.004 0.000 0.156 0.032 0.152
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.3972     0.5656 0.664 0.000 0.004 0.000 0.320 0.012
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     6  0.6115    -0.0464 0.000 0.000 0.308 0.000 0.324 0.368
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     6  0.3314     0.6627 0.012 0.000 0.000 0.000 0.224 0.764
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.4449     0.5848 0.124 0.000 0.000 0.000 0.712 0.164
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.0000     0.8559 0.000 0.000 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2092     0.6857 0.876 0.000 0.000 0.000 0.000 0.124
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     6  0.3804     0.2859 0.000 0.000 0.000 0.424 0.000 0.576
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0858     0.5756 0.004 0.000 0.000 0.000 0.968 0.028
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4170     0.6727 0.756 0.000 0.072 0.000 0.012 0.160
#> C98275CD-C39A-4E14-A731-4F3EB7396665     6  0.2730     0.7936 0.192 0.000 0.000 0.000 0.000 0.808
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2631     0.6574 0.840 0.000 0.000 0.000 0.008 0.152
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3515     0.5637 0.676 0.000 0.000 0.000 0.324 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3620     0.2753 0.648 0.000 0.000 0.000 0.000 0.352
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8538 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4107     0.3939 0.036 0.000 0.684 0.000 0.280 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2257     0.7161 0.876 0.000 0.000 0.000 0.116 0.008
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4937     0.5223 0.676 0.000 0.096 0.000 0.212 0.016
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     6  0.2883     0.7976 0.212 0.000 0.000 0.000 0.000 0.788
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3017     0.5550 0.020 0.000 0.000 0.000 0.816 0.164
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9438 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1075     0.8546 0.000 0.000 0.952 0.000 0.000 0.048
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2257     0.6884 0.876 0.000 0.000 0.000 0.008 0.116
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.5561     0.4108 0.536 0.000 0.000 0.000 0.292 0.172
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3838    -0.1010 0.552 0.000 0.000 0.000 0.000 0.448

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-pam-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


SD:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "mclust"]
# you can also extract it by
# res = res_list["SD:mclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.989       0.995         0.3797 0.621   0.621
#> 3 3 0.700           0.873       0.922         0.6702 0.721   0.555
#> 4 4 0.580           0.753       0.812         0.0599 0.967   0.911
#> 5 5 0.561           0.565       0.729         0.0862 0.886   0.693
#> 6 6 0.569           0.461       0.696         0.0577 0.928   0.755

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0672      0.989 0.992 0.008
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.997 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.997 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.997 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.997 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.997 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.4431      0.896 0.092 0.908
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.992 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.997 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.997 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.997 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.997 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.997 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.992 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.997 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.997 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.997 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.997 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.997 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.997 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.992 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.997 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.997 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.997 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.997 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.997 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.997 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.997 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.992 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.992 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.997 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.997 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.997 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.997 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.992 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.997 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.997 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.992 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.997 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.997 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.992 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.997 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.997 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.997 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.997 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.997 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.997 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.992 0.000 1.000
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#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000      0.997 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0000      0.997 1.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.997 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.997 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.992 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000      0.997 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000      0.997 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000      0.997 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.992 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.992 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.997 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.992 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.992 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.997 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.997 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.992 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.992 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.2603      0.952 0.956 0.044
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.997 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.997 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.992 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.997 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.992 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.997 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.997 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.997 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.997 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.997 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.992 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.997 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.997 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.997 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.997 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.997 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.997 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.997 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.997 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.997 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.997 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.997 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.997 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.992 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.997 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000      0.997 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.997 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.997 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.997 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.992 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000      0.997 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.8016      0.677 0.756 0.244
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000      0.997 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.8207      0.656 0.744 0.256
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.997 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000      0.997 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.997 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.997 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.992 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.997 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.992 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.997 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.997 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.997 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.9661      0.358 0.392 0.608
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.997 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.997 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000      0.997 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.997 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000      0.997 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.997 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.997 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.997 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.997 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.992 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.992 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.997 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.997 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.997 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.997 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.3267    0.90202 0.116 0.000 0.884
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.3267    0.90202 0.116 0.000 0.884
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2878    0.89910 0.096 0.000 0.904
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1031    0.91340 0.976 0.000 0.024
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0747    0.91587 0.984 0.000 0.016
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2537    0.88149 0.920 0.000 0.080
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4750    0.68870 0.000 0.216 0.784
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.98971 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.2625    0.87352 0.084 0.000 0.916
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0237    0.91689 0.996 0.000 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.91661 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000    0.91661 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3340    0.90144 0.120 0.000 0.880
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.98971 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5178    0.74144 0.256 0.000 0.744
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3340    0.90144 0.120 0.000 0.880
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4291    0.74557 0.820 0.000 0.180
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0892    0.91475 0.980 0.000 0.020
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0747    0.91481 0.984 0.000 0.016
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5465    0.74376 0.288 0.000 0.712
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.98971 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1031    0.91340 0.976 0.000 0.024
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0747    0.91587 0.984 0.000 0.016
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0747    0.91587 0.984 0.000 0.016
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3267    0.90202 0.116 0.000 0.884
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.1031    0.91340 0.976 0.000 0.024
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3267    0.90202 0.116 0.000 0.884
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.1289    0.90613 0.968 0.000 0.032
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.98971 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.98971 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.5835    0.49279 0.660 0.000 0.340
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     3  0.5216    0.69217 0.260 0.000 0.740
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1031    0.91340 0.976 0.000 0.024
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000    0.91661 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.98971 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.1289    0.87300 0.032 0.000 0.968
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.2261    0.88904 0.068 0.000 0.932
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.98971 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1031    0.91340 0.976 0.000 0.024
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0747    0.91587 0.984 0.000 0.016
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.98971 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.5291    0.77124 0.268 0.000 0.732
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.3267    0.90202 0.116 0.000 0.884
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4235    0.73472 0.824 0.000 0.176
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.3192    0.83530 0.888 0.000 0.112
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.3192    0.84647 0.888 0.000 0.112
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000    0.91661 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.98971 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5254    0.77044 0.264 0.000 0.736
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.98971 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0237    0.91641 0.996 0.000 0.004
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000    0.98971 0.000 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.4887    0.81770 0.228 0.000 0.772
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.4452    0.85224 0.192 0.000 0.808
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0747    0.91587 0.984 0.000 0.016
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.3267    0.90202 0.116 0.000 0.884
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3116    0.90166 0.108 0.000 0.892
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     3  0.3340    0.85879 0.120 0.000 0.880
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000    0.98971 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0747    0.91587 0.984 0.000 0.016
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.6204    0.38778 0.576 0.000 0.424
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.3340    0.89885 0.120 0.000 0.880
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.5254    0.77399 0.264 0.000 0.736
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0747    0.91587 0.984 0.000 0.016
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.98971 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2878    0.89987 0.096 0.000 0.904
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000    0.91661 1.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.2959    0.85146 0.900 0.000 0.100
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.3267    0.90202 0.116 0.000 0.884
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000    0.98971 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.3038    0.87624 0.896 0.000 0.104
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000    0.91661 1.000 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.5905    0.38987 0.648 0.000 0.352
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0892    0.91475 0.980 0.000 0.020
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     3  0.6260    0.42945 0.448 0.000 0.552
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000    0.91661 1.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     3  0.6026    0.44442 0.376 0.000 0.624
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.98971 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.3267    0.90202 0.116 0.000 0.884
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000    0.98971 0.000 1.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0592    0.91652 0.988 0.000 0.012
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.4654    0.69539 0.000 0.208 0.792
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.1964    0.90709 0.944 0.000 0.056
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000    0.91661 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0892    0.91492 0.980 0.000 0.020
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     3  0.3412    0.86259 0.124 0.000 0.876
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.1643    0.89920 0.956 0.000 0.044
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000    0.98971 0.000 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000    0.98971 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.3686    0.89398 0.140 0.000 0.860
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.5397    0.62361 0.720 0.000 0.280
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#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0747    0.91231 0.984 0.000 0.016
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.98971 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.1529    0.90181 0.960 0.000 0.040
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.98971 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.91661 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000    0.91661 1.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6045    0.27877 0.620 0.000 0.380
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.5327    0.58876 0.728 0.000 0.272
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.5397    0.57244 0.720 0.000 0.280
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.98971 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000    0.91661 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000    0.91661 1.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.5098    0.67454 0.752 0.000 0.248
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.2796    0.87674 0.908 0.000 0.092
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.1031    0.86673 0.024 0.000 0.976
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2066    0.89206 0.940 0.000 0.060
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0237    0.91689 0.996 0.000 0.004
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.6079    0.59094 0.388 0.000 0.612
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     3  0.1163    0.86798 0.028 0.000 0.972
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1289    0.90690 0.968 0.000 0.032
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.6126    0.46078 0.400 0.000 0.600
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1031    0.91340 0.976 0.000 0.024
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.98971 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.5706    0.46308 0.680 0.000 0.320
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     3  0.2261    0.88727 0.068 0.000 0.932
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2711    0.87825 0.912 0.000 0.088
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000    0.91661 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.91661 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.98971 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.3267    0.90202 0.116 0.000 0.884
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2796    0.89883 0.092 0.000 0.908
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.2878    0.89991 0.096 0.000 0.904
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     3  0.1337    0.86097 0.016 0.012 0.972
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4452    0.85852 0.192 0.000 0.808
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.3340    0.90139 0.120 0.000 0.880
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0237    0.91689 0.996 0.000 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.91661 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.98971 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0747    0.91587 0.984 0.000 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.5138    0.67033 0.000 0.748 0.252
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.5560    0.74160 0.300 0.000 0.700
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.3340    0.90148 0.120 0.000 0.880
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.3267    0.90202 0.116 0.000 0.884
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.0661    0.86008 0.008 0.004 0.988
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5926    0.57419 0.356 0.000 0.644
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1031    0.91340 0.976 0.000 0.024
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.0892    0.86521 0.020 0.000 0.980
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3267    0.90202 0.116 0.000 0.884
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1411    0.87525 0.036 0.000 0.964
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.2796    0.89883 0.092 0.000 0.908
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.1411    0.90377 0.964 0.000 0.036
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.91661 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0892    0.91492 0.980 0.000 0.020
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.98971 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.98971 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3267    0.90202 0.116 0.000 0.884
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4555    0.75514 0.800 0.000 0.200
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1289    0.91060 0.968 0.000 0.032
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1163    0.91400 0.972 0.000 0.028

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0592     0.7421 0.000 0.000 0.984 0.016
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.3074     0.7306 0.000 0.000 0.848 0.152
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.3969     0.7391 0.016 0.000 0.804 0.180
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3306     0.8236 0.840 0.000 0.004 0.156
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2530     0.8384 0.888 0.000 0.000 0.112
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1743     0.8401 0.940 0.000 0.004 0.056
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.7185     0.3992 0.000 0.284 0.540 0.176
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.1022     0.8956 0.000 0.968 0.000 0.032
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.7569     0.4010 0.368 0.000 0.436 0.196
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3583     0.8287 0.816 0.000 0.004 0.180
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1824     0.8377 0.936 0.000 0.004 0.060
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2999     0.8469 0.864 0.000 0.004 0.132
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3659     0.7513 0.136 0.000 0.840 0.024
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.6320     0.7047 0.160 0.000 0.660 0.180
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1936     0.7587 0.032 0.000 0.940 0.028
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4171     0.7703 0.828 0.000 0.088 0.084
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2216     0.8434 0.908 0.000 0.000 0.092
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0707     0.8446 0.980 0.000 0.000 0.020
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.7165     0.4474 0.372 0.000 0.488 0.140
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.1118     0.8952 0.000 0.964 0.000 0.036
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2868     0.8317 0.864 0.000 0.000 0.136
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3024     0.8275 0.852 0.000 0.000 0.148
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3306     0.8243 0.840 0.000 0.004 0.156
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2480     0.7430 0.008 0.000 0.904 0.088
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2973     0.8297 0.856 0.000 0.000 0.144
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0921     0.7425 0.000 0.000 0.972 0.028
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.4348     0.8284 0.780 0.000 0.024 0.196
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.4916     0.7163 0.000 0.576 0.000 0.424
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.1022     0.8956 0.000 0.968 0.000 0.032
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.3856     0.7369 0.832 0.000 0.136 0.032
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.7443     0.0289 0.492 0.000 0.312 0.196
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2760     0.8358 0.872 0.000 0.000 0.128
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1970     0.8348 0.932 0.000 0.008 0.060
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.2586     0.8756 0.000 0.912 0.040 0.048
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.4605     0.7612 0.132 0.012 0.808 0.048
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.6864     0.7095 0.192 0.004 0.616 0.188
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.1302     0.8938 0.000 0.956 0.000 0.044
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3123     0.8247 0.844 0.000 0.000 0.156
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.3024     0.8277 0.852 0.000 0.000 0.148
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6378     0.6361 0.264 0.000 0.628 0.108
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0188     0.7420 0.000 0.000 0.996 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4415     0.8136 0.804 0.000 0.056 0.140
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.3051     0.8124 0.884 0.000 0.028 0.088
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.3850     0.8292 0.840 0.000 0.044 0.116
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0707     0.8446 0.980 0.000 0.000 0.020
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.4679     0.7576 0.000 0.648 0.000 0.352
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5256     0.6964 0.204 0.000 0.732 0.064
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2329     0.8369 0.916 0.000 0.012 0.072
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0707     0.8970 0.000 0.980 0.000 0.020
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.4908     0.5979 0.292 0.000 0.692 0.016
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5721     0.6443 0.284 0.000 0.660 0.056
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3123     0.8247 0.844 0.000 0.000 0.156
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1389     0.7404 0.000 0.000 0.952 0.048
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3219     0.7297 0.000 0.000 0.836 0.164
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     3  0.7625     0.4185 0.360 0.000 0.432 0.208
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.1022     0.8956 0.000 0.968 0.000 0.032
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3074     0.8259 0.848 0.000 0.000 0.152
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.4982     0.6794 0.772 0.000 0.136 0.092
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.6943     0.6089 0.264 0.000 0.576 0.160
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.7073     0.4547 0.364 0.000 0.504 0.132
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3074     0.8259 0.848 0.000 0.000 0.152
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.4907     0.7189 0.000 0.580 0.000 0.420
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3172     0.7289 0.000 0.000 0.840 0.160
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1902     0.8388 0.932 0.000 0.004 0.064
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.3015     0.8128 0.884 0.000 0.024 0.092
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.3074     0.7306 0.000 0.000 0.848 0.152
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.1284     0.8458 0.964 0.000 0.012 0.024
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0921     0.8446 0.972 0.000 0.000 0.028
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.5272     0.6633 0.752 0.000 0.136 0.112
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.2647     0.8376 0.880 0.000 0.000 0.120
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     3  0.6862     0.2768 0.408 0.000 0.488 0.104
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.1004     0.8445 0.972 0.000 0.004 0.024
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.6903     0.3455 0.592 0.000 0.224 0.184
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.4916     0.7163 0.000 0.576 0.000 0.424
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.2868     0.7332 0.000 0.000 0.864 0.136
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0895     0.8932 0.000 0.976 0.004 0.020
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.2973     0.8292 0.856 0.000 0.000 0.144
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6924     0.5155 0.000 0.232 0.588 0.180
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0817     0.8445 0.976 0.000 0.000 0.024
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.1902     0.8396 0.932 0.000 0.004 0.064
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2973     0.8290 0.856 0.000 0.000 0.144
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     3  0.7421     0.3477 0.400 0.000 0.432 0.168
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3117     0.8237 0.880 0.000 0.028 0.092
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0336     0.8973 0.000 0.992 0.000 0.008
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.5558     0.7041 0.208 0.000 0.712 0.080
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.4511     0.6812 0.784 0.000 0.176 0.040
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.3051     0.8176 0.884 0.000 0.028 0.088
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.6095     0.6830 0.224 0.000 0.668 0.108
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.5619     0.6432 0.724 0.000 0.124 0.152
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.1398     0.8424 0.956 0.000 0.004 0.040
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.1767     0.7472 0.012 0.000 0.944 0.044
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.6204     0.7027 0.164 0.000 0.672 0.164
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#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0524     0.7412 0.000 0.004 0.988 0.008
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0817     0.8448 0.976 0.000 0.000 0.024
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.2706     0.8206 0.900 0.000 0.020 0.080
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.1022     0.8956 0.000 0.968 0.000 0.032
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.3143     0.8119 0.876 0.000 0.024 0.100
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0707     0.8446 0.980 0.000 0.000 0.020
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.1109     0.8452 0.968 0.000 0.004 0.028
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.5655     0.6130 0.704 0.000 0.212 0.084
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.5369     0.6548 0.740 0.000 0.164 0.096
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4581     0.7256 0.800 0.000 0.120 0.080
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0336     0.8973 0.000 0.992 0.000 0.008
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1398     0.8478 0.956 0.000 0.004 0.040
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.3024     0.8283 0.852 0.000 0.000 0.148
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.5018     0.7109 0.768 0.000 0.088 0.144
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5551     0.7324 0.728 0.000 0.112 0.160
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.6194     0.6907 0.200 0.000 0.668 0.132
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.1022     0.8490 0.968 0.000 0.000 0.032
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.3123     0.8247 0.844 0.000 0.000 0.156
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.6615    -0.0565 0.512 0.000 0.404 0.084
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     3  0.6781     0.6370 0.256 0.000 0.596 0.148
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3013     0.8349 0.888 0.000 0.032 0.080
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.7402     0.5206 0.308 0.000 0.500 0.192
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3306     0.8233 0.840 0.000 0.004 0.156
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0336     0.8973 0.000 0.992 0.000 0.008
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.5816     0.5787 0.688 0.000 0.224 0.088
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     3  0.5891     0.7204 0.132 0.000 0.700 0.168
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1398     0.8430 0.956 0.000 0.004 0.040
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2918     0.8466 0.876 0.000 0.008 0.116
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1978     0.8386 0.928 0.000 0.004 0.068
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.4907     0.7189 0.000 0.580 0.000 0.420
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.0817     0.7416 0.000 0.000 0.976 0.024
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4281     0.7083 0.000 0.028 0.792 0.180
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.1256     0.7456 0.008 0.000 0.964 0.028
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     3  0.8430     0.4105 0.036 0.300 0.452 0.212
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6688     0.4609 0.368 0.000 0.536 0.096
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4083     0.7588 0.100 0.000 0.832 0.068
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2281     0.8415 0.904 0.000 0.000 0.096
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0707     0.8446 0.980 0.000 0.000 0.020
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.8967 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3123     0.8255 0.844 0.000 0.000 0.156
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.4182     0.7332 0.000 0.796 0.180 0.024
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.6552     0.5077 0.328 0.000 0.576 0.096
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.3681     0.7376 0.008 0.000 0.816 0.176
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0817     0.7419 0.000 0.000 0.976 0.024
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.6077     0.6835 0.044 0.136 0.736 0.084
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.6055     0.4740 0.372 0.000 0.576 0.052
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3123     0.8247 0.844 0.000 0.000 0.156
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.5410     0.7138 0.192 0.000 0.728 0.080
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1109     0.7439 0.004 0.000 0.968 0.028
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.6875     0.6688 0.220 0.000 0.596 0.184
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.3991     0.7391 0.020 0.000 0.808 0.172
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4944     0.8106 0.768 0.000 0.072 0.160
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2831     0.8477 0.876 0.000 0.004 0.120
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1637     0.8487 0.940 0.000 0.000 0.060
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.4916     0.7163 0.000 0.576 0.000 0.424
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.3942     0.8160 0.000 0.764 0.000 0.236
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1022     0.7417 0.000 0.000 0.968 0.032
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5576     0.6679 0.720 0.000 0.184 0.096
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0817     0.8451 0.976 0.000 0.000 0.024
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0817     0.8463 0.976 0.000 0.000 0.024

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.1493   0.697742 0.000 0.000 0.948 0.028 0.024
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.2513   0.680851 0.000 0.000 0.876 0.116 0.008
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.3857   0.682256 0.044 0.000 0.820 0.120 0.016
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1106   0.659522 0.964 0.000 0.000 0.012 0.024
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0566   0.673889 0.984 0.000 0.000 0.004 0.012
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4940   0.557144 0.576 0.000 0.000 0.032 0.392
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6072   0.395814 0.000 0.252 0.568 0.180 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.6115   0.384066 0.136 0.000 0.280 0.008 0.576
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3080   0.570666 0.852 0.000 0.004 0.020 0.124
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.5080   0.577404 0.588 0.000 0.000 0.044 0.368
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2891   0.688051 0.824 0.000 0.000 0.000 0.176
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1981   0.692717 0.048 0.000 0.924 0.000 0.028
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000   0.826327 0.000 1.000 0.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5535   0.648442 0.060 0.000 0.720 0.108 0.112
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2305   0.687919 0.012 0.000 0.896 0.000 0.092
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5320   0.475634 0.524 0.000 0.016 0.024 0.436
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1792   0.684651 0.916 0.000 0.000 0.000 0.084
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.4898   0.595489 0.592 0.000 0.000 0.032 0.376
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.6709   0.326666 0.208 0.000 0.360 0.004 0.428
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0451   0.669111 0.988 0.000 0.000 0.004 0.008
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0162   0.667213 0.996 0.000 0.000 0.004 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1211   0.658383 0.960 0.000 0.000 0.016 0.024
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0955   0.699728 0.000 0.000 0.968 0.028 0.004
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2236   0.637662 0.908 0.000 0.000 0.024 0.068
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0963   0.697888 0.000 0.000 0.964 0.000 0.036
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.3569   0.585560 0.816 0.000 0.004 0.028 0.152
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.5631  -0.342102 0.460 0.000 0.036 0.020 0.484
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.6108   0.450388 0.164 0.000 0.216 0.012 0.608
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1043   0.672172 0.960 0.000 0.000 0.000 0.040
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.4088   0.646099 0.688 0.000 0.000 0.008 0.304
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.3551   0.729996 0.000 0.772 0.008 0.220 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.4998   0.604284 0.104 0.000 0.724 0.008 0.164
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.6035   0.065267 0.056 0.000 0.408 0.028 0.508
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1117   0.659945 0.964 0.000 0.000 0.016 0.020
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1403   0.661195 0.952 0.000 0.000 0.024 0.024
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0162   0.824888 0.000 0.996 0.000 0.004 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6452   0.193912 0.192 0.000 0.540 0.008 0.260
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1195   0.698169 0.000 0.000 0.960 0.012 0.028
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5233   0.541548 0.700 0.000 0.112 0.008 0.180
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4362   0.607986 0.632 0.000 0.004 0.004 0.360
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4498   0.581774 0.688 0.000 0.000 0.032 0.280
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.4703   0.620085 0.632 0.000 0.000 0.028 0.340
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     4  0.4219   0.756488 0.000 0.416 0.000 0.584 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.4712   0.510973 0.168 0.000 0.732 0.000 0.100
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0609   0.816007 0.000 0.980 0.000 0.020 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4522   0.649296 0.660 0.000 0.000 0.024 0.316
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.2230   0.797400 0.000 0.884 0.000 0.116 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5610   0.376763 0.212 0.000 0.656 0.008 0.124
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5276   0.557440 0.144 0.000 0.692 0.004 0.160
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1493   0.654644 0.948 0.000 0.000 0.024 0.028
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0566   0.698852 0.000 0.000 0.984 0.012 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2563   0.679146 0.000 0.000 0.872 0.120 0.008
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.5571   0.359802 0.096 0.000 0.276 0.004 0.624
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0324   0.668162 0.992 0.000 0.000 0.004 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.4858  -0.251793 0.424 0.000 0.008 0.012 0.556
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.5976   0.249536 0.116 0.000 0.376 0.000 0.508
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.6291   0.323860 0.164 0.000 0.344 0.000 0.492
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0566   0.664664 0.984 0.000 0.000 0.012 0.004
#> 131213AD-0313-4DF1-B013-CE67ED262C37     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2612   0.678905 0.000 0.000 0.868 0.124 0.008
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4184   0.664472 0.700 0.000 0.000 0.016 0.284
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.4436   0.575173 0.596 0.000 0.000 0.008 0.396
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.2462   0.681652 0.000 0.000 0.880 0.112 0.008
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000   0.826327 0.000 1.000 0.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.5234   0.547176 0.524 0.000 0.004 0.036 0.436
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.4384   0.639056 0.660 0.000 0.000 0.016 0.324
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.5078  -0.327130 0.464 0.000 0.020 0.008 0.508
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1608   0.682560 0.928 0.000 0.000 0.000 0.072
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     3  0.6177  -0.032646 0.428 0.000 0.452 0.004 0.116
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.4774   0.604883 0.612 0.000 0.000 0.028 0.360
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.5351   0.213015 0.304 0.000 0.068 0.004 0.624
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.1908   0.688015 0.000 0.000 0.908 0.092 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.1831   0.808864 0.000 0.920 0.000 0.076 0.004
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0771   0.669997 0.976 0.000 0.000 0.004 0.020
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.5086   0.578621 0.000 0.144 0.700 0.156 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.5188   0.569130 0.540 0.000 0.000 0.044 0.416
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.4651   0.583589 0.608 0.000 0.000 0.020 0.372
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0693   0.666762 0.980 0.000 0.000 0.008 0.012
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     5  0.6392   0.405983 0.192 0.000 0.272 0.004 0.532
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4537   0.556764 0.592 0.000 0.000 0.012 0.396
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#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.4824   0.583274 0.596 0.000 0.004 0.020 0.380
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.4718   0.623297 0.628 0.000 0.000 0.028 0.344
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1270   0.695465 0.000 0.000 0.948 0.000 0.052
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0794   0.698421 0.000 0.000 0.972 0.000 0.028
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.7007   0.414995 0.260 0.000 0.300 0.012 0.428
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.4101   0.629881 0.664 0.000 0.000 0.004 0.332
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.3242   0.708048 0.000 0.784 0.000 0.216 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.6724   0.025925 0.316 0.000 0.452 0.004 0.228
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1697   0.694856 0.000 0.000 0.932 0.060 0.008
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.7811  -0.103650 0.468 0.000 0.244 0.136 0.152
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0955   0.806829 0.000 0.968 0.000 0.028 0.004
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2471   0.787594 0.000 0.864 0.000 0.136 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.3476   0.688138 0.804 0.000 0.000 0.020 0.176
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000   0.826327 0.000 1.000 0.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3659   0.729007 0.000 0.768 0.012 0.220 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.4366   0.602903 0.664 0.000 0.000 0.016 0.320
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.1753   0.651613 0.936 0.000 0.000 0.032 0.032
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.2424   0.788733 0.000 0.868 0.000 0.132 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.1403   0.698174 0.000 0.000 0.952 0.024 0.024
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.4655   0.627956 0.644 0.000 0.000 0.028 0.328
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.4252   0.624518 0.652 0.000 0.000 0.008 0.340
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.3109   0.732268 0.000 0.800 0.000 0.200 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4310   0.584372 0.604 0.000 0.000 0.004 0.392
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000   0.826327 0.000 1.000 0.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.4558   0.628352 0.652 0.000 0.000 0.024 0.324
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.5086   0.591976 0.564 0.000 0.000 0.040 0.396
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6604   0.030487 0.556 0.000 0.252 0.024 0.168
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.5328  -0.430661 0.468 0.000 0.012 0.028 0.492
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.5000  -0.362992 0.476 0.000 0.016 0.008 0.500
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.2020   0.801744 0.000 0.900 0.000 0.100 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.3607   0.675427 0.752 0.000 0.000 0.004 0.244
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.2535   0.638375 0.892 0.000 0.000 0.032 0.076
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.4580  -0.319847 0.460 0.000 0.004 0.004 0.532
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5911   0.339011 0.668 0.000 0.100 0.044 0.188
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.6459   0.225074 0.180 0.000 0.504 0.004 0.312
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3163   0.690587 0.824 0.000 0.000 0.012 0.164
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.2304   0.631869 0.908 0.000 0.000 0.044 0.048
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.6832  -0.211695 0.364 0.000 0.392 0.004 0.240
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     5  0.6157   0.249072 0.140 0.000 0.364 0.000 0.496
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5750   0.397526 0.612 0.000 0.116 0.004 0.268
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.7254   0.505886 0.164 0.000 0.560 0.132 0.144
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2221   0.639745 0.912 0.000 0.000 0.036 0.052
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2424   0.786142 0.000 0.868 0.000 0.132 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.6377   0.099814 0.584 0.000 0.236 0.020 0.160
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     5  0.4627  -0.042571 0.000 0.000 0.444 0.012 0.544
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4898   0.576632 0.592 0.000 0.000 0.032 0.376
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2439   0.694137 0.876 0.000 0.000 0.004 0.120
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.4306   0.630064 0.660 0.000 0.000 0.012 0.328
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.1357   0.695323 0.000 0.000 0.948 0.004 0.048
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.3326   0.664582 0.000 0.024 0.824 0.152 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0880   0.699001 0.000 0.000 0.968 0.000 0.032
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.6939   0.098234 0.004 0.140 0.280 0.040 0.536
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6640  -0.019664 0.312 0.000 0.472 0.004 0.212
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4464   0.448367 0.004 0.000 0.632 0.008 0.356
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1831   0.685439 0.920 0.000 0.000 0.004 0.076
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4703   0.626060 0.632 0.000 0.000 0.028 0.340
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000   0.826327 0.000 1.000 0.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0912   0.662458 0.972 0.000 0.000 0.012 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.3909   0.601003 0.000 0.808 0.124 0.064 0.004
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.6547   0.142804 0.216 0.000 0.504 0.004 0.276
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.4513   0.667401 0.004 0.000 0.764 0.128 0.104
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1018   0.699176 0.000 0.000 0.968 0.016 0.016
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.6242   0.505043 0.048 0.004 0.628 0.080 0.240
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5805   0.458142 0.192 0.000 0.640 0.008 0.160
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.2889   0.607317 0.872 0.000 0.000 0.044 0.084
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.5959   0.432426 0.152 0.000 0.600 0.004 0.244
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1638   0.692206 0.000 0.000 0.932 0.004 0.064
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.6209   0.261843 0.096 0.000 0.336 0.020 0.548
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.3010   0.689654 0.020 0.000 0.868 0.100 0.012
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4054   0.609828 0.812 0.000 0.028 0.040 0.120
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3304   0.686470 0.816 0.000 0.000 0.016 0.168
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4562   0.659213 0.676 0.000 0.000 0.032 0.292
#> 206865A9-A67C-49A6-93AD-55D06E777559     4  0.3774   0.955891 0.000 0.296 0.000 0.704 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.4101   0.183969 0.000 0.628 0.000 0.372 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0510   0.699324 0.000 0.000 0.984 0.000 0.016
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.6670  -0.091528 0.528 0.000 0.296 0.024 0.152
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4779   0.629279 0.628 0.000 0.000 0.032 0.340
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4292   0.665288 0.704 0.000 0.000 0.024 0.272

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.1838    0.71692 0.000 0.012 0.928 0.000 0.040 0.020
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.2278    0.71270 0.000 0.044 0.900 0.000 0.004 0.052
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4044    0.69236 0.008 0.044 0.788 0.000 0.024 0.136
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1843    0.48379 0.912 0.004 0.000 0.000 0.004 0.080
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1863    0.36242 0.896 0.000 0.000 0.000 0.000 0.104
#> 03E81178-E971-4E91-8BED-D8273EA1425C     6  0.4165    0.93068 0.452 0.000 0.000 0.000 0.012 0.536
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6024    0.30127 0.000 0.120 0.520 0.324 0.000 0.036
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     4  0.2730    0.76876 0.000 0.192 0.000 0.808 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4876    0.63420 0.104 0.000 0.152 0.000 0.712 0.032
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4108    0.47424 0.748 0.008 0.000 0.000 0.060 0.184
#> B710293C-41D3-4A2E-8104-5402F91DD859     6  0.4242    0.91587 0.448 0.000 0.000 0.000 0.016 0.536
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2959    0.39828 0.852 0.008 0.000 0.000 0.036 0.104
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1036    0.72525 0.024 0.000 0.964 0.000 0.008 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.0146    0.83672 0.000 0.004 0.000 0.996 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5496    0.59267 0.016 0.036 0.660 0.000 0.076 0.212
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2445    0.68262 0.008 0.000 0.868 0.000 0.120 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.6035    0.30737 0.460 0.004 0.000 0.000 0.300 0.236
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2085    0.42964 0.912 0.008 0.000 0.000 0.024 0.056
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     6  0.3854    0.90578 0.464 0.000 0.000 0.000 0.000 0.536
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.6452    0.60561 0.192 0.000 0.144 0.000 0.560 0.104
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     4  0.2730    0.76876 0.000 0.192 0.000 0.808 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1387    0.40047 0.932 0.000 0.000 0.000 0.000 0.068
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1296    0.44330 0.948 0.004 0.000 0.000 0.004 0.044
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2904    0.48843 0.852 0.008 0.000 0.000 0.028 0.112
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0976    0.72671 0.000 0.008 0.968 0.000 0.016 0.008
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2300    0.45368 0.856 0.000 0.000 0.000 0.000 0.144
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0713    0.72362 0.000 0.000 0.972 0.000 0.028 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.4171    0.46570 0.732 0.008 0.000 0.000 0.052 0.208
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.3076    0.95968 0.000 0.760 0.000 0.240 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     4  0.2762    0.76483 0.000 0.196 0.000 0.804 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.6211   -0.38812 0.388 0.000 0.004 0.000 0.292 0.316
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.5893    0.60733 0.192 0.008 0.120 0.000 0.628 0.052
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2085    0.45814 0.912 0.008 0.000 0.000 0.024 0.056
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.4193   -0.12202 0.684 0.000 0.000 0.000 0.044 0.272
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     4  0.3348    0.76324 0.000 0.216 0.000 0.768 0.000 0.016
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6261    0.32055 0.076 0.000 0.560 0.000 0.240 0.124
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.5800    0.53560 0.056 0.008 0.236 0.000 0.620 0.080
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.2912    0.74037 0.000 0.216 0.000 0.784 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1267    0.45811 0.940 0.000 0.000 0.000 0.000 0.060
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1387    0.45402 0.932 0.000 0.000 0.000 0.000 0.068
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.0363    0.83163 0.000 0.012 0.000 0.988 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6997   -0.23990 0.156 0.000 0.400 0.000 0.344 0.100
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1080    0.72227 0.000 0.004 0.960 0.000 0.032 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5282    0.36669 0.700 0.004 0.088 0.000 0.136 0.072
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.5824    0.11125 0.540 0.008 0.000 0.000 0.228 0.224
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4145    0.45452 0.700 0.000 0.000 0.000 0.048 0.252
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     6  0.4083    0.91792 0.460 0.000 0.000 0.000 0.008 0.532
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.3607    0.80546 0.000 0.652 0.000 0.348 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5446    0.45645 0.132 0.000 0.676 0.000 0.120 0.072
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.0777    0.82263 0.000 0.024 0.000 0.972 0.000 0.004
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4845    0.29594 0.692 0.012 0.000 0.000 0.176 0.120
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.2260    0.81279 0.000 0.140 0.000 0.860 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.6655    0.18419 0.204 0.000 0.520 0.000 0.088 0.188
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.6628    0.28051 0.132 0.000 0.544 0.000 0.152 0.172
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3310    0.48625 0.816 0.016 0.000 0.000 0.020 0.148
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0291    0.72465 0.000 0.000 0.992 0.000 0.004 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2575    0.70824 0.000 0.044 0.880 0.000 0.004 0.072
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.5110    0.63379 0.132 0.000 0.132 0.000 0.696 0.040
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.2793    0.76649 0.000 0.200 0.000 0.800 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1461    0.43461 0.940 0.000 0.000 0.000 0.016 0.044
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#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.3076    0.95968 0.000 0.760 0.000 0.240 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.1897    0.70396 0.000 0.004 0.908 0.000 0.084 0.004
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#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.4959    0.52371 0.000 0.008 0.160 0.068 0.720 0.044
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#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     6  0.3864    0.88877 0.480 0.000 0.000 0.000 0.000 0.520
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Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-mclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


SD:NMF*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "NMF"]
# you can also extract it by
# res = res_list["SD:NMF"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 5.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.986           0.956       0.982         0.4262 0.586   0.586
#> 3 3 0.868           0.888       0.953         0.5018 0.734   0.562
#> 4 4 0.777           0.788       0.912         0.0907 0.885   0.703
#> 5 5 0.923           0.883       0.948         0.0818 0.873   0.621
#> 6 6 0.807           0.735       0.880         0.0566 0.931   0.737

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 5
#> attr(,"optional")
#> [1] 2

There is also optional best \(k\) = 2 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0376      0.990 0.004 0.996
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.977 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.977 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.977 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.977 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.977 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.993 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.993 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.977 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.977 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.977 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.977 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.977 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.993 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.977 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.977 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.977 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.977 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.977 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.977 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.993 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.977 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.977 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.977 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.977 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.977 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0938      0.966 0.988 0.012
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.977 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.993 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.993 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.977 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.977 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.977 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.977 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.993 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.7950      0.693 0.760 0.240
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.977 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.993 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.977 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.977 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.993 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.977 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     2  0.0672      0.986 0.008 0.992
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.977 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.977 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.977 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.977 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.993 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.977 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.993 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.977 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.993 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.977 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.977 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.977 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.6712      0.786 0.824 0.176
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.977 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000      0.977 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.993 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.977 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.977 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0672      0.970 0.992 0.008
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.977 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.977 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.993 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.8081      0.679 0.752 0.248
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.977 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.977 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0376      0.973 0.996 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.993 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.977 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.977 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.977 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.977 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000      0.977 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.977 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.977 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.993 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.9993      0.100 0.516 0.484
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000      0.993 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.977 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.0000      0.993 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.977 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.977 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.977 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000      0.977 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000      0.977 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000      0.993 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000      0.993 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.977 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000      0.977 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.977 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000      0.993 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.977 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000      0.977 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000      0.977 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.6712      0.780 0.176 0.824
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0000      0.977 1.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000      0.977 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.977 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000      0.977 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.993 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.993 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000      0.977 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000      0.977 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.993 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000      0.993 0.000 1.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000      0.977 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000      0.977 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000      0.993 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000      0.993 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000      0.977 1.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0000      0.977 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000      0.977 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000      0.977 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000      0.977 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000      0.977 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000      0.977 1.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000      0.977 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000      0.977 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000      0.977 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000      0.977 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000      0.977 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000      0.977 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     1  0.9754      0.325 0.592 0.408
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.0000      0.993 0.000 1.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.0000      0.993 0.000 1.000
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000      0.977 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.0000      0.977 1.000 0.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0000      0.977 1.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.0000      0.977 1.000 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000      0.977 1.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000      0.993 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.0000      0.977 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000      0.993 0.000 1.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000      0.993 0.000 1.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000      0.977 1.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000      0.993 0.000 1.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000      0.993 0.000 1.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000      0.977 1.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.0000      0.977 1.000 0.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000      0.993 0.000 1.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.0000      0.977 1.000 0.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0000      0.993 0.000 1.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000      0.993 0.000 1.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.0000      0.977 1.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.0000      0.977 1.000 0.000
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000      0.993 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.0000      0.977 1.000 0.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0000      0.977 1.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000      0.977 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0000      0.977 1.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000      0.993 0.000 1.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0000      0.977 1.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     2  0.2236      0.958 0.036 0.964
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.0000      0.993 0.000 1.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000      0.977 1.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.0000      0.977 1.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.0000      0.993 0.000 1.000
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000      0.993 0.000 1.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.0000      0.977 1.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1  0.0000      0.977 1.000 0.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000      0.993 0.000 1.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000      0.977 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000      0.993 0.000 1.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000      0.993 0.000 1.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.9248      0.506 0.660 0.340
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000      0.993 0.000 1.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000      0.977 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000      0.993 0.000 1.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.0000      0.977 1.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000      0.977 1.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.0938      0.966 0.988 0.012
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000      0.977 1.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.0000      0.977 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0000      0.977 1.000 0.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0000      0.977 1.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000      0.977 1.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0000      0.977 1.000 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000      0.993 0.000 1.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000      0.993 0.000 1.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.0000      0.977 1.000 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000      0.993 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000      0.977 1.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000      0.977 1.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000      0.993 0.000 1.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000      0.977 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0000      0.977 1.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000      0.993 0.000 1.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000      0.993 0.000 1.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000      0.993 0.000 1.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000      0.977 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000      0.977 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000      0.977 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000      0.977 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000      0.977 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000      0.993 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.0000      0.977 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000      0.977 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.5519      0.844 0.872 0.128
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000      0.977 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.3274      0.933 0.060 0.940
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000      0.977 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000      0.977 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000      0.977 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000      0.977 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000      0.977 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.9393      0.458 0.644 0.356
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000      0.977 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000      0.993 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000      0.993 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0000      0.977 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000      0.977 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000      0.977 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000      0.977 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000      0.977 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000      0.993 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.8386      0.646 0.732 0.268
#> DD51C17C-300F-44A4-955A-C9BC85417842     2  0.3879      0.914 0.076 0.924
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.977 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.977 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000      0.993 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0000      0.977 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000      0.993 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.993 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.993 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000      0.977 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     2  0.0000      0.993 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000      0.977 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.977 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.977 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000      0.977 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.6887      0.775 0.816 0.184
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.977 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.977 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.993 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000      0.977 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000      0.977 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000      0.977 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.993 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.993 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.977 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.993 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.993 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.977 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.977 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.993 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.993 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     2  0.0000      0.993 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.977 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.977 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.993 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.977 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.993 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.977 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.977 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.977 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.977 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.977 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.993 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.977 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.977 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.977 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.977 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.7745      0.712 0.772 0.228
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.977 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.977 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.977 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.6973      0.770 0.812 0.188
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.977 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.977 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.977 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.993 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.977 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.7674      0.707 0.224 0.776
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.977 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.977 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.977 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.993 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000      0.977 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000      0.993 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.9552      0.423 0.624 0.376
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.993 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.977 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.9522      0.419 0.628 0.372
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.977 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.977 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.993 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.977 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.993 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.977 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.977 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.9988      0.115 0.520 0.480
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.993 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.977 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.977 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3274      0.921 0.940 0.060
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0376      0.973 0.996 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.9954      0.179 0.540 0.460
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.977 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.977 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.977 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.977 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.993 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.993 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.977 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.977 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.977 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.977 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.2165      0.872 0.000 0.064 0.936
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000      0.915 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000      0.915 0.000 0.000 1.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.949 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.949 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.949 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.0892      0.904 0.000 0.020 0.980
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.977 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.949 1.000 0.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.6274      0.111 0.544 0.000 0.456
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.949 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.949 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000      0.915 0.000 0.000 1.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.977 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0000      0.915 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000      0.915 0.000 0.000 1.000
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#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.0000      0.949 1.000 0.000 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000      0.977 0.000 1.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000      0.949 1.000 0.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000      0.949 1.000 0.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000      0.977 0.000 1.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000      0.949 1.000 0.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.5733      0.513 0.676 0.000 0.324
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000      0.977 0.000 1.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000      0.977 0.000 1.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     3  0.4887      0.690 0.000 0.228 0.772
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000      0.949 1.000 0.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000      0.949 1.000 0.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000      0.949 1.000 0.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.4555      0.731 0.800 0.000 0.200
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000      0.949 1.000 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000      0.977 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.5591      0.553 0.696 0.000 0.304
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000      0.949 1.000 0.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.0424      0.943 0.992 0.008 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000      0.949 1.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.2165      0.905 0.064 0.936 0.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.6295      0.119 0.472 0.000 0.528
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000      0.949 1.000 0.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000      0.949 1.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000      0.949 1.000 0.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000      0.949 1.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     3  0.5012      0.723 0.008 0.204 0.788
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.6204      0.279 0.424 0.000 0.576
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000      0.977 0.000 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.4399      0.759 0.000 0.812 0.188
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0000      0.915 0.000 0.000 1.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.1031      0.905 0.024 0.000 0.976
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000      0.949 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000      0.949 1.000 0.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000      0.949 1.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.1031      0.957 0.000 0.976 0.024
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0000      0.915 0.000 0.000 1.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000      0.915 0.000 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.949 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.949 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000      0.977 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000      0.915 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000      0.977 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.977 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.977 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5465      0.583 0.712 0.000 0.288
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000      0.915 0.000 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000      0.949 1.000 0.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.949 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.949 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000      0.915 0.000 0.000 1.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000      0.915 0.000 0.000 1.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.949 1.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.949 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.977 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1753      0.909 0.952 0.000 0.048
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000      0.915 0.000 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0237      0.913 0.004 0.000 0.996
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.977 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.977 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.949 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.977 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.977 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.5058      0.685 0.244 0.000 0.756
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4291      0.759 0.820 0.000 0.180
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.977 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.977 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0424      0.911 0.000 0.008 0.992
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.949 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.949 1.000 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.977 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.949 1.000 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.977 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.949 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.949 1.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.2959      0.852 0.100 0.000 0.900
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.6180      0.276 0.584 0.000 0.416
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.949 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.977 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.949 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.949 1.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.949 1.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0747      0.909 0.016 0.000 0.984
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.9667      0.147 0.264 0.464 0.272
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.949 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.4555      0.754 0.200 0.000 0.800
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5760      0.486 0.672 0.000 0.328
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.6008      0.418 0.628 0.372 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3619      0.816 0.864 0.000 0.136
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000      0.915 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0237      0.946 0.996 0.000 0.004
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.977 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.4887      0.710 0.228 0.000 0.772
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.6012      0.749 0.124 0.788 0.088
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.949 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0747      0.937 0.984 0.000 0.016
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.949 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.977 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.0000      0.915 0.000 0.000 1.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000      0.915 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0000      0.915 0.000 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0424      0.969 0.008 0.992 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1031      0.905 0.024 0.000 0.976
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4335      0.832 0.036 0.100 0.864
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.949 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.949 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.977 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.949 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.5810      0.495 0.000 0.336 0.664
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.2165      0.882 0.064 0.000 0.936
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000      0.915 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000      0.915 0.000 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.977 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.2261      0.876 0.068 0.000 0.932
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1031      0.930 0.976 0.000 0.024
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.9278      0.245 0.196 0.516 0.288
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000      0.915 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.4110      0.787 0.152 0.844 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0000      0.915 0.000 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.0424      0.912 0.008 0.000 0.992
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.949 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.949 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.977 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.977 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000      0.915 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.1411      0.900 0.036 0.000 0.964
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.949 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.949 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.0707     0.7671 0.000 0.000 0.020 0.980
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.3610     0.6844 0.000 0.000 0.800 0.200
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0188     0.7851 0.000 0.000 0.996 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0188     0.9411 0.996 0.000 0.004 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.1042     0.7787 0.000 0.020 0.972 0.008
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.5147     0.1732 0.460 0.000 0.004 0.536
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.5292     0.0193 0.512 0.000 0.480 0.008
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3219     0.7172 0.000 0.000 0.836 0.164
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0707     0.9264 0.000 0.980 0.000 0.020
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4985     0.2061 0.000 0.000 0.532 0.468
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.6752     0.2210 0.440 0.000 0.468 0.092
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.6179     0.3430 0.608 0.000 0.320 0.072
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2408     0.8516 0.896 0.000 0.104 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     4  0.4994    -0.0738 0.000 0.000 0.480 0.520
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1389     0.7781 0.000 0.000 0.952 0.048
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4868     0.5680 0.256 0.000 0.720 0.024
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.5070     0.2855 0.416 0.000 0.004 0.580
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9410 0.000 1.000 0.000 0.000
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#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.1004     0.7662 0.000 0.004 0.024 0.972
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0336     0.9388 0.992 0.000 0.008 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     3  0.4866     0.3911 0.404 0.000 0.596 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.5842     0.5983 0.704 0.000 0.128 0.168
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.1211     0.9158 0.960 0.000 0.000 0.040
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.0188     0.9410 0.996 0.000 0.000 0.004
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.5150     0.3007 0.396 0.596 0.000 0.008
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.5827     0.2804 0.436 0.000 0.532 0.032
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.0657     0.7691 0.004 0.000 0.012 0.984
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.4522     0.5059 0.320 0.000 0.680 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0188     0.7684 0.000 0.000 0.004 0.996
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.3833     0.7381 0.072 0.000 0.848 0.080
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0188     0.9412 0.996 0.000 0.004 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.3024     0.7285 0.000 0.000 0.852 0.148
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0707     0.9304 0.980 0.000 0.000 0.020
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.1389     0.7782 0.000 0.000 0.952 0.048
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5604    -0.0721 0.504 0.000 0.476 0.020
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.2081     0.7650 0.000 0.000 0.916 0.084
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0188     0.9411 0.996 0.000 0.000 0.004
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.4222     0.6039 0.000 0.000 0.728 0.272
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.2149     0.7637 0.000 0.000 0.912 0.088
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.4985     0.2129 0.468 0.000 0.532 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1022     0.7817 0.000 0.000 0.968 0.032
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1474     0.7629 0.000 0.052 0.000 0.948
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.6206     0.3521 0.404 0.000 0.540 0.056
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.4933     0.3226 0.432 0.000 0.568 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.4998     0.1470 0.000 0.000 0.512 0.488
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.1042     0.9249 0.972 0.000 0.008 0.020
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0188     0.9412 0.996 0.000 0.004 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0524     0.7848 0.004 0.000 0.988 0.008
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.6189     0.2098 0.568 0.000 0.372 0.060
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1584     0.9103 0.952 0.000 0.036 0.012
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.7851 0.000 0.000 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.5487     0.2700 0.400 0.580 0.020 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.1022     0.7804 0.032 0.000 0.968 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.4741     0.6314 0.744 0.000 0.228 0.028
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.3266     0.7561 0.832 0.168 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4713     0.3801 0.640 0.000 0.360 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2814     0.8157 0.868 0.000 0.132 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.3591     0.6391 0.168 0.000 0.824 0.008
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.0707     0.7706 0.000 0.020 0.000 0.980
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4605     0.4438 0.664 0.000 0.336 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.1302     0.7579 0.000 0.000 0.044 0.956
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.1118     0.7724 0.000 0.000 0.964 0.036
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6393     0.4837 0.284 0.000 0.616 0.100
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.0336     0.7658 0.000 0.000 0.008 0.992
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.3873     0.6984 0.000 0.772 0.000 0.228
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0188     0.7684 0.000 0.000 0.004 0.996
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.7010     0.3460 0.184 0.000 0.240 0.576
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1389     0.7789 0.000 0.000 0.952 0.048
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.0672     0.7839 0.008 0.000 0.984 0.008
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4500     0.4991 0.684 0.000 0.316 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.6634     0.4256 0.112 0.248 0.632 0.008
#> CE6B6871-3ED3-44DE-A777-7558D4429057     4  0.4989    -0.0488 0.000 0.000 0.472 0.528
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.4505     0.7360 0.112 0.824 0.028 0.036
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.0469     0.7860 0.012 0.000 0.988 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9410 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     4  0.4989    -0.0470 0.000 0.000 0.472 0.528
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.0336     0.7851 0.000 0.000 0.992 0.008
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9433 1.000 0.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9433 1.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.0162     0.8798 0.000 0.000 0.004 0.996 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0510     0.9599 0.000 0.000 0.984 0.000 0.016
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.3816     0.5788 0.000 0.000 0.304 0.000 0.696
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0404     0.9584 0.988 0.000 0.000 0.000 0.012
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0162     0.9604 0.996 0.000 0.000 0.000 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5841     0.4434 0.000 0.180 0.608 0.000 0.212
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.4001     0.6604 0.204 0.000 0.020 0.768 0.008
#> 53062969-D209-490B-9C9B-5D297625E2AE     5  0.3928     0.5546 0.296 0.000 0.000 0.004 0.700
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0162     0.9604 0.996 0.000 0.000 0.000 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0510     0.9599 0.000 0.000 0.984 0.000 0.016
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4297     0.0929 0.000 0.528 0.000 0.472 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.0404     0.9008 0.000 0.000 0.012 0.000 0.988
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0404     0.9594 0.000 0.000 0.988 0.012 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0510     0.9607 0.016 0.000 0.984 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0566     0.9554 0.984 0.000 0.012 0.000 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0609     0.9597 0.020 0.000 0.980 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1851     0.8956 0.912 0.000 0.000 0.000 0.088
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0609     0.9566 0.000 0.000 0.980 0.020 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0290     0.9597 0.992 0.000 0.008 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0609     0.9587 0.000 0.000 0.980 0.000 0.020
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0671     0.9610 0.016 0.000 0.980 0.000 0.004
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0162     0.9604 0.996 0.000 0.000 0.000 0.004
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#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0566     0.9554 0.984 0.000 0.012 0.000 0.004
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0324     0.9596 0.992 0.000 0.004 0.000 0.004
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     5  0.0324     0.9011 0.000 0.000 0.004 0.004 0.992
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     4  0.0404     0.8761 0.000 0.012 0.000 0.988 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     4  0.1059     0.8687 0.020 0.000 0.008 0.968 0.004
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0290     0.9595 0.992 0.000 0.008 0.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.0609     0.9597 0.020 0.000 0.980 0.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.1012     0.9495 0.968 0.000 0.012 0.000 0.020
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.3966     0.5040 0.664 0.000 0.000 0.000 0.336
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0162     0.9604 0.996 0.000 0.004 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.0771     0.9586 0.020 0.000 0.976 0.000 0.004
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.4084     0.4782 0.668 0.000 0.000 0.328 0.004
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.1095     0.9480 0.968 0.000 0.012 0.012 0.008
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.6776     0.2883 0.176 0.544 0.016 0.256 0.008
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0510     0.9607 0.016 0.000 0.984 0.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.0703     0.9567 0.024 0.000 0.976 0.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     5  0.0404     0.9002 0.000 0.000 0.012 0.000 0.988
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     5  0.4004     0.7119 0.172 0.000 0.004 0.040 0.784
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.3796     0.5806 0.700 0.000 0.300 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0693     0.9542 0.980 0.000 0.012 0.000 0.008
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0162     0.9323 0.000 0.996 0.004 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     5  0.0510     0.9003 0.000 0.000 0.016 0.000 0.984
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0609     0.9587 0.000 0.000 0.980 0.000 0.020
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.2352     0.8772 0.896 0.000 0.008 0.092 0.004
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0404     0.9603 0.000 0.000 0.988 0.000 0.012
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0510     0.9607 0.016 0.000 0.984 0.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0510     0.9599 0.000 0.000 0.984 0.000 0.016
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1095     0.9481 0.968 0.000 0.012 0.012 0.008
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0510     0.9599 0.000 0.000 0.984 0.000 0.016
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0703     0.9568 0.000 0.000 0.976 0.000 0.024
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0162     0.9604 0.996 0.000 0.004 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.2124     0.8856 0.900 0.000 0.004 0.000 0.096
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0510     0.9599 0.000 0.000 0.984 0.000 0.016
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.0609     0.8990 0.000 0.000 0.020 0.000 0.980
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.0794     0.9538 0.028 0.000 0.972 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.1670     0.9227 0.936 0.000 0.012 0.000 0.052
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0566     0.9586 0.000 0.004 0.984 0.012 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0771     0.9514 0.976 0.000 0.020 0.000 0.004
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.0955     0.9528 0.028 0.000 0.968 0.000 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0671     0.9541 0.980 0.000 0.016 0.000 0.004
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.1478     0.8806 0.000 0.936 0.000 0.064 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0566     0.9578 0.984 0.000 0.012 0.000 0.004
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     5  0.0324     0.9022 0.004 0.000 0.004 0.000 0.992
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0609     0.9597 0.020 0.000 0.980 0.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.0703     0.9574 0.024 0.000 0.976 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0162     0.9607 0.996 0.000 0.000 0.000 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0162     0.9604 0.996 0.000 0.004 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     5  0.3928     0.5953 0.004 0.000 0.296 0.000 0.700
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.4430     0.1333 0.456 0.540 0.000 0.000 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.6631     0.2291 0.224 0.000 0.356 0.000 0.420
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.0955     0.9525 0.028 0.000 0.968 0.000 0.004
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.2732     0.7872 0.840 0.160 0.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1965     0.8785 0.904 0.000 0.096 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.0510     0.9001 0.000 0.000 0.016 0.000 0.984
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0703     0.9521 0.976 0.000 0.000 0.000 0.024
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     5  0.0671     0.8998 0.016 0.000 0.004 0.000 0.980
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9608 1.000 0.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     3  0.2891     0.7377 0.176 0.000 0.824 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0162     0.9604 0.996 0.000 0.004 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.0162     0.8792 0.000 0.000 0.000 0.996 0.004
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.0963     0.8908 0.000 0.000 0.036 0.000 0.964
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     5  0.0324     0.9011 0.000 0.000 0.004 0.004 0.992
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0162     0.9325 0.000 0.996 0.000 0.000 0.004
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0451     0.9613 0.004 0.000 0.988 0.000 0.008
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.3366     0.6519 0.000 0.000 0.232 0.768 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0162     0.9604 0.996 0.000 0.004 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.3774     0.5475 0.000 0.296 0.000 0.704 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0290     0.9599 0.992 0.000 0.000 0.000 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0000     0.8807 0.000 0.000 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.4161     0.3802 0.392 0.000 0.000 0.608 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0609     0.8990 0.000 0.000 0.020 0.000 0.980
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     5  0.2763     0.7993 0.000 0.000 0.148 0.004 0.848
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     5  0.0451     0.9020 0.008 0.000 0.004 0.000 0.988
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3492     0.7492 0.796 0.000 0.016 0.000 0.188
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     5  0.1282     0.8804 0.044 0.004 0.000 0.000 0.952
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0404     0.9594 0.000 0.000 0.988 0.012 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0932     0.9522 0.004 0.020 0.972 0.000 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     5  0.0324     0.9011 0.000 0.000 0.004 0.004 0.992
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.1197     0.9383 0.000 0.000 0.952 0.000 0.048
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0451     0.9575 0.988 0.000 0.008 0.000 0.004
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9355 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0510     0.9582 0.000 0.000 0.984 0.016 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     5  0.0579     0.9024 0.008 0.000 0.008 0.000 0.984
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0290     0.9591 0.992 0.000 0.008 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0162     0.9606 0.996 0.000 0.000 0.000 0.004

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.3409    0.64266 0.000 0.000 0.000 0.700 0.300 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0146    0.95486 0.000 0.000 0.996 0.000 0.004 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.6119    0.33092 0.000 0.000 0.312 0.000 0.324 0.364
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0363    0.82320 0.988 0.000 0.000 0.000 0.000 0.012
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3023    0.64355 0.784 0.000 0.000 0.000 0.212 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.3789    0.34238 0.416 0.000 0.000 0.000 0.584 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5697    0.31569 0.000 0.240 0.548 0.000 0.004 0.208
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.94415 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.2562    0.44606 0.000 0.000 0.000 0.172 0.828 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4063    0.58317 0.736 0.000 0.000 0.052 0.004 0.208
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#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     6  0.0260    0.77324 0.000 0.000 0.000 0.000 0.008 0.992
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.3828    0.14404 0.000 0.440 0.000 0.000 0.560 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0260    0.95330 0.000 0.000 0.992 0.000 0.008 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.1644    0.80562 0.004 0.000 0.076 0.920 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0146    0.82297 0.996 0.000 0.000 0.000 0.000 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0260    0.82212 0.992 0.000 0.000 0.000 0.008 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.6122    0.16886 0.000 0.324 0.000 0.360 0.316 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0458    0.82196 0.984 0.000 0.000 0.000 0.000 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0000    0.86840 0.000 0.000 0.000 1.000 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.4724    0.49418 0.184 0.000 0.016 0.724 0.060 0.016
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.3314    0.68060 0.000 0.000 0.004 0.000 0.256 0.740
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     6  0.2845    0.67765 0.000 0.000 0.172 0.004 0.004 0.820
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0260    0.93944 0.000 0.992 0.000 0.000 0.008 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     6  0.0260    0.77182 0.008 0.000 0.000 0.000 0.000 0.992
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5859    0.01386 0.460 0.000 0.000 0.000 0.332 0.208
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     6  0.3974    0.57943 0.048 0.000 0.000 0.000 0.224 0.728
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.95537 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0291    0.95359 0.000 0.004 0.992 0.000 0.004 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.0363    0.77321 0.000 0.000 0.000 0.000 0.012 0.988
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.3740    0.63792 0.228 0.000 0.740 0.000 0.000 0.032
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0725    0.82008 0.976 0.000 0.000 0.000 0.012 0.012
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1387    0.79451 0.932 0.000 0.000 0.000 0.068 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.94415 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.94415 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.95537 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.3376    0.61851 0.016 0.000 0.000 0.000 0.220 0.764
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.3847    0.10198 0.544 0.000 0.000 0.000 0.456 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2964    0.66276 0.792 0.000 0.000 0.000 0.204 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-NMF-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-NMF-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "hclust"]
# you can also extract it by
# res = res_list["CV:hclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   There is no best k.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.579           0.818       0.889         0.2537 0.663   0.663
#> 3 3 0.795           0.857       0.931         0.6283 0.900   0.851
#> 4 4 0.833           0.809       0.897         0.0428 0.986   0.976
#> 5 5 0.683           0.778       0.861         0.0963 0.989   0.982
#> 6 6 0.456           0.677       0.788         0.1223 0.992   0.985

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] NA

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.9988     -0.515 0.520 0.480
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.940 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.940 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.940 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.940 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.940 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.0672      0.932 0.992 0.008
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.9358      0.792 0.352 0.648
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0672      0.932 0.992 0.008
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0938      0.928 0.988 0.012
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.940 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2043      0.905 0.968 0.032
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.940 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.9944      0.725 0.456 0.544
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.940 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.940 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.940 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0376      0.936 0.996 0.004
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.940 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.940 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.9754      0.802 0.408 0.592
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.940 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.940 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.940 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.940 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.940 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.940 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.940 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.9732      0.803 0.404 0.596
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     1  0.9866     -0.522 0.568 0.432
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.940 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0376      0.936 0.996 0.004
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.940 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.940 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.3879      0.828 0.924 0.076
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0376      0.936 0.996 0.004
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0376      0.936 0.996 0.004
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.9754      0.802 0.408 0.592
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.940 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.940 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.9358      0.792 0.352 0.648
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.940 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.5178      0.748 0.884 0.116
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3431      0.856 0.936 0.064
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.940 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.940 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.940 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.9732      0.803 0.404 0.596
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.940 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.6531      0.647 0.168 0.832
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1184      0.925 0.984 0.016
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.9815      0.778 0.420 0.580
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.940 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0938      0.928 0.988 0.012
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.940 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000      0.940 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.940 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0376      0.936 0.996 0.004
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     1  0.9988     -0.649 0.520 0.480
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.940 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.940 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.9988     -0.515 0.520 0.480
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.940 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.940 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.9754      0.802 0.408 0.592
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.940 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1184      0.925 0.984 0.016
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.940 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.940 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.9944      0.725 0.456 0.544
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.940 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.940 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.940 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0376      0.936 0.996 0.004
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3431      0.856 0.936 0.064
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.940 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.940 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.9775      0.799 0.412 0.588
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000      0.940 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.6973      0.640 0.188 0.812
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.940 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.0938      0.927 0.988 0.012
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.940 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.940 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.940 1.000 0.000
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#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.940 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.940 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.940 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.6148      0.678 0.848 0.152
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.940 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.940 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.940 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.6148      0.678 0.848 0.152
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.940 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.940 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.940 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.9358      0.792 0.352 0.648
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.940 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.9988     -0.515 0.520 0.480
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.940 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.940 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.940 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.9933      0.763 0.452 0.548
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.1633      0.915 0.976 0.024
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.0672      0.932 0.992 0.008
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0938      0.928 0.988 0.012
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.9866     -0.522 0.568 0.432
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.940 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.9552     -0.120 0.624 0.376
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0672      0.932 0.992 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.940 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.9954      0.719 0.460 0.540
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.940 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.7056      0.640 0.192 0.808
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3114      0.868 0.944 0.056
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.940 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.940 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1414      0.916 0.980 0.020
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.940 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.940 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0938      0.929 0.988 0.012
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.940 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000      0.940 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.940 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.940 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2043      0.904 0.968 0.032
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.940 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.9732      0.803 0.404 0.596
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.9795      0.797 0.416 0.584
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.940 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.940 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.940 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0672      0.931 0.992 0.008

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.8727      0.533 0.236 0.176 0.588
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.973 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.973 1.000 0.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.973 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.973 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.973 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.1529      0.940 0.960 0.040 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3983      0.772 0.004 0.852 0.144
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0747      0.963 0.984 0.000 0.016
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1877      0.939 0.956 0.032 0.012
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.973 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2806      0.910 0.928 0.040 0.032
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.973 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     3  0.6497      0.406 0.016 0.336 0.648
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0237      0.971 0.996 0.000 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.973 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.973 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0661      0.967 0.988 0.004 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.973 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.973 1.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0661      0.861 0.004 0.988 0.008
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.973 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.973 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.973 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.973 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.973 1.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.973 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.973 1.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0892      0.856 0.000 0.980 0.020
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.7603      0.441 0.096 0.668 0.236
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.973 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0661      0.967 0.988 0.004 0.008
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0424      0.968 0.992 0.000 0.008
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.973 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.3644      0.832 0.872 0.124 0.004
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0848      0.964 0.984 0.008 0.008
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.1453      0.948 0.968 0.024 0.008
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0661      0.861 0.004 0.988 0.008
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.973 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.973 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.3983      0.772 0.004 0.852 0.144
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.973 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.5357      0.760 0.820 0.064 0.116
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3764      0.869 0.892 0.040 0.068
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.973 1.000 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.973 1.000 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.973 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0237      0.858 0.000 0.996 0.004
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.973 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     3  0.1860      0.518 0.000 0.052 0.948
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1774      0.943 0.960 0.024 0.016
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.6442      0.259 0.004 0.564 0.432
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.973 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.1031      0.957 0.976 0.000 0.024
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.973 1.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000      0.973 1.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.973 1.000 0.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0475      0.969 0.992 0.004 0.004
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.6936      0.562 0.064 0.704 0.232
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.973 1.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.973 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.8727      0.533 0.236 0.176 0.588
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.973 1.000 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.973 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0237      0.860 0.004 0.996 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.973 1.000 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1774      0.943 0.960 0.024 0.016
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.973 1.000 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.973 1.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     3  0.6497      0.406 0.016 0.336 0.648
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.973 1.000 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.973 1.000 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.973 1.000 0.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0661      0.966 0.988 0.008 0.004
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3764      0.869 0.892 0.040 0.068
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.973 1.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1170      0.957 0.976 0.016 0.008
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0661      0.860 0.008 0.988 0.004
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000      0.973 1.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     3  0.1411      0.557 0.036 0.000 0.964
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.973 1.000 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.1337      0.954 0.972 0.012 0.016
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.973 1.000 0.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.973 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.973 1.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4652      0.818 0.856 0.064 0.080
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0848      0.964 0.984 0.008 0.008
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     3  0.7801      0.465 0.076 0.308 0.616
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.3983      0.772 0.004 0.852 0.144
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.973 1.000 0.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0661      0.966 0.988 0.004 0.008
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.973 1.000 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     3  0.7067      0.327 0.028 0.376 0.596
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.973 1.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000      0.973 1.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000      0.973 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.1781      0.945 0.960 0.020 0.020
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.5621      0.479 0.308 0.000 0.692
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.2926      0.907 0.924 0.036 0.040
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.973 1.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0237      0.971 0.996 0.000 0.004
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0475      0.861 0.004 0.992 0.004
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0237      0.860 0.004 0.996 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.1491      0.950 0.968 0.016 0.016
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0237      0.970 0.996 0.004 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0661      0.861 0.004 0.988 0.008
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.4745      0.813 0.852 0.068 0.080
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000      0.973 1.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000      0.973 1.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     3  0.6960      0.586 0.152 0.116 0.732
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0892      0.856 0.000 0.980 0.020
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0237      0.971 0.996 0.000 0.004
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0000      0.973 1.000 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000      0.973 1.000 0.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000      0.973 1.000 0.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0237      0.971 0.996 0.000 0.004
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000      0.973 1.000 0.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0829      0.964 0.984 0.004 0.012
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000      0.973 1.000 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0424      0.968 0.992 0.008 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000      0.973 1.000 0.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000      0.973 1.000 0.000 0.000
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#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1711      0.942 0.960 0.032 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.973 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     3  0.6603      0.416 0.020 0.332 0.648
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0424      0.968 0.992 0.008 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.1529      0.559 0.040 0.000 0.960
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3530      0.880 0.900 0.032 0.068
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.973 1.000 0.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.973 1.000 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1765      0.938 0.956 0.004 0.040
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.973 1.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.973 1.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1491      0.951 0.968 0.016 0.016
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.973 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0237      0.971 0.996 0.000 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0237      0.971 0.996 0.000 0.004
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.973 1.000 0.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2569      0.920 0.936 0.032 0.032
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.973 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0424      0.858 0.000 0.992 0.008
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1129      0.851 0.020 0.976 0.004
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.973 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.973 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.973 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1015      0.961 0.980 0.008 0.012

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.7036     0.0896 0.208 0.000 0.216 0.576
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.2010     0.9251 0.940 0.040 0.012 0.008
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.5803     0.6891 0.004 0.716 0.172 0.108
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0804     0.9602 0.980 0.000 0.008 0.012
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1398     0.9415 0.956 0.000 0.004 0.040
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2101     0.9141 0.928 0.000 0.012 0.060
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.2101     0.2928 0.000 0.012 0.060 0.928
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0188     0.9696 0.996 0.000 0.000 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0592     0.9656 0.984 0.000 0.000 0.016
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2266     0.8148 0.000 0.912 0.084 0.004
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.3577     0.7882 0.000 0.832 0.156 0.012
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     4  0.7666     0.1682 0.076 0.368 0.052 0.504
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0524     0.9664 0.988 0.000 0.004 0.008
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0524     0.9661 0.988 0.000 0.004 0.008
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.3668     0.8134 0.852 0.116 0.028 0.004
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0779     0.9632 0.980 0.004 0.000 0.016
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.1118     0.9491 0.964 0.000 0.000 0.036
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.2401     0.8135 0.000 0.904 0.092 0.004
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.5815     0.6864 0.004 0.716 0.168 0.112
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.4483     0.7540 0.808 0.000 0.088 0.104
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.2882     0.8734 0.892 0.000 0.024 0.084
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.2928     0.8080 0.000 0.880 0.108 0.012
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     3  0.5281     0.3058 0.000 0.008 0.528 0.464
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1356     0.9449 0.960 0.000 0.008 0.032
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.7577     0.0813 0.000 0.376 0.196 0.428
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0921     0.9571 0.972 0.000 0.000 0.028
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0376     0.9679 0.992 0.000 0.004 0.004
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.7814     0.2899 0.056 0.528 0.092 0.324
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.7036     0.0896 0.208 0.000 0.216 0.576
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0524     0.8182 0.000 0.988 0.008 0.004
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1356     0.9449 0.960 0.000 0.008 0.032
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.2101     0.2928 0.000 0.012 0.060 0.928
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0469     0.9659 0.988 0.000 0.000 0.012
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.2882     0.8734 0.892 0.000 0.024 0.084
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0817     0.9583 0.976 0.000 0.000 0.024
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.2197     0.8109 0.000 0.916 0.080 0.004
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     3  0.5110     0.4064 0.012 0.000 0.636 0.352
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.1229     0.9539 0.968 0.008 0.004 0.020
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.3663     0.8204 0.848 0.016 0.008 0.128
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0657     0.9638 0.984 0.000 0.004 0.012
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.3009     0.3015 0.052 0.000 0.056 0.892
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.5761     0.6906 0.004 0.720 0.168 0.108
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0657     0.9652 0.984 0.004 0.000 0.012
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.7627     0.2101 0.012 0.264 0.192 0.532
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.1492     0.9457 0.956 0.004 0.004 0.036
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.7011     0.2147 0.300 0.000 0.552 0.148
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.2125     0.9090 0.920 0.000 0.004 0.076
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0524     0.9673 0.988 0.000 0.004 0.008
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0188     0.9696 0.996 0.000 0.000 0.004
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.2053     0.8157 0.000 0.924 0.072 0.004
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.1004     0.8179 0.000 0.972 0.024 0.004
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.1109     0.9519 0.968 0.000 0.004 0.028
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0188     0.9696 0.996 0.000 0.000 0.004
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.2401     0.8135 0.000 0.904 0.092 0.004
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.3774     0.8155 0.844 0.020 0.008 0.128
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.6882    -0.0131 0.124 0.000 0.328 0.548
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.3647     0.7886 0.000 0.832 0.152 0.016
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0336     0.9686 0.992 0.000 0.000 0.008
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0188     0.9696 0.996 0.000 0.000 0.004
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0707     0.9631 0.980 0.000 0.000 0.020
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0336     0.9678 0.992 0.000 0.000 0.008
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0657     0.9652 0.984 0.004 0.000 0.012
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0469     0.9675 0.988 0.000 0.000 0.012
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.7028     0.2185 0.260 0.000 0.568 0.172
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     4  0.6882    -0.0131 0.124 0.000 0.328 0.548
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     1  0.4987     0.6913 0.772 0.036 0.016 0.176
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.0992     0.9598 0.976 0.008 0.004 0.012
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     3  0.6990     0.2145 0.304 0.000 0.552 0.144
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000     0.9706 1.000 0.000 0.000 0.000
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#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.7721    -0.3095 0.448 0.000 0.280 0.272
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1302     0.9440 0.956 0.000 0.000 0.044
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.1978     0.2850 0.000 0.004 0.068 0.928
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0336     0.9678 0.992 0.000 0.000 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.5203     0.4076 0.016 0.000 0.636 0.348
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2845     0.8826 0.896 0.000 0.028 0.076
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1930     0.9227 0.936 0.004 0.004 0.056
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1209     0.9517 0.964 0.000 0.004 0.032
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0469     0.9673 0.988 0.000 0.000 0.012
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0336     0.9689 0.992 0.000 0.000 0.008
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1938     0.9220 0.936 0.000 0.012 0.052
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2867     0.8088 0.000 0.884 0.104 0.012
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.3852     0.7657 0.008 0.800 0.192 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0188     0.9698 0.996 0.000 0.000 0.004
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9706 1.000 0.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0817     0.9602 0.976 0.000 0.000 0.024

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2 p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.7643    0.22508 0.140 0.000 NA 0.276 0.472
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0798    0.93964 0.976 0.000 NA 0.008 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.2046    0.92373 0.916 0.000 NA 0.016 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1430    0.93152 0.944 0.000 NA 0.004 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0771    0.93930 0.976 0.000 NA 0.004 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.3439    0.87580 0.848 0.028 NA 0.020 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.5844    0.65949 0.000 0.672 NA 0.060 0.068
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.1891    0.92562 0.936 0.000 NA 0.016 0.016
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2701    0.90055 0.884 0.000 NA 0.012 0.012
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0865    0.93631 0.972 0.000 NA 0.004 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3483    0.86809 0.852 0.000 NA 0.032 0.028
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.1701    0.93233 0.936 0.000 NA 0.016 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     5  0.2077    0.27723 0.000 0.008 NA 0.084 0.908
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.1991    0.92173 0.916 0.000 NA 0.004 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.1661    0.93264 0.940 0.000 NA 0.024 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0693    0.93896 0.980 0.000 NA 0.012 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1243    0.93984 0.960 0.000 NA 0.008 0.004
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0771    0.93645 0.976 0.000 NA 0.004 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.1197    0.76554 0.000 0.952 NA 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0609    0.93797 0.980 0.000 NA 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0510    0.93896 0.984 0.000 NA 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1831    0.92245 0.920 0.000 NA 0.004 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0807    0.93861 0.976 0.000 NA 0.012 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0510    0.93720 0.984 0.000 NA 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.2423    0.91453 0.896 0.000 NA 0.024 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0771    0.93845 0.976 0.000 NA 0.004 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.3209    0.71412 0.000 0.812 NA 0.008 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     5  0.8785    0.14836 0.052 0.280 NA 0.108 0.396
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0609    0.93607 0.980 0.000 NA 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.1412    0.93245 0.952 0.000 NA 0.004 0.008
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2032    0.92761 0.924 0.000 NA 0.020 0.004
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0609    0.93844 0.980 0.000 NA 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.4716    0.75524 0.760 0.072 NA 0.020 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2642    0.91088 0.888 0.000 NA 0.024 0.004
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.1988    0.92843 0.928 0.000 NA 0.008 0.016
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.1341    0.76364 0.000 0.944 NA 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0510    0.93898 0.984 0.000 NA 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0703    0.93924 0.976 0.000 NA 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.5844    0.65737 0.000 0.672 NA 0.060 0.068
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.1403    0.93620 0.952 0.000 NA 0.024 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.4876    0.76050 0.772 0.000 NA 0.084 0.060
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4137    0.82345 0.816 0.000 NA 0.064 0.032
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0609    0.93914 0.980 0.000 NA 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.1965    0.75441 0.000 0.904 NA 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.1300    0.93847 0.956 0.000 NA 0.016 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.5661    0.38441 0.000 0.000 NA 0.608 0.272
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2644    0.90983 0.896 0.000 NA 0.020 0.016
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.8552   -0.10927 0.000 0.288 NA 0.276 0.200
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.1502    0.93080 0.940 0.000 NA 0.004 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.3169    0.89708 0.868 0.000 NA 0.024 0.024
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1270    0.93148 0.948 0.000 NA 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.2482    0.91238 0.892 0.000 NA 0.024 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0807    0.93861 0.976 0.000 NA 0.012 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1285    0.93341 0.956 0.000 NA 0.004 0.004
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.8688    0.27590 0.040 0.408 NA 0.120 0.164
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1357    0.93263 0.948 0.000 NA 0.004 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0771    0.93681 0.976 0.000 NA 0.004 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.7643    0.22508 0.140 0.000 NA 0.276 0.472
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.1026    0.93918 0.968 0.000 NA 0.004 0.004
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0880    0.93719 0.968 0.000 NA 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.1792    0.76772 0.000 0.916 NA 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.2171    0.92313 0.912 0.000 NA 0.024 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2644    0.90983 0.896 0.000 NA 0.020 0.016
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0932    0.93700 0.972 0.000 NA 0.004 0.004
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.1661    0.93264 0.940 0.000 NA 0.024 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     5  0.2077    0.27723 0.000 0.008 NA 0.084 0.908
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0609    0.93607 0.980 0.000 NA 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0609    0.93607 0.980 0.000 NA 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0932    0.93781 0.972 0.000 NA 0.004 0.004
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1952    0.91917 0.912 0.000 NA 0.000 0.004
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4137    0.82345 0.816 0.000 NA 0.064 0.032
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1560    0.93670 0.948 0.000 NA 0.004 0.020
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.3160    0.75193 0.000 0.808 NA 0.004 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.1741    0.93197 0.936 0.000 NA 0.024 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2304    0.42626 0.000 0.000 NA 0.892 0.100
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0609    0.93810 0.980 0.000 NA 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.1960    0.93242 0.936 0.004 NA 0.020 0.012
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0609    0.93607 0.980 0.000 NA 0.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0703    0.93740 0.976 0.000 NA 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0510    0.93896 0.984 0.000 NA 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4996    0.76595 0.780 0.016 NA 0.060 0.088
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.1442    0.93808 0.952 0.000 NA 0.012 0.004
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     5  0.3646    0.31421 0.040 0.000 NA 0.072 0.848
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.5814    0.66077 0.000 0.676 NA 0.060 0.068
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.1211    0.93824 0.960 0.000 NA 0.016 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.1564    0.93446 0.948 0.000 NA 0.024 0.004
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0771    0.93645 0.976 0.000 NA 0.004 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.8551    0.22415 0.004 0.200 NA 0.332 0.284
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.1012    0.93797 0.968 0.000 NA 0.012 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.1041    0.93575 0.964 0.000 NA 0.000 0.004
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3107    0.89550 0.864 0.000 NA 0.032 0.008
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.4998    0.10552 0.264 0.000 NA 0.680 0.044
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3134    0.88569 0.876 0.000 NA 0.024 0.056
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.1661    0.93264 0.940 0.000 NA 0.024 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.2054    0.92305 0.916 0.000 NA 0.008 0.004
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.1197    0.76565 0.000 0.952 NA 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.2020    0.76747 0.000 0.900 NA 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.2302    0.92267 0.916 0.000 NA 0.020 0.016
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.1124    0.93478 0.960 0.000 NA 0.000 0.004
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.1341    0.76364 0.000 0.944 NA 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.5059    0.76040 0.776 0.016 NA 0.064 0.088
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0693    0.93896 0.980 0.000 NA 0.012 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     5  0.7707   -0.02369 0.080 0.000 NA 0.372 0.376
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.2997    0.73002 0.000 0.840 NA 0.012 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0833    0.93861 0.976 0.000 NA 0.004 0.004
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0912    0.93847 0.972 0.000 NA 0.012 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.1502    0.93080 0.940 0.000 NA 0.004 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.1671    0.92261 0.924 0.000 NA 0.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0960    0.93851 0.972 0.000 NA 0.008 0.004
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.1369    0.93895 0.956 0.000 NA 0.008 0.008
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.1341    0.93018 0.944 0.000 NA 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.1732    0.92225 0.920 0.000 NA 0.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0609    0.93844 0.980 0.000 NA 0.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0880    0.93663 0.968 0.000 NA 0.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.2522    0.91560 0.896 0.000 NA 0.024 0.004
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#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0609    0.93914 0.980 0.000 NA 0.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.5903    0.65524 0.000 0.664 NA 0.060 0.068
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1671    0.92261 0.924 0.000 NA 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     5  0.7643    0.22508 0.140 0.000 NA 0.276 0.472
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0865    0.93993 0.972 0.000 NA 0.004 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0703    0.93740 0.976 0.000 NA 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.6481    0.56153 0.000 0.588 NA 0.080 0.064
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3426    0.88980 0.856 0.000 NA 0.032 0.028
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.2362    0.91872 0.900 0.000 NA 0.024 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3169    0.89708 0.868 0.000 NA 0.024 0.024
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.8882    0.15355 0.060 0.280 NA 0.108 0.388
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0932    0.93868 0.972 0.000 NA 0.004 0.004
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.8115   -0.38010 0.380 0.000 NA 0.312 0.140
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2756    0.90006 0.880 0.000 NA 0.012 0.012
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0865    0.93583 0.972 0.000 NA 0.000 0.004
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     5  0.2017    0.27518 0.000 0.000 NA 0.080 0.912
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.1732    0.92324 0.920 0.000 NA 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.2463    0.42635 0.004 0.000 NA 0.888 0.100
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4061    0.83981 0.824 0.000 NA 0.064 0.040
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0955    0.93988 0.968 0.000 NA 0.004 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.2233    0.91778 0.904 0.000 NA 0.016 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.3664    0.87431 0.848 0.000 NA 0.056 0.036
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.1671    0.92261 0.924 0.000 NA 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0963    0.93882 0.964 0.000 NA 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2720    0.90280 0.880 0.000 NA 0.020 0.004
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0807    0.93861 0.976 0.000 NA 0.012 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.1211    0.93715 0.960 0.000 NA 0.016 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2069    0.92078 0.912 0.000 NA 0.012 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.1341    0.93083 0.944 0.000 NA 0.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2990    0.89170 0.876 0.000 NA 0.032 0.012
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0703    0.93555 0.976 0.000 NA 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2011    0.75525 0.000 0.908 NA 0.004 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.4251    0.66303 0.000 0.624 NA 0.004 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0807    0.93861 0.976 0.000 NA 0.012 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1956    0.92162 0.916 0.000 NA 0.008 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0609    0.93607 0.980 0.000 NA 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1651    0.93575 0.944 0.000 NA 0.008 0.012

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.7859   -0.08247 0.056 0.000 0.084 0.176 0.360 0.324
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.1814    0.88016 0.900 0.000 0.000 0.000 0.000 0.100
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.2941    0.83850 0.780 0.000 0.000 0.000 0.000 0.220
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2378    0.86093 0.848 0.000 0.000 0.000 0.000 0.152
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1814    0.88194 0.900 0.000 0.000 0.000 0.000 0.100
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1152    0.86778 0.952 0.000 0.004 0.000 0.000 0.044
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.4403    0.76111 0.684 0.016 0.032 0.000 0.000 0.268
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.5409    0.48431 0.000 0.692 0.172 0.028 0.040 0.068
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.2196    0.84087 0.884 0.000 0.004 0.004 0.000 0.108
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3683    0.81528 0.760 0.000 0.020 0.004 0.004 0.212
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1152    0.87513 0.952 0.000 0.004 0.000 0.000 0.044
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4251    0.76094 0.708 0.000 0.040 0.004 0.004 0.244
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.2491    0.86745 0.836 0.000 0.000 0.000 0.000 0.164
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     5  0.1333    0.27142 0.000 0.008 0.000 0.048 0.944 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3081    0.82551 0.776 0.000 0.000 0.000 0.004 0.220
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.2491    0.86247 0.836 0.000 0.000 0.000 0.000 0.164
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1556    0.88039 0.920 0.000 0.000 0.000 0.000 0.080
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1956    0.88462 0.908 0.000 0.008 0.000 0.004 0.080
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1152    0.86927 0.952 0.000 0.004 0.000 0.000 0.044
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0865    0.87911 0.964 0.000 0.000 0.000 0.000 0.036
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2191    0.61782 0.000 0.876 0.120 0.004 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1556    0.88088 0.920 0.000 0.000 0.000 0.000 0.080
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1471    0.88180 0.932 0.000 0.004 0.000 0.000 0.064
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2941    0.82701 0.780 0.000 0.000 0.000 0.000 0.220
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.1957    0.87510 0.888 0.000 0.000 0.000 0.000 0.112
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0632    0.87601 0.976 0.000 0.000 0.000 0.000 0.024
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.3221    0.80868 0.736 0.000 0.000 0.000 0.000 0.264
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0937    0.87984 0.960 0.000 0.000 0.000 0.000 0.040
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.3519    0.47048 0.000 0.752 0.232 0.008 0.000 0.008
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     5  0.8654   -0.41022 0.028 0.256 0.204 0.084 0.348 0.080
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1082    0.86918 0.956 0.000 0.004 0.000 0.000 0.040
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.1699    0.86637 0.928 0.000 0.004 0.004 0.004 0.060
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2697    0.85168 0.812 0.000 0.000 0.000 0.000 0.188
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1285    0.87974 0.944 0.000 0.004 0.000 0.000 0.052
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.5682    0.62028 0.600 0.068 0.064 0.000 0.000 0.268
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3354    0.82097 0.752 0.000 0.004 0.000 0.004 0.240
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.2358    0.87866 0.876 0.000 0.016 0.000 0.000 0.108
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.2100    0.60853 0.000 0.884 0.112 0.004 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1327    0.88233 0.936 0.000 0.000 0.000 0.000 0.064
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1663    0.88464 0.912 0.000 0.000 0.000 0.000 0.088
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.5409    0.48155 0.000 0.692 0.172 0.028 0.040 0.068
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.2092    0.86871 0.876 0.000 0.000 0.000 0.000 0.124
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.5502    0.72411 0.684 0.000 0.088 0.044 0.020 0.164
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4751    0.72281 0.684 0.000 0.040 0.020 0.008 0.248
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.1082    0.86856 0.956 0.000 0.004 0.000 0.000 0.040
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0632    0.88077 0.976 0.000 0.000 0.000 0.000 0.024
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1152    0.86995 0.952 0.000 0.004 0.000 0.000 0.044
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.2553    0.58357 0.000 0.848 0.144 0.000 0.000 0.008
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.1714    0.87822 0.908 0.000 0.000 0.000 0.000 0.092
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.7015    0.22928 0.000 0.000 0.136 0.480 0.184 0.200
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2826    0.85955 0.844 0.000 0.028 0.000 0.000 0.128
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.8582    0.46599 0.000 0.252 0.300 0.212 0.140 0.096
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.2527    0.86435 0.832 0.000 0.000 0.000 0.000 0.168
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.3601    0.75958 0.684 0.000 0.000 0.000 0.004 0.312
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2340    0.86196 0.852 0.000 0.000 0.000 0.000 0.148
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.3309    0.79659 0.720 0.000 0.000 0.000 0.000 0.280
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.1863    0.87746 0.896 0.000 0.000 0.000 0.000 0.104
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1615    0.86550 0.928 0.000 0.004 0.004 0.000 0.064
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.8183   -0.57078 0.024 0.360 0.348 0.104 0.100 0.064
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2378    0.86216 0.848 0.000 0.000 0.000 0.000 0.152
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0790    0.87541 0.968 0.000 0.000 0.000 0.000 0.032
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.7859   -0.08247 0.056 0.000 0.084 0.176 0.360 0.324
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.1219    0.87521 0.948 0.000 0.004 0.000 0.000 0.048
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2003    0.87647 0.884 0.000 0.000 0.000 0.000 0.116
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0937    0.64048 0.000 0.960 0.040 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.3076    0.82577 0.760 0.000 0.000 0.000 0.000 0.240
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2826    0.85955 0.844 0.000 0.028 0.000 0.000 0.128
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.1152    0.87054 0.952 0.000 0.004 0.000 0.000 0.044
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.2491    0.86247 0.836 0.000 0.000 0.000 0.000 0.164
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     5  0.1333    0.27142 0.000 0.008 0.000 0.048 0.944 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0713    0.87295 0.972 0.000 0.000 0.000 0.000 0.028
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0935    0.86942 0.964 0.000 0.004 0.000 0.000 0.032
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.1152    0.87500 0.952 0.000 0.004 0.000 0.000 0.044
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3012    0.83898 0.796 0.000 0.008 0.000 0.000 0.196
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4751    0.72281 0.684 0.000 0.040 0.020 0.008 0.248
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.1152    0.86778 0.952 0.000 0.004 0.000 0.000 0.044
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1983    0.87979 0.916 0.000 0.012 0.000 0.012 0.060
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.3253    0.59840 0.000 0.788 0.192 0.000 0.000 0.020
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.2762    0.85172 0.804 0.000 0.000 0.000 0.000 0.196
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2144    0.33174 0.000 0.000 0.004 0.908 0.048 0.040
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0790    0.87807 0.968 0.000 0.000 0.000 0.000 0.032
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.2704    0.87286 0.876 0.004 0.008 0.004 0.016 0.092
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0713    0.87295 0.972 0.000 0.000 0.000 0.000 0.028
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.1010    0.87713 0.960 0.000 0.004 0.000 0.000 0.036
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.1411    0.88137 0.936 0.000 0.004 0.000 0.000 0.060
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5456    0.64928 0.644 0.016 0.028 0.016 0.032 0.264
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.2402    0.88091 0.868 0.000 0.012 0.000 0.000 0.120
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     5  0.3508    0.32903 0.036 0.000 0.028 0.028 0.848 0.060
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.5378    0.48618 0.000 0.696 0.168 0.028 0.040 0.068
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.1908    0.87549 0.900 0.000 0.004 0.000 0.000 0.096
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.1531    0.87748 0.928 0.000 0.000 0.000 0.004 0.068
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0937    0.87937 0.960 0.000 0.000 0.000 0.000 0.040
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.8906   -0.23377 0.000 0.180 0.204 0.264 0.184 0.168
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.1765    0.87547 0.904 0.000 0.000 0.000 0.000 0.096
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.1411    0.86661 0.936 0.000 0.004 0.000 0.000 0.060
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.1010    0.87166 0.960 0.000 0.004 0.000 0.000 0.036
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3583    0.80517 0.728 0.000 0.004 0.000 0.008 0.260
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.5558   -0.03071 0.196 0.000 0.000 0.600 0.012 0.192
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3697    0.83399 0.804 0.000 0.028 0.004 0.024 0.140
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.2491    0.86247 0.836 0.000 0.000 0.000 0.000 0.164
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.2912    0.83317 0.784 0.000 0.000 0.000 0.000 0.216
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.1958    0.61263 0.000 0.896 0.100 0.000 0.000 0.004
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#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.1610    0.88322 0.916 0.000 0.000 0.000 0.000 0.084
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.5286    0.27784 0.000 0.000 0.100 0.696 0.092 0.112
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     3  0.7300    0.41396 0.000 0.240 0.360 0.052 0.328 0.020
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1531    0.87605 0.928 0.000 0.004 0.000 0.000 0.068
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     5  0.6746    0.07817 0.000 0.008 0.108 0.196 0.544 0.144
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.7285    0.20696 0.116 0.584 0.128 0.064 0.028 0.080
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0937    0.87984 0.960 0.000 0.000 0.000 0.000 0.040
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.1444    0.88092 0.928 0.000 0.000 0.000 0.000 0.072
#> CE539000-92D7-4622-9C8D-BC6E01310681     1  0.8373   -0.24436 0.380 0.280 0.156 0.056 0.024 0.104
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.2218    0.63648 0.000 0.884 0.104 0.000 0.000 0.012
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.2883    0.84347 0.788 0.000 0.000 0.000 0.000 0.212
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1082    0.86918 0.956 0.000 0.004 0.000 0.000 0.040
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.1152    0.86778 0.952 0.000 0.004 0.000 0.000 0.044
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     5  0.6913    0.01490 0.260 0.016 0.020 0.052 0.532 0.120
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4559    0.66957 0.752 0.000 0.004 0.036 0.072 0.136
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     5  0.6746    0.07817 0.000 0.008 0.108 0.196 0.544 0.144
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0632    0.87698 0.976 0.000 0.000 0.000 0.000 0.024
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.1152    0.86778 0.952 0.000 0.004 0.000 0.000 0.044
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.2883    0.82886 0.788 0.000 0.000 0.000 0.000 0.212
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1075    0.87950 0.952 0.000 0.000 0.000 0.000 0.048
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.1806    0.87890 0.908 0.000 0.004 0.000 0.000 0.088
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.4801    0.50564 0.000 0.752 0.124 0.024 0.040 0.060
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1082    0.86906 0.956 0.000 0.004 0.000 0.000 0.040
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0865    0.88144 0.964 0.000 0.000 0.000 0.000 0.036
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.1219    0.87348 0.948 0.000 0.004 0.000 0.000 0.048
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.1141    0.88253 0.948 0.000 0.000 0.000 0.000 0.052
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.7306   -0.02609 0.412 0.016 0.048 0.104 0.040 0.380
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.1910    0.87906 0.892 0.000 0.000 0.000 0.000 0.108
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.2491    0.86382 0.836 0.000 0.000 0.000 0.000 0.164
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.3248    0.83195 0.768 0.004 0.004 0.000 0.000 0.224
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.7306   -0.02609 0.412 0.016 0.048 0.104 0.040 0.380
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.2883    0.83558 0.788 0.000 0.000 0.000 0.000 0.212
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.1957    0.87911 0.888 0.000 0.000 0.000 0.000 0.112
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0632    0.88077 0.976 0.000 0.000 0.000 0.000 0.024
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.5491    0.47845 0.000 0.684 0.176 0.028 0.040 0.072
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2941    0.82893 0.780 0.000 0.000 0.000 0.000 0.220
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     5  0.7859   -0.08247 0.056 0.000 0.084 0.176 0.360 0.324
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1152    0.87343 0.952 0.000 0.004 0.000 0.000 0.044
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.1714    0.88269 0.908 0.000 0.000 0.000 0.000 0.092
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1082    0.87769 0.956 0.000 0.004 0.000 0.000 0.040
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.5950   -0.18532 0.000 0.528 0.356 0.068 0.028 0.020
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3915    0.75547 0.680 0.000 0.000 0.008 0.008 0.304
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.3699    0.80613 0.728 0.000 0.008 0.004 0.004 0.256
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3601    0.75958 0.684 0.000 0.000 0.000 0.004 0.312
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.8761   -0.39976 0.036 0.256 0.204 0.084 0.340 0.080
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.1524    0.87930 0.932 0.000 0.008 0.000 0.000 0.060
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     6  0.8055    0.02237 0.304 0.000 0.128 0.188 0.044 0.336
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3711    0.81745 0.756 0.000 0.020 0.004 0.004 0.216
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.1152    0.86830 0.952 0.000 0.004 0.000 0.000 0.044
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     5  0.1599    0.27234 0.000 0.000 0.008 0.028 0.940 0.024
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3073    0.84006 0.788 0.000 0.008 0.000 0.000 0.204
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.2288    0.33008 0.004 0.000 0.004 0.904 0.048 0.040
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4694    0.73287 0.684 0.000 0.028 0.016 0.016 0.256
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.1327    0.88357 0.936 0.000 0.000 0.000 0.000 0.064
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.3198    0.81076 0.740 0.000 0.000 0.000 0.000 0.260
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4352    0.75136 0.684 0.000 0.004 0.012 0.024 0.276
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2883    0.82886 0.788 0.000 0.000 0.000 0.000 0.212
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1588    0.88401 0.924 0.000 0.004 0.000 0.000 0.072
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3380    0.81411 0.748 0.000 0.004 0.000 0.004 0.244
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.1957    0.87510 0.888 0.000 0.000 0.000 0.000 0.112
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.1644    0.87009 0.920 0.000 0.004 0.000 0.000 0.076
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.3023    0.82376 0.768 0.000 0.000 0.000 0.000 0.232
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.2491    0.86449 0.836 0.000 0.000 0.000 0.000 0.164
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4016    0.80978 0.752 0.000 0.036 0.016 0.000 0.196
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1152    0.86778 0.952 0.000 0.004 0.000 0.000 0.044
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2504    0.58744 0.000 0.856 0.136 0.004 0.000 0.004
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.4963    0.44548 0.000 0.568 0.368 0.008 0.000 0.056
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.1957    0.87510 0.888 0.000 0.000 0.000 0.000 0.112
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2996    0.82490 0.772 0.000 0.000 0.000 0.000 0.228
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0713    0.87453 0.972 0.000 0.000 0.000 0.000 0.028
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2982    0.86945 0.828 0.000 0.008 0.000 0.012 0.152

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-hclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "kmeans"]
# you can also extract it by
# res = res_list["CV:kmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.986           0.957       0.982         0.3812 0.612   0.612
#> 3 3 0.453           0.477       0.768         0.5390 0.845   0.749
#> 4 4 0.508           0.547       0.731         0.1683 0.795   0.595
#> 5 5 0.607           0.667       0.801         0.1022 0.821   0.519
#> 6 6 0.617           0.513       0.720         0.0569 0.894   0.603

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.8443    0.66185 0.272 0.728
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000    0.99250 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000    0.99250 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.99250 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.99250 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000    0.99250 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.0000    0.99250 1.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.95145 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000    0.99250 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000    0.99250 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.99250 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000    0.99250 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000    0.99250 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.95145 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000    0.99250 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000    0.99250 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000    0.99250 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000    0.99250 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000    0.99250 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000    0.99250 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.95145 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.99250 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000    0.99250 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.99250 1.000 0.000
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#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000    0.99250 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000    0.99250 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000    0.99250 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000    0.99250 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000    0.99250 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.0000    0.99250 1.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000    0.99250 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000    0.95145 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.7056    0.77800 0.192 0.808
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0000    0.99250 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000    0.99250 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000    0.99250 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000    0.99250 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000    0.99250 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000    0.95145 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.0000    0.99250 1.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.0000    0.99250 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.99250 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000    0.99250 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000    0.95145 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0000    0.99250 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.95145 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.95145 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.95145 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000    0.99250 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.0000    0.99250 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000    0.99250 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.99250 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000    0.99250 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000    0.99250 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0000    0.99250 1.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000    0.99250 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000    0.99250 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.95145 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000    0.99250 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000    0.99250 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000    0.99250 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.95145 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.95145 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000    0.99250 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.95145 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.95145 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000    0.99250 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000    0.99250 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.95145 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.95145 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.0000    0.99250 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000    0.99250 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000    0.99250 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.95145 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000    0.99250 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.95145 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.99250 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000    0.99250 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000    0.99250 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000    0.99250 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000    0.99250 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.95145 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000    0.99250 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000    0.99250 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000    0.99250 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000    0.99250 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.9993   -0.00224 0.516 0.484
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.99250 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000    0.99250 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000    0.99250 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.9954    0.19468 0.460 0.540
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000    0.99250 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000    0.99250 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000    0.99250 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.95145 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000    0.99250 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.7602    0.74240 0.220 0.780
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000    0.99250 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000    0.99250 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.99250 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.95145 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000    0.99250 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.0000    0.99250 1.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000    0.99250 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.6148    0.82113 0.152 0.848
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000    0.99250 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0672    0.98435 0.992 0.008
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.99250 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.99250 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.95145 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.99250 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.7219    0.76850 0.200 0.800
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000    0.99250 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000    0.99250 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000    0.99250 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.7139    0.77344 0.196 0.804
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.99250 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000    0.99250 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000    0.99250 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000    0.99250 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000    0.99250 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000    0.99250 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000    0.99250 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.99250 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000    0.99250 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.95145 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.95145 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000    0.99250 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000    0.99250 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000    0.99250 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000    0.99250 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.6234    0.38170 0.096 0.128 0.776
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.5988    0.35802 0.632 0.000 0.368
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.6079    0.34091 0.612 0.000 0.388
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5178    0.37276 0.744 0.000 0.256
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.61840 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0424    0.61589 0.992 0.000 0.008
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5988    0.17247 0.368 0.000 0.632
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.88998 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.1643    0.60372 0.956 0.000 0.044
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.6062    0.16279 0.616 0.000 0.384
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1411    0.59980 0.964 0.000 0.036
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6244    0.00773 0.560 0.000 0.440
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.6140    0.32198 0.596 0.000 0.404
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.5178    0.83653 0.000 0.744 0.256
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.6244    0.08566 0.440 0.000 0.560
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.6026    0.34988 0.624 0.000 0.376
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5926    0.37274 0.644 0.000 0.356
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.5988    0.19520 0.632 0.000 0.368
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0237    0.61730 0.996 0.000 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.5882    0.38050 0.652 0.000 0.348
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.88998 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0237    0.61818 0.996 0.000 0.004
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.5178    0.37276 0.744 0.000 0.256
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.5968    0.20116 0.636 0.000 0.364
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.5988    0.35802 0.632 0.000 0.368
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.1529    0.60787 0.960 0.000 0.040
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.5988    0.17247 0.368 0.000 0.632
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5882    0.38151 0.652 0.000 0.348
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.88998 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.3116    0.88156 0.000 0.892 0.108
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0424    0.61589 0.992 0.000 0.008
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3267    0.52336 0.884 0.000 0.116
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.5254    0.36141 0.736 0.000 0.264
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000    0.61840 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.1163    0.88144 0.000 0.972 0.028
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6260    0.07777 0.448 0.000 0.552
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.3551    0.55047 0.868 0.000 0.132
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.88998 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0424    0.61805 0.992 0.000 0.008
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0424    0.61758 0.992 0.000 0.008
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.2711    0.87766 0.000 0.912 0.088
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.6026    0.34988 0.624 0.000 0.376
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2537    0.42653 0.080 0.000 0.920
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.6309   -0.15154 0.500 0.000 0.500
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4605    0.49336 0.796 0.000 0.204
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4654    0.50116 0.792 0.000 0.208
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0747    0.61214 0.984 0.000 0.016
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.88998 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.5988    0.35802 0.632 0.000 0.368
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.5178    0.83653 0.000 0.744 0.256
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.6026    0.17688 0.624 0.000 0.376
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.5138    0.83864 0.000 0.748 0.252
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.6252    0.25762 0.556 0.000 0.444
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.6309    0.03892 0.496 0.000 0.504
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.5363    0.35058 0.724 0.000 0.276
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.5926    0.19124 0.356 0.000 0.644
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.6140    0.32198 0.596 0.000 0.404
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.6274   -0.08805 0.544 0.000 0.456
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3482    0.87767 0.000 0.872 0.128
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.5178    0.37276 0.744 0.000 0.256
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0237    0.61827 0.996 0.000 0.004
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#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.88998 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.2448    0.88587 0.000 0.924 0.076
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5926    0.37274 0.644 0.000 0.356
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.6045    0.34640 0.620 0.000 0.380
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1031    0.60715 0.976 0.000 0.024
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.61840 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000    0.61840 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.6299    0.20460 0.524 0.000 0.476
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.5988    0.17247 0.368 0.000 0.632
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0237    0.61725 0.996 0.000 0.004
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000    0.61840 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.88998 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5397    0.35525 0.720 0.000 0.280
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.6305    0.18790 0.516 0.000 0.484
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.4062    0.53623 0.836 0.000 0.164
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.5216    0.83392 0.000 0.740 0.260
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.3038    0.88226 0.000 0.896 0.104
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000    0.61840 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4346    0.86432 0.000 0.816 0.184
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.2356    0.88623 0.000 0.928 0.072
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.5905    0.37759 0.648 0.000 0.352
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4750    0.50098 0.784 0.000 0.216
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3551    0.87729 0.000 0.868 0.132
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.88998 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.6026    0.34988 0.624 0.000 0.376
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000    0.61840 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.4504    0.50066 0.804 0.000 0.196
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.5178    0.83653 0.000 0.744 0.256
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.3816    0.54850 0.852 0.000 0.148
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4346    0.86432 0.000 0.816 0.184
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.61840 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000    0.61840 1.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.5882    0.26996 0.652 0.000 0.348
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.5882    0.38151 0.652 0.000 0.348
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.6280    0.03923 0.540 0.000 0.460
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.88998 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.4555    0.49710 0.800 0.000 0.200
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000    0.61840 1.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.2878    0.57583 0.904 0.000 0.096
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5905    0.37759 0.648 0.000 0.352
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.8199    0.36342 0.200 0.160 0.640
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.61840 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5926    0.34798 0.644 0.000 0.356
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5621    0.42554 0.692 0.000 0.308
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     3  0.8231    0.37045 0.208 0.156 0.636
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.6204    0.17196 0.576 0.000 0.424
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5835    0.39252 0.660 0.000 0.340
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2261    0.60084 0.932 0.000 0.068
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.88998 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.5948    0.21319 0.640 0.000 0.360
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     3  0.6858    0.27975 0.084 0.188 0.728
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000    0.61840 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4178    0.54149 0.828 0.000 0.172
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.61840 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.88998 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.5785    0.37023 0.332 0.000 0.668
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.5988    0.17247 0.368 0.000 0.632
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.5810    0.36637 0.336 0.000 0.664
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5760    0.81741 0.064 0.796 0.140
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5760    0.40081 0.672 0.000 0.328
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4750    0.42113 0.216 0.000 0.784
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.5859    0.23431 0.656 0.000 0.344
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.61840 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.5178    0.83653 0.000 0.744 0.256
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.5397    0.33950 0.720 0.000 0.280
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.5529   -0.03565 0.000 0.296 0.704
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6111    0.14925 0.604 0.000 0.396
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.5560    0.42414 0.700 0.000 0.300
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4178    0.39115 0.172 0.000 0.828
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.5506    0.18493 0.016 0.220 0.764
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.6095    0.16436 0.608 0.000 0.392
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000    0.61840 1.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.6267    0.05056 0.548 0.000 0.452
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.6309   -0.16345 0.496 0.000 0.504
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5926    0.37083 0.644 0.000 0.356
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6305   -0.02076 0.516 0.000 0.484
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5431    0.45850 0.716 0.000 0.284
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.6026    0.17688 0.624 0.000 0.376
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000    0.61840 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.88998 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.88998 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.6204    0.03483 0.424 0.000 0.576
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5859    0.27254 0.656 0.000 0.344
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000    0.61840 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.5948    0.20981 0.640 0.000 0.360

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1406     0.6172 0.016 0.000 0.024 0.960
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4406     0.6598 0.300 0.000 0.700 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.3837     0.6729 0.224 0.000 0.776 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.6444     0.5242 0.612 0.000 0.284 0.104
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1109     0.6600 0.968 0.000 0.028 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1109     0.6505 0.968 0.000 0.004 0.028
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.1661     0.6004 0.052 0.000 0.944 0.004
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.2197     0.6327 0.916 0.000 0.004 0.080
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.7661     0.4105 0.464 0.000 0.264 0.272
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1151     0.6625 0.968 0.000 0.024 0.008
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.7726     0.4023 0.444 0.000 0.260 0.296
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3975     0.6731 0.240 0.000 0.760 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.5233     0.5474 0.000 0.332 0.020 0.648
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5620     0.3513 0.208 0.000 0.708 0.084
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4454     0.6563 0.308 0.000 0.692 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.4699     0.6489 0.320 0.000 0.676 0.004
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.6814     0.5109 0.584 0.000 0.276 0.140
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0921     0.6527 0.972 0.000 0.000 0.028
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4907     0.5599 0.420 0.000 0.580 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0336     0.6563 0.992 0.000 0.008 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.6708     0.5226 0.592 0.000 0.280 0.128
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.6836     0.5074 0.580 0.000 0.280 0.140
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.4454     0.6563 0.308 0.000 0.692 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0524     0.6553 0.988 0.000 0.008 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1890     0.6023 0.056 0.000 0.936 0.008
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5292    -0.4177 0.512 0.000 0.480 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.4797     0.5618 0.000 0.720 0.020 0.260
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1151     0.6623 0.968 0.000 0.024 0.008
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3763     0.6029 0.832 0.000 0.024 0.144
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.6522     0.5245 0.608 0.000 0.280 0.112
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1256     0.6490 0.964 0.000 0.008 0.028
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.1677     0.8447 0.000 0.948 0.040 0.012
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.5279     0.4099 0.232 0.000 0.716 0.052
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.3542     0.5246 0.852 0.000 0.120 0.028
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3105     0.6284 0.856 0.000 0.140 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1520     0.6547 0.956 0.000 0.024 0.020
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.4621     0.4497 0.000 0.708 0.008 0.284
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.4406     0.6598 0.300 0.000 0.700 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.5184     0.3340 0.024 0.000 0.672 0.304
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.7714     0.3892 0.448 0.000 0.260 0.292
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.5157     0.1366 0.688 0.000 0.284 0.028
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.3751     0.4128 0.800 0.000 0.196 0.004
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1284     0.6619 0.964 0.000 0.024 0.012
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.4431     0.6583 0.304 0.000 0.696 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.4761     0.5542 0.000 0.332 0.004 0.664
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.7497     0.4406 0.500 0.000 0.260 0.240
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.4897     0.5532 0.000 0.332 0.008 0.660
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.2675     0.6373 0.100 0.000 0.892 0.008
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.7554    -0.2338 0.376 0.000 0.432 0.192
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.6558     0.5121 0.596 0.000 0.296 0.108
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1890     0.6023 0.056 0.000 0.936 0.008
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3975     0.6731 0.240 0.000 0.760 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5992     0.3823 0.516 0.000 0.040 0.444
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.4936     0.5259 0.000 0.700 0.020 0.280
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.6444     0.5242 0.612 0.000 0.284 0.104
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0524     0.6566 0.988 0.000 0.008 0.004
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.1471     0.6235 0.004 0.012 0.024 0.960
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.6025     0.4612 0.668 0.000 0.096 0.236
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.6473     0.5247 0.612 0.000 0.280 0.108
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2345     0.6397 0.100 0.000 0.900 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.7402     0.4635 0.516 0.000 0.264 0.220
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.5781     0.4385 0.484 0.000 0.488 0.028
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.3975     0.6731 0.240 0.000 0.760 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.5233     0.5474 0.000 0.332 0.020 0.648
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0336     0.6563 0.992 0.000 0.008 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.3913     0.4719 0.824 0.000 0.148 0.028
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.5097     0.5483 0.428 0.000 0.568 0.004
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#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.3443     0.7505 0.000 0.848 0.016 0.136
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.4776     0.6071 0.376 0.000 0.624 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.4103     0.6702 0.256 0.000 0.744 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1297     0.6623 0.964 0.000 0.016 0.020
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.1109     0.6505 0.968 0.000 0.004 0.028
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0336     0.6563 0.992 0.000 0.008 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.3649     0.6695 0.204 0.000 0.796 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.1890     0.6023 0.056 0.000 0.936 0.008
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0707     0.6571 0.980 0.000 0.000 0.020
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0592     0.6559 0.984 0.000 0.000 0.016
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.6587     0.5144 0.596 0.000 0.292 0.112
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.2345     0.6397 0.100 0.000 0.900 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.4008     0.4003 0.756 0.000 0.244 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.4053     0.6193 0.000 0.228 0.004 0.768
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.5173     0.4359 0.000 0.660 0.020 0.320
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1733     0.6591 0.948 0.000 0.024 0.028
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.5364     0.4357 0.000 0.392 0.016 0.592
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.4004     0.7135 0.000 0.812 0.024 0.164
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.4543     0.6505 0.324 0.000 0.676 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4431     0.2134 0.696 0.000 0.304 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.5010     0.5298 0.000 0.700 0.024 0.276
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.4406     0.6598 0.300 0.000 0.700 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1109     0.6505 0.968 0.000 0.004 0.028
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.4775     0.2868 0.740 0.000 0.232 0.028
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     4  0.5306     0.5245 0.000 0.348 0.020 0.632
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.3286     0.6030 0.876 0.000 0.044 0.080
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.5352     0.4442 0.000 0.388 0.016 0.596
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0524     0.6553 0.988 0.000 0.008 0.004
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.1109     0.6505 0.968 0.000 0.004 0.028
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6991     0.4486 0.524 0.000 0.348 0.128
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.4961     0.5272 0.448 0.000 0.552 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.5624     0.5756 0.724 0.000 0.128 0.148
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.5050     0.1894 0.704 0.000 0.268 0.028
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0707     0.6576 0.980 0.000 0.020 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.2670     0.5974 0.904 0.000 0.072 0.024
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.4624     0.6389 0.340 0.000 0.660 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     4  0.7615     0.2867 0.120 0.040 0.268 0.572
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.1256     0.6628 0.964 0.000 0.028 0.008
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6549     0.2599 0.488 0.000 0.436 0.076
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.5339     0.5326 0.356 0.000 0.624 0.020
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     4  0.5088     0.5210 0.080 0.020 0.108 0.792
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     3  0.6785    -0.0807 0.420 0.000 0.484 0.096
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.5090     0.3779 0.324 0.000 0.660 0.016
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2149     0.6158 0.912 0.000 0.088 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.7031     0.4825 0.552 0.000 0.296 0.152
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.1739     0.6211 0.016 0.008 0.024 0.952
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.6586 1.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5193     0.4198 0.656 0.000 0.324 0.020
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0921     0.6527 0.972 0.000 0.000 0.028
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.7546     0.0573 0.188 0.000 0.412 0.400
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.1743     0.6038 0.056 0.000 0.940 0.004
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.7720    -0.0175 0.228 0.000 0.412 0.360
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.7880     0.2025 0.192 0.528 0.024 0.256
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5383    -0.3521 0.536 0.000 0.452 0.012
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.4832     0.4946 0.176 0.000 0.056 0.768
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.6708     0.5179 0.592 0.000 0.280 0.128
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.1109     0.6505 0.968 0.000 0.004 0.028
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.5108     0.5733 0.000 0.308 0.020 0.672
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.6570     0.5203 0.604 0.000 0.280 0.116
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.2297     0.6333 0.004 0.044 0.024 0.928
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.7714     0.3966 0.448 0.000 0.260 0.292
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.5097    -0.2477 0.568 0.000 0.428 0.004
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4669     0.4435 0.036 0.000 0.764 0.200
#> C98275CD-C39A-4E14-A731-4F3EB7396665     4  0.5344     0.3816 0.032 0.000 0.300 0.668
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.7329     0.4602 0.516 0.000 0.296 0.188
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0188     0.6580 0.996 0.000 0.004 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.7761     0.3870 0.436 0.000 0.280 0.284
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3801     0.6719 0.220 0.000 0.780 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4898     0.5636 0.416 0.000 0.584 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.7446    -0.2552 0.396 0.000 0.432 0.172
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6000     0.2218 0.508 0.000 0.452 0.040
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.7494     0.4426 0.500 0.000 0.264 0.236
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1256     0.6490 0.964 0.000 0.008 0.028
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8782 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0336     0.8772 0.000 0.992 0.008 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2345     0.6397 0.100 0.000 0.900 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.6993     0.4612 0.532 0.000 0.336 0.132
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1042     0.6626 0.972 0.000 0.020 0.008
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.6083     0.5642 0.672 0.000 0.216 0.112

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.3656    0.77132 0.168 0.000 0.032 0.800 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.1608    0.85697 0.000 0.000 0.928 0.000 0.072
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2067    0.84918 0.032 0.000 0.920 0.000 0.048
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4475    0.65741 0.692 0.000 0.032 0.000 0.276
#> 78F79407-D49F-4FA2-B09F-0665C502827C     5  0.4452    0.60877 0.272 0.000 0.032 0.000 0.696
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1282    0.73459 0.044 0.000 0.000 0.004 0.952
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2172    0.81233 0.076 0.000 0.908 0.000 0.016
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.3963    0.67220 0.256 0.000 0.004 0.008 0.732
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2818    0.72488 0.860 0.000 0.004 0.008 0.128
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.3734    0.66714 0.240 0.000 0.004 0.004 0.752
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4265    0.64222 0.712 0.000 0.012 0.008 0.268
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1331    0.85767 0.008 0.000 0.952 0.000 0.040
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.1808    0.86388 0.040 0.020 0.004 0.936 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.4980    0.61431 0.676 0.000 0.252 0.000 0.072
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3093    0.73197 0.824 0.000 0.008 0.000 0.168
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0290    0.72684 0.008 0.000 0.000 0.000 0.992
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4610    0.39463 0.016 0.000 0.596 0.000 0.388
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0162    0.88005 0.000 0.996 0.004 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     5  0.3305    0.70403 0.224 0.000 0.000 0.000 0.776
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.5003    0.57726 0.544 0.000 0.032 0.000 0.424
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3085    0.73500 0.852 0.000 0.032 0.000 0.116
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.2891    0.73465 0.176 0.000 0.000 0.000 0.824
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2110    0.81349 0.072 0.000 0.912 0.000 0.016
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     5  0.5215    0.28804 0.052 0.000 0.372 0.000 0.576
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0290    0.87902 0.000 0.992 0.008 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.5242    0.36763 0.036 0.576 0.008 0.380 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.2970    0.74075 0.168 0.000 0.000 0.004 0.828
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.4317    0.59395 0.320 0.000 0.004 0.008 0.668
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4623    0.66931 0.664 0.000 0.032 0.000 0.304
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.0290    0.72759 0.008 0.000 0.000 0.000 0.992
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0960    0.86855 0.016 0.972 0.004 0.008 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.5404    0.58757 0.636 0.000 0.264 0.000 0.100
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.3999    0.70992 0.240 0.000 0.020 0.000 0.740
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0290    0.88005 0.000 0.992 0.008 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     5  0.5024    0.10992 0.440 0.000 0.032 0.000 0.528
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.2722    0.68709 0.108 0.000 0.020 0.000 0.872
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.4517    0.15568 0.000 0.556 0.008 0.436 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1954    0.80378 0.032 0.000 0.932 0.028 0.008
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3622    0.71255 0.804 0.000 0.016 0.008 0.172
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.3242    0.54058 0.000 0.000 0.216 0.000 0.784
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.4352    0.69435 0.244 0.000 0.036 0.000 0.720
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.3086    0.73223 0.180 0.000 0.000 0.004 0.816
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0290    0.88005 0.000 0.992 0.008 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.1471    0.87027 0.024 0.020 0.004 0.952 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3124    0.72428 0.840 0.000 0.008 0.008 0.144
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.0932    0.87073 0.004 0.020 0.004 0.972 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1399    0.84961 0.020 0.000 0.952 0.000 0.028
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2922    0.73015 0.872 0.000 0.056 0.000 0.072
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.4276    0.69056 0.724 0.000 0.032 0.000 0.244
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2110    0.81349 0.072 0.000 0.912 0.000 0.016
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1408    0.85878 0.008 0.000 0.948 0.000 0.044
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.5280    0.45422 0.372 0.000 0.024 0.020 0.584
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.5311    0.28882 0.036 0.544 0.008 0.412 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.4747    0.63445 0.636 0.000 0.032 0.000 0.332
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.3336    0.71606 0.228 0.000 0.000 0.000 0.772
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.3035    0.81321 0.112 0.000 0.032 0.856 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.4589    0.57650 0.292 0.000 0.020 0.008 0.680
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3805    0.72664 0.784 0.000 0.032 0.000 0.184
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#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.4758    0.62964 0.772 0.000 0.048 0.124 0.056
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.5188    0.25045 0.044 0.000 0.540 0.000 0.416
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0162    0.88005 0.000 0.996 0.004 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.2325    0.85177 0.068 0.000 0.028 0.904 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.3051    0.73003 0.864 0.000 0.060 0.000 0.076
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.3863    0.72673 0.796 0.000 0.052 0.000 0.152
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     5  0.3656    0.72598 0.196 0.000 0.020 0.000 0.784
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.3160    0.73412 0.188 0.000 0.000 0.004 0.808
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     5  0.3048    0.73540 0.176 0.000 0.000 0.004 0.820
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.4025    0.55734 0.008 0.700 0.292 0.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.3110    0.72335 0.860 0.000 0.080 0.000 0.060
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.1310    0.84936 0.020 0.000 0.956 0.000 0.024
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     5  0.0794    0.72994 0.028 0.000 0.000 0.000 0.972
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.4353    0.58388 0.328 0.000 0.004 0.008 0.660
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.1836    0.86443 0.040 0.016 0.008 0.936 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0324    0.87924 0.004 0.992 0.004 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0162    0.88005 0.000 0.996 0.004 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.4758    0.59777 0.032 0.696 0.012 0.260 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.3171    0.77704 0.008 0.000 0.816 0.000 0.176
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.1522    0.85822 0.012 0.000 0.944 0.000 0.044
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.4122    0.64215 0.304 0.000 0.004 0.004 0.688
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.0324    0.72917 0.004 0.000 0.000 0.004 0.992
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.2929    0.72809 0.180 0.000 0.000 0.000 0.820
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1444    0.85751 0.012 0.000 0.948 0.000 0.040
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.2110    0.81349 0.072 0.000 0.912 0.000 0.016
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.3550    0.71372 0.236 0.000 0.000 0.004 0.760
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.1043    0.74063 0.040 0.000 0.000 0.000 0.960
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4779    0.63999 0.628 0.000 0.032 0.000 0.340
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1310    0.84936 0.020 0.000 0.956 0.000 0.024
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.6155    0.47421 0.252 0.000 0.192 0.000 0.556
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1772    0.86668 0.032 0.008 0.020 0.940 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     4  0.5366    0.06159 0.032 0.428 0.012 0.528 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.0703    0.72984 0.024 0.000 0.000 0.000 0.976
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.2960    0.81759 0.036 0.080 0.008 0.876 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.4749    0.60110 0.040 0.700 0.008 0.252 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.4064    0.74113 0.116 0.000 0.792 0.000 0.092
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     5  0.6261    0.46555 0.264 0.000 0.200 0.000 0.536
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.5306    0.31445 0.044 0.552 0.004 0.400 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.1671    0.85617 0.000 0.000 0.924 0.000 0.076
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.0324    0.72781 0.004 0.000 0.000 0.004 0.992
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.2011    0.68359 0.004 0.000 0.088 0.000 0.908
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     4  0.2075    0.85867 0.040 0.032 0.004 0.924 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.4017    0.67876 0.248 0.000 0.012 0.004 0.736
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.2960    0.81759 0.036 0.080 0.008 0.876 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.2773    0.73874 0.164 0.000 0.000 0.000 0.836
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0162    0.72697 0.004 0.000 0.000 0.000 0.996
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.3991    0.71458 0.780 0.000 0.048 0.000 0.172
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.5289    0.12223 0.048 0.000 0.500 0.000 0.452
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4649    0.02555 0.580 0.000 0.016 0.000 0.404
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.3812    0.56300 0.024 0.000 0.204 0.000 0.772
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.4040    0.66254 0.260 0.000 0.016 0.000 0.724
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3278    0.73561 0.156 0.000 0.020 0.000 0.824
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.3307    0.80124 0.052 0.000 0.844 0.000 0.104
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4801    0.53679 0.744 0.004 0.012 0.180 0.060
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     5  0.3480    0.69919 0.248 0.000 0.000 0.000 0.752
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.5884   -0.37111 0.420 0.000 0.100 0.000 0.480
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3720    0.72073 0.012 0.000 0.760 0.000 0.228
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5554    0.31961 0.644 0.004 0.020 0.280 0.052
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5329    0.60364 0.656 0.000 0.108 0.000 0.236
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.6307    0.47645 0.532 0.000 0.244 0.000 0.224
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     5  0.4758    0.62340 0.276 0.000 0.048 0.000 0.676
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.4248    0.72004 0.728 0.000 0.032 0.000 0.240
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.3616    0.77484 0.164 0.000 0.032 0.804 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.3003    0.72465 0.188 0.000 0.000 0.000 0.812
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     5  0.6387   -0.00842 0.272 0.000 0.216 0.000 0.512
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.0404    0.72738 0.012 0.000 0.000 0.000 0.988
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0290    0.87902 0.000 0.992 0.008 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3115    0.69874 0.876 0.000 0.048 0.020 0.056
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.1626    0.83375 0.044 0.000 0.940 0.000 0.016
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.2844    0.71224 0.888 0.000 0.032 0.016 0.064
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.8476    0.08751 0.168 0.172 0.008 0.276 0.376
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.5870    0.48532 0.136 0.000 0.284 0.000 0.580
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.6743    0.53118 0.184 0.000 0.036 0.564 0.216
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4182    0.65587 0.644 0.000 0.004 0.000 0.352
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0000    0.72764 0.000 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.1648    0.86517 0.040 0.020 0.000 0.940 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.4276    0.71227 0.724 0.000 0.032 0.000 0.244
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.2511    0.84567 0.080 0.000 0.028 0.892 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2533    0.71290 0.888 0.000 0.008 0.008 0.096
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.6529    0.42383 0.228 0.000 0.296 0.000 0.476
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4804    0.13872 0.524 0.000 0.460 0.008 0.008
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4288    0.26523 0.664 0.000 0.012 0.324 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2824    0.73519 0.872 0.000 0.032 0.000 0.096
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.3109    0.72769 0.200 0.000 0.000 0.000 0.800
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1831    0.72387 0.920 0.000 0.004 0.000 0.076
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1408    0.85878 0.008 0.000 0.948 0.000 0.044
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4138    0.42794 0.000 0.000 0.616 0.000 0.384
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.3090    0.73274 0.860 0.000 0.052 0.000 0.088
#> 835AAE7F-F873-4D11-8845-232D261A38DF     5  0.6240   -0.26760 0.360 0.000 0.152 0.000 0.488
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3450    0.71666 0.808 0.000 0.008 0.008 0.176
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.0794    0.72770 0.028 0.000 0.000 0.000 0.972
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0162    0.88005 0.000 0.996 0.004 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0162    0.87995 0.000 0.996 0.004 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1310    0.84936 0.020 0.000 0.956 0.000 0.024
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3882    0.71920 0.788 0.000 0.044 0.000 0.168
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.3336    0.71408 0.228 0.000 0.000 0.000 0.772
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3756    0.60511 0.744 0.000 0.008 0.000 0.248

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     6  0.4603   -0.14240 0.040 0.000 0.000 0.416 0.000 0.544
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.1562    0.84719 0.004 0.000 0.940 0.000 0.024 0.032
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4386    0.65704 0.228 0.000 0.712 0.000 0.020 0.040
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2320    0.60366 0.864 0.000 0.000 0.000 0.132 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4099    0.19720 0.612 0.000 0.000 0.000 0.372 0.016
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.2070    0.64777 0.008 0.000 0.000 0.000 0.892 0.100
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2527    0.79173 0.084 0.000 0.876 0.000 0.000 0.040
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0405    0.87534 0.008 0.988 0.004 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4819    0.54503 0.116 0.000 0.000 0.000 0.656 0.228
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4432   -0.08817 0.600 0.000 0.000 0.000 0.036 0.364
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.4877    0.56302 0.192 0.000 0.000 0.000 0.660 0.148
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     6  0.5873    0.43215 0.352 0.000 0.000 0.000 0.204 0.444
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1605    0.84996 0.016 0.000 0.940 0.000 0.012 0.032
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.0547    0.75458 0.000 0.000 0.000 0.980 0.000 0.020
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3893    0.51804 0.796 0.000 0.120 0.000 0.028 0.056
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0777    0.84769 0.004 0.000 0.972 0.000 0.024 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1723    0.84223 0.000 0.000 0.928 0.000 0.036 0.036
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4482    0.01823 0.628 0.000 0.000 0.000 0.048 0.324
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1398    0.65188 0.008 0.000 0.000 0.000 0.940 0.052
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5156    0.19136 0.020 0.000 0.540 0.000 0.392 0.048
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.1410    0.87516 0.008 0.944 0.004 0.000 0.000 0.044
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4263   -0.15233 0.504 0.000 0.000 0.000 0.480 0.016
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3998    0.48602 0.644 0.000 0.000 0.000 0.340 0.016
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3027    0.42300 0.824 0.000 0.000 0.000 0.028 0.148
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1562    0.84719 0.004 0.000 0.940 0.000 0.024 0.032
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.4049    0.52077 0.332 0.000 0.000 0.000 0.648 0.020
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2457    0.79330 0.084 0.000 0.880 0.000 0.000 0.036
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     5  0.5886    0.46757 0.096 0.000 0.280 0.000 0.572 0.052
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1410    0.87516 0.008 0.944 0.004 0.000 0.000 0.044
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     4  0.5091    0.00502 0.004 0.424 0.004 0.512 0.000 0.056
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4454    0.60995 0.224 0.000 0.000 0.000 0.692 0.084
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.5529    0.34496 0.148 0.000 0.000 0.004 0.556 0.292
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3319    0.59838 0.800 0.000 0.000 0.000 0.164 0.036
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.1616    0.65121 0.048 0.000 0.000 0.000 0.932 0.020
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.2827    0.82436 0.012 0.884 0.044 0.020 0.000 0.040
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3968    0.53697 0.788 0.000 0.132 0.000 0.048 0.032
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4993    0.55556 0.304 0.000 0.004 0.000 0.608 0.084
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.1410    0.87516 0.008 0.944 0.004 0.000 0.000 0.044
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3871    0.34966 0.676 0.000 0.000 0.000 0.308 0.016
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.4261    0.13771 0.408 0.000 0.000 0.000 0.572 0.020
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#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.4468    0.58941 0.056 0.000 0.144 0.000 0.752 0.048
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4205    0.04040 0.564 0.000 0.000 0.000 0.420 0.016
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3785    0.65566 0.152 0.000 0.004 0.000 0.780 0.064
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.6376    0.13590 0.384 0.000 0.436 0.000 0.132 0.048
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     6  0.6048    0.51107 0.348 0.000 0.000 0.132 0.028 0.492
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     5  0.4649    0.47256 0.380 0.000 0.000 0.000 0.572 0.048
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4841    0.27742 0.504 0.000 0.012 0.000 0.452 0.032
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3928    0.68760 0.020 0.000 0.760 0.000 0.192 0.028
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     6  0.5448    0.58886 0.280 0.000 0.000 0.120 0.012 0.588
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4868    0.53370 0.712 0.000 0.028 0.000 0.124 0.136
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#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4292    0.14199 0.588 0.000 0.000 0.000 0.388 0.024
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0405    0.87534 0.008 0.988 0.004 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3423    0.51587 0.812 0.000 0.000 0.000 0.088 0.100
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     6  0.4603   -0.14240 0.040 0.000 0.000 0.416 0.000 0.544
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.3464    0.55759 0.312 0.000 0.000 0.000 0.688 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5701    0.19202 0.492 0.000 0.076 0.000 0.400 0.032
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.1462    0.65043 0.056 0.000 0.000 0.000 0.936 0.008
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.1788    0.87001 0.012 0.928 0.004 0.004 0.000 0.052
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     6  0.4530    0.47259 0.420 0.000 0.012 0.000 0.016 0.552
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2221    0.80681 0.072 0.000 0.896 0.000 0.000 0.032
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4323   -0.36213 0.508 0.000 0.008 0.000 0.008 0.476
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.7824    0.03016 0.100 0.048 0.004 0.388 0.324 0.136
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.5977    0.51609 0.100 0.000 0.256 0.000 0.580 0.064
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     6  0.6687    0.28579 0.056 0.000 0.004 0.256 0.192 0.492
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.5421    0.36371 0.580 0.000 0.000 0.000 0.204 0.216
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1049    0.65677 0.032 0.000 0.000 0.000 0.960 0.008
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.0937    0.75561 0.000 0.000 0.000 0.960 0.000 0.040
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3655    0.55152 0.792 0.000 0.000 0.000 0.112 0.096
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.4167    0.57287 0.000 0.000 0.020 0.612 0.000 0.368
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4336   -0.36021 0.504 0.000 0.000 0.000 0.020 0.476
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.6219    0.07511 0.512 0.000 0.136 0.000 0.308 0.044
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5819    0.06826 0.368 0.000 0.444 0.000 0.000 0.188
#> C98275CD-C39A-4E14-A731-4F3EB7396665     4  0.5982   -0.31882 0.228 0.000 0.000 0.392 0.000 0.380
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2282    0.49993 0.888 0.000 0.000 0.000 0.024 0.088
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4473   -0.17511 0.488 0.000 0.000 0.000 0.484 0.028
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4057   -0.12241 0.600 0.000 0.000 0.000 0.012 0.388
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1605    0.84996 0.016 0.000 0.940 0.000 0.012 0.032
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4141    0.26447 0.000 0.000 0.596 0.000 0.388 0.016
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.1982    0.52305 0.912 0.000 0.004 0.000 0.016 0.068
#> 835AAE7F-F873-4D11-8845-232D261A38DF     5  0.5249   -0.22555 0.464 0.000 0.028 0.000 0.468 0.040
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4814   -0.21757 0.532 0.000 0.000 0.000 0.056 0.412
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.2981    0.62697 0.160 0.000 0.000 0.000 0.820 0.020
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.1340    0.87586 0.008 0.948 0.004 0.000 0.000 0.040
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0405    0.87534 0.008 0.988 0.004 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1592    0.84886 0.020 0.000 0.940 0.000 0.008 0.032
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2506    0.57467 0.880 0.000 0.000 0.000 0.068 0.052
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.4552    0.56706 0.300 0.000 0.000 0.000 0.640 0.060
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.5515   -0.19643 0.492 0.000 0.000 0.000 0.136 0.372

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-kmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-kmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:skmeans*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "skmeans"]
# you can also extract it by
# res = res_list["CV:skmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.921           0.950       0.978         0.4500 0.542   0.542
#> 3 3 0.661           0.681       0.837         0.4508 0.721   0.525
#> 4 4 0.681           0.627       0.842         0.1368 0.837   0.578
#> 5 5 0.688           0.713       0.831         0.0681 0.849   0.506
#> 6 6 0.684           0.626       0.793         0.0431 0.911   0.617

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000      0.949 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.992 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.992 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.992 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.992 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.992 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.949 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.949 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.992 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.992 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.992 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6343      0.797 0.840 0.160
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.992 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.949 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.992 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.992 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.992 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.992 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.992 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.992 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.949 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.992 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.992 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.992 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.992 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.992 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.992 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.992 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.949 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.949 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.992 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.992 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.992 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.992 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.949 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.992 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.992 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.949 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.992 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.992 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.949 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.992 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     2  0.0000      0.949 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     2  0.9866      0.313 0.432 0.568
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.992 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.992 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.992 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.949 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.992 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.949 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.992 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.949 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.992 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.992 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.992 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0672      0.984 0.992 0.008
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.992 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.7815      0.679 0.768 0.232
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.949 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.992 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.992 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.0000      0.949 0.000 1.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.992 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.992 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.949 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.992 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.992 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.992 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.992 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.949 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.992 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.992 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.992 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.992 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     2  0.9795      0.358 0.416 0.584
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.992 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.992 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.949 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0376      0.988 0.996 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000      0.949 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.992 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.9491      0.456 0.368 0.632
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.992 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.992 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.992 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     2  0.7815      0.726 0.232 0.768
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000      0.992 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000      0.949 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000      0.949 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.992 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000      0.992 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.992 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000      0.949 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.992 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000      0.992 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000      0.992 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.6887      0.788 0.184 0.816
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     2  0.7219      0.769 0.200 0.800
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.4815      0.874 0.896 0.104
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.992 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000      0.992 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.949 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.949 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000      0.992 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000      0.992 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.949 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000      0.949 0.000 1.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000      0.992 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000      0.992 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000      0.949 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000      0.949 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.9710      0.401 0.400 0.600
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0000      0.992 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000      0.992 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000      0.992 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000      0.992 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000      0.992 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.8207      0.634 0.744 0.256
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000      0.992 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000      0.992 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000      0.992 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000      0.992 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000      0.992 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000      0.992 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.6712      0.797 0.176 0.824
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#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.949 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.992 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.992 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.992 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.992 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000     0.9809 0.000 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.7236 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.1031     0.7197 0.024 0.000 0.976
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.6203 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.6008     0.6336 0.628 0.000 0.372
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.6154     0.6309 0.592 0.000 0.408
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6513     0.5119 0.400 0.008 0.592
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9809 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6154     0.6309 0.592 0.000 0.408
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.6203 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.6126     0.6328 0.600 0.000 0.400
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.6203 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0892     0.7208 0.020 0.000 0.980
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9809 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.6154     0.5090 0.408 0.000 0.592
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.7236 0.000 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.7236 0.000 0.000 1.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.6203 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.6154     0.6309 0.592 0.000 0.408
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0000     0.7236 0.000 0.000 1.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9809 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.6154     0.6309 0.592 0.000 0.408
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.6203 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.6203 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.7236 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.6244     0.5870 0.560 0.000 0.440
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.6126     0.5169 0.400 0.000 0.600
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0000     0.7236 0.000 0.000 1.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9809 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9809 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.6140     0.6323 0.596 0.000 0.404
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.6126     0.6328 0.600 0.000 0.400
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.6203 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.6154     0.6309 0.592 0.000 0.408
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9809 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6126     0.5169 0.400 0.000 0.600
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.6111    -0.2377 0.396 0.000 0.604
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9809 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3551     0.6176 0.868 0.000 0.132
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.6154     0.6309 0.592 0.000 0.408
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9809 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.7236 0.000 0.000 1.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.6359     0.2048 0.004 0.404 0.592
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.6203 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4555     0.4394 0.200 0.000 0.800
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.2356     0.6515 0.072 0.000 0.928
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.6140     0.6323 0.596 0.000 0.404
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9809 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.7236 0.000 0.000 1.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9809 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.6203 1.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9809 0.000 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5560     0.5905 0.300 0.000 0.700
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4555     0.3361 0.800 0.000 0.200
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.6203 1.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.6126     0.5169 0.400 0.000 0.600
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1031     0.7197 0.024 0.000 0.976
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5591     0.6310 0.696 0.000 0.304
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9809 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.6203 1.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.6154     0.6309 0.592 0.000 0.408
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.0000     0.9809 0.000 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.5678     0.2519 0.316 0.000 0.684
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.6203 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9809 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.5397     0.6026 0.280 0.000 0.720
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.6203 1.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.0237     0.7208 0.004 0.000 0.996
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0747     0.7217 0.016 0.000 0.984
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9809 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.6154     0.6309 0.592 0.000 0.408
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.4796     0.3938 0.220 0.000 0.780
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0000     0.7236 0.000 0.000 1.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.6203 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000     0.6203 1.000 0.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.6154     0.6309 0.592 0.000 0.408
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.6154     0.6309 0.592 0.000 0.408
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9809 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5560     0.5909 0.300 0.000 0.700
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000     0.9809 0.000 1.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.6154     0.6309 0.592 0.000 0.408
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0000     0.7236 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.6154     0.6309 0.592 0.000 0.408
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.6154     0.6309 0.592 0.000 0.408
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0237     0.6199 0.996 0.000 0.004
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.6302     0.0634 0.520 0.480 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.6140     0.5140 0.404 0.000 0.596
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9809 0.000 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9809 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0000     0.7236 0.000 0.000 1.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     3  0.4399     0.4479 0.188 0.000 0.812
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.1529     0.6877 0.040 0.000 0.960
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9809 0.000 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.7236 0.000 0.000 1.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.6126     0.6328 0.600 0.000 0.400
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.6154     0.6309 0.592 0.000 0.408
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.9612    -0.1633 0.424 0.372 0.204
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.4399     0.4076 0.812 0.188 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.6126     0.6328 0.600 0.000 0.400
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0747     0.7217 0.016 0.000 0.984
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.6126     0.5169 0.400 0.000 0.600
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9809 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9809 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.4887     0.6317 0.772 0.000 0.228
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.6008     0.6336 0.628 0.000 0.372
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9809 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000     0.9809 0.000 1.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000     0.7236 0.000 0.000 1.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.6154     0.6309 0.592 0.000 0.408
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000     0.9809 0.000 1.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9809 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.8720     0.5375 0.584 0.164 0.252
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.4931     0.6294 0.232 0.000 0.768
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.6126     0.5169 0.400 0.000 0.600
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0237     0.6173 0.996 0.000 0.004
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.3340     0.6298 0.880 0.000 0.120
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.6154     0.6309 0.592 0.000 0.408
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.6126     0.6328 0.600 0.000 0.400
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0237     0.6199 0.996 0.000 0.004
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000     0.6203 1.000 0.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.6260     0.5740 0.552 0.000 0.448
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.2448     0.6181 0.924 0.000 0.076
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     3  0.6126     0.5169 0.400 0.000 0.600
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000     0.6203 1.000 0.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.7078     0.6371 0.088 0.712 0.200
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.0000     0.9809 0.000 1.000 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.1860     0.9287 0.000 0.948 0.052
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.1964     0.6273 0.944 0.000 0.056
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.0000     0.7236 0.000 0.000 1.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.2356     0.6183 0.928 0.000 0.072
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.6308     0.0106 0.508 0.492 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.6154     0.6309 0.592 0.000 0.408
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000     0.9809 0.000 1.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     3  0.0000     0.7236 0.000 0.000 1.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000     0.9809 0.000 1.000 0.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000     0.9809 0.000 1.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000     0.6203 1.000 0.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000     0.9809 0.000 1.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000     0.9809 0.000 1.000 0.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000     0.6203 1.000 0.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.6140     0.6323 0.596 0.000 0.404
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000     0.9809 0.000 1.000 0.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     3  0.6154     0.1477 0.408 0.000 0.592
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0000     0.9809 0.000 1.000 0.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000     0.9809 0.000 1.000 0.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.3038     0.6151 0.896 0.000 0.104
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.0424     0.6141 0.992 0.000 0.008
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000     0.9809 0.000 1.000 0.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.6154     0.6309 0.592 0.000 0.408
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0237     0.6199 0.996 0.000 0.004
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0237     0.6199 0.996 0.000 0.004
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     3  0.5465     0.1708 0.288 0.000 0.712
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000     0.9809 0.000 1.000 0.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     3  0.4504     0.4482 0.196 0.000 0.804
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     2  0.0237     0.9772 0.004 0.996 0.000
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.0000     0.9809 0.000 1.000 0.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000     0.6203 1.000 0.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.5397     0.6313 0.720 0.000 0.280
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.0000     0.9809 0.000 1.000 0.000
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000     0.9809 0.000 1.000 0.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     3  0.0000     0.7236 0.000 0.000 1.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     3  0.0000     0.7236 0.000 0.000 1.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000     0.9809 0.000 1.000 0.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000     0.6203 1.000 0.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000     0.9809 0.000 1.000 0.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000     0.9809 0.000 1.000 0.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.0000     0.6203 1.000 0.000 0.000
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000     0.9809 0.000 1.000 0.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000     0.6203 1.000 0.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000     0.9809 0.000 1.000 0.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.6154     0.6309 0.592 0.000 0.408
#> C1411CDA-814D-4E21-8929-C0F77858828F     3  0.6140     0.5143 0.404 0.000 0.596
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     2  0.0000     0.9809 0.000 1.000 0.000
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000     0.6203 1.000 0.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     3  0.6308    -0.4677 0.492 0.000 0.508
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.6154     0.6309 0.592 0.000 0.408
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.6095     0.6335 0.608 0.000 0.392
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.6154     0.6309 0.592 0.000 0.408
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0892     0.6032 0.980 0.000 0.020
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000     0.9809 0.000 1.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000     0.9809 0.000 1.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.6244     0.5902 0.560 0.000 0.440
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000     0.9809 0.000 1.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.6154     0.6309 0.592 0.000 0.408
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000     0.6203 1.000 0.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000     0.9809 0.000 1.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000     0.6203 1.000 0.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.0000     0.7236 0.000 0.000 1.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000     0.9809 0.000 1.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.9809 0.000 1.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000     0.9809 0.000 1.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000     0.6203 1.000 0.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.6180     0.6226 0.584 0.000 0.416
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.6154     0.6309 0.592 0.000 0.408
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.5098     0.3202 0.752 0.000 0.248
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.4235     0.6235 0.824 0.000 0.176
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9809 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.0000     0.7236 0.000 0.000 1.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.5497     0.6309 0.708 0.000 0.292
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.6154     0.6309 0.592 0.000 0.408
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.6140     0.6323 0.596 0.000 0.404
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.5497     0.5240 0.000 0.708 0.292
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0000     0.7236 0.000 0.000 1.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.6126     0.6328 0.600 0.000 0.400
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000     0.6203 1.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.6154     0.6309 0.592 0.000 0.408
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000     0.6203 1.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.5708     0.7071 0.028 0.768 0.204
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.0000     0.7236 0.000 0.000 1.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9809 0.000 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000     0.9809 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.4504     0.3441 0.804 0.000 0.196
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.4121     0.3981 0.832 0.000 0.168
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     3  0.6280    -0.4002 0.460 0.000 0.540
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.6154     0.6309 0.592 0.000 0.408
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.6140     0.6323 0.596 0.000 0.404
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000     0.9809 0.000 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.6373     0.5070 0.408 0.004 0.588
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.5431     0.6005 0.284 0.000 0.716
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.6154     0.6309 0.592 0.000 0.408
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.6126     0.6328 0.600 0.000 0.400
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9809 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000     0.7236 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9809 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9809 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9809 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0000     0.7236 0.000 0.000 1.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.5254     0.5244 0.000 0.264 0.736
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.6126     0.6328 0.600 0.000 0.400
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.6154     0.6309 0.592 0.000 0.408
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.6154     0.6309 0.592 0.000 0.408
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.4842     0.6336 0.224 0.000 0.776
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.6126     0.5169 0.400 0.000 0.600
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.6154     0.6309 0.592 0.000 0.408
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.6154     0.6309 0.592 0.000 0.408
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9809 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5254     0.1697 0.736 0.000 0.264
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.5560     0.5905 0.300 0.000 0.700
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.3038     0.6090 0.104 0.000 0.896
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9809 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9809 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.6140     0.6323 0.596 0.000 0.404
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9809 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9809 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.0000     0.7236 0.000 0.000 1.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.0237     0.7208 0.004 0.000 0.996
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9809 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9809 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0237     0.7225 0.000 0.004 0.996
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.6154     0.6309 0.592 0.000 0.408
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.4605     0.4307 0.204 0.000 0.796
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9809 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.6180     0.6219 0.584 0.000 0.416
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9809 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.6154     0.6309 0.592 0.000 0.408
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.6154     0.6309 0.592 0.000 0.408
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0892     0.6032 0.980 0.000 0.020
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0000     0.7236 0.000 0.000 1.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.5431     0.5872 0.716 0.000 0.284
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9809 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.4291     0.4810 0.180 0.000 0.820
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.6154     0.6309 0.592 0.000 0.408
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.6280     0.5588 0.540 0.000 0.460
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.7236 0.000 0.000 1.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.6126     0.4339 0.400 0.600 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.6140     0.6323 0.596 0.000 0.404
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6126    -0.2295 0.600 0.000 0.400
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.6260     0.3999 0.448 0.000 0.552
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.0747     0.9659 0.016 0.984 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     3  0.6079     0.5261 0.388 0.000 0.612
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.5591     0.5876 0.304 0.000 0.696
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.6274     0.5657 0.544 0.000 0.456
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9809 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000     0.6203 1.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0000     0.9809 0.000 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.6154     0.6309 0.592 0.000 0.408
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     3  0.6309     0.3180 0.500 0.000 0.500
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.6154     0.6309 0.592 0.000 0.408
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9809 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.9706    -0.2063 0.456 0.272 0.272
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6126     0.5169 0.400 0.000 0.600
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.9576    -0.1833 0.408 0.396 0.196
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9809 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000     0.7236 0.000 0.000 1.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.7180     0.6023 0.196 0.708 0.096
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.6203 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.6154     0.6309 0.592 0.000 0.408
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9809 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.6203 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9809 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.6203 1.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.7236 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6154     0.5090 0.408 0.000 0.592
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9809 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.6203 1.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.6140     0.6323 0.596 0.000 0.404
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.6203 1.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.4796     0.6356 0.220 0.000 0.780
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0000     0.7236 0.000 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4504     0.3441 0.804 0.000 0.196
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6309    -0.3217 0.504 0.000 0.496
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.6203 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.6154     0.6309 0.592 0.000 0.408
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9809 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9809 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.5591     0.5888 0.304 0.000 0.696
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0424     0.6141 0.992 0.000 0.008
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.6140     0.6323 0.596 0.000 0.404
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.6203 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4992   -0.11641 0.000 0.476 0.000 0.524
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0188    0.85692 0.004 0.000 0.996 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5165    0.10389 0.512 0.000 0.004 0.484
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1978    0.71677 0.928 0.000 0.004 0.068
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2216    0.68204 0.908 0.000 0.000 0.092
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2469    0.78149 0.000 0.000 0.892 0.108
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4661    0.31939 0.652 0.000 0.000 0.348
#> 53062969-D209-490B-9C9B-5D297625E2AE     4  0.3024    0.60400 0.148 0.000 0.000 0.852
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.4008    0.50734 0.756 0.000 0.000 0.244
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.3610    0.58624 0.200 0.000 0.000 0.800
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.85651 0.000 0.000 1.000 0.000
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#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     4  0.5260    0.01755 0.424 0.004 0.004 0.568
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     4  0.1302    0.60381 0.044 0.000 0.000 0.956
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.3074    0.67750 0.848 0.000 0.000 0.152
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.7665    0.07584 0.424 0.000 0.216 0.360
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     2  0.4941    0.31655 0.000 0.564 0.000 0.436
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     4  0.5105    0.00463 0.432 0.000 0.004 0.564
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.1792    0.67943 0.932 0.000 0.068 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0707    0.71850 0.980 0.000 0.000 0.020
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.1807    0.71911 0.940 0.000 0.008 0.052
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     4  0.2654    0.61346 0.108 0.000 0.004 0.888
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.4866    0.30698 0.596 0.000 0.000 0.404
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.2101    0.71718 0.928 0.000 0.012 0.060
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     4  0.5112   -0.00281 0.436 0.000 0.004 0.560
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.5070    0.14321 0.580 0.000 0.004 0.416
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.3610    0.73471 0.200 0.000 0.800 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.1389    0.90700 0.000 0.952 0.000 0.048
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     4  0.3873    0.53426 0.228 0.000 0.000 0.772
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.3074    0.67750 0.848 0.000 0.000 0.152
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0707    0.71582 0.980 0.000 0.000 0.020
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     4  0.7396   -0.07528 0.404 0.000 0.164 0.432
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.1824    0.69320 0.936 0.000 0.004 0.060
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.3024    0.77062 0.148 0.000 0.852 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     4  0.4477    0.31857 0.312 0.000 0.000 0.688
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.4277    0.44581 0.720 0.000 0.000 0.280
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.1474    0.71790 0.948 0.000 0.000 0.052
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.6233    0.26477 0.388 0.552 0.000 0.060
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0336    0.85582 0.008 0.000 0.992 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0592    0.71968 0.984 0.000 0.000 0.016
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     4  0.3074    0.60205 0.152 0.000 0.000 0.848
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.1557    0.71798 0.944 0.000 0.000 0.056
#> 331A9160-D730-45DD-A985-C6CAC03035ED     4  0.3123    0.59977 0.156 0.000 0.000 0.844
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.6069    0.20006 0.000 0.356 0.056 0.588
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.0188    0.85692 0.004 0.000 0.996 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.4925    0.33134 0.000 0.572 0.000 0.428
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     4  0.1209    0.61224 0.004 0.000 0.032 0.964
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     4  0.5226    0.46563 0.180 0.000 0.076 0.744
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.4336    0.64915 0.812 0.000 0.128 0.060
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.3266    0.66547 0.832 0.000 0.000 0.168
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.2530    0.69386 0.888 0.000 0.000 0.112
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.1940    0.87227 0.000 0.924 0.076 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     4  0.4661    0.26998 0.000 0.000 0.348 0.652
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     4  0.4994    0.10644 0.480 0.000 0.000 0.520
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0188    0.85692 0.004 0.000 0.996 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0336    0.85582 0.008 0.000 0.992 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0188    0.85523 0.000 0.004 0.996 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.4730    0.37154 0.636 0.000 0.000 0.364
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.1637    0.71784 0.940 0.000 0.000 0.060
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.2469    0.78149 0.000 0.000 0.892 0.108
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1867    0.71803 0.928 0.000 0.000 0.072
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5193    0.14667 0.580 0.000 0.008 0.412
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.6120    0.25107 0.520 0.000 0.432 0.048
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0188    0.71779 0.996 0.000 0.000 0.004
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.0336    0.85437 0.000 0.000 0.992 0.008
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.6334   -0.12192 0.456 0.000 0.484 0.060
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0188    0.85692 0.004 0.000 0.996 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.4643    0.35970 0.656 0.000 0.344 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.5075    0.30646 0.644 0.000 0.012 0.344
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.1716    0.71767 0.936 0.000 0.000 0.064
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     4  0.5097    0.01724 0.428 0.000 0.004 0.568
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.3351    0.76730 0.148 0.000 0.844 0.008
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     4  0.4720    0.49504 0.264 0.000 0.016 0.720
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.5000    0.12596 0.496 0.000 0.504 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1940    0.71756 0.924 0.000 0.000 0.076
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.1209    0.71263 0.964 0.000 0.004 0.032
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0336    0.85437 0.000 0.000 0.992 0.008
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     4  0.4866    0.24557 0.000 0.404 0.000 0.596
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2589    0.70082 0.884 0.000 0.000 0.116
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.7625    0.11430 0.472 0.000 0.276 0.252
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3569    0.69733 0.196 0.000 0.804 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.4989    0.18260 0.000 0.528 0.000 0.472
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     3  0.5643    0.32701 0.024 0.000 0.548 0.428
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.6984    0.37955 0.184 0.000 0.580 0.236
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3164    0.70612 0.884 0.000 0.052 0.064
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     4  0.4872    0.32095 0.356 0.000 0.004 0.640
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.4994   -0.12737 0.000 0.480 0.000 0.520
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1716    0.71773 0.936 0.000 0.000 0.064
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4948    0.21029 0.560 0.000 0.440 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.1557    0.60500 0.000 0.000 0.056 0.944
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.1389    0.60708 0.000 0.000 0.048 0.952
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.3441    0.78233 0.120 0.000 0.856 0.024
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.7371    0.06664 0.160 0.416 0.000 0.424
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     4  0.4992    0.05765 0.476 0.000 0.000 0.524
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.71684 1.000 0.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.5132    0.11795 0.548 0.000 0.004 0.448
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.4972    0.27172 0.000 0.544 0.000 0.456
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.0336    0.61470 0.008 0.000 0.000 0.992
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.1256    0.84257 0.028 0.000 0.964 0.008
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     4  0.4888    0.11857 0.000 0.000 0.412 0.588
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     4  0.2266    0.61051 0.084 0.000 0.004 0.912
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1637    0.71811 0.940 0.000 0.000 0.060
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     4  0.0000    0.61329 0.000 0.000 0.000 1.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.2868    0.78054 0.136 0.000 0.864 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.3088    0.60236 0.060 0.000 0.052 0.888
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6944    0.14036 0.484 0.000 0.404 0.112
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     4  0.3024    0.60400 0.148 0.000 0.000 0.852
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0336    0.71856 0.992 0.000 0.000 0.008
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.94611 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.85651 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.5097    0.01724 0.428 0.000 0.004 0.568
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.3024    0.68031 0.852 0.000 0.000 0.148
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     4  0.4948    0.10727 0.440 0.000 0.000 0.560

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.0000     0.7827 0.000 0.000 0.000 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8668 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0609     0.8576 0.020 0.000 0.980 0.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1851     0.7702 0.912 0.000 0.000 0.000 0.088
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2891     0.7162 0.824 0.000 0.000 0.000 0.176
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1648     0.7284 0.040 0.000 0.000 0.020 0.940
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.1965     0.8054 0.096 0.000 0.904 0.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9247 0.000 1.000 0.000 0.000 0.000
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#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     4  0.4101     0.5986 0.372 0.000 0.000 0.628 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8668 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3143     0.7009 0.000 0.000 0.796 0.000 0.204
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000     0.7579 1.000 0.000 0.000 0.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4675     0.5734 0.600 0.000 0.020 0.000 0.380
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     4  0.4889     0.7554 0.144 0.000 0.000 0.720 0.136
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3003     0.6662 0.188 0.000 0.000 0.000 0.812
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9247 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9247 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8668 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0671     0.7629 0.980 0.000 0.000 0.004 0.016
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.4323     0.6129 0.332 0.000 0.000 0.012 0.656
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.6420    -0.0396 0.448 0.000 0.000 0.176 0.376

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2003     0.7632 0.116 0.000 0.000 0.884 0.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.1956     0.8126 0.004 0.000 0.908 0.008 0.000 0.080
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     6  0.2003     0.6620 0.116 0.000 0.000 0.000 0.000 0.884
#> 78F79407-D49F-4FA2-B09F-0665C502827C     6  0.1838     0.6642 0.016 0.000 0.000 0.000 0.068 0.916
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.2912     0.6817 0.116 0.000 0.000 0.040 0.844 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2356     0.7781 0.016 0.000 0.884 0.004 0.000 0.096
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4239     0.6466 0.156 0.000 0.000 0.088 0.748 0.008
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3701     0.6822 0.788 0.000 0.000 0.000 0.112 0.100
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.4139     0.6532 0.136 0.000 0.000 0.036 0.776 0.052
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3648     0.6904 0.776 0.000 0.000 0.024 0.188 0.012
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.2092     0.8519 0.000 0.124 0.000 0.876 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.5104     0.5312 0.172 0.000 0.164 0.008 0.000 0.656
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0508     0.8505 0.000 0.000 0.984 0.004 0.012 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3533     0.6785 0.820 0.000 0.000 0.016 0.060 0.104
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0972     0.6992 0.000 0.000 0.000 0.008 0.964 0.028
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.3357     0.6482 0.000 0.000 0.764 0.004 0.224 0.008
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     6  0.2402     0.5877 0.004 0.000 0.000 0.000 0.140 0.856
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     6  0.5298     0.5123 0.160 0.000 0.000 0.000 0.248 0.592
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4850    -0.0379 0.524 0.000 0.000 0.020 0.024 0.432
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     6  0.3833    -0.1489 0.000 0.000 0.000 0.000 0.444 0.556
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2356     0.7781 0.016 0.000 0.884 0.004 0.000 0.096
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5445     0.3450 0.000 0.000 0.548 0.004 0.324 0.124
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.2092     0.8081 0.000 0.876 0.000 0.124 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4709     0.6503 0.140 0.000 0.000 0.016 0.716 0.128
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.4680     0.5400 0.264 0.000 0.000 0.084 0.652 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     6  0.5375     0.5019 0.208 0.000 0.000 0.000 0.204 0.588
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.2178     0.6666 0.000 0.000 0.000 0.000 0.868 0.132
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     6  0.3118     0.6462 0.072 0.000 0.092 0.000 0.000 0.836
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.5392     0.4644 0.064 0.000 0.000 0.028 0.564 0.344
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     6  0.0603     0.6733 0.004 0.000 0.000 0.000 0.016 0.980
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     6  0.3309     0.5382 0.000 0.000 0.000 0.000 0.280 0.720
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.3578     0.4181 0.000 0.660 0.000 0.340 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2357     0.7612 0.012 0.000 0.872 0.116 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3406     0.7233 0.832 0.000 0.000 0.024 0.100 0.044
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.4308     0.3996 0.000 0.000 0.300 0.008 0.664 0.028
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     6  0.2631     0.5987 0.004 0.000 0.012 0.000 0.128 0.856
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.4403     0.6549 0.172 0.000 0.000 0.040 0.744 0.044
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.2092     0.8519 0.000 0.124 0.000 0.876 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3557     0.7229 0.828 0.000 0.000 0.032 0.080 0.060
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.2178     0.8468 0.000 0.132 0.000 0.868 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1003     0.8437 0.000 0.000 0.964 0.000 0.016 0.020
#> F941890E-AB33-478F-8C97-1C785DD9428F     6  0.4084     0.3701 0.400 0.000 0.000 0.012 0.000 0.588
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     6  0.2300     0.6491 0.144 0.000 0.000 0.000 0.000 0.856
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2306     0.7819 0.016 0.000 0.888 0.004 0.000 0.092
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5662     0.3264 0.524 0.000 0.000 0.196 0.280 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2597     0.7477 0.000 0.824 0.000 0.176 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     6  0.3908     0.6270 0.132 0.000 0.000 0.000 0.100 0.768
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.4504     0.3524 0.024 0.000 0.000 0.004 0.540 0.432
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.1663     0.7803 0.088 0.000 0.000 0.912 0.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.5582     0.2821 0.332 0.000 0.004 0.092 0.556 0.016
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     6  0.4527     0.2695 0.456 0.000 0.000 0.004 0.024 0.516
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4021     0.7021 0.780 0.000 0.000 0.032 0.144 0.044
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.4579     0.2319 0.000 0.000 0.380 0.008 0.584 0.028
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.2135     0.8501 0.000 0.128 0.000 0.872 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     6  0.4181    -0.2478 0.012 0.000 0.000 0.000 0.476 0.512
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.3840     0.6210 0.000 0.000 0.152 0.004 0.776 0.068
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4325     0.5067 0.000 0.000 0.660 0.008 0.304 0.028
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3552     0.6845 0.800 0.000 0.000 0.000 0.084 0.116
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3736     0.7007 0.788 0.000 0.000 0.032 0.160 0.020
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.0858     0.6968 0.000 0.000 0.000 0.004 0.968 0.028
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.3164     0.6740 0.140 0.000 0.000 0.032 0.824 0.004
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.3695     0.7600 0.060 0.164 0.000 0.776 0.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     6  0.2854     0.5276 0.000 0.000 0.000 0.000 0.208 0.792
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     6  0.3862    -0.2396 0.000 0.000 0.000 0.000 0.476 0.524
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.1970     0.6799 0.008 0.000 0.000 0.000 0.900 0.092
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     6  0.2740     0.6733 0.076 0.000 0.000 0.000 0.060 0.864
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.3515     0.6187 0.780 0.000 0.000 0.192 0.016 0.012
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     6  0.6587     0.2952 0.336 0.000 0.084 0.004 0.100 0.476
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.2048     0.8529 0.000 0.120 0.000 0.880 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.3737     0.2693 0.000 0.608 0.000 0.392 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0146     0.8544 0.000 0.000 0.996 0.004 0.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     6  0.4215     0.2902 0.008 0.000 0.016 0.004 0.300 0.672
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.5510     0.3490 0.000 0.000 0.312 0.008 0.556 0.124
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.2135     0.8499 0.000 0.128 0.000 0.872 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.4552     0.6038 0.204 0.000 0.000 0.092 0.700 0.004
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.3565     0.5152 0.004 0.000 0.000 0.000 0.692 0.304
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3894     0.6244 0.772 0.000 0.072 0.004 0.000 0.152
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.2706     0.6494 0.832 0.000 0.000 0.160 0.000 0.008
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.5075    -0.1652 0.480 0.000 0.000 0.064 0.452 0.004
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     6  0.3817     0.6425 0.120 0.000 0.052 0.020 0.004 0.804
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.4532     0.6022 0.660 0.000 0.000 0.028 0.292 0.020
#> 7822EA86-35A1-4285-9429-2B63111B9885     5  0.4771     0.5360 0.256 0.000 0.000 0.096 0.648 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.5236     0.3445 0.548 0.364 0.000 0.080 0.008 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.0865     0.6970 0.000 0.000 0.000 0.000 0.964 0.036
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.1588     0.8483 0.004 0.072 0.000 0.924 0.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.7077     0.2117 0.220 0.000 0.000 0.324 0.376 0.080
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.4350     0.4685 0.024 0.000 0.648 0.004 0.004 0.320
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     6  0.3390     0.6183 0.200 0.000 0.000 0.008 0.012 0.780
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     5  0.5335     0.2223 0.300 0.000 0.000 0.040 0.604 0.056
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     5  0.3485     0.6908 0.112 0.000 0.000 0.036 0.824 0.028
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     5  0.5291     0.4389 0.364 0.000 0.000 0.052 0.556 0.028
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     6  0.1556     0.6709 0.080 0.000 0.000 0.000 0.000 0.920
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     6  0.2562     0.6415 0.172 0.000 0.000 0.000 0.000 0.828
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     5  0.4847     0.1426 0.000 0.000 0.048 0.004 0.532 0.416
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     6  0.2595     0.6407 0.004 0.000 0.000 0.000 0.160 0.836
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     6  0.5970     0.2331 0.172 0.000 0.376 0.008 0.000 0.444
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     6  0.5479     0.2553 0.388 0.000 0.000 0.000 0.128 0.484
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     4  0.3782     0.2662 0.412 0.000 0.000 0.588 0.000 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     4  0.1644     0.8496 0.004 0.076 0.000 0.920 0.000 0.000
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#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.2748     0.6199 0.024 0.000 0.000 0.000 0.128 0.848
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3369     0.6957 0.040 0.000 0.000 0.028 0.836 0.096
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     6  0.3859     0.4493 0.000 0.000 0.288 0.000 0.020 0.692
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.3979     0.6044 0.720 0.244 0.000 0.032 0.000 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     5  0.5845     0.2641 0.164 0.000 0.000 0.004 0.436 0.396
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     6  0.4794     0.4659 0.056 0.000 0.004 0.000 0.344 0.596
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3201     0.6559 0.000 0.000 0.780 0.000 0.208 0.012
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5273     0.4782 0.604 0.212 0.000 0.184 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     6  0.5378     0.5613 0.160 0.000 0.116 0.036 0.008 0.680
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.1757     0.6569 0.008 0.000 0.076 0.000 0.000 0.916
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     6  0.1327     0.6558 0.000 0.000 0.000 0.000 0.064 0.936
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     6  0.5593     0.3120 0.356 0.000 0.000 0.008 0.120 0.516
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.1910     0.7693 0.108 0.000 0.000 0.892 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.4191     0.4441 0.012 0.000 0.000 0.004 0.596 0.388
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     6  0.3435     0.6284 0.000 0.000 0.060 0.000 0.136 0.804
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2572     0.6573 0.012 0.000 0.000 0.000 0.852 0.136
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5143     0.3383 0.560 0.000 0.012 0.364 0.000 0.064
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2009     0.7964 0.008 0.000 0.904 0.004 0.000 0.084
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4328     0.6019 0.716 0.000 0.000 0.192 0.000 0.092
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.2048     0.8190 0.000 0.880 0.000 0.120 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4688     0.4032 0.020 0.000 0.608 0.012 0.352 0.008
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.4056     0.5930 0.064 0.000 0.000 0.748 0.184 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.5404     0.4086 0.580 0.000 0.000 0.000 0.184 0.236
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1285     0.6936 0.000 0.000 0.000 0.004 0.944 0.052
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.1910     0.8541 0.000 0.108 0.000 0.892 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     6  0.5568     0.3311 0.360 0.000 0.000 0.008 0.116 0.516
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1958     0.7817 0.100 0.004 0.000 0.896 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1575     0.7138 0.936 0.000 0.000 0.032 0.000 0.032
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.3694     0.5353 0.000 0.000 0.232 0.000 0.028 0.740
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6096     0.3103 0.264 0.000 0.552 0.044 0.000 0.140
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.4181    -0.0117 0.012 0.512 0.000 0.476 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     6  0.3847     0.4526 0.348 0.000 0.000 0.008 0.000 0.644
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.4223     0.4531 0.060 0.000 0.000 0.000 0.236 0.704
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2212     0.6749 0.880 0.000 0.000 0.008 0.000 0.112
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3302     0.6408 0.000 0.000 0.760 0.004 0.232 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.3534     0.5495 0.276 0.000 0.000 0.008 0.000 0.716
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.4406     0.4529 0.024 0.000 0.008 0.000 0.344 0.624
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3730     0.7124 0.808 0.000 0.000 0.024 0.112 0.056
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3563     0.4793 0.000 0.000 0.000 0.000 0.664 0.336
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9086 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8556 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.3967     0.5334 0.316 0.000 0.000 0.008 0.008 0.668
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.5645     0.5257 0.144 0.000 0.000 0.016 0.580 0.260
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3533     0.6837 0.820 0.000 0.000 0.016 0.104 0.060

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-skmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "pam"]
# you can also extract it by
# res = res_list["CV:pam"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.980           0.941       0.978         0.2521 0.755   0.755
#> 3 3 0.551           0.759       0.885         1.2370 0.670   0.567
#> 4 4 0.452           0.621       0.799         0.2114 0.808   0.597
#> 5 5 0.498           0.560       0.738         0.1084 0.817   0.500
#> 6 6 0.546           0.602       0.765         0.0357 0.954   0.805

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0000     0.9832 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000     0.9832 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000     0.9832 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9832 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9832 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9832 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.0000     0.9832 1.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9380 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000     0.9832 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9832 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9832 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9832 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000     0.9832 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.9686     0.3931 0.396 0.604
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000     0.9832 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000     0.9832 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000     0.9832 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9832 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9832 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000     0.9832 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9380 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9832 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9832 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9832 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000     0.9832 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9832 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000     0.9832 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.9832 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9380 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     1  0.9933     0.0964 0.548 0.452
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9832 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.9832 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9832 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9832 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.0000     0.9832 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000     0.9832 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000     0.9832 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9380 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9832 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9832 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9380 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000     0.9832 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000     0.9832 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.9832 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9832 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000     0.9832 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9832 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9380 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000     0.9832 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1843     0.9189 0.028 0.972
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.9832 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.9000     0.5722 0.316 0.684
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000     0.9832 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000     0.9832 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9832 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000     0.9832 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000     0.9832 1.000 0.000
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#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9380 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000     0.9832 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000     0.9832 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000     0.9832 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.9866     0.3047 0.432 0.568
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9380 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9832 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     1  0.7745     0.6770 0.772 0.228
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     1  0.0938     0.9712 0.988 0.012
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000     0.9832 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000     0.9832 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     1  0.0000     0.9832 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9380 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.0000     0.9832 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.9832 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000     0.9832 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     1  0.0000     0.9832 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000     0.9832 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     1  0.9881     0.1545 0.564 0.436
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.9832 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000     0.9832 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000     0.9832 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000     0.9832 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9832 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9380 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000     0.9832 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000     0.9832 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9832 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000     0.9832 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000     0.9832 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9832 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000     0.9832 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000     0.9832 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000     0.9832 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000     0.9832 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000     0.9832 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000     0.9832 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9380 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000     0.9832 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000     0.9832 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9832 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.9832 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9832 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9380 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000     0.9832 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.0000     0.9832 1.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000     0.9832 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.0000     0.9832 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000     0.9832 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000     0.9832 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9832 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9832 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.9833     0.3262 0.424 0.576
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9832 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.0000     0.9832 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.9832 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000     0.9832 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000     0.9832 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0000     0.9832 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.9832 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.9832 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.9832 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000     0.9832 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000     0.9832 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000     0.9832 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000     0.9832 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9832 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9832 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9380 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9380 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000     0.9832 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.9832 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9832 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9832 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.4504     0.7843 0.804 0.000 0.196
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.7880 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4654     0.7104 0.208 0.000 0.792
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.8801 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.8801 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1753     0.8758 0.952 0.000 0.048
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.5529     0.6022 0.704 0.000 0.296
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8978 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.4399     0.7433 0.188 0.000 0.812
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1163     0.8805 0.972 0.000 0.028
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1411     0.8795 0.964 0.000 0.036
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1031     0.8817 0.976 0.000 0.024
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0424     0.7898 0.008 0.000 0.992
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.7571     0.3840 0.356 0.592 0.052
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.2356     0.8709 0.928 0.000 0.072
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.7880 0.000 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1289     0.7879 0.032 0.000 0.968
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.8801 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1289     0.8795 0.968 0.000 0.032
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0000     0.7880 0.000 0.000 1.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8978 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1411     0.8790 0.964 0.000 0.036
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.8801 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0747     0.8825 0.984 0.000 0.016
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.7880 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.4121     0.7601 0.168 0.000 0.832
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.6180     0.2879 0.416 0.000 0.584
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4399     0.7077 0.188 0.000 0.812
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.8978 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     1  0.7819     0.0660 0.508 0.440 0.052
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.8801 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3619     0.8214 0.864 0.000 0.136
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.8801 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2711     0.8624 0.912 0.000 0.088
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.3686     0.8253 0.860 0.000 0.140
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.4452     0.7424 0.808 0.000 0.192
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.2878     0.8680 0.904 0.000 0.096
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8978 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0237     0.8811 0.996 0.000 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1289     0.8745 0.968 0.000 0.032
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.8978 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.7880 0.000 0.000 1.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.6045     0.3210 0.380 0.000 0.620
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.8801 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.1964     0.7921 0.056 0.000 0.944
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.1643     0.7964 0.044 0.000 0.956
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1289     0.8795 0.968 0.000 0.032
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8978 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0892     0.7862 0.020 0.000 0.980
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.3295     0.8183 0.008 0.896 0.096
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1411     0.8820 0.964 0.000 0.036
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.7388     0.6241 0.160 0.704 0.136
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1529     0.7881 0.040 0.000 0.960
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.1643     0.8785 0.956 0.000 0.044
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1411     0.8806 0.964 0.000 0.036
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.6295     0.0824 0.472 0.000 0.528
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.7880 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1529     0.8809 0.960 0.000 0.040
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.8389     0.3275 0.372 0.536 0.092
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0424     0.8813 0.992 0.000 0.008
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2165     0.8721 0.936 0.000 0.064
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.3879     0.8252 0.848 0.000 0.152
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.4654     0.7668 0.792 0.000 0.208
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.8801 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8978 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.7880 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1163     0.8802 0.972 0.000 0.028
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.2878     0.7864 0.096 0.000 0.904
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.7880 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     1  0.6151     0.7353 0.764 0.180 0.056
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0237     0.8805 0.996 0.000 0.004
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.3192     0.7813 0.112 0.000 0.888
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.1031     0.7883 0.024 0.000 0.976
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0892     0.8817 0.980 0.000 0.020
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0747     0.8822 0.984 0.000 0.016
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.5178     0.5516 0.744 0.000 0.256
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1529     0.8810 0.960 0.000 0.040
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.8978 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.3686     0.7365 0.140 0.000 0.860
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.7627     0.2166 0.428 0.528 0.044
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4750     0.7626 0.784 0.000 0.216
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.2165     0.7902 0.064 0.000 0.936
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.5431     0.6734 0.284 0.000 0.716
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0237     0.8807 0.996 0.000 0.004
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.8801 1.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.1860     0.8812 0.948 0.000 0.052
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.5431     0.6346 0.716 0.000 0.284
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     1  0.2356     0.8770 0.928 0.000 0.072
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.8978 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0592     0.7875 0.012 0.000 0.988
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.6045     0.3003 0.620 0.000 0.380
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.3038     0.7845 0.104 0.000 0.896
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     1  0.4002     0.8308 0.840 0.000 0.160
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#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     3  0.6244     0.4322 0.440 0.000 0.560
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.6299    -0.1228 0.524 0.000 0.476
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.1289     0.8797 0.968 0.000 0.032
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0000     0.7880 0.000 0.000 1.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.2537     0.8748 0.920 0.000 0.080
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.8978 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3116     0.7824 0.108 0.000 0.892
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1031     0.8790 0.976 0.000 0.024
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.3412     0.7849 0.124 0.000 0.876
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.1163     0.7816 0.028 0.000 0.972
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1163     0.8818 0.972 0.000 0.028
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.8801 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6267     0.1575 0.548 0.000 0.452
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.6274    -0.0916 0.544 0.000 0.456
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0424     0.8813 0.992 0.000 0.008
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.2878     0.8591 0.904 0.000 0.096
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5859     0.4914 0.656 0.000 0.344
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.6062     0.3179 0.616 0.000 0.384
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.8978 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1031     0.8811 0.976 0.000 0.024
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.4178     0.8095 0.828 0.000 0.172
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1289     0.8795 0.968 0.000 0.032
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.6192     0.1199 0.580 0.000 0.420
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0237     0.8805 0.996 0.000 0.004
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.8978 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.4750     0.7655 0.784 0.000 0.216
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.6280     0.2610 0.540 0.000 0.460
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.2625     0.8605 0.916 0.000 0.084
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.1860     0.8807 0.948 0.000 0.052
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.4750     0.7485 0.784 0.000 0.216
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.4750     0.7517 0.784 0.000 0.216
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.8801 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.6299     0.3159 0.476 0.000 0.524
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     1  0.7382     0.0338 0.512 0.456 0.032
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.8801 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.3551     0.8425 0.868 0.000 0.132
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1643     0.8815 0.956 0.000 0.044
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5835     0.4592 0.340 0.000 0.660
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.5058     0.7317 0.756 0.000 0.244
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1163     0.8806 0.972 0.000 0.028
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.1411     0.8795 0.964 0.000 0.036
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1289     0.8795 0.968 0.000 0.032
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1289     0.8797 0.968 0.000 0.032
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1031     0.7896 0.024 0.000 0.976
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1643     0.7946 0.044 0.000 0.956
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.1529     0.8796 0.960 0.000 0.040
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6305    -0.0368 0.516 0.000 0.484
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.8801 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.6291     0.3518 0.468 0.000 0.532
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8978 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8978 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.6026     0.3483 0.376 0.000 0.624
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1289     0.8797 0.968 0.000 0.032
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1289     0.8795 0.968 0.000 0.032
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.8801 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4365     0.6907 0.188 0.000 0.028 0.784
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.6193     0.5394 0.180 0.000 0.672 0.148
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2589     0.7014 0.884 0.000 0.000 0.116
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2081     0.7086 0.916 0.000 0.000 0.084
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1888     0.6775 0.940 0.000 0.016 0.044
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.6916     0.5164 0.588 0.000 0.236 0.176
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.6121     0.5098 0.352 0.000 0.588 0.060
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4103     0.6410 0.744 0.000 0.000 0.256
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.4804     0.4907 0.384 0.000 0.000 0.616
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4817     0.4146 0.612 0.000 0.000 0.388
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.4595     0.5109 0.040 0.184 0.000 0.776
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.5318     0.6606 0.732 0.000 0.072 0.196
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2589     0.7004 0.884 0.000 0.000 0.116
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0817     0.6926 0.976 0.000 0.000 0.024
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0188     0.8092 0.000 0.000 0.996 0.004
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2741     0.7117 0.892 0.000 0.012 0.096
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.6976 1.000 0.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3356     0.6948 0.824 0.000 0.000 0.176
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.5141     0.6542 0.268 0.000 0.700 0.032
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4585     0.4133 0.332 0.000 0.668 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5962     0.5990 0.260 0.000 0.660 0.080
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.7617    -0.0380 0.216 0.452 0.000 0.332
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1716     0.7118 0.936 0.000 0.000 0.064
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.6202     0.5618 0.312 0.000 0.076 0.612
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2530     0.7010 0.888 0.000 0.000 0.112
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.4057     0.7049 0.816 0.000 0.032 0.152
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.5773     0.5353 0.632 0.000 0.048 0.320
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.6224     0.6107 0.668 0.000 0.144 0.188
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5559     0.6496 0.696 0.000 0.064 0.240
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0804     0.7030 0.980 0.000 0.012 0.008
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0188     0.6979 0.996 0.000 0.004 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.3873     0.7139 0.000 0.772 0.000 0.228
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.4744     0.5039 0.284 0.000 0.704 0.012
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4866     0.3062 0.596 0.000 0.000 0.404
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2670     0.7833 0.072 0.000 0.904 0.024
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.4706     0.7356 0.140 0.000 0.788 0.072
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1637     0.6928 0.940 0.000 0.000 0.060
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.4761     0.6059 0.000 0.628 0.000 0.372
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.4643     0.5588 0.344 0.000 0.000 0.656
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.5334     0.5208 0.008 0.588 0.004 0.400
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4955     0.6160 0.708 0.000 0.024 0.268
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3991     0.6889 0.808 0.000 0.020 0.172
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.6249     0.2571 0.336 0.000 0.592 0.072
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.4643     0.5555 0.344 0.000 0.000 0.656
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.7812     0.1725 0.216 0.520 0.016 0.248
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1022     0.6879 0.968 0.000 0.000 0.032
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2256     0.6813 0.924 0.000 0.020 0.056
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.4253     0.6817 0.208 0.000 0.016 0.776
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.6991     0.4955 0.580 0.000 0.232 0.188
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2760     0.7015 0.872 0.000 0.000 0.128
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4164     0.5649 0.736 0.000 0.000 0.264
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4387     0.7235 0.200 0.000 0.776 0.024
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.3652     0.6757 0.052 0.092 0.000 0.856
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.6976 1.000 0.000 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.4706     0.7013 0.224 0.000 0.748 0.028
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3172     0.7081 0.840 0.000 0.000 0.160
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4585     0.4745 0.668 0.000 0.000 0.332
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.4669     0.4703 0.764 0.000 0.200 0.036
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.3144     0.6934 0.884 0.000 0.044 0.072
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.2859     0.7417 0.112 0.000 0.880 0.008
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2654     0.5432 0.004 0.108 0.000 0.888
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.6416     0.6070 0.648 0.000 0.152 0.200
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6013     0.6545 0.196 0.000 0.684 0.120
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.5937    -0.2307 0.492 0.000 0.472 0.036
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0817     0.7013 0.976 0.000 0.000 0.024
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.6976 1.000 0.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     4  0.3751     0.7017 0.196 0.000 0.004 0.800
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.6809     0.4325 0.552 0.000 0.332 0.116
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.4372     0.5829 0.268 0.000 0.004 0.728
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.2589     0.8372 0.000 0.884 0.000 0.116
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0336     0.8092 0.008 0.000 0.992 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.6698     0.4594 0.604 0.000 0.256 0.140
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.3383     0.7702 0.076 0.000 0.872 0.052
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.1970     0.7085 0.060 0.000 0.008 0.932
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     4  0.4961     0.3427 0.448 0.000 0.000 0.552
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.2589     0.7014 0.884 0.000 0.000 0.116
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.4889     0.5517 0.636 0.000 0.004 0.360
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.3649     0.6932 0.204 0.000 0.000 0.796
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     4  0.4855     0.5497 0.400 0.000 0.000 0.600
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.3224     0.6791 0.864 0.000 0.016 0.120
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.8976 0.000 1.000 0.000 0.000
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#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.4855     0.0556 0.600 0.000 0.400 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.5755     0.2284 0.624 0.000 0.332 0.044
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.4134     0.6358 0.740 0.000 0.000 0.260
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1474     0.7895 0.000 0.000 0.948 0.052
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4576     0.6367 0.748 0.000 0.020 0.232
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0336     0.8948 0.000 0.992 0.000 0.008
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3910     0.7499 0.156 0.000 0.820 0.024
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0336     0.7006 0.992 0.000 0.008 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.4720     0.6717 0.264 0.000 0.720 0.016
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4511     0.6167 0.724 0.000 0.008 0.268
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3311     0.6895 0.828 0.000 0.000 0.172
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5530     0.3167 0.632 0.000 0.336 0.032
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.7059     0.3798 0.528 0.000 0.332 0.140
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.3907     0.6473 0.768 0.000 0.000 0.232
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5062     0.6750 0.752 0.000 0.064 0.184
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5083     0.5267 0.716 0.000 0.248 0.036
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.5491     0.4787 0.688 0.000 0.260 0.052
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3356     0.6894 0.824 0.000 0.000 0.176
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.3501     0.7113 0.132 0.000 0.020 0.848
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4560     0.2355 0.700 0.000 0.004 0.296
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.6618     0.4910 0.604 0.000 0.272 0.124
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2530     0.7010 0.888 0.000 0.000 0.112
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0188     0.8964 0.000 0.996 0.000 0.004
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.6192     0.2467 0.512 0.000 0.052 0.436
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6487    -0.0231 0.428 0.000 0.500 0.072
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5417     0.3841 0.572 0.000 0.016 0.412
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.4277     0.6696 0.280 0.000 0.000 0.720
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5723     0.4817 0.684 0.000 0.244 0.072
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.7091     0.5842 0.224 0.000 0.208 0.568
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2530     0.7010 0.888 0.000 0.000 0.112
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4978     0.1431 0.612 0.000 0.384 0.004
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.3367     0.5363 0.028 0.108 0.000 0.864
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2647     0.7016 0.880 0.000 0.000 0.120
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0592     0.6756 0.016 0.000 0.000 0.984
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.5442     0.6410 0.288 0.000 0.040 0.672
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.7037     0.2129 0.416 0.000 0.464 0.120
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6574     0.3902 0.548 0.000 0.088 0.364
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4382     0.5939 0.704 0.000 0.000 0.296
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4372     0.6287 0.728 0.000 0.004 0.268
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1022     0.6893 0.968 0.000 0.000 0.032
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4522     0.5705 0.680 0.000 0.000 0.320
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8103 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3450     0.7588 0.156 0.000 0.836 0.008
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4910     0.6091 0.704 0.000 0.020 0.276
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6417     0.2299 0.540 0.000 0.388 0.072
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3356     0.6797 0.824 0.000 0.000 0.176
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.5756     0.1094 0.592 0.000 0.372 0.036
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8976 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.4647     0.4974 0.288 0.000 0.704 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4277     0.6135 0.720 0.000 0.000 0.280
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.2530     0.6412 0.888 0.000 0.000 0.112
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2868     0.6989 0.864 0.000 0.000 0.136

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.5441    -0.3632 0.536 0.000 0.008 0.412 0.044
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5318     0.0570 0.460 0.000 0.496 0.004 0.040
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3684     0.6325 0.720 0.000 0.000 0.000 0.280
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4201     0.4578 0.592 0.000 0.000 0.000 0.408
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0880     0.7004 0.032 0.000 0.000 0.000 0.968
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.4893     0.5711 0.704 0.000 0.208 0.000 0.088
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4208     0.5792 0.016 0.000 0.204 0.020 0.760
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2361     0.6916 0.892 0.000 0.000 0.012 0.096
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.6786     0.2274 0.292 0.000 0.000 0.384 0.324
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4216     0.5546 0.780 0.000 0.000 0.120 0.100
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.5052     0.6350 0.156 0.084 0.000 0.736 0.024
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.3339     0.6796 0.840 0.000 0.048 0.000 0.112
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3707     0.6375 0.716 0.000 0.000 0.000 0.284
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1478     0.7018 0.064 0.000 0.000 0.000 0.936
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0162     0.8041 0.004 0.000 0.996 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     5  0.4655    -0.1612 0.476 0.000 0.012 0.000 0.512
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.3048     0.6636 0.176 0.000 0.000 0.004 0.820
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3424     0.6698 0.760 0.000 0.000 0.000 0.240
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.4980     0.2583 0.036 0.000 0.380 0.000 0.584
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2806     0.6943 0.152 0.000 0.844 0.000 0.004
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.6337     0.2603 0.192 0.000 0.512 0.000 0.296
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0162     0.8625 0.000 0.996 0.000 0.004 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.7303     0.0628 0.356 0.444 0.000 0.136 0.064
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4321     0.2026 0.396 0.000 0.000 0.004 0.600
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.7800     0.3330 0.256 0.000 0.064 0.372 0.308
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3876     0.6103 0.684 0.000 0.000 0.000 0.316
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.4651     0.5997 0.608 0.000 0.020 0.000 0.372
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.2758     0.6531 0.888 0.000 0.024 0.012 0.076
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.4149     0.6678 0.784 0.000 0.088 0.000 0.128
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.4100     0.6723 0.792 0.000 0.052 0.008 0.148
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     5  0.2929     0.6905 0.152 0.000 0.008 0.000 0.840
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.2424     0.6866 0.132 0.000 0.000 0.000 0.868
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.3661     0.6189 0.000 0.724 0.000 0.276 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2464     0.7387 0.096 0.000 0.888 0.016 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4835     0.5660 0.724 0.000 0.000 0.156 0.120
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2424     0.7345 0.000 0.000 0.868 0.000 0.132
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.5685     0.2340 0.084 0.000 0.520 0.000 0.396
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.2471     0.6332 0.136 0.000 0.000 0.000 0.864
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.4380    -0.2471 0.008 0.376 0.000 0.616 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.6695     0.2195 0.368 0.000 0.000 0.392 0.240
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.5503     0.4111 0.024 0.484 0.000 0.468 0.024
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2046     0.6770 0.916 0.000 0.016 0.000 0.068
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3391     0.6791 0.800 0.000 0.012 0.000 0.188
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.4084     0.4294 0.328 0.000 0.668 0.000 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1270     0.7836 0.000 0.000 0.948 0.000 0.052
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.6224     0.4846 0.152 0.000 0.000 0.496 0.352
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.6936     0.1110 0.368 0.464 0.008 0.020 0.140
#> A22892DE-0AF4-4B63-9513-1D6825059040     5  0.3074     0.6356 0.196 0.000 0.000 0.000 0.804
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.2280     0.6830 0.120 0.000 0.000 0.000 0.880
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.5345    -0.3397 0.540 0.000 0.000 0.404 0.056
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.5882     0.4787 0.588 0.000 0.148 0.000 0.264
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3949     0.5974 0.668 0.000 0.000 0.000 0.332
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.5379     0.5906 0.648 0.000 0.000 0.108 0.244
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4443     0.1843 0.004 0.000 0.524 0.000 0.472
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.6024     0.6474 0.216 0.104 0.000 0.644 0.036
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.3395     0.6119 0.236 0.000 0.000 0.000 0.764
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.4891     0.1128 0.016 0.000 0.500 0.004 0.480
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     5  0.4650    -0.3128 0.468 0.000 0.000 0.012 0.520
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.6211     0.3553 0.544 0.000 0.000 0.264 0.192
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.2130     0.7014 0.080 0.000 0.012 0.000 0.908
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.4019     0.6728 0.152 0.000 0.052 0.004 0.792
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.1444     0.7866 0.040 0.000 0.948 0.000 0.012
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.0703     0.5934 0.024 0.000 0.000 0.976 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.5562     0.5237 0.604 0.000 0.100 0.000 0.296
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.5608     0.4769 0.116 0.000 0.224 0.008 0.652
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.3164     0.6923 0.104 0.000 0.044 0.000 0.852
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.3883     0.5524 0.244 0.000 0.004 0.008 0.744
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     5  0.2798     0.6868 0.140 0.000 0.000 0.008 0.852
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     4  0.5986     0.5987 0.336 0.000 0.004 0.548 0.112
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4716     0.4946 0.656 0.000 0.308 0.000 0.036
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     1  0.4774    -0.3090 0.556 0.000 0.000 0.424 0.020
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.3480     0.6705 0.000 0.752 0.000 0.248 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0510     0.8009 0.000 0.000 0.984 0.000 0.016
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.5915     0.3556 0.552 0.000 0.124 0.000 0.324
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.3506     0.7160 0.064 0.000 0.832 0.000 0.104
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.4798     0.6067 0.272 0.000 0.008 0.684 0.036
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
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#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4585     0.6621 0.728 0.000 0.052 0.004 0.216
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.2020     0.7441 0.100 0.000 0.900 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.2358     0.7076 0.104 0.000 0.008 0.000 0.888
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.0963     0.5974 0.036 0.000 0.000 0.964 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.3460     0.7703 0.044 0.828 0.000 0.128 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.2424     0.6937 0.132 0.000 0.000 0.000 0.868
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.6276     0.6221 0.332 0.056 0.004 0.564 0.044
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     1  0.4492     0.5573 0.776 0.000 0.144 0.020 0.060
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.1403     0.7855 0.024 0.000 0.952 0.000 0.024
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.5492     0.1461 0.064 0.000 0.504 0.000 0.432
#> CE539000-92D7-4622-9C8D-BC6E01310681     3  0.8565    -0.3532 0.268 0.000 0.280 0.252 0.200
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0324     0.8025 0.004 0.000 0.992 0.000 0.004
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.5829     0.5288 0.572 0.000 0.088 0.008 0.332
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.4449     0.1540 0.004 0.000 0.512 0.000 0.484
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     1  0.5139     0.2474 0.624 0.000 0.000 0.316 0.060
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.3863     0.6219 0.176 0.000 0.020 0.012 0.792
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.7663     0.6209 0.292 0.144 0.012 0.480 0.072
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.3184     0.6973 0.100 0.000 0.048 0.000 0.852
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0000     0.7015 0.000 0.000 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.1851     0.6812 0.912 0.000 0.000 0.000 0.088
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1638     0.7710 0.064 0.000 0.932 0.000 0.004
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4581     0.3618 0.624 0.000 0.012 0.004 0.360
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0404     0.8591 0.000 0.988 0.000 0.012 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3992     0.5767 0.012 0.000 0.720 0.000 0.268
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.2563     0.6910 0.120 0.000 0.008 0.000 0.872
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.4583     0.4645 0.032 0.000 0.296 0.000 0.672
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.3478     0.6875 0.828 0.000 0.004 0.032 0.136
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3750     0.6651 0.756 0.000 0.000 0.012 0.232
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.4719     0.5195 0.056 0.000 0.248 0.000 0.696
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.6462     0.5056 0.548 0.000 0.176 0.012 0.264
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.3841     0.6774 0.780 0.000 0.000 0.032 0.188
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3958     0.6779 0.776 0.000 0.040 0.000 0.184
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.6225     0.5062 0.256 0.000 0.200 0.000 0.544
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     5  0.4069     0.6693 0.076 0.000 0.136 0.000 0.788
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2966     0.6813 0.816 0.000 0.000 0.000 0.184
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.4970     0.6456 0.340 0.000 0.008 0.624 0.028
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.1798     0.7081 0.064 0.000 0.004 0.004 0.928
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5887     0.5471 0.596 0.000 0.164 0.000 0.240
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.3661     0.6335 0.724 0.000 0.000 0.000 0.276
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0609     0.8564 0.000 0.980 0.000 0.020 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3878     0.4658 0.828 0.000 0.044 0.100 0.028
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.5347     0.5329 0.108 0.000 0.672 0.004 0.216
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.2908     0.5796 0.884 0.000 0.016 0.032 0.068
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.6684     0.4465 0.372 0.000 0.000 0.392 0.236
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.4696     0.6066 0.084 0.000 0.172 0.004 0.740
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.7410     0.5693 0.168 0.000 0.108 0.532 0.192
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3999     0.5889 0.656 0.000 0.000 0.000 0.344
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.3416     0.7039 0.088 0.000 0.072 0.000 0.840
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2280     0.6322 0.120 0.000 0.000 0.880 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3508     0.6441 0.748 0.000 0.000 0.000 0.252
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.3086     0.6540 0.180 0.000 0.000 0.816 0.004
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6881    -0.2822 0.448 0.000 0.048 0.400 0.104
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.5006     0.5718 0.136 0.000 0.156 0.000 0.708
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.3807     0.5600 0.828 0.000 0.088 0.012 0.072
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2813     0.6771 0.876 0.000 0.000 0.040 0.084
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2286     0.6833 0.888 0.000 0.004 0.000 0.108
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.1792     0.7045 0.084 0.000 0.000 0.000 0.916
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1670     0.6553 0.936 0.000 0.000 0.012 0.052
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8054 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4227     0.3092 0.000 0.000 0.580 0.000 0.420
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2349     0.6722 0.900 0.000 0.012 0.004 0.084
#> 835AAE7F-F873-4D11-8845-232D261A38DF     5  0.6624     0.2562 0.264 0.000 0.280 0.000 0.456
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3852     0.6650 0.760 0.000 0.000 0.020 0.220
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.1915     0.7087 0.040 0.000 0.032 0.000 0.928
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8639 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2127     0.7353 0.108 0.000 0.892 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1732     0.6808 0.920 0.000 0.000 0.000 0.080
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.1197     0.7048 0.048 0.000 0.000 0.000 0.952
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4206     0.6409 0.696 0.000 0.000 0.016 0.288

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4844    0.57791 0.328 0.000 0.004 0.616 0.040 0.012
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5019   -0.02837 0.468 0.000 0.476 0.012 0.044 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2300    0.72256 0.856 0.000 0.000 0.000 0.144 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3515    0.55025 0.676 0.000 0.000 0.000 0.324 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.2179    0.71161 0.036 0.000 0.000 0.064 0.900 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.3604    0.60636 0.788 0.000 0.168 0.036 0.008 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.3985    0.63751 0.016 0.000 0.136 0.068 0.780 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1668    0.72156 0.928 0.000 0.000 0.060 0.008 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.5682    0.53209 0.224 0.000 0.000 0.528 0.248 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4454    0.52755 0.684 0.000 0.000 0.252 0.060 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.3141    0.34619 0.012 0.020 0.000 0.828 0.000 0.140
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.1353    0.71493 0.952 0.000 0.012 0.024 0.012 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0260    0.79115 0.000 0.000 0.992 0.008 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0146    0.79133 0.000 0.000 0.996 0.000 0.004 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3231    0.72397 0.784 0.000 0.000 0.016 0.200 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1572    0.71920 0.028 0.000 0.000 0.036 0.936 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0146    0.79191 0.004 0.000 0.996 0.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3684    0.36314 0.628 0.000 0.000 0.000 0.372 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.3834    0.69423 0.232 0.000 0.000 0.036 0.732 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3424    0.71043 0.772 0.000 0.000 0.024 0.204 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.4664    0.30357 0.052 0.000 0.364 0.000 0.584 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2631    0.67844 0.152 0.000 0.840 0.008 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5922    0.24095 0.192 0.000 0.504 0.008 0.296 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0291    0.83277 0.000 0.992 0.000 0.004 0.000 0.004
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.6965    0.11715 0.164 0.424 0.000 0.348 0.032 0.032
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4815    0.23768 0.384 0.000 0.000 0.060 0.556 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.6101    0.55646 0.148 0.000 0.036 0.536 0.280 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3050    0.70429 0.764 0.000 0.000 0.000 0.236 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.4113    0.69126 0.712 0.000 0.000 0.040 0.244 0.004
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.2401    0.69454 0.892 0.000 0.016 0.076 0.016 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2070    0.72382 0.908 0.000 0.048 0.000 0.044 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.3346    0.68723 0.840 0.000 0.024 0.056 0.080 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     5  0.2558    0.73901 0.156 0.000 0.004 0.000 0.840 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.2915    0.73582 0.164 0.000 0.004 0.004 0.824 0.004
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.5071    0.40966 0.000 0.632 0.000 0.212 0.000 0.156
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0260    0.79115 0.000 0.000 0.992 0.008 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2355    0.71324 0.112 0.000 0.876 0.008 0.000 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4706    0.52183 0.652 0.000 0.000 0.284 0.052 0.012
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2913    0.71578 0.000 0.000 0.848 0.032 0.116 0.004
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.5433    0.16643 0.076 0.000 0.504 0.016 0.404 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.2999    0.68190 0.112 0.000 0.000 0.048 0.840 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     6  0.2854    0.73423 0.000 0.000 0.000 0.208 0.000 0.792
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.5715    0.51684 0.284 0.000 0.000 0.532 0.180 0.004
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     6  0.5820    0.11423 0.000 0.400 0.000 0.184 0.000 0.416
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0653    0.78762 0.000 0.000 0.980 0.012 0.004 0.004
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0858    0.71032 0.968 0.000 0.000 0.028 0.004 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1267    0.73115 0.940 0.000 0.000 0.000 0.060 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.3867    0.42533 0.328 0.000 0.660 0.012 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1204    0.76834 0.000 0.000 0.944 0.000 0.056 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.5953    0.53488 0.100 0.000 0.000 0.536 0.320 0.044
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.6320    0.16263 0.356 0.476 0.000 0.104 0.064 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     5  0.3653    0.61762 0.300 0.000 0.000 0.008 0.692 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.3558    0.68513 0.212 0.000 0.000 0.028 0.760 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.4504    0.58656 0.296 0.000 0.000 0.652 0.048 0.004
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.5383    0.54464 0.600 0.000 0.104 0.016 0.280 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3221    0.67773 0.736 0.000 0.000 0.000 0.264 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0260    0.79115 0.000 0.000 0.992 0.008 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.5150    0.58174 0.624 0.000 0.000 0.188 0.188 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4705    0.12697 0.016 0.000 0.504 0.012 0.464 0.004
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0260    0.79115 0.000 0.000 0.992 0.008 0.000 0.000
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#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.4526    0.66636 0.184 0.000 0.116 0.000 0.700 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.6091    0.14574 0.388 0.000 0.000 0.292 0.320 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.3381    0.53822 0.772 0.000 0.008 0.212 0.008 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.3329    0.63223 0.004 0.000 0.756 0.004 0.236 0.000
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#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.3971    0.60493 0.748 0.000 0.000 0.068 0.184 0.000
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#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.1649    0.72249 0.036 0.000 0.000 0.032 0.932 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     5  0.4842    0.46467 0.324 0.000 0.000 0.076 0.600 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.3302    0.68659 0.856 0.008 0.052 0.040 0.044 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.5059    0.42891 0.636 0.000 0.012 0.088 0.264 0.000
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#> 58FF391C-1D83-426C-8F92-C15F78F56C95     5  0.2473    0.73605 0.136 0.000 0.000 0.008 0.856 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     4  0.4903    0.25104 0.060 0.000 0.000 0.476 0.464 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.5071    0.32756 0.032 0.000 0.036 0.720 0.164 0.048
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#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.3972    0.43816 0.100 0.008 0.000 0.796 0.012 0.084
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     1  0.5352    0.56497 0.680 0.000 0.148 0.112 0.060 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.1334    0.77300 0.032 0.000 0.948 0.000 0.020 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.5029    0.06893 0.072 0.000 0.484 0.000 0.444 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     4  0.7254    0.32869 0.308 0.000 0.232 0.360 0.100 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0622    0.78788 0.000 0.000 0.980 0.012 0.008 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.5805    0.55348 0.572 0.000 0.052 0.068 0.304 0.004
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.4664    0.11988 0.000 0.000 0.488 0.032 0.476 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     4  0.5147    0.31695 0.332 0.000 0.000 0.592 0.028 0.048
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#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.4789    0.49971 0.144 0.028 0.004 0.748 0.056 0.020
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.2956    0.74406 0.120 0.000 0.040 0.000 0.840 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.1555    0.70541 0.004 0.000 0.000 0.060 0.932 0.004
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.1151    0.71334 0.956 0.000 0.000 0.032 0.012 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1829    0.75250 0.064 0.000 0.920 0.012 0.004 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4989    0.32212 0.568 0.000 0.004 0.068 0.360 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0458    0.82773 0.000 0.984 0.000 0.016 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3876    0.54672 0.024 0.000 0.700 0.000 0.276 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.2320    0.73580 0.132 0.000 0.000 0.004 0.864 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3641    0.61651 0.028 0.000 0.224 0.000 0.748 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.2984    0.71442 0.848 0.000 0.000 0.104 0.044 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2697    0.72831 0.864 0.000 0.000 0.044 0.092 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.4739    0.58778 0.060 0.000 0.204 0.024 0.708 0.004
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5342    0.61849 0.684 0.000 0.144 0.044 0.124 0.004
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.3174    0.71658 0.836 0.000 0.000 0.104 0.056 0.004
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3667    0.69842 0.788 0.000 0.036 0.012 0.164 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.5801    0.53057 0.296 0.000 0.188 0.004 0.512 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     5  0.3468    0.73033 0.088 0.000 0.092 0.004 0.816 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1141    0.72763 0.948 0.000 0.000 0.000 0.052 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.4503    0.56101 0.144 0.000 0.004 0.744 0.016 0.092
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.2311    0.74552 0.104 0.000 0.000 0.016 0.880 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4811    0.63799 0.696 0.000 0.148 0.004 0.148 0.004
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.3630    0.72194 0.780 0.000 0.000 0.040 0.176 0.004
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0547    0.82515 0.000 0.980 0.000 0.000 0.000 0.020
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.4242    0.49188 0.728 0.000 0.020 0.216 0.036 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.5227    0.50282 0.112 0.000 0.664 0.028 0.196 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4103    0.60901 0.776 0.000 0.012 0.132 0.076 0.004
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.5303    0.62214 0.232 0.000 0.000 0.596 0.172 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.3815    0.66808 0.036 0.000 0.144 0.028 0.792 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.7061    0.57083 0.128 0.000 0.056 0.560 0.164 0.092
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3917    0.65817 0.692 0.000 0.000 0.024 0.284 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.3485    0.74603 0.096 0.000 0.052 0.024 0.828 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2703    0.32973 0.004 0.000 0.000 0.824 0.000 0.172
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2260    0.72747 0.860 0.000 0.000 0.000 0.140 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     6  0.3727    0.61243 0.128 0.000 0.000 0.088 0.000 0.784
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.5276    0.54128 0.316 0.000 0.012 0.592 0.076 0.004
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.4316    0.64961 0.140 0.000 0.072 0.028 0.760 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.4864    0.59241 0.732 0.000 0.076 0.080 0.112 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2798    0.70740 0.852 0.000 0.000 0.112 0.036 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.1074    0.71187 0.960 0.000 0.000 0.028 0.012 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.1610    0.74274 0.084 0.000 0.000 0.000 0.916 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2212    0.68481 0.880 0.000 0.000 0.112 0.008 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.79241 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4262    0.25827 0.004 0.000 0.560 0.012 0.424 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.1442    0.70554 0.944 0.000 0.004 0.040 0.012 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     5  0.6433    0.28876 0.264 0.000 0.228 0.024 0.480 0.004
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3002    0.72457 0.848 0.000 0.000 0.048 0.100 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.2501    0.74600 0.072 0.000 0.028 0.012 0.888 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.83660 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2243    0.71517 0.112 0.000 0.880 0.004 0.004 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1088    0.71836 0.960 0.000 0.000 0.024 0.016 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.2651    0.73433 0.112 0.000 0.000 0.028 0.860 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3344    0.71410 0.804 0.000 0.000 0.044 0.152 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-pam-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "mclust"]
# you can also extract it by
# res = res_list["CV:mclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.979           0.949       0.979         0.4212 0.583   0.583
#> 3 3 0.590           0.569       0.815         0.4974 0.800   0.661
#> 4 4 0.465           0.518       0.718         0.0905 0.748   0.465
#> 5 5 0.500           0.338       0.634         0.0888 0.746   0.372
#> 6 6 0.558           0.413       0.692         0.0584 0.804   0.390

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.2603   0.937830 0.044 0.956
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000   0.980574 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0376   0.978073 0.996 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000   0.980574 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000   0.980574 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000   0.980574 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.9129   0.508995 0.672 0.328
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000   0.972747 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000   0.980574 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000   0.980574 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000   0.980574 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3584   0.913785 0.932 0.068
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0376   0.978073 0.996 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000   0.972747 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000   0.980574 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0376   0.978073 0.996 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000   0.980574 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000   0.980574 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000   0.980574 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000   0.980574 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000   0.972747 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000   0.980574 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000   0.980574 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000   0.980574 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0376   0.978073 0.996 0.004
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000   0.980574 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0376   0.978073 0.996 0.004
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000   0.980574 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000   0.972747 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000   0.972747 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000   0.980574 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000   0.980574 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000   0.980574 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000   0.980574 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000   0.972747 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0376   0.978073 0.996 0.004
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000   0.980574 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000   0.972747 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000   0.980574 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000   0.980574 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000   0.972747 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0376   0.978073 0.996 0.004
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.9732   0.306796 0.596 0.404
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.7674   0.702635 0.776 0.224
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000   0.980574 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000   0.980574 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000   0.980574 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000   0.972747 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000   0.980574 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000   0.972747 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000   0.980574 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000   0.972747 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0376   0.978073 0.996 0.004
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000   0.980574 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000   0.980574 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0376   0.978073 0.996 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0376   0.978073 0.996 0.004
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.9661   0.338498 0.608 0.392
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000   0.972747 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000   0.980574 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000   0.980574 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.2603   0.937830 0.044 0.956
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000   0.980574 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000   0.980574 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000   0.972747 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0376   0.978073 0.996 0.004
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000   0.980574 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000   0.980574 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0376   0.978073 0.996 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000   0.972747 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000   0.980574 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000   0.980574 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000   0.980574 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000   0.980574 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.9998  -0.000259 0.508 0.492
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000   0.980574 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000   0.980574 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000   0.972747 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0376   0.978073 0.996 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000   0.972747 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000   0.980574 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.3584   0.916089 0.932 0.068
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000   0.980574 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000   0.980574 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000   0.980574 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5946   0.822133 0.856 0.144
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000   0.980574 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000   0.972747 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000   0.972747 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0376   0.978073 0.996 0.004
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000   0.980574 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000   0.980574 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000   0.972747 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000   0.980574 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000   0.980574 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000   0.980574 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0376   0.978073 0.996 0.004
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     2  0.9881   0.243178 0.436 0.564
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000   0.980574 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0376   0.978073 0.996 0.004
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000   0.980574 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000   0.972747 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000   0.972747 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000   0.980574 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000   0.980574 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000   0.972747 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.2603   0.937830 0.044 0.956
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0376   0.978073 0.996 0.004
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000   0.980574 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000   0.972747 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000   0.972747 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000   0.980574 1.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0376   0.978073 0.996 0.004
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0376   0.978073 0.996 0.004
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000   0.980574 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000   0.980574 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000   0.980574 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000   0.980574 1.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000   0.980574 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000   0.980574 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000   0.980574 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000   0.980574 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000   0.980574 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000   0.980574 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.0000   0.972747 0.000 1.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.0000   0.972747 0.000 1.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.5737   0.836025 0.136 0.864
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000   0.980574 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.0000   0.980574 1.000 0.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0000   0.980574 1.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     2  0.9460   0.441405 0.364 0.636
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000   0.980574 1.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000   0.972747 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.0000   0.980574 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000   0.972747 0.000 1.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000   0.972747 0.000 1.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000   0.980574 1.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000   0.972747 0.000 1.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000   0.972747 0.000 1.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000   0.980574 1.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.0000   0.980574 1.000 0.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000   0.972747 0.000 1.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.0000   0.980574 1.000 0.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0000   0.972747 0.000 1.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000   0.972747 0.000 1.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.0000   0.980574 1.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     2  0.9922   0.207593 0.448 0.552
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000   0.972747 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.0000   0.980574 1.000 0.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0000   0.980574 1.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000   0.980574 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0000   0.980574 1.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000   0.972747 0.000 1.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0000   0.980574 1.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     2  0.2603   0.937830 0.044 0.956
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.0000   0.972747 0.000 1.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000   0.980574 1.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.0000   0.980574 1.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.0672   0.966763 0.008 0.992
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000   0.972747 0.000 1.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.0000   0.980574 1.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1  0.0376   0.978073 0.996 0.004
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000   0.972747 0.000 1.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000   0.980574 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000   0.972747 0.000 1.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000   0.972747 0.000 1.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.6148   0.813418 0.848 0.152
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000   0.972747 0.000 1.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000   0.980574 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000   0.972747 0.000 1.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.0000   0.980574 1.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000   0.980574 1.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     2  0.2603   0.937830 0.044 0.956
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#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.0000   0.980574 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0000   0.980574 1.000 0.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0000   0.980574 1.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000   0.980574 1.000 0.000
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#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000   0.972747 0.000 1.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000   0.972747 0.000 1.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.6887   0.766840 0.816 0.184
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000   0.972747 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000   0.980574 1.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000   0.980574 1.000 0.000
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#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000   0.980574 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0000   0.980574 1.000 0.000
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#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000   0.972747 0.000 1.000
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#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.1414   0.963074 0.980 0.020
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000   0.980574 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000   0.980574 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000   0.980574 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000   0.980574 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000   0.972747 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.0000   0.980574 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000   0.980574 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.0000   0.980574 1.000 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000   0.980574 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.9427   0.436986 0.640 0.360
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000   0.980574 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000   0.980574 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000   0.980574 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000   0.980574 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000   0.980574 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.9209   0.485357 0.664 0.336
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000   0.980574 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000   0.972747 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000   0.972747 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0000   0.980574 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000   0.980574 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000   0.980574 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000   0.980574 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000   0.980574 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000   0.972747 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.0376   0.978073 0.996 0.004
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.0376   0.978073 0.996 0.004
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000   0.980574 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0938   0.970570 0.988 0.012
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000   0.972747 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0376   0.978073 0.996 0.004
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000   0.972747 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000   0.972747 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000   0.972747 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000   0.980574 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     2  0.8955   0.552298 0.312 0.688
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000   0.980574 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000   0.980574 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000   0.980574 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0376   0.978073 0.996 0.004
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0376   0.978073 0.996 0.004
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000   0.980574 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000   0.980574 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000   0.972747 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000   0.980574 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0376   0.978073 0.996 0.004
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000   0.980574 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000   0.972747 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000   0.972747 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000   0.980574 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000   0.972747 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000   0.972747 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000   0.980574 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000   0.980574 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000   0.972747 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000   0.972747 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.0376   0.978073 0.996 0.004
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000   0.980574 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000   0.980574 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000   0.972747 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000   0.980574 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000   0.972747 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000   0.980574 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000   0.980574 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000   0.980574 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000   0.980574 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000   0.980574 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000   0.972747 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000   0.980574 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000   0.980574 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000   0.980574 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000   0.980574 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.2603   0.937830 0.044 0.956
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000   0.980574 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000   0.980574 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.7299   0.738042 0.796 0.204
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.2603   0.937830 0.044 0.956
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000   0.980574 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000   0.980574 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000   0.980574 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000   0.972747 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000   0.980574 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.2603   0.937830 0.044 0.956
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000   0.980574 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000   0.980574 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000   0.980574 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000   0.972747 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.9608   0.368420 0.616 0.384
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.0376   0.978073 0.996 0.004
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.4815   0.872345 0.896 0.104
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000   0.972747 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000   0.980574 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.9087   0.531641 0.324 0.676
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000   0.980574 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000   0.980574 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000   0.972747 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000   0.980574 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000   0.972747 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000   0.980574 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000   0.980574 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0376   0.978073 0.996 0.004
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000   0.972747 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000   0.980574 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000   0.980574 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000   0.980574 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0376   0.978073 0.996 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.2423   0.944301 0.960 0.040
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000   0.980574 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000   0.980574 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000   0.980574 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000   0.980574 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000   0.972747 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000   0.972747 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0376   0.978073 0.996 0.004
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000   0.980574 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000   0.980574 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000   0.980574 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000     0.9645 0.000 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.6307     0.1124 0.488 0.000 0.512
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5263     0.6232 0.088 0.084 0.828
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1860     0.5938 0.948 0.000 0.052
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0237     0.6029 0.996 0.000 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1163     0.5943 0.972 0.000 0.028
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.1919     0.6320 0.024 0.020 0.956
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0892     0.9639 0.000 0.980 0.020
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6672     0.2250 0.520 0.008 0.472
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.6295     0.2354 0.528 0.000 0.472
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.6079     0.3386 0.612 0.000 0.388
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6274     0.2650 0.544 0.000 0.456
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.6126     0.2396 0.400 0.000 0.600
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9645 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5595     0.4837 0.228 0.016 0.756
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2066     0.6417 0.060 0.000 0.940
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5948     0.2010 0.640 0.000 0.360
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.6225     0.2977 0.568 0.000 0.432
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1031     0.5958 0.976 0.000 0.024
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.5650     0.3087 0.688 0.000 0.312
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0892     0.9639 0.000 0.980 0.020
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#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.3267     0.5329 0.884 0.000 0.116
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     3  0.6309    -0.2018 0.496 0.000 0.504
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0892     0.9639 0.000 0.980 0.020
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.3551     0.5678 0.868 0.000 0.132
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.5138     0.3936 0.748 0.000 0.252
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0892     0.9639 0.000 0.980 0.020
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0892     0.9639 0.000 0.980 0.020
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000     0.9645 0.000 1.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     3  0.8559     0.2680 0.304 0.124 0.572
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0892     0.5986 0.980 0.000 0.020
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0892     0.5978 0.980 0.000 0.020
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.4931     0.4449 0.768 0.000 0.232
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.1031     0.6007 0.976 0.000 0.024
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9645 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.5178     0.3935 0.744 0.000 0.256
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.6672     0.2250 0.520 0.008 0.472
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.6509     0.2305 0.524 0.004 0.472
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.5178     0.4202 0.744 0.000 0.256
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.6460     0.2502 0.004 0.440 0.556
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.5968     0.1918 0.636 0.000 0.364
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0237     0.6028 0.996 0.000 0.004
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.6204     0.3032 0.576 0.000 0.424
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0237     0.6029 0.996 0.000 0.004
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.6225     0.2977 0.568 0.000 0.432
#> 9EEECA0E-530D-4724-B016-A716F0782148     3  0.9447     0.3444 0.188 0.348 0.464
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.5254     0.3793 0.736 0.000 0.264
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0892     0.9639 0.000 0.980 0.020
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000     0.9645 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.6299     0.2334 0.524 0.000 0.476
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.6180     0.3070 0.584 0.000 0.416
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.4504     0.5258 0.804 0.000 0.196
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0424     0.6020 0.992 0.000 0.008
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.5431     0.4074 0.716 0.000 0.284
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0892     0.9639 0.000 0.980 0.020
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.7007     0.5078 0.176 0.100 0.724
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.1964     0.6428 0.056 0.000 0.944
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.6032 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     3  0.8339    -0.0618 0.448 0.080 0.472
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9645 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.6225     0.1975 0.432 0.000 0.568
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0892     0.9639 0.000 0.980 0.020
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0892     0.9639 0.000 0.980 0.020
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9645 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5591     0.3102 0.696 0.000 0.304
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.2846     0.6142 0.020 0.056 0.924
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.5216     0.4484 0.740 0.000 0.260
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0592     0.6009 0.988 0.000 0.012
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.6032 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1964     0.6428 0.056 0.000 0.944
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.1964     0.6428 0.056 0.000 0.944
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     3  0.5896     0.3018 0.292 0.008 0.700
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0237     0.6028 0.996 0.000 0.004
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0892     0.9639 0.000 0.980 0.020
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.5760     0.2883 0.328 0.000 0.672
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1964     0.6428 0.056 0.000 0.944
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5058     0.4049 0.756 0.000 0.244
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9645 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9645 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0237     0.6029 0.996 0.000 0.004
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9645 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0892     0.9639 0.000 0.980 0.020
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.5327     0.3655 0.728 0.000 0.272
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4796     0.4346 0.780 0.000 0.220
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0892     0.9639 0.000 0.980 0.020
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0892     0.9639 0.000 0.980 0.020
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.1964     0.6428 0.056 0.000 0.944
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.6032 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.3816     0.5091 0.852 0.000 0.148
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9645 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.6553     0.2960 0.580 0.008 0.412
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9645 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.6032 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0424     0.6021 0.992 0.000 0.008
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6140     0.3112 0.596 0.000 0.404
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.5327     0.3640 0.728 0.000 0.272
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.6215     0.3008 0.572 0.000 0.428
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0892     0.9639 0.000 0.980 0.020
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.3879     0.5015 0.848 0.000 0.152
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0237     0.6029 0.996 0.000 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.5785     0.3829 0.668 0.000 0.332
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5216     0.3827 0.740 0.000 0.260
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.2625     0.8830 0.000 0.916 0.084
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2878     0.5711 0.904 0.000 0.096
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5397     0.3895 0.720 0.000 0.280
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.7276     0.5509 0.104 0.192 0.704
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.1411     0.9392 0.000 0.964 0.036
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     3  0.5733     0.2712 0.324 0.000 0.676
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5363     0.3874 0.724 0.000 0.276
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4796     0.4346 0.780 0.000 0.220
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0892     0.9639 0.000 0.980 0.020
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.6192     0.3076 0.580 0.000 0.420
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0237     0.9628 0.000 0.996 0.004
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0237     0.6028 0.996 0.000 0.004
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4796     0.4346 0.780 0.000 0.220
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.6032 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0892     0.9639 0.000 0.980 0.020
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.9319     0.3508 0.168 0.368 0.464
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2200     0.6430 0.056 0.004 0.940
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.9613     0.2632 0.284 0.244 0.472
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.1031     0.9498 0.000 0.976 0.024
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6045     0.2835 0.620 0.000 0.380
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.5598     0.6859 0.148 0.800 0.052
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.6192     0.3076 0.580 0.000 0.420
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.6032 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9645 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.6154     0.3123 0.592 0.000 0.408
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9645 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6260     0.2736 0.552 0.000 0.448
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.5098     0.3992 0.752 0.000 0.248
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.8010     0.3611 0.068 0.384 0.548
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0747     0.9558 0.000 0.984 0.016
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.6286     0.2482 0.536 0.000 0.464
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.6032 1.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.7063    -0.1323 0.464 0.020 0.516
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1964     0.6428 0.056 0.000 0.944
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5036     0.6138 0.048 0.120 0.832
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6308     0.1730 0.508 0.000 0.492
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5431     0.3834 0.716 0.000 0.284
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.6204     0.3032 0.576 0.000 0.424
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.6032 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0892     0.9639 0.000 0.980 0.020
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0892     0.9639 0.000 0.980 0.020
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1964     0.6428 0.056 0.000 0.944
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.6235     0.2789 0.564 0.000 0.436
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0424     0.6020 0.992 0.000 0.008
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.6267     0.2751 0.548 0.000 0.452

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0921    0.77231 0.000 0.972 0.028 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.5764    0.40206 0.644 0.000 0.304 0.052
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.6272    0.33751 0.276 0.048 0.652 0.024
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5126   -0.09294 0.552 0.000 0.444 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2714    0.64859 0.884 0.000 0.112 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.3052    0.62985 0.860 0.000 0.136 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5266    0.43610 0.020 0.012 0.704 0.264
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     4  0.4730    0.82173 0.000 0.364 0.000 0.636
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.7035    0.33214 0.384 0.108 0.504 0.004
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.4677    0.52758 0.316 0.000 0.680 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.4761    0.31315 0.664 0.000 0.332 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     3  0.5888    0.53024 0.308 0.048 0.640 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.5528    0.42098 0.064 0.000 0.700 0.236
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0188    0.78621 0.000 0.996 0.000 0.004
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.4800    0.29580 0.340 0.000 0.656 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.7536    0.13130 0.264 0.000 0.492 0.244
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.3718    0.60405 0.820 0.000 0.168 0.012
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     3  0.4679    0.50485 0.352 0.000 0.648 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.3105    0.62202 0.856 0.000 0.140 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3791    0.60630 0.796 0.000 0.200 0.004
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     4  0.4134    0.90943 0.000 0.260 0.000 0.740
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1661    0.68659 0.944 0.000 0.052 0.004
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4999   -0.23445 0.508 0.000 0.492 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     3  0.4679    0.50485 0.352 0.000 0.648 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.7748    0.08778 0.424 0.000 0.332 0.244
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2125    0.69324 0.920 0.000 0.076 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4964    0.43871 0.032 0.000 0.724 0.244
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.2675    0.65836 0.892 0.000 0.100 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     4  0.4134    0.90943 0.000 0.260 0.000 0.740
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.4994   -0.39816 0.000 0.520 0.000 0.480
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.6182    0.36718 0.616 0.076 0.308 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     3  0.5852    0.51591 0.332 0.040 0.624 0.004
#> 904EDF2E-411E-43BD-901D-46129AFA283A     3  0.4981    0.24064 0.464 0.000 0.536 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1398    0.69175 0.956 0.000 0.040 0.004
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     4  0.4722    0.86974 0.000 0.300 0.008 0.692
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#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.2799    0.65334 0.884 0.000 0.108 0.008
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.3400    0.58852 0.000 0.820 0.000 0.180
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     4  0.4277    0.90276 0.000 0.280 0.000 0.720
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000    0.78755 0.000 1.000 0.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     3  0.5777    0.52467 0.072 0.228 0.696 0.004
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.1557    0.69331 0.944 0.000 0.056 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.2593    0.65601 0.892 0.000 0.104 0.004
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.4991    0.13165 0.608 0.000 0.388 0.004
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.4920    0.11398 0.628 0.000 0.368 0.004
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.2081    0.71687 0.000 0.916 0.000 0.084
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.2988    0.65586 0.876 0.000 0.112 0.012
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     3  0.5651    0.52947 0.308 0.036 0.652 0.004
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     3  0.6900    0.27728 0.416 0.092 0.488 0.004
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.3105    0.66846 0.856 0.004 0.140 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.5135    0.48432 0.012 0.684 0.296 0.008
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.4535    0.52212 0.744 0.000 0.240 0.016
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.2401    0.66537 0.904 0.000 0.092 0.004
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     3  0.4713    0.50000 0.360 0.000 0.640 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.1305    0.69027 0.960 0.000 0.036 0.004
#> 331A9160-D730-45DD-A985-C6CAC03035ED     3  0.4679    0.50485 0.352 0.000 0.648 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     3  0.6943    0.51034 0.140 0.268 0.588 0.004
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.3583    0.59378 0.816 0.000 0.180 0.004
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     4  0.4134    0.90943 0.000 0.260 0.000 0.740
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000    0.78755 0.000 1.000 0.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.4406    0.53154 0.300 0.000 0.700 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.4776    0.48778 0.376 0.000 0.624 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.2921    0.67428 0.860 0.000 0.140 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.2401    0.66999 0.904 0.000 0.092 0.004
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.3626    0.63709 0.812 0.004 0.184 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     4  0.4746    0.86580 0.000 0.304 0.008 0.688
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.5702    0.51745 0.076 0.196 0.720 0.008
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.5106    0.43950 0.040 0.000 0.720 0.240
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.1743    0.68825 0.940 0.000 0.056 0.004
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     3  0.6697    0.51609 0.144 0.224 0.628 0.004
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0188    0.78621 0.000 0.996 0.000 0.004
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.5660    0.33588 0.576 0.000 0.396 0.028
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     4  0.4250    0.90495 0.000 0.276 0.000 0.724
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     4  0.4134    0.90943 0.000 0.260 0.000 0.740
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.4977   -0.40300 0.000 0.540 0.000 0.460
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.4175    0.56861 0.784 0.000 0.200 0.016
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     4  0.5759    0.29044 0.028 0.020 0.276 0.676
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.4535    0.39207 0.704 0.000 0.292 0.004
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.1824    0.68901 0.936 0.000 0.060 0.004
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.1824    0.68109 0.936 0.000 0.060 0.004
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.4964    0.43871 0.032 0.000 0.724 0.244
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4964    0.43871 0.032 0.000 0.724 0.244
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     3  0.7710    0.27724 0.200 0.340 0.456 0.004
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.2466    0.66157 0.900 0.000 0.096 0.004
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     4  0.4193    0.90823 0.000 0.268 0.000 0.732
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.5126    0.22701 0.444 0.004 0.552 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.4964    0.43871 0.032 0.000 0.724 0.244
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.3300    0.64667 0.848 0.000 0.144 0.008
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.78755 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2216    0.70794 0.000 0.908 0.000 0.092
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1743    0.68539 0.940 0.000 0.056 0.004
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.1211    0.76109 0.000 0.960 0.000 0.040
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     4  0.4790    0.75907 0.000 0.380 0.000 0.620
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.4098    0.59107 0.784 0.000 0.204 0.012
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4422    0.52318 0.736 0.000 0.256 0.008
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.4992   -0.45054 0.000 0.524 0.000 0.476
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     4  0.4643    0.84427 0.000 0.344 0.000 0.656
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.6229    0.36844 0.116 0.000 0.656 0.228
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1902    0.68204 0.932 0.000 0.064 0.004
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.1978    0.67953 0.928 0.000 0.068 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.3975    0.42491 0.000 0.760 0.000 0.240
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.5874    0.25613 0.616 0.032 0.344 0.008
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.1867    0.72982 0.000 0.928 0.000 0.072
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.1398    0.68769 0.956 0.000 0.040 0.004
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0657    0.69118 0.984 0.000 0.012 0.004
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.4972   -0.16831 0.544 0.000 0.456 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.3479    0.62074 0.840 0.000 0.148 0.012
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     3  0.4697    0.50237 0.356 0.000 0.644 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.4992   -0.45032 0.000 0.524 0.000 0.476
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1398    0.68614 0.956 0.000 0.040 0.004
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1576    0.68601 0.948 0.000 0.048 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.4088    0.51615 0.764 0.000 0.232 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.4630    0.55039 0.732 0.000 0.252 0.016
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.5296    0.02694 0.000 0.492 0.500 0.008
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2647    0.67847 0.880 0.000 0.120 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5277    0.00306 0.532 0.000 0.460 0.008
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.7353    0.37776 0.252 0.180 0.560 0.008
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.3668    0.62094 0.000 0.808 0.188 0.004
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     3  0.5155    0.22779 0.468 0.000 0.528 0.004
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5288    0.00760 0.520 0.000 0.472 0.008
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2593    0.66984 0.892 0.000 0.104 0.004
#> 20EB9CC6-EABB-438A-9030-E766459996D1     4  0.4925    0.69932 0.000 0.428 0.000 0.572
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.4925    0.40794 0.428 0.000 0.572 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0921    0.77231 0.000 0.972 0.028 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2334    0.66686 0.908 0.000 0.088 0.004
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4741    0.33712 0.668 0.000 0.328 0.004
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2081    0.67165 0.916 0.000 0.084 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     4  0.4164    0.90899 0.000 0.264 0.000 0.736
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.7215    0.46202 0.140 0.328 0.528 0.004
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.5326    0.43762 0.040 0.008 0.724 0.228
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.6138    0.40896 0.048 0.332 0.612 0.008
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.2412    0.72771 0.000 0.908 0.084 0.008
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.3528    0.61162 0.808 0.000 0.192 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.4155    0.61609 0.100 0.828 0.072 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     3  0.4761    0.48744 0.372 0.000 0.628 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.2266    0.67010 0.912 0.000 0.084 0.004
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.78755 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     3  0.4916    0.40938 0.424 0.000 0.576 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0188    0.78696 0.000 0.996 0.004 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.5075    0.51378 0.344 0.012 0.644 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.3161    0.65401 0.864 0.000 0.124 0.012
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.7972    0.35529 0.144 0.372 0.456 0.028
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.5219    0.42430 0.000 0.712 0.044 0.244
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.4699    0.52588 0.320 0.000 0.676 0.004
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.1824    0.68082 0.936 0.000 0.060 0.004
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.5590    0.44064 0.028 0.304 0.660 0.008
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.4964    0.43871 0.032 0.000 0.724 0.244
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.8433    0.19001 0.256 0.284 0.432 0.028
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4843    0.41005 0.396 0.000 0.604 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5277    0.01440 0.532 0.000 0.460 0.008
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     3  0.4872    0.50363 0.356 0.004 0.640 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.2334    0.66686 0.908 0.000 0.088 0.004
#> 206865A9-A67C-49A6-93AD-55D06E777559     4  0.4134    0.90943 0.000 0.260 0.000 0.740
#> 26DABC83-DB30-452F-9BE2-366760CB138E     4  0.4164    0.90892 0.000 0.264 0.000 0.736
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.5052    0.43841 0.036 0.000 0.720 0.244
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4999   -0.20418 0.508 0.000 0.492 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.2466    0.66249 0.900 0.000 0.096 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     3  0.4605    0.51365 0.336 0.000 0.664 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.0290    0.79981 0.000 0.000 0.000 0.992 0.008
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.6422    0.23315 0.256 0.000 0.508 0.000 0.236
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.7863   -0.08158 0.404 0.004 0.336 0.084 0.172
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2012    0.39565 0.920 0.000 0.020 0.000 0.060
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3695    0.32867 0.800 0.000 0.036 0.000 0.164
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.6737    0.18213 0.424 0.008 0.380 0.000 0.188
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.7450    0.14047 0.260 0.012 0.452 0.024 0.252
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2690    0.79974 0.000 0.844 0.000 0.156 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.6670    0.71184 0.188 0.000 0.036 0.200 0.576
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4307   -0.27362 0.504 0.000 0.000 0.000 0.496
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.6721    0.14891 0.304 0.000 0.276 0.000 0.420
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     5  0.6386    0.55313 0.368 0.000 0.000 0.172 0.460
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.6970    0.23710 0.272 0.012 0.444 0.000 0.272
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.1043    0.78747 0.000 0.040 0.000 0.960 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.7068    0.05396 0.436 0.000 0.272 0.016 0.276
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4007    0.30970 0.020 0.012 0.776 0.000 0.192
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.5255    0.15986 0.388 0.000 0.560 0.000 0.052
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4030   -0.05408 0.648 0.000 0.000 0.000 0.352
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.6800    0.19871 0.436 0.008 0.348 0.000 0.208
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5126    0.20858 0.300 0.000 0.636 0.000 0.064
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.1544    0.83326 0.000 0.932 0.000 0.068 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.5684    0.22213 0.644 0.004 0.196 0.000 0.156
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2605    0.33661 0.852 0.000 0.000 0.000 0.148
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4219   -0.11267 0.584 0.000 0.000 0.000 0.416
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.4261    0.30576 0.048 0.012 0.780 0.000 0.160
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4294    0.06546 0.532 0.000 0.468 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.6992    0.17369 0.284 0.012 0.436 0.000 0.268
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5557    0.07246 0.464 0.000 0.468 0.000 0.068
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#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     4  0.1041    0.79318 0.004 0.000 0.000 0.964 0.032
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.3723    0.37997 0.804 0.000 0.044 0.000 0.152
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     3  0.4517    0.08429 0.436 0.000 0.556 0.000 0.008
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.5221    0.19242 0.552 0.000 0.400 0.000 0.048
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.4835    0.26720 0.724 0.000 0.120 0.000 0.156
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.5724    0.15802 0.516 0.008 0.412 0.000 0.064
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.4201   -0.08524 0.592 0.000 0.000 0.000 0.408
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     4  0.1043    0.78747 0.000 0.040 0.000 0.960 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     5  0.6492    0.71466 0.172 0.000 0.020 0.240 0.568
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0703    0.84434 0.000 0.976 0.000 0.024 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.5006    0.25486 0.708 0.000 0.136 0.000 0.156
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.5246   -0.09495 0.564 0.000 0.052 0.000 0.384
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.3612    0.75149 0.000 0.764 0.008 0.228 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.4167    0.35367 0.788 0.004 0.072 0.000 0.136
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.4885    0.14189 0.400 0.000 0.572 0.000 0.028
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     4  0.4201    0.11813 0.000 0.408 0.000 0.592 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.3274    0.75939 0.000 0.780 0.000 0.220 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.0000    0.80040 0.000 0.000 0.000 1.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.7392   -0.33140 0.412 0.000 0.052 0.172 0.364
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.5099    0.17182 0.612 0.000 0.336 0.000 0.052
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.6514    0.18916 0.444 0.008 0.400 0.000 0.148
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.5159    0.21806 0.692 0.000 0.164 0.000 0.144
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.2153    0.39780 0.916 0.000 0.040 0.000 0.044
#> 25A5BC09-0D88-4385-87AF-997F9018522D     4  0.4088    0.22778 0.000 0.368 0.000 0.632 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.5314    0.09402 0.420 0.000 0.528 0.000 0.052
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     5  0.6109    0.72102 0.212 0.000 0.000 0.220 0.568
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.6431    0.71734 0.176 0.000 0.020 0.224 0.580
#> 297611E9-9555-4BCA-A723-02E846ACC23A     3  0.6461    0.00111 0.332 0.008 0.504 0.000 0.156
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     4  0.3387    0.69617 0.004 0.000 0.004 0.796 0.196
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.5420    0.20919 0.332 0.000 0.592 0.000 0.076
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.6083    0.21864 0.528 0.008 0.360 0.000 0.104
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.4238    0.00467 0.628 0.000 0.000 0.004 0.368
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.4557    0.11623 0.584 0.000 0.404 0.000 0.012
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.5077   -0.24130 0.568 0.000 0.000 0.040 0.392
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.5303    0.36611 0.108 0.000 0.000 0.660 0.232
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.5895    0.08971 0.440 0.000 0.460 0.000 0.100
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0000    0.80040 0.000 0.000 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     5  0.4307    0.24864 0.500 0.000 0.000 0.000 0.500
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.3835    0.20578 0.732 0.000 0.008 0.000 0.260
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     3  0.4452   -0.01997 0.496 0.000 0.500 0.000 0.004
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.6270    0.16300 0.472 0.008 0.404 0.000 0.116
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     3  0.6681   -0.04640 0.392 0.008 0.424 0.000 0.176
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.5145    0.41823 0.004 0.564 0.008 0.404 0.020
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.8027   -0.25835 0.352 0.000 0.104 0.200 0.344
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.6941    0.21105 0.344 0.012 0.424 0.000 0.220
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.6105    0.23148 0.596 0.008 0.232 0.000 0.164
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.5970    0.71302 0.184 0.000 0.000 0.228 0.588
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.0000    0.80040 0.000 0.000 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.4466    0.28038 0.176 0.000 0.748 0.000 0.076
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.2966    0.78304 0.000 0.816 0.000 0.184 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.3636    0.66604 0.000 0.728 0.000 0.272 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.5498    0.18879 0.356 0.000 0.568 0.000 0.076
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.8460    0.08476 0.236 0.032 0.448 0.120 0.164
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.6794    0.06480 0.300 0.000 0.320 0.000 0.380
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.5735    0.14684 0.508 0.008 0.420 0.000 0.064
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.4912    0.16840 0.572 0.008 0.404 0.000 0.016
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.6862    0.20766 0.352 0.012 0.436 0.000 0.200
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.6992    0.17369 0.284 0.012 0.436 0.000 0.268
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.7755    0.19954 0.084 0.004 0.380 0.148 0.384
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.5338    0.19969 0.544 0.000 0.400 0.000 0.056
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.2966    0.78304 0.000 0.816 0.000 0.184 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.6497    0.03222 0.504 0.000 0.164 0.008 0.324
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.6965    0.20504 0.320 0.012 0.432 0.000 0.236
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5787    0.13169 0.616 0.000 0.204 0.000 0.180
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.0000    0.80040 0.000 0.000 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     4  0.4201    0.13910 0.000 0.408 0.000 0.592 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.5421    0.12054 0.584 0.004 0.352 0.000 0.060
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.2929    0.66717 0.000 0.180 0.000 0.820 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3689    0.72406 0.000 0.740 0.000 0.256 0.004
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.6120    0.06515 0.560 0.000 0.256 0.000 0.184
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.5046    0.23742 0.704 0.000 0.140 0.000 0.156
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.4084    0.63355 0.000 0.668 0.000 0.328 0.004
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.6293    0.25802 0.136 0.012 0.664 0.044 0.144
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.5659    0.16730 0.528 0.008 0.404 0.000 0.060
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.4256    0.09710 0.436 0.000 0.564 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     4  0.0880    0.79435 0.000 0.032 0.000 0.968 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.6319    0.35656 0.196 0.000 0.284 0.000 0.520
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.3424    0.56959 0.000 0.240 0.000 0.760 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.4464    0.14465 0.584 0.008 0.408 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.4892    0.00160 0.492 0.004 0.488 0.000 0.016
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.2771    0.38837 0.860 0.000 0.012 0.000 0.128
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.4866    0.15219 0.392 0.000 0.580 0.000 0.028
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.4482   -0.14451 0.612 0.000 0.000 0.012 0.376
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.4126    0.50722 0.000 0.620 0.000 0.380 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.4449    0.02598 0.512 0.000 0.484 0.000 0.004
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4696    0.27613 0.736 0.000 0.108 0.000 0.156
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.6691   -0.20489 0.360 0.000 0.400 0.000 0.240
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5314    0.13815 0.672 0.000 0.192 0.000 0.136
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     4  0.3777    0.72887 0.056 0.008 0.008 0.836 0.092
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.6721    0.08728 0.452 0.008 0.348 0.000 0.192
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4449    0.23691 0.752 0.000 0.168 0.000 0.080
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.8491   -0.04073 0.396 0.012 0.240 0.140 0.212
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     4  0.2420    0.77055 0.000 0.008 0.008 0.896 0.088
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5338    0.02736 0.604 0.000 0.072 0.000 0.324
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4349    0.22972 0.756 0.000 0.176 0.000 0.068
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.5502    0.18701 0.652 0.000 0.192 0.000 0.156
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.4088    0.51503 0.000 0.632 0.000 0.368 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3983    0.07724 0.660 0.000 0.000 0.000 0.340
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.0290    0.79981 0.000 0.000 0.000 0.992 0.008
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.5368    0.19522 0.548 0.004 0.400 0.000 0.048
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5184    0.21495 0.688 0.000 0.136 0.000 0.176
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.5304    0.19645 0.560 0.000 0.384 0.000 0.056
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0703    0.84403 0.000 0.976 0.000 0.024 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.5551    0.24819 0.096 0.000 0.000 0.600 0.304
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6890    0.15353 0.264 0.012 0.468 0.000 0.256
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.6790   -0.21733 0.316 0.000 0.000 0.384 0.300
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.4167    0.72019 0.000 0.136 0.004 0.788 0.072
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5596    0.14039 0.304 0.000 0.596 0.000 0.100
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.4054    0.58628 0.036 0.000 0.000 0.760 0.204
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4015    0.04161 0.652 0.000 0.000 0.000 0.348
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.5706    0.19591 0.528 0.008 0.400 0.000 0.064
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.1043    0.78747 0.000 0.040 0.000 0.960 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3796    0.12679 0.700 0.000 0.000 0.000 0.300
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0290    0.80015 0.000 0.000 0.000 0.992 0.008
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4675   -0.16759 0.600 0.000 0.000 0.020 0.380
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.6176    0.09147 0.548 0.000 0.268 0.000 0.184
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.8090   -0.17179 0.356 0.000 0.096 0.272 0.276
#> C98275CD-C39A-4E14-A731-4F3EB7396665     4  0.3225    0.76513 0.048 0.024 0.004 0.876 0.048
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4268   -0.16346 0.556 0.000 0.000 0.000 0.444
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5908    0.25461 0.628 0.008 0.180 0.000 0.184
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     5  0.6778    0.35219 0.348 0.000 0.004 0.228 0.420
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.6907    0.19791 0.344 0.012 0.432 0.000 0.212
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.6690    0.16442 0.028 0.004 0.576 0.216 0.176
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4674   -0.11395 0.568 0.000 0.016 0.000 0.416
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4833    0.23164 0.736 0.008 0.168 0.000 0.088
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4242   -0.12653 0.572 0.000 0.000 0.000 0.428
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.5306    0.19364 0.552 0.004 0.400 0.000 0.044
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0609    0.84425 0.000 0.980 0.000 0.020 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.6938    0.19494 0.356 0.012 0.416 0.000 0.216
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3630    0.31297 0.780 0.000 0.016 0.000 0.204
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.6193    0.17901 0.484 0.008 0.400 0.000 0.108
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4074   -0.08838 0.636 0.000 0.000 0.000 0.364

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2367   0.749492 0.088 0.000 0.008 0.888 0.000 0.016
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.5423   0.201594 0.000 0.000 0.444 0.000 0.116 0.440
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.5647   0.342496 0.044 0.000 0.348 0.000 0.064 0.544
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     5  0.5341   0.168741 0.004 0.000 0.276 0.000 0.588 0.132
#> 78F79407-D49F-4FA2-B09F-0665C502827C     5  0.4144   0.171810 0.004 0.000 0.008 0.000 0.580 0.408
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.2300   0.463139 0.144 0.000 0.000 0.000 0.856 0.000
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#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.1914   0.751738 0.056 0.000 0.008 0.920 0.000 0.016
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0547   0.513490 0.020 0.000 0.000 0.000 0.980 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     6  0.3168   0.568663 0.000 0.000 0.024 0.000 0.172 0.804
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.1625   0.503529 0.012 0.000 0.000 0.000 0.928 0.060
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0146   0.823487 0.000 0.996 0.000 0.004 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.6557   0.249568 0.304 0.000 0.204 0.460 0.012 0.020
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2172   0.490800 0.020 0.000 0.912 0.000 0.024 0.044
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6267   0.422358 0.452 0.000 0.308 0.224 0.000 0.016
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.7135   0.329917 0.124 0.296 0.000 0.436 0.004 0.140
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.4427  -0.003892 0.020 0.000 0.004 0.000 0.548 0.428
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.4130   0.588724 0.300 0.000 0.000 0.672 0.024 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     3  0.6655  -0.300208 0.340 0.000 0.344 0.000 0.288 0.028
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0547   0.513182 0.020 0.000 0.000 0.000 0.980 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.0858   0.746782 0.004 0.000 0.000 0.968 0.000 0.028
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     5  0.6281  -0.094197 0.188 0.000 0.380 0.000 0.412 0.020
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1806   0.751876 0.044 0.000 0.008 0.928 0.000 0.020
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6382   0.578444 0.548 0.000 0.248 0.040 0.152 0.012
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.3345   0.570688 0.000 0.000 0.028 0.000 0.184 0.788
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6866   0.039140 0.084 0.000 0.428 0.376 0.096 0.016
#> C98275CD-C39A-4E14-A731-4F3EB7396665     4  0.6559   0.509497 0.124 0.000 0.196 0.548 0.000 0.132
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5721   0.498880 0.504 0.000 0.360 0.000 0.124 0.012
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.3852   0.203293 0.004 0.000 0.000 0.000 0.612 0.384
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5672   0.498953 0.524 0.000 0.384 0.012 0.044 0.036
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3171   0.505105 0.028 0.000 0.844 0.000 0.024 0.104
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     6  0.6804   0.157793 0.088 0.000 0.116 0.004 0.384 0.408
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.7395  -0.156660 0.300 0.000 0.364 0.000 0.144 0.192
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.5519   0.480489 0.000 0.000 0.280 0.000 0.172 0.548
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.6660   0.522271 0.448 0.000 0.332 0.048 0.168 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.1049   0.509062 0.008 0.000 0.000 0.000 0.960 0.032
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000   0.824187 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000   0.824187 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3125   0.502299 0.024 0.000 0.856 0.000 0.056 0.064
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     5  0.5831   0.095702 0.052 0.000 0.388 0.000 0.496 0.064
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.1075   0.503403 0.048 0.000 0.000 0.000 0.952 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.6877   0.426484 0.488 0.000 0.232 0.000 0.172 0.108

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-mclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


CV:NMF**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "NMF"]
# you can also extract it by
# res = res_list["CV:NMF"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.963       0.985         0.4227 0.575   0.575
#> 3 3 0.560           0.661       0.857         0.4702 0.786   0.639
#> 4 4 0.689           0.727       0.871         0.1522 0.817   0.581
#> 5 5 0.715           0.740       0.833         0.0917 0.868   0.590
#> 6 6 0.729           0.695       0.814         0.0399 0.910   0.636

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.4161      0.891 0.084 0.916
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.991 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5178      0.866 0.884 0.116
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.991 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.991 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.991 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.969 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.969 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.991 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.991 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.991 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.991 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.991 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.969 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0376      0.987 0.996 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.991 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.991 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.991 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.991 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.991 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.969 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.991 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.991 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.991 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.991 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.991 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.991 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.991 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.969 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.969 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.991 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.991 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.991 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.991 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.969 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.8443      0.621 0.728 0.272
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.991 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.969 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.991 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.991 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.969 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.991 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     2  0.5946      0.826 0.144 0.856
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.991 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.991 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.991 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.991 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.969 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.991 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.969 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.991 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.969 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.991 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.991 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.991 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.2043      0.960 0.968 0.032
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.991 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000      0.991 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.969 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.991 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.991 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.8909      0.577 0.308 0.692
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.991 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.991 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.969 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.7674      0.707 0.776 0.224
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.991 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.991 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.991 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.969 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.991 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.991 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.991 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.991 1.000 0.000
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#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.991 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.991 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.991 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.969 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.991 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.991 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.991 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.991 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.1184      0.955 0.016 0.984
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.991 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.991 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.991 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.0000      0.969 0.000 1.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.991 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.991 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.991 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.969 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.991 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.7376      0.743 0.208 0.792
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.991 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.991 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.991 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.969 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000      0.991 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.9460      0.441 0.364 0.636
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000      0.991 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.969 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.991 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.9833      0.224 0.576 0.424
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.991 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.991 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.969 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.991 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.969 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.991 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.991 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0376      0.987 0.996 0.004
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.969 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.991 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.991 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2603      0.948 0.956 0.044
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.991 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0376      0.987 0.996 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.991 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.991 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.991 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.991 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.969 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.969 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.991 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.991 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.991 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.991 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.6045     0.0941 0.000 0.380 0.620
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.3941     0.6782 0.156 0.000 0.844
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4784     0.6377 0.200 0.004 0.796
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5216     0.5904 0.740 0.000 0.260
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.8094 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.8094 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4504     0.5659 0.000 0.196 0.804
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9168 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6235     0.1124 0.564 0.000 0.436
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.5926     0.4499 0.644 0.000 0.356
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.8094 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.5529     0.5400 0.704 0.000 0.296
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3551     0.6946 0.132 0.000 0.868
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0424     0.9129 0.000 0.992 0.008
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.8644     0.2123 0.400 0.104 0.496
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3816     0.6910 0.148 0.000 0.852
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.6192     0.1599 0.580 0.000 0.420
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.8094 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.8094 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.6260     0.0306 0.552 0.000 0.448
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9168 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.8094 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2796     0.7582 0.908 0.000 0.092
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.5678     0.5104 0.684 0.000 0.316
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2625     0.6855 0.084 0.000 0.916
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.8094 1.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3340     0.6998 0.120 0.000 0.880
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5733     0.3886 0.676 0.000 0.324
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9168 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9168 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.8094 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.1643     0.7816 0.956 0.000 0.044
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.8094 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.8094 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9168 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.9850     0.3764 0.264 0.324 0.412
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.2356     0.7676 0.928 0.000 0.072
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9168 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.8094 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.8094 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9168 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.4062     0.6829 0.164 0.000 0.836
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.6795 0.000 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.6204     0.3260 0.576 0.000 0.424
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.3340     0.7186 0.880 0.000 0.120
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.3267     0.7181 0.884 0.000 0.116
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.8094 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9168 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.4654     0.6472 0.208 0.000 0.792
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.5835     0.5971 0.000 0.660 0.340
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.5397     0.5628 0.720 0.000 0.280
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0424     0.9129 0.000 0.992 0.008
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5650     0.4663 0.312 0.000 0.688
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.5785     0.4854 0.668 0.000 0.332
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.5760     0.4907 0.672 0.000 0.328
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0592     0.6882 0.012 0.000 0.988
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.4291     0.6576 0.180 0.000 0.820
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5591     0.4223 0.696 0.000 0.304
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9168 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.4504     0.6660 0.804 0.000 0.196
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.8094 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.6398    -0.0163 0.004 0.416 0.580
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.6299     0.1677 0.476 0.000 0.524
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1031     0.7998 0.976 0.000 0.024
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9168 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.4033     0.6919 0.136 0.008 0.856
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0237     0.8083 0.996 0.000 0.004
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.5706     0.3979 0.680 0.000 0.320
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.2959     0.7055 0.100 0.000 0.900
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.3816     0.8206 0.000 0.852 0.148
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.8094 1.000 0.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0424     0.8061 0.992 0.000 0.008
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.6225     0.0853 0.568 0.000 0.432
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0424     0.8068 0.992 0.000 0.008
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     3  0.6299    -0.0622 0.476 0.000 0.524
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.8094 1.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000     0.8094 1.000 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9168 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0424     0.6858 0.008 0.000 0.992
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.5760     0.6143 0.000 0.672 0.328
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000     0.8094 1.000 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.6295     0.1375 0.000 0.528 0.472
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000     0.8094 1.000 0.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.8094 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0237     0.8082 0.996 0.000 0.004
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.1753     0.7809 0.952 0.000 0.048
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.6280     0.1678 0.540 0.000 0.460
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.3482     0.8358 0.000 0.872 0.128
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9168 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.6079     0.3918 0.388 0.000 0.612
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000     0.8094 1.000 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.5621     0.4223 0.692 0.000 0.308
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.3752     0.8241 0.000 0.856 0.144
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.6008     0.4245 0.372 0.000 0.628
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.1529     0.7843 0.960 0.000 0.040
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.8094 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.5678     0.2897 0.000 0.316 0.684
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.5733     0.3660 0.324 0.000 0.676
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0424     0.8053 0.992 0.000 0.008
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.3340     0.6999 0.120 0.000 0.880
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.5178     0.5714 0.256 0.000 0.744
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9168 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9168 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000     0.8094 1.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.3116     0.7200 0.892 0.000 0.108
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9168 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000     0.9168 0.000 1.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.3686     0.6898 0.140 0.000 0.860
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000     0.8094 1.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.6295     0.3206 0.000 0.528 0.472
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9168 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.3038     0.7290 0.896 0.000 0.104
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.1643     0.7067 0.044 0.000 0.956
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#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5835     0.4778 0.660 0.000 0.340
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.8094 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9168 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.0237     0.6814 0.004 0.000 0.996
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2056     0.6951 0.024 0.024 0.952
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.2165     0.6921 0.064 0.000 0.936
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9168 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5560     0.4414 0.700 0.000 0.300
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.5988     0.5352 0.056 0.168 0.776
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0424     0.8068 0.992 0.000 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.8094 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.4702     0.7555 0.000 0.788 0.212
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.5216     0.5902 0.740 0.000 0.260
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     3  0.6140     0.0339 0.000 0.404 0.596
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.5882     0.4573 0.652 0.000 0.348
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5058     0.5854 0.244 0.000 0.756
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000     0.6795 0.000 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9168 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5835     0.4770 0.660 0.000 0.340
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.8094 1.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.6180     0.4807 0.660 0.008 0.332
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2796     0.7066 0.092 0.000 0.908
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.7699     0.0127 0.532 0.048 0.420
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.5948     0.4442 0.640 0.000 0.360
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6079     0.3866 0.612 0.000 0.388
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.5760     0.4907 0.672 0.000 0.328
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.8094 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9168 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9168 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0424     0.6852 0.008 0.000 0.992
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5760     0.4907 0.672 0.000 0.328
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.8094 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.8094 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.0707      0.833 0.000 0.020 0.000 0.980
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0188      0.799 0.000 0.000 0.996 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4761      0.554 0.664 0.000 0.332 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.3025      0.750 0.004 0.056 0.896 0.044
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.1716      0.816 0.064 0.000 0.000 0.936
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.7278      0.430 0.528 0.000 0.188 0.284
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4713      0.487 0.640 0.000 0.000 0.360
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4972      0.135 0.000 0.544 0.000 0.456
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.3052      0.751 0.008 0.032 0.896 0.064
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0376      0.799 0.004 0.000 0.992 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.3172      0.726 0.160 0.000 0.840 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4585      0.565 0.332 0.000 0.668 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2921      0.748 0.860 0.000 0.140 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.5906      0.554 0.644 0.000 0.292 0.064
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3123      0.682 0.000 0.000 0.844 0.156
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0188      0.799 0.004 0.000 0.996 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4477      0.591 0.312 0.000 0.688 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3448      0.697 0.828 0.000 0.004 0.168
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1211      0.808 0.960 0.000 0.040 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6373      0.321 0.004 0.356 0.576 0.064
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5028      0.206 0.596 0.000 0.004 0.400
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3837      0.679 0.776 0.000 0.224 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0469      0.942 0.000 0.988 0.000 0.012
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0188      0.800 0.004 0.000 0.996 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.4331      0.500 0.000 0.000 0.712 0.288
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5244      0.318 0.556 0.000 0.008 0.436
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4817      0.480 0.388 0.000 0.612 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0707      0.814 0.980 0.000 0.020 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0657      0.798 0.012 0.000 0.984 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.1716      0.832 0.000 0.064 0.000 0.936
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4866      0.400 0.596 0.000 0.000 0.404
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.4746      0.390 0.000 0.632 0.000 0.368
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.6295      0.461 0.580 0.000 0.348 0.072
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.6106      0.495 0.604 0.000 0.332 0.064
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0188      0.799 0.000 0.000 0.996 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.3219      0.739 0.164 0.000 0.000 0.836
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.4543      0.568 0.676 0.000 0.324 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.1716      0.832 0.000 0.064 0.000 0.936
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.2578      0.814 0.036 0.000 0.052 0.912
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2216      0.780 0.908 0.000 0.092 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4585      0.565 0.332 0.000 0.668 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0188      0.799 0.000 0.000 0.996 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.1792      0.830 0.000 0.068 0.000 0.932
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.4008      0.557 0.756 0.000 0.244 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4585      0.565 0.332 0.000 0.668 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.4866      0.172 0.404 0.000 0.000 0.596
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0376      0.821 0.992 0.000 0.004 0.004
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0188      0.799 0.000 0.000 0.996 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.3764      0.654 0.000 0.216 0.000 0.784
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.4522      0.453 0.000 0.320 0.680 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.1211      0.808 0.960 0.000 0.040 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4925      0.235 0.572 0.000 0.000 0.428
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.4307      0.716 0.192 0.000 0.784 0.024
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.1940      0.827 0.000 0.076 0.000 0.924
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.2345      0.763 0.100 0.000 0.900 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0188      0.822 0.996 0.000 0.004 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4855      0.454 0.400 0.000 0.600 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.3356      0.737 0.000 0.176 0.000 0.824
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.3074      0.731 0.152 0.000 0.848 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.4509      0.484 0.708 0.000 0.004 0.288
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     4  0.4584      0.462 0.004 0.000 0.300 0.696
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.0000      0.829 0.000 0.000 0.000 1.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3448      0.678 0.828 0.000 0.004 0.168
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.7067      0.335 0.160 0.000 0.552 0.288
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     4  0.4428      0.578 0.276 0.000 0.004 0.720
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0707      0.929 0.020 0.980 0.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000      0.800 0.000 0.000 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.1716      0.832 0.000 0.064 0.000 0.936
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     4  0.4877      0.370 0.408 0.000 0.000 0.592
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0336      0.798 0.000 0.000 0.992 0.008
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.0779      0.793 0.004 0.000 0.980 0.016
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.6200      0.455 0.580 0.000 0.356 0.064
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.1209      0.814 0.964 0.000 0.004 0.032
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.4304      0.497 0.716 0.000 0.000 0.284
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.2647      0.763 0.880 0.000 0.120 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.4466      0.698 0.784 0.000 0.180 0.036
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.1716      0.796 0.936 0.000 0.064 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     3  0.1824      0.769 0.004 0.000 0.936 0.060
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.6106      0.495 0.604 0.000 0.332 0.064
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     4  0.0000      0.829 0.000 0.000 0.000 1.000
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#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.0000      0.829 0.000 0.000 0.000 1.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0376      0.797 0.004 0.000 0.992 0.004
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.4761      0.400 0.004 0.000 0.332 0.664
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4585      0.565 0.332 0.000 0.668 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.1637      0.814 0.000 0.000 0.060 0.940
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2011      0.825 0.000 0.080 0.000 0.920
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.5090      0.554 0.660 0.000 0.324 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0000      0.829 0.000 0.000 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4907      0.364 0.580 0.000 0.000 0.420
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.1520      0.786 0.020 0.000 0.956 0.024
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1792      0.767 0.000 0.000 0.932 0.068
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0188      0.948 0.004 0.996 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.6462      0.473 0.580 0.000 0.332 0.088
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.822 1.000 0.000 0.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.7357      0.378 0.500 0.000 0.320 0.180
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0188      0.799 0.000 0.000 0.996 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5344      0.589 0.300 0.032 0.668 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.7775      0.009 0.240 0.000 0.380 0.380
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4609      0.567 0.224 0.000 0.752 0.024
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.5809      0.625 0.692 0.000 0.216 0.092
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.952 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0336      0.798 0.000 0.000 0.992 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.6041      0.499 0.608 0.000 0.332 0.060
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0188      0.823 0.996 0.000 0.004 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.822 1.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1851     0.7831 0.088 0.000 0.000 0.912 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2966     0.8183 0.136 0.000 0.848 0.016 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3684     0.7503 0.720 0.000 0.000 0.000 0.280
#> 78F79407-D49F-4FA2-B09F-0665C502827C     5  0.2813     0.7529 0.168 0.000 0.000 0.000 0.832
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.3424     0.6533 0.240 0.000 0.000 0.000 0.760
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.5195     0.1632 0.536 0.044 0.420 0.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.4021     0.7222 0.200 0.000 0.000 0.764 0.036
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4660     0.7413 0.728 0.000 0.000 0.080 0.192
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.2471     0.7627 0.136 0.000 0.000 0.000 0.864
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     5  0.4588     0.6080 0.116 0.000 0.000 0.136 0.748
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.4592     0.4279 0.024 0.332 0.000 0.644 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.5697     0.5069 0.620 0.020 0.292 0.000 0.068
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     5  0.3143     0.7254 0.204 0.000 0.000 0.000 0.796
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1732     0.7368 0.080 0.000 0.000 0.000 0.920
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.1331     0.8882 0.040 0.000 0.952 0.000 0.008
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     5  0.2813     0.7399 0.168 0.000 0.000 0.000 0.832
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.3684     0.4369 0.280 0.000 0.000 0.000 0.720
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3561     0.7518 0.740 0.000 0.000 0.000 0.260
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.0510     0.7625 0.016 0.000 0.000 0.000 0.984
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.1485     0.8844 0.020 0.000 0.948 0.000 0.032
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0703     0.9524 0.024 0.976 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0703     0.9524 0.024 0.976 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.2891     0.7558 0.176 0.000 0.000 0.000 0.824
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.6455     0.4918 0.236 0.000 0.000 0.500 0.264
#> 904EDF2E-411E-43BD-901D-46129AFA283A     5  0.2966     0.6958 0.184 0.000 0.000 0.000 0.816
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.0794     0.7678 0.028 0.000 0.000 0.000 0.972
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.6085     0.6375 0.668 0.168 0.080 0.000 0.084
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.5680     0.5408 0.240 0.000 0.000 0.140 0.620
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     5  0.4192     0.2929 0.404 0.000 0.000 0.000 0.596
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     5  0.1732     0.7570 0.080 0.000 0.000 0.000 0.920
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0794     0.9408 0.000 0.972 0.000 0.028 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5277     0.7055 0.664 0.000 0.000 0.108 0.228
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3326     0.7990 0.024 0.000 0.824 0.000 0.152
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.4523     0.7317 0.212 0.000 0.032 0.016 0.740
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.3480     0.6870 0.248 0.000 0.000 0.000 0.752
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.0609     0.7893 0.020 0.000 0.000 0.980 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.6401     0.0586 0.184 0.000 0.000 0.480 0.336
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.4484     0.5719 0.024 0.668 0.000 0.308 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4082     0.7651 0.740 0.000 0.008 0.012 0.240
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3837     0.7443 0.692 0.000 0.000 0.000 0.308
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.5091     0.6776 0.236 0.000 0.000 0.676 0.088
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2236     0.9053 0.024 0.908 0.000 0.068 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3876     0.7356 0.684 0.000 0.000 0.000 0.316
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.3074     0.7563 0.196 0.000 0.000 0.000 0.804
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.2648     0.7628 0.152 0.000 0.000 0.848 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.5837     0.6350 0.208 0.000 0.004 0.624 0.164
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     5  0.3707     0.6212 0.284 0.000 0.000 0.000 0.716
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     5  0.2732     0.7417 0.160 0.000 0.000 0.000 0.840
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.2233     0.8500 0.004 0.000 0.892 0.000 0.104
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.2362     0.7727 0.024 0.076 0.000 0.900 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.2605     0.7581 0.148 0.000 0.000 0.000 0.852
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.3913     0.5533 0.000 0.000 0.676 0.000 0.324
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0671     0.9008 0.004 0.000 0.980 0.000 0.016
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     5  0.3336     0.6918 0.228 0.000 0.000 0.000 0.772
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.6033     0.3131 0.220 0.000 0.000 0.580 0.200
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.1270     0.7498 0.052 0.000 0.000 0.000 0.948
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.3910     0.6503 0.272 0.000 0.000 0.008 0.720
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2905     0.7548 0.036 0.096 0.000 0.868 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     5  0.0510     0.7675 0.016 0.000 0.000 0.000 0.984
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.1544     0.7752 0.068 0.000 0.000 0.000 0.932
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.1043     0.7677 0.040 0.000 0.000 0.000 0.960
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     5  0.2773     0.7175 0.164 0.000 0.000 0.000 0.836
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     4  0.5478     0.4737 0.180 0.000 0.000 0.656 0.164
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.3409     0.7530 0.032 0.000 0.824 0.000 0.144
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.2464     0.7856 0.096 0.016 0.000 0.888 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.3534     0.6606 0.256 0.000 0.000 0.000 0.744
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4805     0.7110 0.128 0.000 0.728 0.000 0.144
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.2561     0.7574 0.020 0.096 0.000 0.884 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.5264     0.5709 0.256 0.000 0.000 0.092 0.652
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.1270     0.7670 0.052 0.000 0.000 0.000 0.948
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3837     0.4154 0.692 0.000 0.000 0.308 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.2561     0.7329 0.144 0.000 0.000 0.856 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.4584     0.6379 0.312 0.000 0.000 0.028 0.660
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0162     0.9066 0.004 0.000 0.996 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.3847     0.4010 0.800 0.000 0.004 0.156 0.040
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.2230     0.7595 0.116 0.000 0.000 0.000 0.884
#> 7822EA86-35A1-4285-9429-2B63111B9885     4  0.5866     0.6126 0.248 0.000 0.000 0.596 0.156
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.5201     0.6756 0.144 0.732 0.000 0.092 0.032
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.1197     0.7678 0.048 0.000 0.000 0.000 0.952
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.1197     0.7896 0.048 0.000 0.000 0.952 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0162     0.9586 0.004 0.996 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     4  0.6285     0.1233 0.152 0.000 0.000 0.456 0.392
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.1671     0.8558 0.076 0.000 0.924 0.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.3177     0.7379 0.792 0.000 0.000 0.000 0.208
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     5  0.1478     0.7411 0.000 0.000 0.000 0.064 0.936
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     5  0.2929     0.7106 0.180 0.000 0.000 0.000 0.820
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     5  0.5306     0.5959 0.316 0.000 0.000 0.072 0.612
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#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.1544     0.8738 0.000 0.000 0.932 0.000 0.068
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.2690     0.7629 0.156 0.000 0.000 0.000 0.844
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.5027     0.5949 0.196 0.000 0.032 0.048 0.724
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.2966     0.7376 0.184 0.000 0.816 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5737     0.5874 0.660 0.224 0.000 0.028 0.088
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     5  0.2966     0.7411 0.184 0.000 0.000 0.000 0.816
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.5562     0.5335 0.156 0.000 0.644 0.000 0.200
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1788     0.8755 0.004 0.008 0.932 0.000 0.056
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     4  0.7188     0.4756 0.096 0.280 0.000 0.520 0.104
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.7965    -0.1548 0.368 0.000 0.356 0.144 0.132
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4980     0.3502 0.584 0.000 0.380 0.000 0.036
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     5  0.2929     0.7377 0.180 0.000 0.000 0.000 0.820
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3796     0.7488 0.700 0.000 0.000 0.000 0.300
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.1544     0.7875 0.068 0.000 0.000 0.932 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.2020     0.7684 0.100 0.000 0.000 0.000 0.900
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5930     0.6234 0.516 0.000 0.112 0.000 0.372
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.1341     0.7649 0.056 0.000 0.000 0.000 0.944
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0703     0.9524 0.024 0.976 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.0963     0.7880 0.036 0.000 0.000 0.964 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.1965     0.8416 0.096 0.000 0.904 0.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.3636     0.4606 0.728 0.000 0.000 0.272 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.1544     0.9203 0.068 0.932 0.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0162     0.9057 0.004 0.000 0.996 0.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.1211     0.7848 0.024 0.000 0.016 0.960 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     5  0.2605     0.7406 0.148 0.000 0.000 0.000 0.852
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1671     0.7413 0.076 0.000 0.000 0.000 0.924
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2648     0.7688 0.152 0.000 0.000 0.848 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3707     0.7475 0.716 0.000 0.000 0.000 0.284
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0963     0.7847 0.036 0.000 0.000 0.964 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.6552     0.0998 0.276 0.000 0.000 0.476 0.248
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5264     0.5475 0.256 0.000 0.660 0.004 0.080
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4171     0.3276 0.396 0.000 0.604 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.1830     0.9162 0.068 0.924 0.000 0.008 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4136     0.7528 0.764 0.000 0.000 0.048 0.188
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.2852     0.7495 0.172 0.000 0.000 0.000 0.828
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3731     0.7413 0.800 0.000 0.000 0.040 0.160
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1800     0.8779 0.048 0.000 0.932 0.000 0.020
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4133     0.6307 0.768 0.000 0.000 0.180 0.052
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5851     0.3900 0.140 0.000 0.588 0.000 0.272
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3586     0.7596 0.736 0.000 0.000 0.000 0.264
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.0000     0.7651 0.000 0.000 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9597 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.9068 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3305     0.7442 0.776 0.000 0.000 0.000 0.224
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.3109     0.7558 0.200 0.000 0.000 0.000 0.800
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     5  0.3242     0.7430 0.216 0.000 0.000 0.000 0.784

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.3023     0.7124 0.000 0.000 0.000 0.212 0.784 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0146     0.8882 0.000 0.000 0.996 0.000 0.004 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.3674     0.5766 0.000 0.000 0.268 0.000 0.716 0.016
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3765     0.5454 0.596 0.000 0.000 0.000 0.000 0.404
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3198     0.7366 0.740 0.000 0.000 0.000 0.000 0.260
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4400     0.4113 0.592 0.000 0.000 0.000 0.376 0.032
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     6  0.5144     0.3605 0.000 0.100 0.340 0.000 0.000 0.560
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.2320     0.7663 0.024 0.000 0.000 0.080 0.892 0.004
#> 53062969-D209-490B-9C9B-5D297625E2AE     6  0.5222     0.0340 0.080 0.000 0.000 0.416 0.004 0.500
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3213     0.7577 0.808 0.000 0.000 0.000 0.032 0.160
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4596     0.4952 0.672 0.000 0.000 0.240 0.000 0.088
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.5454     0.7092 0.000 0.676 0.000 0.144 0.092 0.088
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.4650     0.5413 0.052 0.000 0.264 0.008 0.004 0.672
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0146     0.8882 0.000 0.000 0.996 0.000 0.004 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3670     0.7187 0.704 0.000 0.000 0.000 0.012 0.284
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1910     0.6767 0.892 0.000 0.000 0.000 0.108 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.1610     0.8459 0.000 0.000 0.916 0.000 0.084 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3076     0.7392 0.760 0.000 0.000 0.000 0.000 0.240
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0790     0.7438 0.968 0.000 0.000 0.000 0.000 0.032
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     6  0.2309     0.7165 0.084 0.000 0.000 0.000 0.028 0.888
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0146     0.8882 0.000 0.000 0.996 0.000 0.004 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0508     0.7333 0.984 0.000 0.000 0.000 0.012 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.1462     0.8612 0.008 0.000 0.936 0.000 0.056 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.2283     0.8564 0.000 0.904 0.000 0.020 0.020 0.056
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.3270     0.8316 0.000 0.844 0.000 0.028 0.040 0.088
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4435     0.7084 0.672 0.000 0.000 0.000 0.064 0.264
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.6429     0.1519 0.460 0.000 0.000 0.200 0.308 0.032
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2996     0.7429 0.772 0.000 0.000 0.000 0.000 0.228
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0405     0.7336 0.988 0.000 0.000 0.000 0.008 0.004
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     6  0.3386     0.6760 0.040 0.104 0.024 0.000 0.000 0.832
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.1194     0.7675 0.004 0.000 0.000 0.008 0.956 0.032
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3482     0.6879 0.684 0.000 0.000 0.000 0.000 0.316
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1444     0.7522 0.928 0.000 0.000 0.000 0.000 0.072
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0260     0.8755 0.000 0.992 0.000 0.008 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     4  0.4963     0.4539 0.100 0.000 0.000 0.612 0.000 0.288
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3975     0.6904 0.244 0.000 0.716 0.000 0.040 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.5534     0.5960 0.608 0.000 0.012 0.004 0.240 0.136
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.4408     0.5780 0.656 0.000 0.000 0.000 0.292 0.052
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.2511     0.6742 0.000 0.000 0.000 0.880 0.056 0.064
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.5523     0.3689 0.180 0.000 0.000 0.552 0.000 0.268
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.6771     0.3849 0.000 0.484 0.000 0.164 0.264 0.088
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0291     0.8878 0.004 0.000 0.992 0.000 0.004 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     6  0.2792     0.6859 0.036 0.000 0.004 0.072 0.012 0.876
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     6  0.2340     0.7098 0.148 0.000 0.000 0.000 0.000 0.852
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0146     0.8882 0.000 0.000 0.996 0.000 0.004 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.4915     0.5451 0.076 0.000 0.000 0.680 0.220 0.024
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.4487     0.7789 0.000 0.756 0.000 0.116 0.040 0.088
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3101     0.7364 0.756 0.000 0.000 0.000 0.000 0.244
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.4024     0.7220 0.700 0.000 0.000 0.000 0.036 0.264
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.2668     0.7416 0.004 0.000 0.000 0.168 0.828 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.2177     0.7622 0.052 0.000 0.008 0.032 0.908 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3819     0.6922 0.672 0.000 0.000 0.000 0.012 0.316
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3259     0.7481 0.772 0.000 0.000 0.012 0.000 0.216
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.3081     0.7407 0.220 0.000 0.776 0.000 0.004 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.3739     0.6345 0.000 0.040 0.000 0.816 0.056 0.088
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.3175     0.7348 0.744 0.000 0.000 0.000 0.000 0.256
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.3706     0.5347 0.380 0.000 0.620 0.000 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0891     0.8797 0.008 0.000 0.968 0.000 0.024 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3221     0.7301 0.736 0.000 0.000 0.000 0.000 0.264
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.4277     0.6353 0.144 0.000 0.000 0.732 0.000 0.124
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.1075     0.7117 0.952 0.000 0.000 0.000 0.048 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.4344     0.5591 0.652 0.000 0.000 0.000 0.304 0.044
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.1492     0.7362 0.000 0.036 0.000 0.940 0.000 0.024
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0777     0.7266 0.972 0.000 0.000 0.000 0.024 0.004
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.3995    -0.0166 0.000 0.000 0.516 0.000 0.480 0.004
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.2772     0.7607 0.816 0.000 0.000 0.000 0.004 0.180
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0146     0.7363 0.996 0.000 0.000 0.000 0.000 0.004
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2631     0.7561 0.820 0.000 0.000 0.000 0.000 0.180
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     4  0.5449     0.4230 0.188 0.000 0.000 0.572 0.000 0.240
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.2980     0.6787 0.192 0.000 0.800 0.000 0.008 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     5  0.4239     0.6788 0.000 0.008 0.000 0.156 0.748 0.088
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3534     0.7230 0.716 0.000 0.008 0.000 0.000 0.276
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4732     0.6418 0.148 0.000 0.680 0.000 0.172 0.000
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#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0146     0.7374 0.996 0.000 0.000 0.000 0.000 0.004
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.2793     0.7558 0.800 0.000 0.000 0.000 0.000 0.200
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.5711     0.4768 0.568 0.000 0.000 0.020 0.280 0.132
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0865     0.7184 0.964 0.000 0.000 0.000 0.036 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.2854     0.7006 0.792 0.000 0.000 0.000 0.000 0.208
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     6  0.3198     0.6565 0.260 0.000 0.000 0.000 0.000 0.740
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.0632     0.7313 0.000 0.000 0.000 0.976 0.024 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.6003     0.1287 0.000 0.444 0.000 0.044 0.424 0.088
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0405     0.7379 0.988 0.000 0.000 0.000 0.004 0.008
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4686     0.7647 0.000 0.736 0.000 0.136 0.040 0.088
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.2918     0.8409 0.000 0.864 0.000 0.020 0.032 0.084
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.0363     0.8843 0.012 0.000 0.988 0.000 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     6  0.3747     0.2546 0.396 0.000 0.000 0.000 0.000 0.604
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0260     0.8788 0.000 0.992 0.000 0.000 0.000 0.008
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0937     0.7160 0.960 0.000 0.000 0.000 0.040 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.3986     0.6183 0.316 0.000 0.664 0.000 0.020 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.4266     0.7929 0.000 0.776 0.000 0.096 0.040 0.088
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.1528     0.7658 0.028 0.000 0.000 0.016 0.944 0.012
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4787     0.7580 0.000 0.728 0.000 0.140 0.044 0.088
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.2121     0.7638 0.892 0.000 0.000 0.000 0.012 0.096
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.1556     0.6996 0.920 0.000 0.000 0.000 0.080 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     6  0.1946     0.7127 0.072 0.000 0.000 0.012 0.004 0.912
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.3714     0.7329 0.196 0.000 0.760 0.000 0.044 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     4  0.3930     0.7110 0.096 0.000 0.000 0.796 0.024 0.084
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2442     0.8030 0.144 0.000 0.852 0.000 0.004 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.5826     0.1917 0.324 0.000 0.000 0.000 0.204 0.472
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.2086     0.7610 0.064 0.000 0.008 0.012 0.912 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.3950     0.1488 0.000 0.000 0.564 0.000 0.004 0.432
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     4  0.5449     0.3946 0.032 0.384 0.000 0.528 0.000 0.056
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3555     0.7223 0.712 0.000 0.000 0.000 0.008 0.280
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.5016     0.5023 0.324 0.000 0.584 0.000 0.000 0.092
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1950     0.8442 0.064 0.024 0.912 0.000 0.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     4  0.4990     0.6728 0.028 0.164 0.000 0.696 0.000 0.112
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     5  0.2437     0.7512 0.008 0.000 0.008 0.020 0.896 0.068
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.3853     0.5499 0.008 0.000 0.272 0.000 0.012 0.708
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     6  0.3717     0.2104 0.384 0.000 0.000 0.000 0.000 0.616
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     6  0.2340     0.7099 0.148 0.000 0.000 0.000 0.000 0.852
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     5  0.3830     0.5309 0.000 0.000 0.000 0.376 0.620 0.004
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2527     0.7632 0.832 0.000 0.000 0.000 0.000 0.168
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5294     0.1744 0.532 0.000 0.356 0.000 0.000 0.112
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0146     0.7363 0.996 0.000 0.000 0.000 0.000 0.004
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2345     0.8552 0.000 0.900 0.000 0.020 0.020 0.060
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     6  0.6112    -0.1253 0.000 0.000 0.000 0.332 0.300 0.368
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2300     0.7557 0.000 0.000 0.856 0.000 0.000 0.144
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     6  0.3698     0.5910 0.000 0.000 0.000 0.096 0.116 0.788
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.3714     0.8079 0.000 0.800 0.000 0.020 0.044 0.136
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0806     0.8807 0.008 0.000 0.972 0.000 0.020 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.0964     0.7339 0.012 0.000 0.000 0.968 0.016 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2854     0.7505 0.792 0.000 0.000 0.000 0.000 0.208
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.1444     0.7069 0.928 0.000 0.000 0.000 0.072 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     5  0.3327     0.7293 0.000 0.000 0.000 0.092 0.820 0.088
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     6  0.2597     0.6729 0.176 0.000 0.000 0.000 0.000 0.824
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1176     0.7376 0.000 0.000 0.000 0.956 0.020 0.024
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.5112     0.4355 0.112 0.000 0.000 0.592 0.000 0.296
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.5875     0.4072 0.044 0.000 0.304 0.004 0.084 0.564
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     6  0.3789     0.2811 0.000 0.000 0.416 0.000 0.000 0.584
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.4488     0.7364 0.000 0.724 0.000 0.036 0.040 0.200
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     6  0.2190     0.7057 0.060 0.000 0.000 0.040 0.000 0.900
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3383     0.7327 0.728 0.000 0.000 0.000 0.004 0.268
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     6  0.1713     0.7022 0.044 0.000 0.000 0.028 0.000 0.928
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1007     0.8727 0.000 0.000 0.956 0.000 0.044 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.2066     0.6839 0.024 0.000 0.000 0.072 0.000 0.904
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4763     0.5155 0.344 0.000 0.592 0.000 0.000 0.064
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.5926     0.3572 0.464 0.000 0.000 0.260 0.000 0.276
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0260     0.7331 0.992 0.000 0.000 0.000 0.008 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8797 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8891 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.2376     0.7133 0.068 0.000 0.000 0.000 0.044 0.888
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4634     0.7002 0.656 0.000 0.000 0.000 0.080 0.264
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3799     0.7206 0.704 0.000 0.000 0.000 0.020 0.276

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-NMF-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-NMF-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "hclust"]
# you can also extract it by
# res = res_list["MAD:hclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.306           0.590       0.838         0.2891 0.760   0.760
#> 3 3 0.158           0.653       0.778         0.6347 0.793   0.738
#> 4 4 0.359           0.500       0.744         0.2486 0.835   0.733
#> 5 5 0.397           0.500       0.701         0.1585 0.831   0.653
#> 6 6 0.454           0.478       0.659         0.0894 0.945   0.846

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.7745     0.6196 0.772 0.228
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.5408     0.7574 0.876 0.124
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.7139     0.6797 0.804 0.196
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1414     0.8012 0.980 0.020
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1414     0.8004 0.980 0.020
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0938     0.8013 0.988 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.8555     0.5346 0.720 0.280
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     1  0.9983    -0.4751 0.524 0.476
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5737     0.6887 0.864 0.136
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2236     0.7999 0.964 0.036
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0376     0.7984 0.996 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1184     0.8013 0.984 0.016
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.6148     0.7315 0.848 0.152
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.9996     0.5792 0.488 0.512
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.6148     0.7229 0.848 0.152
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#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0376     0.7997 0.996 0.004
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0376     0.8002 0.996 0.004
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.9710     0.7027 0.400 0.600
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     1  0.9983    -0.4751 0.524 0.476
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.9358     0.7175 0.352 0.648
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.2043     0.7946 0.968 0.032
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.4431     0.7744 0.908 0.092
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0672     0.8001 0.992 0.008
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.2603     0.7956 0.956 0.044
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000     0.7983 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     1  0.9983    -0.4751 0.524 0.476
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.1184     0.8017 0.984 0.016
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.2423     0.7973 0.960 0.040
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.5737     0.6887 0.864 0.136
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000     0.7983 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.9552     0.0715 0.624 0.376
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.1184     0.8019 0.984 0.016
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0376     0.7997 0.996 0.004
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.1414     0.8004 0.980 0.020
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.2043     0.7913 0.968 0.032
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.1184     0.8002 0.984 0.016
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.8081     0.5947 0.752 0.248
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.4431     0.7798 0.908 0.092
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.1633     0.5419 0.024 0.976
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.8861     0.7222 0.304 0.696
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.8267     0.5722 0.740 0.260
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.3114     0.7969 0.944 0.056
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0376     0.7984 0.996 0.004
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.9248     0.2898 0.660 0.340
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0938     0.8018 0.988 0.012
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.8555     0.5287 0.720 0.280
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.4562     0.7660 0.904 0.096
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.7815     0.6281 0.768 0.232
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.1184     0.8004 0.984 0.016
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.4939     0.7238 0.892 0.108
#> B2088466-FA5D-491C-9982-99B33683E66F     1  0.9954    -0.4396 0.540 0.460
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.8081     0.5608 0.752 0.248
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     1  0.9983    -0.4751 0.524 0.476
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     1  0.9983    -0.4751 0.524 0.476
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     1  0.9988    -0.4891 0.520 0.480
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.1184     0.8019 0.984 0.016
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.7745     0.6344 0.772 0.228
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.2778     0.7966 0.952 0.048
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0376     0.7998 0.996 0.004
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.7983 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.4690     0.7726 0.900 0.100
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.6148     0.7315 0.848 0.152
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0672     0.8009 0.992 0.008
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0672     0.8004 0.992 0.008
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     1  0.9983    -0.4751 0.524 0.476
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4022     0.7836 0.920 0.080
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.8016     0.6067 0.756 0.244
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     2  0.9944     0.1264 0.456 0.544
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.9209     0.7391 0.336 0.664
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     1  0.9922    -0.3945 0.552 0.448
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1633     0.7956 0.976 0.024
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.9993     0.5893 0.484 0.516
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     1  0.9977    -0.4562 0.528 0.472
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.1414     0.8033 0.980 0.020
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.1633     0.7993 0.976 0.024
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.9963     0.6244 0.464 0.536
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     1  0.9983    -0.4751 0.524 0.476
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.7602     0.6475 0.780 0.220
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.7983 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000     0.7983 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.9996     0.5805 0.488 0.512
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.2043     0.8008 0.968 0.032
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.9993     0.5893 0.484 0.516
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0672     0.8004 0.992 0.008
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0938     0.8009 0.988 0.012
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6343     0.7123 0.840 0.160
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1184     0.8017 0.984 0.016
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.7983 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     1  0.9983    -0.4756 0.524 0.476
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000     0.7983 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4298     0.7738 0.912 0.088
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.7983 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.3879     0.7853 0.924 0.076
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1184     0.8013 0.984 0.016
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0672     0.8013 0.992 0.008
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4431     0.7744 0.908 0.092
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.6048     0.7131 0.852 0.148
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1184     0.8009 0.984 0.016
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1843     0.8031 0.972 0.028
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.9129     0.3906 0.672 0.328
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4161     0.7782 0.916 0.084
#> 20EB9CC6-EABB-438A-9030-E766459996D1     1  0.9983    -0.4756 0.524 0.476
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.6148     0.7215 0.848 0.152
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.5629     0.7371 0.868 0.132
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.7983 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.7983 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.7983 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     1  1.0000    -0.5376 0.504 0.496
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.8016     0.6024 0.756 0.244
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.9881     0.2459 0.436 0.564
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.7299     0.6637 0.796 0.204
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.9286     0.0489 0.656 0.344
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.3431     0.7871 0.936 0.064
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.6801     0.6704 0.820 0.180
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0672     0.8005 0.992 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.7983 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.9977     0.6141 0.472 0.528
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0672     0.8004 0.992 0.008
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.8861     0.7222 0.304 0.696
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2236     0.7967 0.964 0.036
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     2  0.9896     0.1524 0.440 0.560
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.8386     0.5473 0.732 0.268
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.4562     0.7727 0.904 0.096
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.6148     0.7215 0.848 0.152
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4562     0.7659 0.904 0.096
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2043     0.8012 0.968 0.032
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.4161     0.7783 0.916 0.084
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.2423     0.8018 0.960 0.040
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6148     0.7215 0.848 0.152
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5519     0.7481 0.872 0.128
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0672     0.8005 0.992 0.008
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1633     0.7956 0.976 0.024
#> 206865A9-A67C-49A6-93AD-55D06E777559     1  0.9988    -0.4891 0.520 0.480
#> 26DABC83-DB30-452F-9BE2-366760CB138E     1  0.9983    -0.4751 0.524 0.476
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.4562     0.7706 0.904 0.096
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2603     0.7977 0.956 0.044
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1843     0.7937 0.972 0.028
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0938     0.8018 0.988 0.012

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1   0.965   -0.07263 0.468 0.272 0.260
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1   0.615    0.73119 0.764 0.056 0.180
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1   0.698    0.66015 0.708 0.072 0.220
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1   0.333    0.80095 0.904 0.020 0.076
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1   0.341    0.80417 0.900 0.020 0.080
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1   0.348    0.78055 0.904 0.048 0.048
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1   0.843    0.46370 0.604 0.136 0.260
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2   0.452    0.71034 0.180 0.816 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1   0.743    0.47004 0.688 0.212 0.100
#> 53062969-D209-490B-9C9B-5D297625E2AE     1   0.375    0.79539 0.884 0.020 0.096
#> B710293C-41D3-4A2E-8104-5402F91DD859     1   0.164    0.79393 0.964 0.016 0.020
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1   0.379    0.80484 0.892 0.048 0.060
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1   0.677    0.68710 0.724 0.068 0.208
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2   0.783    0.66413 0.160 0.672 0.168
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1   0.636    0.67905 0.728 0.040 0.232
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1   0.595    0.74691 0.772 0.048 0.180
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1   0.494    0.79046 0.840 0.056 0.104
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1   0.318    0.80203 0.912 0.024 0.064
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1   0.175    0.78884 0.960 0.012 0.028
#> C204D355-B876-4341-A111-36D48CBDD2A8     1   0.509    0.77340 0.836 0.092 0.072
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2   0.429    0.71023 0.180 0.820 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1   0.354    0.79044 0.888 0.012 0.100
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1   0.191    0.79207 0.956 0.016 0.028
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1   0.401    0.79117 0.876 0.028 0.096
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1   0.591    0.75321 0.784 0.060 0.156
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1   0.399    0.80633 0.872 0.020 0.108
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1   0.689    0.67468 0.716 0.072 0.212
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1   0.383    0.81020 0.888 0.036 0.076
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2   0.429    0.71023 0.180 0.820 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2   0.429    0.71023 0.180 0.820 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1   0.398    0.76198 0.884 0.068 0.048
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1   0.709    0.52509 0.716 0.188 0.096
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1   0.295    0.80363 0.920 0.020 0.060
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1   0.101    0.79590 0.980 0.012 0.008
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1   0.858    0.44191 0.596 0.152 0.252
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1   0.691    0.69185 0.728 0.092 0.180
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1   0.949   -0.05573 0.496 0.260 0.244
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2   0.435    0.70626 0.184 0.816 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1   0.399    0.78661 0.872 0.020 0.108
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1   0.238    0.79773 0.940 0.016 0.044
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2   0.719    0.48398 0.056 0.664 0.280
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1   0.556    0.77323 0.800 0.048 0.152
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1   0.640    0.71906 0.748 0.060 0.192
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1   0.379    0.80484 0.892 0.048 0.060
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1   0.232    0.79260 0.944 0.028 0.028
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1   0.504    0.76538 0.808 0.020 0.172
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#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2   0.630    0.15538 0.000 0.524 0.476
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2   0.682    0.25092 0.012 0.512 0.476
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1   0.804    0.47028 0.608 0.092 0.300
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1   0.433    0.79971 0.864 0.036 0.100
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1   0.191    0.80663 0.956 0.016 0.028
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1   0.817    0.22026 0.600 0.100 0.300
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1   0.260    0.80646 0.932 0.016 0.052
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1   0.853    0.45222 0.600 0.148 0.252
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1   0.506    0.77216 0.816 0.028 0.156
#> DD51C17C-300F-44A4-955A-C9BC85417842     1   0.763    0.57112 0.652 0.084 0.264
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1   0.300    0.80275 0.916 0.016 0.068
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1   0.618    0.65569 0.780 0.120 0.100
#> B2088466-FA5D-491C-9982-99B33683E66F     2   0.734    0.63099 0.224 0.688 0.088
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1   0.671    0.54941 0.672 0.032 0.296
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2   0.452    0.71009 0.180 0.816 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2   0.429    0.71023 0.180 0.820 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2   0.470    0.71064 0.180 0.812 0.008
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1   0.318    0.80727 0.908 0.016 0.076
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1   0.760    0.58078 0.656 0.084 0.260
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1   0.359    0.80598 0.896 0.028 0.076
#> B55743F2-4D63-4375-85D3-F58281CFD852     1   0.244    0.78614 0.940 0.028 0.032
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1   0.218    0.78768 0.948 0.020 0.032
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1   0.606    0.74793 0.776 0.064 0.160
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1   0.677    0.68710 0.724 0.068 0.208
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1   0.367    0.76641 0.896 0.064 0.040
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1   0.245    0.79716 0.936 0.012 0.052
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2   0.452    0.71009 0.180 0.816 0.004
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1   0.522    0.76874 0.816 0.040 0.144
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1   0.788    0.53539 0.636 0.096 0.268
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3   0.762    0.47118 0.368 0.052 0.580
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2   0.763    0.34927 0.044 0.524 0.432
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2   0.550    0.67534 0.208 0.772 0.020
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1   0.249    0.79679 0.936 0.016 0.048
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2   0.807    0.65223 0.160 0.652 0.188
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2   0.602    0.49274 0.288 0.700 0.012
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1   0.311    0.81296 0.916 0.028 0.056
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1   0.399    0.78661 0.872 0.020 0.108
#> CE539000-92D7-4622-9C8D-BC6E01310681     2   0.832    0.63954 0.160 0.628 0.212
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2   0.429    0.71023 0.180 0.820 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1   0.741    0.60117 0.668 0.076 0.256
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1   0.218    0.78649 0.948 0.020 0.032
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1   0.219    0.79180 0.948 0.024 0.028
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2   0.778    0.66500 0.164 0.676 0.160
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1   0.334    0.80560 0.908 0.032 0.060
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2   0.807    0.65223 0.160 0.652 0.188
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1   0.243    0.79447 0.940 0.024 0.036
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1   0.274    0.78719 0.928 0.020 0.052
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1   0.648    0.66327 0.716 0.040 0.244
#> 54504893-92C5-4328-85A8-2A882680B5E0     1   0.334    0.80294 0.908 0.032 0.060
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1   0.191    0.78845 0.956 0.016 0.028
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2   0.551    0.70282 0.188 0.784 0.028
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1   0.175    0.79141 0.960 0.012 0.028
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1   0.416    0.79179 0.848 0.008 0.144
#> D365A238-4739-4B54-9608-DC548F21C04E     1   0.175    0.78978 0.960 0.012 0.028
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1   0.511    0.75425 0.808 0.024 0.168
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1   0.326    0.80530 0.912 0.048 0.040
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1   0.203    0.80540 0.952 0.016 0.032
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1   0.528    0.75347 0.796 0.024 0.180
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1   0.583    0.72067 0.784 0.052 0.164
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1   0.290    0.80225 0.924 0.048 0.028
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1   0.324    0.80718 0.912 0.032 0.056
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1   0.770    0.26009 0.560 0.052 0.388
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1   0.509    0.75746 0.804 0.020 0.176
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2   0.556    0.69935 0.192 0.780 0.028
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1   0.632    0.67896 0.732 0.040 0.228
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1   0.699    0.65314 0.728 0.108 0.164
#> 9AF0E82E-E621-437A-8D19-700532B95090     1   0.205    0.78892 0.952 0.020 0.028
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1   0.101    0.79560 0.980 0.012 0.008
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1   0.158    0.78994 0.964 0.008 0.028
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2   0.517    0.70454 0.172 0.804 0.024
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1   0.892    0.35707 0.560 0.172 0.268
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3   0.903    0.48134 0.352 0.144 0.504
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1   0.775    0.57313 0.652 0.096 0.252
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2   0.695    0.30676 0.376 0.600 0.024
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1   0.418    0.80065 0.876 0.052 0.072
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1   0.937   -0.03306 0.500 0.300 0.200
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1   0.270    0.80378 0.928 0.016 0.056
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1   0.158    0.78994 0.964 0.008 0.028
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2   0.826    0.62677 0.152 0.632 0.216
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1   0.260    0.80550 0.932 0.016 0.052
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2   0.682    0.25092 0.012 0.512 0.476
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1   0.419    0.79077 0.876 0.060 0.064
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3   0.774    0.49906 0.356 0.060 0.584
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1   0.978   -0.14655 0.440 0.284 0.276
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1   0.547    0.76542 0.808 0.052 0.140
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1   0.661    0.66564 0.716 0.048 0.236
#> 6752EED9-7990-433F-A206-D5398C396471     1   0.481    0.77376 0.828 0.024 0.148
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1   0.375    0.80043 0.884 0.020 0.096
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1   0.534    0.77252 0.816 0.052 0.132
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1   0.557    0.75447 0.812 0.108 0.080
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1   0.661    0.66564 0.716 0.048 0.236
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1   0.635    0.70104 0.744 0.052 0.204
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1   0.270    0.80378 0.928 0.016 0.056
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1   0.217    0.79315 0.944 0.008 0.048
#> 206865A9-A67C-49A6-93AD-55D06E777559     2   0.452    0.71043 0.180 0.816 0.004
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2   0.429    0.71023 0.180 0.820 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1   0.576    0.75419 0.792 0.056 0.152
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1   0.432    0.78722 0.860 0.028 0.112
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1   0.265    0.79282 0.928 0.012 0.060
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1   0.301    0.80861 0.920 0.028 0.052

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.8522    -0.3845 0.340 0.024 0.284 0.352
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.6548     0.3633 0.616 0.012 0.296 0.076
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.6691    -0.1005 0.508 0.032 0.428 0.032
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4098     0.6265 0.784 0.012 0.204 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3991     0.6580 0.808 0.020 0.172 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.3622     0.6177 0.872 0.052 0.064 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.7520     0.3946 0.388 0.096 0.488 0.028
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0657     0.8189 0.012 0.984 0.000 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.7963     0.1736 0.560 0.264 0.092 0.084
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4955     0.5458 0.708 0.016 0.272 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1953     0.6705 0.940 0.012 0.044 0.004
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.5214     0.6437 0.772 0.032 0.160 0.036
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.6926     0.1250 0.544 0.020 0.368 0.068
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4707     0.6253 0.012 0.744 0.008 0.236
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5406     0.1400 0.480 0.012 0.508 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.6370     0.4345 0.644 0.024 0.280 0.052
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4751     0.6497 0.808 0.020 0.120 0.052
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4722     0.5918 0.748 0.020 0.228 0.004
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1109     0.6671 0.968 0.004 0.028 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.4931     0.6009 0.800 0.088 0.096 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0469     0.8190 0.012 0.988 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4482     0.5576 0.728 0.008 0.264 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1356     0.6715 0.960 0.008 0.032 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.5035     0.5177 0.696 0.016 0.284 0.004
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.6496     0.4467 0.640 0.016 0.268 0.076
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4319     0.6157 0.760 0.012 0.228 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.7112     0.0315 0.528 0.036 0.380 0.056
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.4715     0.6513 0.788 0.028 0.168 0.016
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0469     0.8190 0.012 0.988 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0992     0.8172 0.012 0.976 0.008 0.004
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.3711     0.6009 0.864 0.076 0.052 0.008
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.7654     0.2280 0.596 0.240 0.084 0.080
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4436     0.6016 0.764 0.020 0.216 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1489     0.6785 0.952 0.004 0.044 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     3  0.7732     0.3961 0.384 0.116 0.472 0.028
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.6899    -0.0760 0.508 0.060 0.412 0.020
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.9056     0.1925 0.332 0.272 0.336 0.060
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0707     0.8143 0.020 0.980 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.4883     0.5170 0.696 0.016 0.288 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1722     0.6769 0.944 0.008 0.048 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.5384     0.3257 0.004 0.420 0.008 0.568
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.5587     0.5745 0.740 0.028 0.188 0.044
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.6840     0.3271 0.600 0.032 0.308 0.060
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5214     0.6437 0.772 0.032 0.160 0.036
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.2353     0.6589 0.928 0.024 0.040 0.008
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4917     0.4406 0.656 0.008 0.336 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.5766     0.4511 0.732 0.172 0.080 0.016
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0657     0.8189 0.012 0.984 0.000 0.004
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.5120     0.6194 0.776 0.028 0.160 0.036
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.4856     0.6183 0.008 0.272 0.008 0.712
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4121     0.6713 0.844 0.020 0.100 0.036
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.7011     0.3486 0.008 0.592 0.136 0.264
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.6179    -0.0342 0.504 0.012 0.456 0.028
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.7182     0.3439 0.404 0.028 0.500 0.068
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.4908     0.5114 0.692 0.016 0.292 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.8512     0.4141 0.212 0.040 0.444 0.304
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.6672     0.2070 0.456 0.004 0.468 0.072
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.7710     0.2265 0.592 0.240 0.088 0.080
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3455     0.7623 0.012 0.880 0.044 0.064
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3810     0.6261 0.804 0.008 0.188 0.000
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#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.1297     0.5879 0.000 0.016 0.020 0.964
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.7045     0.4056 0.368 0.028 0.540 0.064
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.5563     0.5650 0.704 0.020 0.248 0.028
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.3004     0.6799 0.884 0.008 0.100 0.008
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.7835     0.0940 0.556 0.068 0.284 0.092
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.3757     0.6562 0.828 0.020 0.152 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.7697     0.3924 0.388 0.112 0.472 0.028
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.5653     0.4804 0.656 0.016 0.308 0.020
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.7214     0.2666 0.448 0.044 0.460 0.048
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.4214     0.6289 0.780 0.016 0.204 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.6403     0.4675 0.724 0.116 0.084 0.076
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.4804     0.7077 0.056 0.812 0.028 0.104
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.6256     0.1468 0.580 0.004 0.360 0.056
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0657     0.8185 0.012 0.984 0.000 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0469     0.8190 0.012 0.988 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.1509     0.8123 0.012 0.960 0.008 0.020
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.3006     0.6745 0.888 0.008 0.092 0.012
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.7278    -0.2550 0.456 0.044 0.448 0.052
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.4483     0.6669 0.828 0.032 0.104 0.036
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.2214     0.6472 0.928 0.028 0.044 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.1913     0.6545 0.940 0.020 0.040 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.6731     0.4037 0.620 0.020 0.280 0.080
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.6926     0.1250 0.544 0.020 0.368 0.068
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.3648     0.6138 0.868 0.068 0.056 0.008
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.2302     0.6820 0.924 0.008 0.060 0.008
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0657     0.8185 0.012 0.984 0.000 0.004
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5723     0.3662 0.624 0.032 0.340 0.004
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.7253     0.3390 0.412 0.052 0.492 0.044
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.4439     0.3242 0.140 0.004 0.808 0.048
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.4074     0.6348 0.004 0.196 0.008 0.792
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2353     0.7873 0.040 0.928 0.008 0.024
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1722     0.6729 0.944 0.008 0.048 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4813     0.5848 0.012 0.716 0.004 0.268
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3790     0.5968 0.132 0.840 0.024 0.004
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.4000     0.6706 0.828 0.012 0.144 0.016
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4908     0.5120 0.692 0.016 0.292 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.5245     0.4770 0.016 0.660 0.004 0.320
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0469     0.8190 0.012 0.988 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.7205    -0.2049 0.472 0.040 0.436 0.052
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.2002     0.6512 0.936 0.020 0.044 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.2153     0.6607 0.936 0.020 0.036 0.008
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.4318     0.6633 0.012 0.776 0.004 0.208
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4330     0.6751 0.836 0.032 0.100 0.032
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4813     0.5848 0.012 0.716 0.004 0.268
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.2570     0.6722 0.916 0.028 0.052 0.004
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.2604     0.6517 0.916 0.016 0.056 0.012
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.5378     0.2355 0.448 0.012 0.540 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.3363     0.6701 0.884 0.024 0.072 0.020
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.1256     0.6695 0.964 0.008 0.028 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.1707     0.8091 0.020 0.952 0.004 0.024
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1706     0.6633 0.948 0.016 0.036 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4567     0.6102 0.748 0.004 0.236 0.012
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.1109     0.6679 0.968 0.004 0.028 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5256     0.3013 0.596 0.012 0.392 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4925     0.6563 0.796 0.032 0.136 0.036
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3606     0.6624 0.840 0.020 0.140 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.5256     0.2649 0.596 0.012 0.392 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5947     0.3281 0.644 0.028 0.308 0.020
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4666     0.6666 0.820 0.052 0.100 0.028
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3824     0.6743 0.852 0.036 0.104 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.5675     0.4466 0.312 0.016 0.652 0.020
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4990     0.4085 0.640 0.008 0.352 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.1920     0.8057 0.028 0.944 0.004 0.024
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.5407     0.1371 0.484 0.012 0.504 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.7214     0.4419 0.644 0.044 0.148 0.164
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1388     0.6675 0.960 0.012 0.028 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.1978     0.6804 0.928 0.004 0.068 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1022     0.6711 0.968 0.000 0.032 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2384     0.7989 0.016 0.928 0.016 0.040
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.8225     0.3737 0.368 0.032 0.432 0.168
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6511     0.3259 0.152 0.064 0.708 0.076
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.7056     0.3467 0.400 0.028 0.512 0.060
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5353     0.4938 0.200 0.744 0.028 0.028
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5633     0.6343 0.752 0.052 0.160 0.036
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.7859    -0.2298 0.420 0.024 0.136 0.420
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4317     0.6209 0.784 0.016 0.196 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0817     0.6664 0.976 0.000 0.024 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.5632     0.3984 0.020 0.620 0.008 0.352
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3597     0.6596 0.836 0.016 0.148 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1297     0.5879 0.000 0.016 0.020 0.964
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.5327     0.6451 0.784 0.036 0.112 0.068
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.4254     0.2833 0.120 0.004 0.824 0.052
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.8512     0.4141 0.212 0.040 0.444 0.304
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.5947     0.3416 0.616 0.044 0.336 0.004
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5653     0.2357 0.448 0.016 0.532 0.004
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5112     0.4855 0.668 0.012 0.316 0.004
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5148     0.5737 0.720 0.020 0.248 0.012
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.5252     0.6223 0.776 0.016 0.128 0.080
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5732     0.5700 0.748 0.108 0.124 0.020
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.5653     0.2357 0.448 0.016 0.532 0.004
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6182    -0.0595 0.500 0.012 0.460 0.028
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4317     0.6209 0.784 0.016 0.196 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1302     0.6674 0.956 0.000 0.044 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0657     0.8181 0.012 0.984 0.004 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0469     0.8190 0.012 0.988 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6145     0.5310 0.692 0.016 0.212 0.080
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5202     0.4741 0.668 0.016 0.312 0.004
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.2198     0.6562 0.920 0.008 0.072 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3653     0.6708 0.844 0.028 0.128 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.8136    0.30645 0.212 0.008 0.364 0.332 0.084
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.6784   -0.19788 0.436 0.000 0.412 0.032 0.120
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5909    0.64028 0.284 0.024 0.628 0.016 0.048
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4268    0.47724 0.708 0.004 0.272 0.000 0.016
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4164    0.56425 0.764 0.012 0.200 0.000 0.024
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4427    0.51606 0.752 0.032 0.016 0.000 0.200
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5841    0.65269 0.168 0.076 0.700 0.016 0.040
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0486    0.77753 0.004 0.988 0.004 0.004 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.6846    0.70759 0.272 0.180 0.020 0.004 0.524
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4798    0.30941 0.624 0.004 0.352 0.004 0.016
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2977    0.64231 0.876 0.008 0.040 0.000 0.076
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.5475    0.53536 0.696 0.008 0.212 0.028 0.056
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.6454    0.52339 0.340 0.008 0.544 0.028 0.080
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.3906    0.58041 0.000 0.744 0.000 0.240 0.016
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.4044    0.64908 0.252 0.004 0.732 0.000 0.012
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.6637   -0.18686 0.460 0.008 0.408 0.016 0.108
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5937    0.50553 0.660 0.004 0.176 0.020 0.140
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4654    0.39438 0.664 0.008 0.312 0.004 0.012
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.2983    0.61958 0.864 0.000 0.040 0.000 0.096
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.6268    0.51587 0.664 0.064 0.092 0.008 0.172
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0162    0.77765 0.004 0.996 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4464    0.33134 0.632 0.004 0.356 0.000 0.008
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1907    0.63380 0.928 0.000 0.028 0.000 0.044
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4598    0.21942 0.600 0.004 0.388 0.004 0.004
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.6874    0.11735 0.508 0.004 0.332 0.036 0.120
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.5466    0.42441 0.628 0.004 0.284 0.000 0.084
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.6356    0.58948 0.312 0.020 0.580 0.024 0.064
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5278    0.51762 0.684 0.008 0.244 0.012 0.052
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0162    0.77765 0.004 0.996 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0865    0.77320 0.000 0.972 0.000 0.004 0.024
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4243    0.50650 0.772 0.056 0.004 0.000 0.168
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.6908    0.70612 0.336 0.172 0.016 0.004 0.472
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4280    0.40195 0.676 0.008 0.312 0.000 0.004
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2514    0.64418 0.896 0.000 0.060 0.000 0.044
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     3  0.6029    0.64340 0.168 0.096 0.684 0.016 0.036
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6081    0.61193 0.320 0.044 0.592 0.016 0.028
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.8469    0.41641 0.148 0.192 0.244 0.012 0.404
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0740    0.77541 0.008 0.980 0.004 0.000 0.008
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.4438    0.25319 0.608 0.004 0.384 0.000 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.2830    0.63241 0.876 0.000 0.080 0.000 0.044
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.4595    0.35538 0.000 0.400 0.004 0.588 0.008
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.6649    0.10356 0.516 0.008 0.328 0.012 0.136
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.6938    0.34559 0.408 0.016 0.448 0.024 0.104
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.5475    0.53536 0.696 0.008 0.212 0.028 0.056
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.3835    0.61434 0.812 0.004 0.040 0.004 0.140
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.5295    0.21206 0.464 0.000 0.488 0.000 0.048
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.6567   -0.09874 0.568 0.140 0.032 0.000 0.260
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0324    0.77757 0.004 0.992 0.004 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.6333    0.34430 0.584 0.008 0.256 0.008 0.144
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.3963    0.63178 0.000 0.256 0.004 0.732 0.008
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4906    0.59671 0.760 0.004 0.132 0.024 0.080
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#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.1907    0.63380 0.928 0.000 0.028 0.000 0.044
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0865    0.77320 0.000 0.972 0.000 0.004 0.024
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.4806    0.59095 0.744 0.016 0.052 0.004 0.184
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.5438    0.58790 0.740 0.012 0.108 0.040 0.100
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.6855    0.70549 0.268 0.184 0.020 0.004 0.524
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.3465    0.59252 0.840 0.052 0.004 0.000 0.104
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     5  0.8153    0.54728 0.200 0.240 0.048 0.048 0.464
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.5009    0.57873 0.716 0.004 0.112 0.000 0.168
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.4273    0.55383 0.748 0.004 0.212 0.000 0.036
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.4892    0.58982 0.752 0.004 0.156 0.020 0.068
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.3648    0.60577 0.824 0.000 0.084 0.000 0.092
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.4340    0.60142 0.780 0.000 0.148 0.012 0.060
#> 9EEECA0E-530D-4724-B016-A716F0782148     3  0.7312    0.61286 0.192 0.020 0.572 0.152 0.064
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.5828    0.23646 0.432 0.016 0.496 0.000 0.056
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.7006    0.14652 0.000 0.416 0.212 0.016 0.356
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.0693    0.54015 0.000 0.000 0.012 0.980 0.008
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.5853    0.65531 0.164 0.020 0.704 0.044 0.068
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.5932    0.26051 0.556 0.008 0.364 0.012 0.060
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.4265    0.61538 0.776 0.004 0.168 0.004 0.048
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.5491    0.59661 0.300 0.004 0.080 0.000 0.616
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.4106    0.57009 0.768 0.008 0.196 0.000 0.028
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.5979    0.64534 0.168 0.092 0.688 0.016 0.036
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.5573    0.01447 0.520 0.008 0.432 0.016 0.024
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.5875    0.66428 0.224 0.028 0.672 0.024 0.052
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.4479    0.49540 0.704 0.004 0.264 0.000 0.028
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.6050   -0.11737 0.528 0.060 0.020 0.004 0.388
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.4550    0.68111 0.020 0.804 0.036 0.100 0.040
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.6712    0.29763 0.392 0.000 0.448 0.020 0.140
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0775    0.77673 0.004 0.980 0.004 0.008 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0162    0.77765 0.004 0.996 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.1310    0.76872 0.000 0.956 0.000 0.024 0.020
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5009    0.57873 0.716 0.004 0.112 0.000 0.168
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.5945    0.66007 0.232 0.028 0.664 0.028 0.048
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.5599    0.56916 0.684 0.008 0.100 0.012 0.196
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.3099    0.60599 0.848 0.012 0.008 0.000 0.132
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.2645    0.61974 0.884 0.012 0.008 0.000 0.096
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.6964   -0.00313 0.480 0.004 0.360 0.040 0.116
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.6454    0.52339 0.340 0.008 0.544 0.028 0.080
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4014    0.55541 0.804 0.060 0.008 0.000 0.128
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.3461    0.64062 0.848 0.008 0.068 0.000 0.076
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0775    0.77673 0.004 0.980 0.004 0.008 0.004
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5177   -0.14760 0.512 0.016 0.456 0.000 0.016
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.5488    0.67156 0.188 0.032 0.716 0.028 0.036
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.5620    0.22360 0.068 0.000 0.604 0.012 0.316
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.3280    0.65267 0.000 0.184 0.004 0.808 0.004
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2050    0.74804 0.008 0.920 0.000 0.008 0.064
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.3574    0.61997 0.836 0.004 0.088 0.000 0.072
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4090    0.53970 0.000 0.716 0.000 0.268 0.016
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3658    0.57933 0.112 0.832 0.044 0.000 0.012
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.5057    0.54611 0.684 0.004 0.240 0.000 0.072
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4449    0.24292 0.604 0.004 0.388 0.000 0.004
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.4538    0.42389 0.004 0.648 0.004 0.336 0.008
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0162    0.77765 0.004 0.996 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.6253    0.64635 0.260 0.024 0.624 0.024 0.068
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.3099    0.61260 0.848 0.012 0.008 0.000 0.132
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.3508    0.62040 0.832 0.004 0.028 0.004 0.132
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.3745    0.62460 0.000 0.780 0.000 0.196 0.024
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.5230    0.62592 0.740 0.012 0.112 0.016 0.120
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4090    0.53970 0.000 0.716 0.000 0.268 0.016
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.3573    0.63635 0.844 0.020 0.040 0.000 0.096
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.3972    0.57656 0.788 0.008 0.032 0.000 0.172
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.3643    0.66351 0.212 0.004 0.776 0.000 0.008
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.4928    0.58703 0.724 0.012 0.072 0.000 0.192
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.1774    0.63383 0.932 0.000 0.016 0.000 0.052
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.1533    0.76874 0.004 0.952 0.016 0.024 0.004
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.3122    0.62980 0.852 0.004 0.024 0.000 0.120
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.5781    0.33316 0.576 0.000 0.308 0.000 0.116
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.2104    0.62930 0.916 0.000 0.024 0.000 0.060
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.4973    0.35302 0.408 0.004 0.564 0.000 0.024
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5222    0.56170 0.724 0.008 0.188 0.028 0.052
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.4187    0.57032 0.764 0.008 0.196 0.000 0.032
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.4798    0.48893 0.404 0.004 0.576 0.000 0.016
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.5548    0.33657 0.452 0.008 0.500 0.008 0.032
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5430    0.60023 0.732 0.020 0.140 0.020 0.088
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4500    0.62770 0.784 0.020 0.100 0.000 0.096
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.5186    0.62341 0.156 0.004 0.712 0.004 0.124
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.5106    0.24155 0.456 0.000 0.508 0.000 0.036
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.1898    0.76712 0.008 0.940 0.016 0.024 0.012
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.4170    0.64061 0.272 0.004 0.712 0.000 0.012
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.7640    0.28970 0.536 0.012 0.200 0.140 0.112
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2141    0.62729 0.916 0.004 0.016 0.000 0.064
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.3033    0.64118 0.864 0.000 0.084 0.000 0.052
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1648    0.63304 0.940 0.000 0.020 0.000 0.040
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2027    0.75599 0.000 0.928 0.008 0.040 0.024
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.7257    0.61557 0.192 0.020 0.576 0.152 0.060
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6075    0.21821 0.020 0.056 0.660 0.040 0.224
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.5505    0.66660 0.184 0.020 0.716 0.044 0.036
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5018    0.43976 0.116 0.716 0.000 0.004 0.164
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6235    0.48938 0.628 0.028 0.244 0.012 0.088
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.8062   -0.18171 0.336 0.004 0.148 0.388 0.124
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4300    0.46962 0.712 0.004 0.268 0.004 0.012
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.2409    0.62554 0.900 0.000 0.032 0.000 0.068
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.4709    0.33727 0.000 0.612 0.000 0.364 0.024
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3880    0.57916 0.784 0.004 0.184 0.000 0.028
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0693    0.54015 0.000 0.000 0.012 0.980 0.008
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.5970    0.54581 0.684 0.008 0.172 0.048 0.088
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5515    0.18360 0.052 0.000 0.608 0.016 0.324
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.7186    0.42842 0.076 0.032 0.556 0.276 0.060
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.5403   -0.14689 0.512 0.028 0.444 0.000 0.016
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.3840    0.66378 0.208 0.008 0.772 0.000 0.012
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5628    0.02947 0.508 0.004 0.424 0.000 0.064
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4891    0.35155 0.632 0.008 0.340 0.008 0.012
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.6321    0.44973 0.636 0.004 0.180 0.036 0.144
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.6789    0.46964 0.624 0.080 0.136 0.008 0.152
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.3840    0.66378 0.208 0.008 0.772 0.000 0.012
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4847    0.63973 0.268 0.000 0.684 0.008 0.040
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4300    0.46962 0.712 0.004 0.268 0.004 0.012
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.3532    0.60174 0.832 0.000 0.076 0.000 0.092
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0451    0.77710 0.004 0.988 0.000 0.000 0.008
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0324    0.77762 0.004 0.992 0.000 0.000 0.004
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6761    0.25557 0.556 0.004 0.280 0.040 0.120
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4531    0.10656 0.568 0.004 0.424 0.004 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4424    0.56535 0.768 0.004 0.084 0.000 0.144
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4290    0.60458 0.780 0.012 0.156 0.000 0.052

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.8428   -0.23312 0.096 0.000 0.300 0.312 0.132 0.160
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.7659    0.27763 0.256 0.000 0.356 0.004 0.192 0.192
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5540    0.60198 0.176 0.008 0.668 0.000 0.052 0.096
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4269    0.39973 0.636 0.004 0.340 0.000 0.016 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4159    0.50708 0.704 0.000 0.252 0.000 0.040 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4194    0.44413 0.692 0.012 0.016 0.000 0.276 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4953    0.49303 0.044 0.044 0.748 0.004 0.032 0.128
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0405    0.81758 0.000 0.988 0.000 0.008 0.000 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4414    0.71792 0.148 0.080 0.000 0.012 0.752 0.008
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.5157    0.27108 0.544 0.004 0.392 0.000 0.016 0.044
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3656    0.61061 0.824 0.000 0.040 0.004 0.096 0.036
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6544    0.46015 0.564 0.004 0.240 0.016 0.116 0.060
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.6850    0.51041 0.176 0.000 0.520 0.004 0.112 0.188
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4225    0.63407 0.000 0.712 0.000 0.240 0.036 0.012
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.3003    0.60233 0.104 0.000 0.852 0.000 0.016 0.028
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.7349    0.28061 0.276 0.004 0.412 0.000 0.136 0.172
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.7226    0.33822 0.468 0.000 0.144 0.008 0.232 0.148
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4492    0.33734 0.604 0.004 0.368 0.004 0.016 0.004
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.2748    0.55756 0.856 0.000 0.016 0.000 0.120 0.008
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.7212    0.41683 0.516 0.064 0.080 0.000 0.240 0.100
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.81701 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4116    0.27954 0.572 0.000 0.416 0.000 0.012 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2113    0.59243 0.916 0.004 0.028 0.000 0.044 0.008
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4565    0.12706 0.516 0.004 0.460 0.004 0.012 0.004
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.7796   -0.07887 0.320 0.000 0.284 0.008 0.200 0.188
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.5520    0.35171 0.556 0.004 0.316 0.000 0.120 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.6347    0.58027 0.168 0.004 0.584 0.000 0.084 0.160
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.6527    0.39103 0.524 0.000 0.284 0.008 0.112 0.072
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#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.2859    0.56990 0.060 0.000 0.872 0.000 0.020 0.048
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5155    0.61841 0.144 0.000 0.708 0.004 0.080 0.064
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.4558    0.41652 0.640 0.004 0.320 0.000 0.016 0.020
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.3536    0.53046 0.812 0.000 0.064 0.000 0.116 0.008
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0260    0.81680 0.000 0.992 0.000 0.000 0.000 0.008
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0260    0.81654 0.000 0.992 0.000 0.000 0.000 0.008
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.7803    0.01831 0.336 0.000 0.252 0.008 0.192 0.212
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.4573   -0.03818 0.480 0.004 0.496 0.004 0.012 0.004
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.4248    0.48427 0.752 0.004 0.060 0.000 0.172 0.012
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4308    0.56226 0.740 0.004 0.172 0.000 0.080 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-hclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "kmeans"]
# you can also extract it by
# res = res_list["MAD:kmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.990       0.996         0.3970 0.603   0.603
#> 3 3 0.602           0.750       0.875         0.5796 0.750   0.592
#> 4 4 0.617           0.691       0.780         0.1441 0.800   0.519
#> 5 5 0.729           0.730       0.796         0.0832 0.908   0.684
#> 6 6 0.716           0.670       0.794         0.0505 0.933   0.723

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.8608      0.600 0.716 0.284
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.998 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.998 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.998 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.998 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.998 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.991 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.991 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.998 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.998 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.998 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.998 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.998 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.991 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.998 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.998 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.998 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.998 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.998 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.998 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.991 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.998 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.998 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.998 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.998 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.998 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.998 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.998 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.991 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.991 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.998 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.998 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.998 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.998 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.991 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.998 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.998 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.991 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.998 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.998 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.991 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.998 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.998 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.998 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.998 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.998 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.998 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.991 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.998 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.991 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.998 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.991 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.998 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.998 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.998 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000      0.998 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.998 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000      0.998 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.991 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.998 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.998 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000      0.998 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.998 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.998 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.991 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.998 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.998 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.998 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.998 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.991 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.998 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.998 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.998 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.998 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000      0.998 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.998 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.998 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.991 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000      0.998 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000      0.991 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.998 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.0000      0.991 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.998 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.998 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.998 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000      0.998 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000      0.998 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000      0.991 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000      0.991 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.998 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000      0.998 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.998 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000      0.991 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.998 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000      0.998 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000      0.998 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0000      0.998 1.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0000      0.998 1.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000      0.998 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.998 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000      0.998 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.991 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.991 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000      0.998 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000      0.998 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.991 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.6343      0.810 0.160 0.840
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#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.991 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.998 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.998 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.998 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.2603      0.948 0.044 0.956
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.998 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.998 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000      0.998 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.998 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000      0.998 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.998 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.998 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.998 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.998 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.991 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.991 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.998 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.998 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.998 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.998 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.4921     0.7323 0.084 0.072 0.844
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.2261     0.8040 0.068 0.000 0.932
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2165     0.8044 0.064 0.000 0.936
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4452     0.7412 0.808 0.000 0.192
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1753     0.8136 0.952 0.000 0.048
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0592     0.8134 0.988 0.000 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5397     0.4897 0.000 0.280 0.720
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9630 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.3116     0.7604 0.892 0.000 0.108
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4750     0.7164 0.784 0.000 0.216
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.8154 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4504     0.7376 0.804 0.000 0.196
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2261     0.8040 0.068 0.000 0.932
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1753     0.9579 0.000 0.952 0.048
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.3340     0.7796 0.120 0.000 0.880
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2261     0.8040 0.068 0.000 0.932
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.5948     0.4998 0.360 0.000 0.640
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4399     0.7445 0.812 0.000 0.188
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0237     0.8148 0.996 0.000 0.004
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.6168     0.1344 0.588 0.000 0.412
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9630 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1860     0.8129 0.948 0.000 0.052
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4346     0.7482 0.816 0.000 0.184
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4974     0.6912 0.764 0.000 0.236
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2261     0.8040 0.068 0.000 0.932
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4702     0.6354 0.788 0.000 0.212
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1860     0.8003 0.052 0.000 0.948
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.2165     0.8044 0.064 0.000 0.936
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9630 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9630 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.8154 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0592     0.8134 0.988 0.000 0.012
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4452     0.7412 0.808 0.000 0.192
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0592     0.8134 0.988 0.000 0.012
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9630 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.6008     0.4587 0.372 0.000 0.628
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.6509    -0.1095 0.524 0.004 0.472
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9630 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.4452     0.7412 0.808 0.000 0.192
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1529     0.8157 0.960 0.000 0.040
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.1753     0.9579 0.000 0.952 0.048
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.4291     0.7409 0.180 0.000 0.820
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0892     0.7743 0.020 0.000 0.980
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4504     0.7376 0.804 0.000 0.196
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.5058     0.5624 0.756 0.000 0.244
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.5591     0.4937 0.696 0.000 0.304
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.8154 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9630 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.2261     0.8040 0.068 0.000 0.932
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1753     0.9579 0.000 0.952 0.048
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4291     0.7506 0.820 0.000 0.180
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.1289     0.9599 0.000 0.968 0.032
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.2165     0.8044 0.064 0.000 0.936
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5905     0.5025 0.352 0.000 0.648
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.5650     0.5637 0.688 0.000 0.312
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1411     0.7958 0.036 0.000 0.964
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.2165     0.8044 0.064 0.000 0.936
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1031     0.8064 0.976 0.000 0.024
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9630 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.4452     0.7412 0.808 0.000 0.192
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0592     0.8134 0.988 0.000 0.012
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.2066     0.8117 0.940 0.000 0.060
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.5178     0.5334 0.744 0.000 0.256
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.4504     0.7376 0.804 0.000 0.196
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9630 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.2165     0.8044 0.064 0.000 0.936
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3879     0.7696 0.848 0.000 0.152
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.3192     0.7377 0.888 0.000 0.112
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.2261     0.8040 0.068 0.000 0.932
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.1753     0.9579 0.000 0.952 0.048
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0592     0.8134 0.988 0.000 0.012
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.1289     0.8052 0.968 0.000 0.032
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.6260     0.0253 0.552 0.000 0.448
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.4452     0.7412 0.808 0.000 0.192
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4887     0.7014 0.772 0.000 0.228
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0592     0.8134 0.988 0.000 0.012
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0592     0.8134 0.988 0.000 0.012
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9630 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.1529     0.7891 0.040 0.000 0.960
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.1753     0.9579 0.000 0.952 0.048
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.1643     0.8150 0.956 0.000 0.044
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6180     0.3380 0.008 0.332 0.660
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.1753     0.7964 0.952 0.000 0.048
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0592     0.8134 0.988 0.000 0.012
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2165     0.8101 0.936 0.000 0.064
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0237     0.8153 0.996 0.000 0.004
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4121     0.7582 0.832 0.000 0.168
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.1753     0.9579 0.000 0.952 0.048
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.1529     0.9589 0.000 0.960 0.040
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.5016     0.6513 0.240 0.000 0.760
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0424     0.8142 0.992 0.000 0.008
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.5216     0.5356 0.740 0.000 0.260
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1753     0.9579 0.000 0.952 0.048
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.6204     0.3716 0.424 0.000 0.576
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0237     0.8148 0.996 0.000 0.004
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.8154 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.6008     0.4499 0.372 0.000 0.628
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.4750     0.7236 0.784 0.000 0.216
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000     0.8154 1.000 0.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.2261     0.8040 0.068 0.000 0.932
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.3816     0.7632 0.148 0.000 0.852
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9630 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9630 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0424     0.8150 0.992 0.000 0.008
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000     0.8154 1.000 0.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9630 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.4645     0.6545 0.816 0.176 0.008
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.2261     0.8040 0.068 0.000 0.932
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0592     0.8134 0.988 0.000 0.012
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.1753     0.9579 0.000 0.952 0.048
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9630 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000     0.8154 1.000 0.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.2165     0.8044 0.064 0.000 0.936
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.1860     0.8003 0.052 0.000 0.948
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     3  0.6225     0.2992 0.432 0.000 0.568
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0592     0.8134 0.988 0.000 0.012
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.1643     0.7985 0.956 0.000 0.044
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000     0.8154 1.000 0.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.4504     0.7381 0.804 0.000 0.196
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.2165     0.8101 0.936 0.000 0.064
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.5988     0.4911 0.632 0.000 0.368
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.6026     0.4405 0.624 0.000 0.376
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     3  0.4504     0.7272 0.196 0.000 0.804
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.4504     0.7376 0.804 0.000 0.196
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.5760     0.4642 0.328 0.000 0.672
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.1753     0.9579 0.000 0.952 0.048
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.1411     0.9594 0.000 0.964 0.036
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0892     0.8138 0.980 0.000 0.020
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.5621     0.5832 0.308 0.000 0.692
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     3  0.6111     0.3484 0.396 0.000 0.604
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.3816     0.7769 0.852 0.000 0.148
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0892     0.8138 0.980 0.000 0.020
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000     0.9630 0.000 1.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.5968     0.3019 0.636 0.000 0.364
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0237     0.9628 0.000 0.996 0.004
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000     0.9630 0.000 1.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.4504     0.7376 0.804 0.000 0.196
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000     0.9630 0.000 1.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.1753     0.9579 0.000 0.952 0.048
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.3879     0.7696 0.848 0.000 0.152
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.6244     0.2557 0.560 0.000 0.440
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.1753     0.9579 0.000 0.952 0.048
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#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9630 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2165     0.8027 0.064 0.000 0.936
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.6126     0.3903 0.400 0.000 0.600
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0237     0.8148 0.996 0.000 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1753     0.8136 0.952 0.000 0.048

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4883    -0.0197 0.000 0.016 0.288 0.696
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0672     0.8639 0.008 0.000 0.984 0.008
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.3428     0.8058 0.012 0.000 0.844 0.144
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     4  0.6007     0.7893 0.340 0.000 0.056 0.604
#> 78F79407-D49F-4FA2-B09F-0665C502827C     4  0.4961     0.6749 0.448 0.000 0.000 0.552
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0188     0.7742 0.996 0.000 0.000 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2635     0.8215 0.000 0.076 0.904 0.020
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4453     0.5995 0.744 0.000 0.012 0.244
#> 53062969-D209-490B-9C9B-5D297625E2AE     4  0.5926     0.7853 0.308 0.000 0.060 0.632
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0707     0.7659 0.980 0.000 0.000 0.020
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.5409    -0.0836 0.012 0.000 0.492 0.496
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0657     0.8626 0.012 0.000 0.984 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.3074     0.7430 0.152 0.000 0.848 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     4  0.5769     0.7707 0.376 0.000 0.036 0.588
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1022     0.7687 0.968 0.000 0.000 0.032
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.4994     0.0863 0.520 0.000 0.480 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     4  0.4961     0.6798 0.448 0.000 0.000 0.552
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     4  0.5884     0.7805 0.364 0.000 0.044 0.592
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     4  0.5905     0.7843 0.304 0.000 0.060 0.636
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0657     0.8626 0.012 0.000 0.984 0.004
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4986     0.5922 0.740 0.000 0.044 0.216
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3402     0.7365 0.004 0.000 0.832 0.164
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0336     0.7728 0.992 0.000 0.000 0.008
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 904EDF2E-411E-43BD-901D-46129AFA283A     4  0.6000     0.7857 0.356 0.000 0.052 0.592
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0469     0.7719 0.988 0.000 0.000 0.012
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     4  0.6585     0.7238 0.188 0.000 0.180 0.632
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5949     0.4773 0.644 0.000 0.068 0.288
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     4  0.5986     0.7871 0.320 0.000 0.060 0.620
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.4967    -0.4490 0.548 0.000 0.000 0.452
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.2773     0.7906 0.116 0.000 0.880 0.004
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0376     0.8597 0.004 0.000 0.992 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4819     0.4514 0.652 0.000 0.344 0.004
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.6106     0.2138 0.604 0.000 0.064 0.332
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0469     0.7716 0.988 0.000 0.000 0.012
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0779     0.8622 0.016 0.000 0.980 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.4883     0.8317 0.000 0.696 0.016 0.288
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     4  0.5626     0.7628 0.384 0.000 0.028 0.588
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.4831     0.8341 0.000 0.704 0.016 0.280
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> F941890E-AB33-478F-8C97-1C785DD9428F     4  0.6739     0.6902 0.172 0.000 0.216 0.612
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     4  0.6036     0.7816 0.292 0.000 0.072 0.636
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1661     0.8535 0.004 0.000 0.944 0.052
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0469     0.7741 0.988 0.000 0.000 0.012
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.7744 1.000 0.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.4866    -0.2629 0.596 0.000 0.000 0.404
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.4328     0.5956 0.748 0.000 0.244 0.008
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     4  0.5973     0.7890 0.332 0.000 0.056 0.612
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.1743     0.8521 0.004 0.000 0.940 0.056
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     4  0.5279     0.7443 0.400 0.000 0.012 0.588
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.2944     0.7154 0.868 0.000 0.128 0.004
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.1022     0.7687 0.968 0.000 0.000 0.032
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0921     0.7700 0.972 0.000 0.028 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.5039     0.2871 0.592 0.000 0.404 0.004
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0188     0.7741 0.996 0.000 0.000 0.004
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0376     0.8624 0.004 0.000 0.992 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.5113     0.8252 0.000 0.684 0.024 0.292
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4776    -0.1282 0.624 0.000 0.000 0.376
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.7140     0.4539 0.008 0.240 0.588 0.164
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.1743     0.7565 0.940 0.000 0.004 0.056
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     4  0.4888     0.7308 0.412 0.000 0.000 0.588
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.3726     0.4503 0.788 0.000 0.000 0.212
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     4  0.5571     0.7544 0.396 0.000 0.024 0.580
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.4831     0.8341 0.000 0.704 0.016 0.280
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.2480     0.8017 0.088 0.000 0.904 0.008
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0336     0.7734 0.992 0.000 0.000 0.008
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.4431     0.5150 0.696 0.000 0.304 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.4040     0.6015 0.248 0.000 0.752 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0707     0.7659 0.980 0.000 0.000 0.020
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     4  0.6933     0.6595 0.172 0.000 0.244 0.584
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.6007     0.7892 0.340 0.000 0.056 0.604
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0469     0.7716 0.988 0.000 0.000 0.012
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0672     0.8639 0.008 0.000 0.984 0.008
#> 00439565-02CE-4BF5-956D-7078B51C0947     4  0.5861    -0.0546 0.032 0.000 0.480 0.488
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.1302     0.7421 0.956 0.000 0.000 0.044
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0469     0.7716 0.988 0.000 0.000 0.012
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.3625     0.6521 0.828 0.160 0.000 0.012
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0672     0.8639 0.008 0.000 0.984 0.008
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.4908     0.8299 0.000 0.692 0.016 0.292
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0469     0.7716 0.988 0.000 0.000 0.012
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0657     0.8637 0.004 0.000 0.984 0.012
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.1902     0.8471 0.004 0.000 0.932 0.064
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     4  0.6534     0.7466 0.220 0.000 0.148 0.632
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0336     0.7736 0.992 0.000 0.000 0.008
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.1209     0.7676 0.964 0.000 0.004 0.032
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0469     0.7716 0.988 0.000 0.000 0.012
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     4  0.6039     0.7885 0.348 0.000 0.056 0.596
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     4  0.4888     0.7275 0.412 0.000 0.000 0.588
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     4  0.6674     0.7720 0.300 0.000 0.116 0.584
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     4  0.5784     0.7283 0.200 0.000 0.100 0.700
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     4  0.6535     0.5380 0.100 0.000 0.312 0.588
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     4  0.6069     0.7859 0.356 0.000 0.056 0.588
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.5924     0.4758 0.040 0.000 0.556 0.404
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.4908     0.8299 0.000 0.692 0.016 0.292
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.5167     0.7988 0.000 0.644 0.016 0.340
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.4564     0.0571 0.672 0.000 0.000 0.328
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.7497     0.3310 0.224 0.000 0.496 0.280
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     4  0.6855     0.5178 0.144 0.000 0.276 0.580
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.5256    -0.0284 0.596 0.000 0.012 0.392
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.4804    -0.1991 0.616 0.000 0.000 0.384
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.4511     0.5485 0.724 0.000 0.268 0.008
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.2149     0.8589 0.000 0.912 0.000 0.088
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     4  0.6023     0.7890 0.344 0.000 0.056 0.600
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     4  0.5290     0.7407 0.404 0.000 0.012 0.584
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     4  0.7062     0.5819 0.204 0.000 0.224 0.572
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> 40855647-E942-4F32-90B7-BEB921929BFB     3  0.6668     0.0146 0.092 0.000 0.528 0.380
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.4908     0.8299 0.000 0.692 0.016 0.292
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.4857     0.8333 0.000 0.700 0.016 0.284
#> EB1DDB14-4076-4C2C-B911-390C17C21486     4  0.6603     0.4352 0.104 0.000 0.316 0.580
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     4  0.5993     0.7872 0.308 0.000 0.064 0.628
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.5229     0.6280 0.000 0.748 0.168 0.084
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.5647     0.5796 0.720 0.000 0.164 0.116
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#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4872     0.4420 0.004 0.000 0.640 0.356
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     4  0.5699     0.7669 0.380 0.000 0.032 0.588
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.3037     0.7259 0.888 0.000 0.036 0.076
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8658 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0672     0.8639 0.008 0.000 0.984 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.6583     0.7269 0.192 0.000 0.176 0.632
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1118     0.7685 0.964 0.000 0.000 0.036
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     4  0.4907     0.7180 0.420 0.000 0.000 0.580

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5085     0.2411 0.128 0.012 0.120 0.736 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5730     0.5753 0.032 0.000 0.580 0.348 0.040
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2144     0.8173 0.912 0.000 0.000 0.068 0.020
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3569     0.7998 0.828 0.000 0.000 0.068 0.104
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1872     0.8625 0.052 0.000 0.000 0.020 0.928
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.3651     0.7571 0.000 0.060 0.828 0.108 0.004
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1671     0.8279 0.000 0.000 0.000 0.076 0.924
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1106     0.8228 0.964 0.000 0.000 0.024 0.012
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.2438     0.8602 0.060 0.000 0.000 0.040 0.900
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1992     0.8185 0.924 0.000 0.000 0.044 0.032
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.4446     0.7242 0.000 0.476 0.000 0.520 0.004
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.7276     0.2449 0.400 0.000 0.208 0.360 0.032
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0613     0.8434 0.004 0.000 0.984 0.008 0.004
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.2568     0.7967 0.004 0.000 0.888 0.016 0.092
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1082     0.8228 0.964 0.000 0.000 0.008 0.028
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1364     0.8602 0.036 0.000 0.000 0.012 0.952
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5028     0.1488 0.008 0.000 0.552 0.020 0.420
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3401     0.8037 0.840 0.000 0.000 0.064 0.096
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2074     0.8219 0.920 0.000 0.000 0.044 0.036
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1851     0.8066 0.912 0.000 0.000 0.088 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.4933     0.6059 0.200 0.000 0.000 0.096 0.704
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0771     0.8413 0.004 0.000 0.976 0.020 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4921     0.6706 0.172 0.000 0.728 0.092 0.008
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.1943     0.8624 0.056 0.000 0.000 0.020 0.924
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.2376     0.8613 0.044 0.000 0.000 0.052 0.904
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1041     0.8226 0.964 0.000 0.000 0.004 0.032
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.3090     0.8320 0.104 0.000 0.000 0.040 0.856
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0162     0.9472 0.000 0.996 0.000 0.004 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3013     0.7820 0.832 0.000 0.008 0.160 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4245     0.6796 0.024 0.000 0.008 0.224 0.744
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2286     0.8033 0.888 0.000 0.000 0.108 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.4758     0.6035 0.676 0.000 0.000 0.048 0.276
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.4300     0.7252 0.000 0.476 0.000 0.524 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1928     0.8103 0.004 0.000 0.920 0.004 0.072
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0486     0.8448 0.004 0.000 0.988 0.004 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1981     0.8181 0.924 0.000 0.000 0.048 0.028
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.5192     0.1156 0.004 0.000 0.472 0.032 0.492
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.6202     0.0656 0.372 0.000 0.000 0.144 0.484
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.2291     0.8611 0.056 0.000 0.000 0.036 0.908
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0727     0.8425 0.004 0.000 0.980 0.004 0.012
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.4294     0.7289 0.000 0.468 0.000 0.532 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2221     0.8142 0.912 0.000 0.000 0.052 0.036
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.4542     0.7239 0.000 0.456 0.000 0.536 0.008
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.3835     0.7531 0.796 0.000 0.048 0.156 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1851     0.8065 0.912 0.000 0.000 0.088 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1041     0.8377 0.004 0.000 0.964 0.032 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3319     0.7635 0.000 0.000 0.820 0.160 0.020
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.2588     0.8570 0.048 0.000 0.000 0.060 0.892
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1281     0.8226 0.956 0.000 0.000 0.012 0.032
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.1893     0.8631 0.048 0.000 0.000 0.024 0.928
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.5187     0.5182 0.656 0.000 0.000 0.084 0.260
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.5585     0.6212 0.016 0.000 0.232 0.092 0.660
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0703     0.8231 0.976 0.000 0.000 0.000 0.024
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3586     0.7455 0.000 0.000 0.792 0.188 0.020
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2300     0.8134 0.908 0.000 0.000 0.052 0.040
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.3011     0.8209 0.012 0.000 0.076 0.036 0.876
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0162     0.8440 0.000 0.000 0.996 0.004 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.4446     0.7242 0.000 0.476 0.000 0.520 0.004
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.1251     0.8599 0.036 0.000 0.000 0.008 0.956
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.2152     0.8592 0.044 0.000 0.004 0.032 0.920
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.5201     0.2371 0.008 0.000 0.432 0.028 0.532
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1281     0.8220 0.956 0.000 0.000 0.012 0.032
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.2054     0.8171 0.920 0.000 0.000 0.052 0.028
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.1121     0.8624 0.044 0.000 0.000 0.000 0.956
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.1907     0.8642 0.044 0.000 0.000 0.028 0.928
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0162     0.8440 0.000 0.000 0.996 0.004 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.5213     0.6861 0.000 0.396 0.048 0.556 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.6028     0.1694 0.468 0.000 0.000 0.116 0.416
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     4  0.7330    -0.2333 0.016 0.120 0.400 0.424 0.040
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.0693     0.8490 0.012 0.000 0.000 0.008 0.980
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.2036     0.8605 0.056 0.000 0.000 0.024 0.920
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2149     0.8214 0.916 0.000 0.000 0.048 0.036
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5626     0.0801 0.504 0.000 0.000 0.076 0.420
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.2751     0.8091 0.888 0.000 0.004 0.056 0.052
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.4297     0.7277 0.000 0.472 0.000 0.528 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     4  0.4297     0.7275 0.000 0.472 0.000 0.528 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.2189     0.8097 0.000 0.000 0.904 0.012 0.084
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.1697     0.8626 0.060 0.000 0.000 0.008 0.932
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.5130     0.2920 0.004 0.000 0.412 0.032 0.552
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.4443     0.7266 0.000 0.472 0.000 0.524 0.004
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.3155     0.7559 0.008 0.000 0.848 0.016 0.128
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.2149     0.8607 0.048 0.000 0.000 0.036 0.916
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.1809     0.8620 0.060 0.000 0.000 0.012 0.928
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3859     0.7502 0.816 0.000 0.084 0.096 0.004
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.2570     0.8118 0.888 0.000 0.000 0.084 0.028
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.2661     0.8560 0.056 0.000 0.000 0.056 0.888
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.7420     0.1887 0.372 0.000 0.232 0.360 0.036
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.2597     0.8475 0.092 0.000 0.000 0.024 0.884
#> 7822EA86-35A1-4285-9429-2B63111B9885     5  0.2450     0.8573 0.048 0.000 0.000 0.052 0.900
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     5  0.5382     0.7093 0.068 0.160 0.000 0.052 0.720
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.2149     0.8603 0.048 0.000 0.000 0.036 0.916
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.4688     0.7280 0.000 0.456 0.008 0.532 0.004
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.2228     0.8604 0.048 0.000 0.000 0.040 0.912
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0162     0.8445 0.004 0.000 0.996 0.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.2972     0.7899 0.024 0.000 0.864 0.108 0.004
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.2358     0.7982 0.888 0.000 0.008 0.104 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     5  0.3003     0.8392 0.092 0.000 0.000 0.044 0.864
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     5  0.1485     0.8591 0.032 0.000 0.000 0.020 0.948
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     5  0.2228     0.8604 0.048 0.000 0.000 0.040 0.912
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.2171     0.8192 0.912 0.000 0.000 0.064 0.024
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.1549     0.8223 0.944 0.000 0.000 0.016 0.040
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.2529     0.8213 0.900 0.000 0.004 0.056 0.040
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.4050     0.7484 0.784 0.000 0.008 0.172 0.036
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.4254     0.7330 0.772 0.000 0.080 0.148 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.1386     0.8215 0.952 0.000 0.000 0.016 0.032
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     4  0.6721    -0.0910 0.168 0.000 0.380 0.440 0.012
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     4  0.4688     0.7280 0.000 0.456 0.008 0.532 0.004
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     4  0.5134     0.5220 0.008 0.284 0.008 0.664 0.036
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.4594     0.5481 0.680 0.000 0.000 0.036 0.284
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     4  0.8446    -0.3487 0.212 0.000 0.304 0.308 0.176
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.6222     0.5376 0.568 0.000 0.076 0.320 0.036
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.6976     0.1319 0.444 0.000 0.020 0.192 0.344
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.4977     0.0585 0.500 0.000 0.000 0.028 0.472
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     5  0.4955     0.4882 0.004 0.000 0.328 0.036 0.632
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.2249     0.7748 0.000 0.896 0.000 0.096 0.008
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0703     0.8229 0.976 0.000 0.000 0.000 0.024
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#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.5246     0.6254 0.024 0.000 0.644 0.300 0.032
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5165     0.6829 0.708 0.000 0.092 0.188 0.012
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.4119     0.6869 0.000 0.212 0.000 0.036 0.752
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4151     0.7376 0.156 0.000 0.788 0.044 0.012
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.5541     0.3953 0.000 0.000 0.552 0.372 0.076
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1485     0.8218 0.948 0.000 0.000 0.020 0.032
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1270     0.8623 0.052 0.000 0.000 0.000 0.948
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.4446     0.7242 0.000 0.476 0.000 0.520 0.004
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0880     0.8226 0.968 0.000 0.000 0.000 0.032
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.5195     0.6806 0.000 0.388 0.048 0.564 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2124     0.8163 0.916 0.000 0.000 0.056 0.028
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.6376     0.5194 0.072 0.000 0.520 0.368 0.040
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5163     0.6420 0.156 0.000 0.692 0.152 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2661     0.8020 0.896 0.052 0.000 0.044 0.008
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.2798     0.7862 0.852 0.000 0.008 0.140 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.6196     0.5603 0.588 0.000 0.076 0.296 0.040
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1628     0.8174 0.936 0.000 0.000 0.056 0.008
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.4468     0.5914 0.004 0.000 0.276 0.024 0.696
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.7038     0.3633 0.452 0.000 0.152 0.360 0.036
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6577     0.0880 0.424 0.000 0.396 0.176 0.004
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1992     0.8170 0.924 0.000 0.000 0.044 0.032
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.1965     0.8253 0.024 0.000 0.000 0.052 0.924
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9524 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0162     0.9493 0.000 0.996 0.000 0.000 0.004
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0324     0.8449 0.004 0.000 0.992 0.000 0.004
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2660     0.7912 0.864 0.000 0.008 0.128 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.1469     0.8600 0.036 0.000 0.000 0.016 0.948
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1725     0.8218 0.936 0.000 0.000 0.020 0.044

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5836     0.3358 0.124 0.000 0.040 0.588 0.000 0.248
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0405     0.7643 0.000 0.000 0.988 0.008 0.000 0.004
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.3602     0.5261 0.000 0.000 0.208 0.032 0.000 0.760
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3668     0.4753 0.668 0.000 0.000 0.004 0.000 0.328
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4908     0.5047 0.644 0.000 0.000 0.020 0.056 0.280
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1296     0.8492 0.004 0.000 0.000 0.032 0.952 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.3592     0.6551 0.000 0.044 0.812 0.020 0.000 0.124
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0146     0.9572 0.000 0.996 0.000 0.000 0.000 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1780     0.8435 0.000 0.000 0.000 0.028 0.924 0.048
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2070     0.6886 0.892 0.000 0.000 0.008 0.000 0.100
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.2471     0.8469 0.044 0.000 0.000 0.040 0.896 0.020
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0790     0.6866 0.968 0.000 0.000 0.032 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0405     0.7643 0.000 0.000 0.988 0.008 0.000 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.3827     0.8731 0.000 0.256 0.000 0.720 0.004 0.020
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.3465     0.6630 0.096 0.000 0.056 0.020 0.000 0.828
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0937     0.7618 0.000 0.000 0.960 0.040 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.3497     0.7275 0.000 0.000 0.832 0.084 0.048 0.036
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1434     0.6953 0.940 0.000 0.000 0.012 0.000 0.048
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1269     0.8491 0.012 0.000 0.000 0.012 0.956 0.020
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5290     0.5965 0.000 0.000 0.648 0.084 0.232 0.036
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4850     0.4929 0.640 0.000 0.000 0.020 0.048 0.292
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3616     0.6249 0.780 0.000 0.000 0.012 0.024 0.184
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3769     0.4088 0.640 0.000 0.000 0.004 0.000 0.356
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.7657 0.000 0.000 1.000 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.5474     0.1179 0.088 0.000 0.000 0.012 0.496 0.404
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1151     0.7524 0.000 0.000 0.956 0.012 0.000 0.032
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.6025     0.2006 0.068 0.000 0.524 0.044 0.012 0.352
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0748     0.9419 0.000 0.976 0.000 0.004 0.004 0.016
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.2016     0.8480 0.016 0.000 0.000 0.040 0.920 0.024
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.2736     0.8460 0.020 0.000 0.000 0.048 0.880 0.052
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1812     0.6897 0.912 0.000 0.000 0.008 0.000 0.080
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.5132     0.7342 0.148 0.000 0.008 0.096 0.708 0.040
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0146     0.9572 0.000 0.996 0.000 0.000 0.000 0.004
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.4263     0.1445 0.504 0.000 0.000 0.016 0.000 0.480
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.4445     0.4199 0.000 0.000 0.000 0.032 0.572 0.396
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0146     0.9572 0.000 0.996 0.000 0.000 0.000 0.004
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3789     0.3024 0.584 0.000 0.000 0.000 0.000 0.416
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.5559     0.4767 0.632 0.000 0.000 0.032 0.144 0.192
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.3314     0.8742 0.000 0.256 0.000 0.740 0.000 0.004
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1555     0.7600 0.000 0.000 0.940 0.040 0.012 0.008
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0820     0.7616 0.000 0.000 0.972 0.012 0.000 0.016
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1124     0.6836 0.956 0.000 0.000 0.036 0.000 0.008
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.6086     0.5042 0.020 0.000 0.576 0.092 0.276 0.036
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     6  0.5407     0.4070 0.108 0.000 0.000 0.008 0.324 0.560
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.2171     0.8441 0.016 0.000 0.000 0.040 0.912 0.032
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1340     0.7604 0.000 0.000 0.948 0.040 0.004 0.008
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.3217     0.8729 0.000 0.224 0.000 0.768 0.000 0.008
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1624     0.6780 0.936 0.000 0.000 0.044 0.008 0.012
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.3794     0.8570 0.000 0.216 0.000 0.744 0.000 0.040
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.7657 0.000 0.000 1.000 0.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4396     0.1827 0.520 0.000 0.000 0.024 0.000 0.456
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3684     0.3873 0.628 0.000 0.000 0.000 0.000 0.372
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1334     0.7488 0.000 0.000 0.948 0.020 0.000 0.032
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3558     0.5856 0.000 0.000 0.760 0.028 0.000 0.212
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.3593     0.8083 0.068 0.000 0.000 0.064 0.828 0.040
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0291     0.9538 0.000 0.992 0.000 0.004 0.000 0.004
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1866     0.6878 0.908 0.000 0.000 0.008 0.000 0.084
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.1116     0.8495 0.004 0.000 0.000 0.028 0.960 0.008
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.4175     0.5798 0.788 0.000 0.000 0.080 0.060 0.072
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.7296     0.5151 0.080 0.000 0.176 0.128 0.536 0.080
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1588     0.6912 0.924 0.000 0.000 0.004 0.000 0.072
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3694     0.5630 0.000 0.000 0.740 0.028 0.000 0.232
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1974     0.6741 0.920 0.000 0.000 0.048 0.020 0.012
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.4699     0.7465 0.024 0.000 0.080 0.096 0.764 0.036
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0508     0.7634 0.000 0.000 0.984 0.012 0.000 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.3744     0.8736 0.000 0.256 0.000 0.724 0.004 0.016
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.1448     0.8492 0.012 0.000 0.000 0.016 0.948 0.024
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.3720     0.8075 0.032 0.000 0.008 0.104 0.820 0.036
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.5764     0.4150 0.000 0.000 0.540 0.088 0.336 0.036
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0865     0.6953 0.964 0.000 0.000 0.000 0.000 0.036
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.1408     0.6806 0.944 0.000 0.000 0.036 0.000 0.020
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.0767     0.8514 0.012 0.000 0.000 0.004 0.976 0.008
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.1952     0.8525 0.012 0.000 0.000 0.052 0.920 0.016
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0725     0.7609 0.000 0.000 0.976 0.012 0.000 0.012
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.4138     0.8205 0.004 0.156 0.036 0.772 0.000 0.032
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     6  0.6041     0.3301 0.200 0.000 0.000 0.008 0.328 0.464
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.6496     0.2441 0.000 0.084 0.200 0.172 0.000 0.544
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.1251     0.8488 0.012 0.000 0.000 0.008 0.956 0.024
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.2484     0.8423 0.036 0.000 0.000 0.044 0.896 0.024
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3858     0.6105 0.760 0.000 0.000 0.012 0.032 0.196
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4639     0.5245 0.748 0.000 0.004 0.076 0.132 0.040
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3278     0.6359 0.852 0.000 0.004 0.072 0.036 0.036
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.3744     0.8736 0.000 0.256 0.000 0.724 0.004 0.016
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     4  0.3582     0.8747 0.000 0.252 0.000 0.732 0.000 0.016
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.3039     0.7335 0.000 0.000 0.852 0.056 0.084 0.008
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.2400     0.8425 0.064 0.000 0.000 0.024 0.896 0.016
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.6351     0.3793 0.024 0.000 0.512 0.092 0.336 0.036
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.3314     0.8745 0.000 0.256 0.000 0.740 0.000 0.004
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.2992     0.7395 0.000 0.000 0.864 0.072 0.032 0.032
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.1867     0.8451 0.004 0.000 0.000 0.036 0.924 0.036
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.2507     0.8446 0.056 0.000 0.000 0.036 0.892 0.016
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.4322     0.5526 0.736 0.000 0.020 0.052 0.000 0.192
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.2999     0.6354 0.856 0.000 0.000 0.068 0.008 0.068
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.4109     0.7845 0.100 0.000 0.000 0.072 0.788 0.040
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0146     0.7655 0.000 0.000 0.996 0.004 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     6  0.3504     0.6659 0.076 0.000 0.060 0.032 0.000 0.832
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.3535     0.7860 0.140 0.000 0.000 0.036 0.808 0.016
#> 7822EA86-35A1-4285-9429-2B63111B9885     5  0.2911     0.8287 0.040 0.000 0.000 0.052 0.872 0.036
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     5  0.5583     0.6896 0.120 0.064 0.000 0.056 0.704 0.056
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000     0.7657 0.000 0.000 1.000 0.000 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.3271     0.8209 0.032 0.000 0.004 0.088 0.848 0.028
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.3314     0.8741 0.000 0.224 0.000 0.764 0.000 0.012
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
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#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3961     0.2474 0.556 0.000 0.000 0.004 0.000 0.440
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.1967     0.8531 0.000 0.904 0.000 0.084 0.000 0.012
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0363     0.7645 0.000 0.000 0.988 0.012 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.3412     0.8188 0.040 0.000 0.004 0.088 0.840 0.028
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.5265     0.6792 0.024 0.000 0.132 0.096 0.712 0.036
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.1478     0.9146 0.000 0.944 0.000 0.032 0.004 0.020
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.3072     0.8304 0.024 0.000 0.000 0.084 0.856 0.036
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.3744     0.8736 0.000 0.256 0.000 0.724 0.004 0.016
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.1353     0.8511 0.012 0.000 0.000 0.024 0.952 0.012
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.1269     0.8498 0.012 0.000 0.000 0.012 0.956 0.020
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     6  0.4219     0.2361 0.388 0.000 0.000 0.020 0.000 0.592
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.5746     0.2533 0.000 0.000 0.484 0.080 0.404 0.032
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.3286     0.8116 0.116 0.000 0.000 0.036 0.832 0.016
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0146     0.9572 0.000 0.996 0.000 0.000 0.000 0.004
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.6479     0.4582 0.036 0.000 0.540 0.100 0.288 0.036
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.4881     0.5747 0.152 0.000 0.004 0.008 0.140 0.696
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.1364     0.8494 0.012 0.000 0.000 0.020 0.952 0.016
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     6  0.4708     0.5843 0.064 0.000 0.212 0.012 0.008 0.704
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1049     0.6844 0.960 0.000 0.000 0.032 0.000 0.008
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2815     0.6879 0.876 0.000 0.000 0.024 0.044 0.056
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4394     0.0279 0.496 0.000 0.016 0.004 0.000 0.484
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.5833     0.5804 0.184 0.000 0.652 0.096 0.032 0.036
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.2466     0.6630 0.896 0.000 0.000 0.052 0.028 0.024
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4125     0.6241 0.740 0.000 0.000 0.028 0.024 0.208
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.3376     0.6663 0.072 0.000 0.060 0.028 0.000 0.840
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     6  0.4478     0.0323 0.452 0.000 0.000 0.008 0.016 0.524
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0146     0.9572 0.000 0.996 0.000 0.000 0.000 0.004
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.4110     0.3492 0.608 0.000 0.000 0.016 0.000 0.376
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.5873     0.2130 0.528 0.000 0.000 0.340 0.040 0.092
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0820     0.8519 0.012 0.000 0.000 0.016 0.972 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.5799     0.5177 0.656 0.000 0.012 0.088 0.076 0.168
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.4478     0.7552 0.152 0.000 0.000 0.056 0.748 0.044
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5925     0.1399 0.496 0.000 0.032 0.088 0.004 0.380
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.4715     0.0749 0.000 0.000 0.416 0.048 0.000 0.536
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5126     0.1172 0.512 0.000 0.016 0.048 0.000 0.424
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.3889     0.7698 0.000 0.100 0.000 0.044 0.804 0.052
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5663     0.5401 0.244 0.000 0.628 0.080 0.016 0.032
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.5890     0.1876 0.048 0.000 0.460 0.436 0.012 0.044
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2076     0.6944 0.912 0.000 0.000 0.016 0.012 0.060
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.1679     0.8479 0.012 0.000 0.000 0.036 0.936 0.016
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.3905     0.8722 0.000 0.256 0.000 0.716 0.004 0.024
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.1501     0.6903 0.924 0.000 0.000 0.000 0.000 0.076
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.4138     0.8205 0.004 0.156 0.036 0.772 0.000 0.032
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1760     0.6752 0.928 0.000 0.000 0.048 0.004 0.020
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.3353     0.5914 0.008 0.000 0.156 0.028 0.000 0.808
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6032     0.2186 0.136 0.000 0.572 0.048 0.000 0.244
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2945     0.6620 0.872 0.032 0.000 0.028 0.004 0.064
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4310     0.2181 0.540 0.000 0.000 0.020 0.000 0.440
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.3970     0.5576 0.260 0.000 0.016 0.012 0.000 0.712
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2504     0.6740 0.880 0.000 0.000 0.028 0.004 0.088
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.7657 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.5467     0.3599 0.000 0.000 0.304 0.088 0.584 0.024
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.3263     0.6539 0.112 0.000 0.028 0.024 0.000 0.836
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.6067     0.4868 0.172 0.000 0.284 0.016 0.004 0.524
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0972     0.6853 0.964 0.000 0.000 0.028 0.000 0.008
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.2755     0.8077 0.012 0.000 0.000 0.012 0.856 0.120
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9585 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0260     0.9559 0.000 0.992 0.000 0.000 0.000 0.008
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0260     0.7649 0.000 0.000 0.992 0.008 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4229     0.2378 0.548 0.000 0.000 0.016 0.000 0.436
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.1780     0.8506 0.012 0.000 0.000 0.028 0.932 0.028
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2833     0.6878 0.876 0.000 0.000 0.028 0.048 0.048

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-kmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-kmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:skmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "skmeans"]
# you can also extract it by
# res = res_list["MAD:skmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.971       0.988         0.4898 0.511   0.511
#> 3 3 0.742           0.804       0.905         0.3300 0.765   0.573
#> 4 4 0.838           0.821       0.925         0.1473 0.822   0.546
#> 5 5 0.827           0.784       0.896         0.0614 0.901   0.646
#> 6 6 0.813           0.759       0.874         0.0461 0.933   0.694

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000      0.987 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     2  0.0376      0.984 0.004 0.996
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     2  0.0000      0.987 0.000 1.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.988 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.988 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.988 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000      0.987 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.987 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.2043      0.957 0.968 0.032
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.988 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.988 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.988 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     2  0.5737      0.842 0.136 0.864
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.987 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.988 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     2  0.3431      0.926 0.064 0.936
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.988 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.988 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.988 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.5178      0.863 0.884 0.116
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.987 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.988 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.988 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.988 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     2  0.0376      0.984 0.004 0.996
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.988 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     2  0.2043      0.958 0.032 0.968
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.988 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.987 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.987 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.988 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.988 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.988 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.988 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.987 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.0000      0.987 0.000 1.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     2  0.0000      0.987 0.000 1.000
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#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000      0.987 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     2  0.0000      0.987 0.000 1.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     2  0.0000      0.987 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.988 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.988 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000      0.987 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     2  0.1414      0.970 0.020 0.980
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000      0.987 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.987 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.987 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000      0.988 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     2  0.0000      0.987 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000      0.988 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.988 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.988 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     2  0.1184      0.974 0.016 0.984
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     2  0.0000      0.987 0.000 1.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.988 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.988 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.987 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0672      0.981 0.992 0.008
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     2  0.0000      0.987 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000      0.988 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.987 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.987 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.988 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.987 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.987 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.988 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.988 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.987 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.987 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     2  0.0000      0.987 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.988 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.988 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.987 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.988 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.987 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.988 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.988 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.988 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.988 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.988 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.987 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.988 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.988 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.988 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.988 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.988 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.988 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.988 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.988 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.988 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.988 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.988 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.988 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.987 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.988 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.2603      0.947 0.044 0.956
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.988 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.988 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.988 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.987 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.0000      0.987 0.000 1.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000      0.987 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000      0.987 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.987 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.988 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.1184      0.973 0.016 0.984
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.988 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.988 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.987 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.988 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.987 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.988 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.9866      0.237 0.568 0.432
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     2  0.0000      0.987 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.987 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.988 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.988 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.9044      0.531 0.320 0.680
#> CE6B6871-3ED3-44DE-A777-7558D4429057     2  0.0376      0.984 0.004 0.996
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.0000      0.987 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     2  0.0000      0.987 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.988 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.988 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.988 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.987 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.987 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     2  0.0376      0.984 0.004 0.996
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.988 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.988 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.988 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.4702     0.6946 0.000 0.788 0.212
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0592     0.8453 0.012 0.000 0.988
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.1636     0.8452 0.016 0.020 0.964
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1643     0.8700 0.956 0.000 0.044
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.8756 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1289     0.8737 0.968 0.000 0.032
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6252     0.2544 0.000 0.444 0.556
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9575 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     2  0.9877    -0.0938 0.352 0.388 0.260
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1753     0.8682 0.952 0.000 0.048
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1289     0.8737 0.968 0.000 0.032
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1643     0.8700 0.956 0.000 0.044
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1289     0.8449 0.032 0.000 0.968
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9575 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.1289     0.8449 0.032 0.000 0.968
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1529     0.8393 0.040 0.000 0.960
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1753     0.8368 0.048 0.000 0.952
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1643     0.8700 0.956 0.000 0.044
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.1289     0.8737 0.968 0.000 0.032
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.2796     0.8171 0.092 0.000 0.908
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9575 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.8756 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1643     0.8700 0.956 0.000 0.044
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2165     0.8600 0.936 0.000 0.064
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1529     0.8390 0.040 0.000 0.960
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.6180     0.3353 0.584 0.000 0.416
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1289     0.8449 0.032 0.000 0.968
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.1289     0.8449 0.032 0.000 0.968
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9575 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9575 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1289     0.8737 0.968 0.000 0.032
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.1289     0.8737 0.968 0.000 0.032
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1643     0.8700 0.956 0.000 0.044
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1289     0.8737 0.968 0.000 0.032
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9575 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.9120     0.3105 0.256 0.544 0.200
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     2  0.5402     0.7004 0.028 0.792 0.180
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9575 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1643     0.8700 0.956 0.000 0.044
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.8756 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9575 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1643     0.8378 0.044 0.000 0.956
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2356     0.8238 0.000 0.072 0.928
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1643     0.8700 0.956 0.000 0.044
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.5397     0.6082 0.280 0.000 0.720
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.6225     0.1608 0.432 0.000 0.568
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1289     0.8737 0.968 0.000 0.032
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9575 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1643     0.8378 0.044 0.000 0.956
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9575 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1529     0.8710 0.960 0.000 0.040
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9575 0.000 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1289     0.8449 0.032 0.000 0.968
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5968     0.3990 0.364 0.000 0.636
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3116     0.8292 0.892 0.000 0.108
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.1289     0.8449 0.032 0.000 0.968
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1289     0.8449 0.032 0.000 0.968
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.1289     0.8737 0.968 0.000 0.032
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9575 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1643     0.8700 0.956 0.000 0.044
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.1289     0.8737 0.968 0.000 0.032
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.1411     0.8742 0.964 0.000 0.036
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.5529     0.5954 0.296 0.000 0.704
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1643     0.8700 0.956 0.000 0.044
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9575 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.1399     0.8453 0.028 0.004 0.968
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1529     0.8710 0.960 0.000 0.040
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.6204     0.2947 0.424 0.000 0.576
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.1399     0.8453 0.028 0.004 0.968
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9575 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.2165     0.8575 0.936 0.000 0.064
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.5058     0.6597 0.756 0.000 0.244
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.2959     0.8125 0.100 0.000 0.900
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1643     0.8700 0.956 0.000 0.044
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.1753     0.8682 0.952 0.000 0.048
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.1289     0.8737 0.968 0.000 0.032
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1289     0.8737 0.968 0.000 0.032
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9575 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.1529     0.8411 0.000 0.040 0.960
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#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9575 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9575 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.8756 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9575 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9575 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.5254     0.6316 0.264 0.000 0.736
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.5621     0.5727 0.692 0.000 0.308
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9575 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9575 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.3340     0.7918 0.000 0.120 0.880
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1289     0.8737 0.968 0.000 0.032
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.6225     0.2706 0.432 0.000 0.568
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9575 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.1289     0.8737 0.968 0.000 0.032
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9575 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.1289     0.8737 0.968 0.000 0.032
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.4702     0.7054 0.788 0.000 0.212
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6154     0.3639 0.592 0.000 0.408
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1964     0.8344 0.056 0.000 0.944
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.1289     0.8737 0.968 0.000 0.032
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9575 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.5859     0.4892 0.344 0.000 0.656
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.6140     0.3065 0.596 0.000 0.404
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.3686     0.7920 0.860 0.000 0.140
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.1289     0.8449 0.032 0.000 0.968
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1643     0.8700 0.956 0.000 0.044
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0592     0.8750 0.988 0.000 0.012
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.4121     0.7466 0.168 0.000 0.832
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.5291     0.6238 0.268 0.000 0.732
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1529     0.8710 0.960 0.000 0.040
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3340     0.8116 0.880 0.000 0.120
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.1289     0.8449 0.032 0.000 0.968
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4399     0.7534 0.812 0.000 0.188
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9575 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3619     0.8059 0.864 0.000 0.136
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.4796     0.6857 0.220 0.780 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1289     0.8737 0.968 0.000 0.032
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.1289     0.8737 0.968 0.000 0.032
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1289     0.8737 0.968 0.000 0.032
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9575 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.8941     0.4357 0.160 0.292 0.548
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4235     0.7410 0.000 0.176 0.824
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.8024     0.5908 0.132 0.220 0.648
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9575 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1289     0.8449 0.032 0.000 0.968
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.6467     0.3503 0.008 0.388 0.604
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1529     0.8710 0.960 0.000 0.040
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.1289     0.8737 0.968 0.000 0.032
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9575 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.1643     0.8700 0.956 0.000 0.044
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9575 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1860     0.8670 0.948 0.000 0.052
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.1289     0.8449 0.032 0.000 0.968
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1289     0.8449 0.032 0.000 0.968
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9575 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5650     0.5658 0.688 0.000 0.312
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.6225     0.3185 0.568 0.000 0.432
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.7301     0.4923 0.640 0.308 0.052
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8460 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.7570     0.2986 0.044 0.404 0.552
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4137     0.8034 0.032 0.096 0.872
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.1289     0.8449 0.032 0.000 0.968
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1643     0.8700 0.956 0.000 0.044
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.5178     0.6429 0.744 0.000 0.256
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9575 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9575 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8460 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5733     0.5434 0.676 0.000 0.324
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.1411     0.8723 0.964 0.000 0.036
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0592     0.8750 0.988 0.000 0.012

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.2149     0.8825 0.000 0.912 0.088 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2921     0.7872 0.860 0.000 0.000 0.140
#> 03E81178-E971-4E91-8BED-D8273EA1425C     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4916     0.1964 0.000 0.424 0.576 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     4  0.0188     0.9153 0.004 0.000 0.000 0.996
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.4679     0.5117 0.648 0.000 0.352 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0592     0.8572 0.000 0.000 0.984 0.016
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4585     0.5279 0.000 0.000 0.668 0.332
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2530     0.8158 0.888 0.000 0.000 0.112
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     4  0.3356     0.7424 0.176 0.000 0.000 0.824
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1888     0.8582 0.940 0.044 0.016 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.4830     0.3359 0.000 0.392 0.000 0.608
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.4998     0.0561 0.512 0.000 0.000 0.488
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4977     0.2842 0.000 0.000 0.540 0.460
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     4  0.5035     0.6660 0.196 0.000 0.056 0.748
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0921     0.8813 0.972 0.000 0.028 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.4989     0.1198 0.472 0.000 0.000 0.528
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.4998    -0.1315 0.000 0.000 0.488 0.512
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     4  0.0336     0.9114 0.000 0.000 0.008 0.992
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4855     0.4148 0.000 0.000 0.600 0.400
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     4  0.4843     0.3200 0.396 0.000 0.000 0.604
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.4843     0.3635 0.000 0.604 0.396 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     4  0.4500     0.5272 0.316 0.000 0.000 0.684
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.5240     0.6433 0.740 0.000 0.188 0.072
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9660 0.000 1.000 0.000 0.000
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#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.4720     0.6691 0.188 0.000 0.768 0.044
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     4  0.0707     0.9005 0.000 0.000 0.020 0.980
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.4776     0.4552 0.000 0.000 0.624 0.376
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.4981     0.2737 0.000 0.000 0.536 0.464
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     4  0.7613     0.0383 0.368 0.000 0.204 0.428
#> D365A238-4739-4B54-9608-DC548F21C04E     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0707     0.8859 0.980 0.000 0.000 0.020
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.4193     0.6397 0.732 0.000 0.268 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3082     0.8017 0.032 0.000 0.884 0.084
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1174     0.8816 0.968 0.000 0.020 0.012
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4817     0.4396 0.612 0.000 0.388 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2973     0.7846 0.856 0.000 0.000 0.144
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.6701     0.3671 0.328 0.564 0.000 0.108
#> 9AF0E82E-E621-437A-8D19-700532B95090     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.7582     0.1558 0.456 0.000 0.208 0.336
#> EFE5A302-D138-4044-A301-5C5FD1C24836     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3448     0.7523 0.828 0.004 0.168 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4661     0.3921 0.000 0.348 0.652 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.1118     0.8769 0.964 0.000 0.036 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.2216     0.8742 0.000 0.908 0.000 0.092
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4922     0.6406 0.000 0.228 0.736 0.036
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1389     0.8300 0.048 0.000 0.952 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4452     0.6449 0.732 0.000 0.260 0.008
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5337     0.3504 0.000 0.012 0.564 0.424
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4250     0.6357 0.724 0.000 0.276 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.2973     0.7385 0.144 0.000 0.856 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9660 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8652 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.8973 1.000 0.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.0000     0.9180 0.000 0.000 0.000 1.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0188     0.8953 0.996 0.000 0.000 0.004

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.6539     0.5653 0.144 0.632 0.084 0.140 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     4  0.3636     0.4574 0.000 0.000 0.272 0.728 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     4  0.4201     0.3425 0.408 0.000 0.000 0.592 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     4  0.6335     0.3918 0.204 0.000 0.000 0.520 0.276
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.5775     0.0180 0.000 0.472 0.440 0.088 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.0290     0.9274 0.000 0.000 0.000 0.008 0.992
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2074     0.8214 0.896 0.000 0.000 0.104 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.0290     0.9276 0.008 0.000 0.000 0.000 0.992
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.1041     0.7299 0.032 0.000 0.004 0.964 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1732     0.8336 0.920 0.000 0.000 0.080 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0404     0.9261 0.000 0.000 0.000 0.012 0.988
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0404     0.8815 0.000 0.000 0.988 0.000 0.012
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     4  0.6303     0.3812 0.268 0.000 0.000 0.528 0.204
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4150     0.3086 0.612 0.000 0.000 0.388 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     4  0.4268     0.2686 0.444 0.000 0.000 0.556 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     4  0.3906     0.5623 0.016 0.000 0.000 0.744 0.240
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3143     0.7148 0.000 0.000 0.796 0.204 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.0510     0.9249 0.016 0.000 0.000 0.000 0.984
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.2127     0.8190 0.892 0.000 0.000 0.108 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.1732     0.8808 0.080 0.000 0.000 0.000 0.920
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     4  0.3563     0.6282 0.208 0.012 0.000 0.780 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.6680     0.0339 0.000 0.236 0.000 0.400 0.364
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     4  0.3561     0.5867 0.260 0.000 0.000 0.740 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     4  0.6314     0.3516 0.180 0.000 0.000 0.508 0.312
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2891     0.7844 0.000 0.000 0.824 0.000 0.176
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     4  0.1628     0.7095 0.008 0.000 0.000 0.936 0.056
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.0162     0.9286 0.004 0.000 0.000 0.000 0.996
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0451     0.8414 0.988 0.000 0.000 0.004 0.008
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0404     0.9520 0.000 0.988 0.000 0.012 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     4  0.4088     0.4353 0.368 0.000 0.000 0.632 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     4  0.4201     0.3471 0.408 0.000 0.000 0.592 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3336     0.6910 0.000 0.000 0.772 0.228 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.1704     0.8910 0.068 0.000 0.000 0.004 0.928
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2020     0.8245 0.900 0.000 0.000 0.100 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.1041     0.8215 0.964 0.000 0.000 0.004 0.032
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.5137     0.6387 0.076 0.000 0.676 0.004 0.244
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2127     0.8194 0.892 0.000 0.000 0.108 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3336     0.6910 0.000 0.000 0.772 0.228 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0451     0.8414 0.988 0.000 0.000 0.004 0.008
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.2127     0.8426 0.000 0.000 0.108 0.000 0.892
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.0404     0.9261 0.000 0.000 0.000 0.012 0.988
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.2929     0.7818 0.000 0.000 0.820 0.000 0.180
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.1732     0.8339 0.920 0.000 0.000 0.080 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     4  0.4400     0.5072 0.020 0.000 0.000 0.672 0.308
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.4455     0.3870 0.000 0.588 0.008 0.404 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.0404     0.9261 0.000 0.000 0.000 0.012 0.988
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.5153     0.0892 0.524 0.000 0.000 0.436 0.040
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#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.1106     0.9201 0.024 0.000 0.000 0.012 0.964
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.0162     0.9285 0.000 0.000 0.000 0.004 0.996
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.0290     0.9281 0.008 0.000 0.000 0.000 0.992
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.2966     0.7360 0.816 0.000 0.000 0.184 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     4  0.0771     0.7292 0.020 0.000 0.004 0.976 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.1768     0.8835 0.004 0.000 0.000 0.072 0.924
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.2068     0.8299 0.004 0.000 0.904 0.092 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     4  0.3210     0.6322 0.212 0.000 0.000 0.788 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.0162     0.9289 0.004 0.000 0.000 0.000 0.996
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.3684     0.5825 0.000 0.000 0.280 0.000 0.720
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0290     0.9274 0.000 0.000 0.000 0.008 0.992
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     4  0.0963     0.7298 0.036 0.000 0.000 0.964 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.2732     0.7987 0.000 0.000 0.840 0.000 0.160
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.0404     0.9269 0.012 0.000 0.000 0.000 0.988
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3123     0.7751 0.004 0.000 0.812 0.000 0.184
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     4  0.1012     0.7274 0.020 0.000 0.000 0.968 0.012
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0290     0.9274 0.000 0.000 0.000 0.008 0.992
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     4  0.0794     0.7177 0.000 0.000 0.028 0.972 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3691     0.7612 0.820 0.000 0.000 0.076 0.104
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     4  0.1043     0.7292 0.040 0.000 0.000 0.960 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3280     0.7548 0.176 0.000 0.812 0.000 0.012
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0566     0.8398 0.984 0.000 0.000 0.004 0.012
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5623     0.1008 0.520 0.000 0.056 0.416 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     4  0.0771     0.7292 0.020 0.000 0.004 0.976 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     4  0.0609     0.7295 0.020 0.000 0.000 0.980 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     4  0.4219     0.3421 0.416 0.000 0.000 0.584 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.1173     0.8192 0.964 0.012 0.000 0.020 0.004
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     3  0.8562    -0.0749 0.244 0.000 0.304 0.216 0.236
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.1410     0.8954 0.060 0.000 0.000 0.000 0.940
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.4787     0.0184 0.548 0.000 0.020 0.432 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.6555     0.1925 0.000 0.320 0.220 0.460 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.4210     0.3770 0.412 0.000 0.000 0.588 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.3534     0.6505 0.000 0.744 0.000 0.000 0.256
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1608     0.8479 0.072 0.000 0.928 0.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.1644     0.8603 0.048 0.000 0.940 0.008 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1792     0.8331 0.916 0.000 0.000 0.084 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0000     0.9294 0.000 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2074     0.8215 0.896 0.000 0.000 0.104 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0771     0.9503 0.004 0.976 0.000 0.020 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     4  0.1851     0.6799 0.000 0.000 0.088 0.912 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6329     0.2669 0.240 0.000 0.528 0.232 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0162     0.9515 0.004 0.996 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     4  0.4182     0.3748 0.400 0.000 0.000 0.600 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.1608     0.7121 0.072 0.000 0.000 0.928 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1908     0.8174 0.908 0.000 0.000 0.092 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3266     0.7547 0.000 0.004 0.796 0.000 0.200
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.0963     0.7298 0.036 0.000 0.000 0.964 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     4  0.1485     0.7223 0.020 0.000 0.032 0.948 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0162     0.8423 0.996 0.000 0.000 0.004 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3730     0.6118 0.000 0.000 0.000 0.288 0.712
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9532 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8852 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.4182     0.3748 0.400 0.000 0.000 0.600 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0404     0.9261 0.000 0.000 0.000 0.012 0.988
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2388     0.8328 0.900 0.000 0.000 0.072 0.028

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1015    0.80859 0.012 0.004 0.004 0.968 0.000 0.012
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     6  0.3398    0.48073 0.000 0.000 0.252 0.008 0.000 0.740
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3866   -0.12773 0.516 0.000 0.000 0.000 0.000 0.484
#> 78F79407-D49F-4FA2-B09F-0665C502827C     6  0.5360    0.12355 0.436 0.000 0.000 0.000 0.108 0.456
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.0146    0.92488 0.000 0.000 0.000 0.004 0.996 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5516    0.30359 0.000 0.360 0.528 0.012 0.000 0.100
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.1408    0.90958 0.000 0.000 0.000 0.036 0.944 0.020
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2060    0.75807 0.900 0.000 0.000 0.016 0.000 0.084
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.0806    0.92122 0.020 0.000 0.000 0.008 0.972 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1075    0.76798 0.952 0.000 0.000 0.048 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.2300    0.85561 0.000 0.144 0.000 0.856 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.0806    0.74368 0.020 0.000 0.000 0.008 0.000 0.972
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.88930 0.000 0.000 1.000 0.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0260    0.88764 0.000 0.000 0.992 0.008 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1398    0.77329 0.940 0.000 0.000 0.008 0.000 0.052
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.0632    0.92049 0.000 0.000 0.000 0.000 0.976 0.024
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0405    0.88720 0.000 0.000 0.988 0.008 0.004 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     6  0.5114    0.11445 0.452 0.000 0.000 0.000 0.080 0.468
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3636    0.39522 0.676 0.000 0.000 0.000 0.004 0.320
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     6  0.4341    0.37521 0.412 0.000 0.000 0.024 0.000 0.564
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     6  0.3014    0.61531 0.012 0.000 0.000 0.000 0.184 0.804
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0405    0.88770 0.000 0.000 0.988 0.008 0.000 0.004
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3023    0.70142 0.000 0.000 0.784 0.004 0.000 0.212
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.0146    0.92488 0.000 0.000 0.000 0.004 0.996 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.0820    0.92235 0.012 0.000 0.000 0.016 0.972 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1556    0.75802 0.920 0.000 0.000 0.000 0.000 0.080
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.2833    0.81174 0.148 0.000 0.004 0.012 0.836 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     6  0.5535    0.49001 0.300 0.132 0.000 0.008 0.000 0.560
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.6014    0.28600 0.000 0.008 0.000 0.448 0.184 0.360
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     6  0.3795    0.49809 0.364 0.000 0.000 0.000 0.004 0.632
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     6  0.6176    0.05031 0.364 0.000 0.000 0.004 0.256 0.376
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.2092    0.86044 0.000 0.124 0.000 0.876 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0000    0.88930 0.000 0.000 1.000 0.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0260    0.88890 0.000 0.000 0.992 0.008 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1141    0.76653 0.948 0.000 0.000 0.052 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2573    0.81160 0.004 0.000 0.856 0.008 0.132 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     6  0.1082    0.73120 0.004 0.000 0.000 0.000 0.040 0.956
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.0405    0.92503 0.004 0.000 0.000 0.008 0.988 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000    0.88930 0.000 0.000 1.000 0.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.1610    0.86045 0.000 0.084 0.000 0.916 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1151    0.77164 0.956 0.000 0.000 0.032 0.012 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.3695    0.55896 0.000 0.376 0.000 0.624 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     6  0.4210    0.56925 0.288 0.000 0.000 0.040 0.000 0.672
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     6  0.3950    0.35398 0.432 0.000 0.000 0.004 0.000 0.564
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0405    0.88770 0.000 0.000 0.988 0.008 0.000 0.004
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3109    0.70447 0.000 0.000 0.772 0.004 0.000 0.224
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.2647    0.86153 0.044 0.000 0.000 0.088 0.868 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1141    0.77298 0.948 0.000 0.000 0.000 0.000 0.052
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.0146    0.92488 0.000 0.000 0.000 0.004 0.996 0.000
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#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.2743    0.78550 0.000 0.000 0.828 0.008 0.164 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     5  0.3108    0.82029 0.128 0.000 0.000 0.044 0.828 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.1327    0.89850 0.000 0.000 0.000 0.064 0.936 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     5  0.0632    0.91964 0.024 0.000 0.000 0.000 0.976 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     4  0.5137    0.58490 0.000 0.084 0.000 0.628 0.272 0.016
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0260    0.88764 0.000 0.000 0.992 0.008 0.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.1984    0.76325 0.912 0.000 0.000 0.000 0.056 0.032
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0790    0.77222 0.968 0.000 0.000 0.032 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.3198    0.68756 0.000 0.000 0.000 0.000 0.740 0.260
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.1092    0.77320 0.960 0.000 0.000 0.020 0.020 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.0603    0.82196 0.000 0.016 0.000 0.980 0.000 0.004
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.3547    0.60396 0.000 0.000 0.696 0.004 0.000 0.300
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0713    0.94271 0.000 0.972 0.000 0.000 0.000 0.028
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.1075    0.84332 0.000 0.048 0.000 0.952 0.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     6  0.0260    0.74120 0.000 0.000 0.000 0.008 0.000 0.992
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.4705   -0.18952 0.480 0.000 0.000 0.044 0.000 0.476
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     5  0.4008    0.55796 0.308 0.000 0.004 0.016 0.672 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.2933    0.76413 0.000 0.000 0.000 0.004 0.796 0.200
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.2474    0.75470 0.880 0.000 0.000 0.000 0.040 0.080
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.1075    0.92311 0.000 0.952 0.000 0.000 0.000 0.048
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     6  0.3558    0.54012 0.248 0.000 0.000 0.016 0.000 0.736
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0405    0.88770 0.000 0.000 0.988 0.008 0.000 0.004
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.4948    0.08677 0.472 0.000 0.000 0.000 0.464 0.064
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.0458    0.92439 0.000 0.000 0.000 0.016 0.984 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.2527    0.84134 0.000 0.168 0.000 0.832 0.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.2902    0.73932 0.000 0.000 0.800 0.004 0.000 0.196
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#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
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#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.1679    0.91342 0.028 0.000 0.000 0.008 0.936 0.028
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#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.0000    0.92483 0.000 0.000 0.000 0.000 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0405    0.88770 0.000 0.000 0.988 0.008 0.000 0.004
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.0000    0.92483 0.000 0.000 0.000 0.000 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.0291    0.92479 0.004 0.000 0.000 0.004 0.992 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.2219    0.70868 0.864 0.000 0.000 0.000 0.000 0.136
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0405    0.88770 0.000 0.000 0.988 0.008 0.000 0.004
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#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1501    0.85724 0.000 0.076 0.000 0.924 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.1391    0.91067 0.016 0.000 0.000 0.000 0.944 0.040
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.2300    0.85561 0.000 0.144 0.000 0.856 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.1812    0.84206 0.000 0.000 0.912 0.008 0.000 0.080
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     6  0.3742    0.52107 0.348 0.000 0.000 0.000 0.004 0.648
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0146    0.96648 0.000 0.996 0.000 0.004 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.0767    0.92210 0.012 0.000 0.004 0.008 0.976 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.3152    0.74452 0.004 0.000 0.196 0.008 0.792 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.0508    0.92524 0.000 0.000 0.004 0.012 0.984 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.2300    0.85561 0.000 0.144 0.000 0.856 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.0146    0.92484 0.000 0.000 0.000 0.004 0.996 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.0547    0.92195 0.000 0.000 0.000 0.000 0.980 0.020
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     6  0.1807    0.74159 0.060 0.000 0.000 0.020 0.000 0.920
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.2473    0.81217 0.000 0.000 0.856 0.008 0.136 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.0000    0.92483 0.000 0.000 0.000 0.000 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2742    0.81169 0.012 0.000 0.852 0.008 0.128 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.0405    0.74226 0.008 0.000 0.000 0.000 0.004 0.988
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0547    0.92186 0.000 0.000 0.000 0.000 0.980 0.020
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     6  0.0146    0.74171 0.000 0.000 0.004 0.000 0.000 0.996
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0713    0.77303 0.972 0.000 0.000 0.028 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2190    0.76011 0.900 0.000 0.000 0.000 0.060 0.040
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     6  0.1556    0.74215 0.080 0.000 0.000 0.000 0.000 0.920
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.2989    0.75241 0.176 0.000 0.812 0.008 0.004 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1225    0.77055 0.952 0.000 0.000 0.036 0.012 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5159    0.05926 0.528 0.000 0.032 0.004 0.024 0.412
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.0260    0.74120 0.000 0.000 0.000 0.008 0.000 0.992
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     6  0.1152    0.74453 0.044 0.000 0.000 0.000 0.004 0.952
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     6  0.4388    0.39807 0.400 0.000 0.000 0.028 0.000 0.572
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.2730    0.65062 0.192 0.000 0.000 0.808 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0000    0.92483 0.000 0.000 0.000 0.000 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.7081    0.27739 0.500 0.000 0.152 0.008 0.140 0.200
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2362    0.82676 0.136 0.000 0.000 0.004 0.860 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.2886    0.72629 0.064 0.000 0.004 0.860 0.000 0.072
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.5448    0.02303 0.000 0.000 0.132 0.352 0.000 0.516
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     6  0.4946    0.59263 0.220 0.000 0.004 0.120 0.000 0.656
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.1858    0.86050 0.000 0.904 0.000 0.004 0.092 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.1471    0.85600 0.064 0.000 0.932 0.004 0.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.3940    0.37664 0.012 0.000 0.348 0.640 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1007    0.77531 0.956 0.000 0.000 0.000 0.000 0.044
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0146    0.92484 0.000 0.000 0.000 0.004 0.996 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2300    0.85561 0.000 0.144 0.000 0.856 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.1267    0.76982 0.940 0.000 0.000 0.000 0.000 0.060
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0937    0.83873 0.000 0.040 0.000 0.960 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1204    0.76539 0.944 0.000 0.000 0.056 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.1049    0.72485 0.000 0.000 0.032 0.008 0.000 0.960
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.6951    0.21281 0.088 0.000 0.456 0.216 0.000 0.240
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     6  0.4166    0.53765 0.324 0.000 0.000 0.028 0.000 0.648
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.0713    0.74018 0.028 0.000 0.000 0.000 0.000 0.972
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2842    0.71911 0.852 0.000 0.000 0.044 0.000 0.104
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.2586    0.83982 0.000 0.032 0.880 0.008 0.080 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.0909    0.74369 0.020 0.000 0.000 0.012 0.000 0.968
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.1500    0.72843 0.012 0.000 0.052 0.000 0.000 0.936
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0713    0.77303 0.972 0.000 0.000 0.028 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3076    0.71408 0.000 0.000 0.000 0.000 0.760 0.240
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.97009 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0146    0.88957 0.000 0.000 0.996 0.004 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.4264    0.49230 0.352 0.000 0.000 0.028 0.000 0.620
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0858    0.91903 0.000 0.000 0.000 0.004 0.968 0.028
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1644    0.77487 0.932 0.000 0.000 0.000 0.028 0.040

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-skmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "pam"]
# you can also extract it by
# res = res_list["MAD:pam"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.983       0.993         0.3742 0.628   0.628
#> 3 3 0.674           0.669       0.854         0.6305 0.797   0.676
#> 4 4 0.749           0.717       0.862         0.1611 0.807   0.570
#> 5 5 0.667           0.603       0.787         0.0774 0.948   0.822
#> 6 6 0.697           0.619       0.783         0.0699 0.877   0.556

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0000      0.994 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.994 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.994 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.994 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.994 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.994 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.9881      0.222 0.564 0.436
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.988 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.994 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.994 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.994 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.994 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.994 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.988 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.994 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.994 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.994 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.994 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.994 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.994 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.988 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.994 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.994 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.994 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.994 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.994 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.994 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.994 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.988 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0376      0.985 0.004 0.996
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.994 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.994 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.994 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.994 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.988 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.994 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.994 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000      0.988 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.994 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.994 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.988 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.994 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.994 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.994 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.994 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.994 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.994 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.988 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.994 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.988 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.994 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000      0.988 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.994 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000      0.994 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.994 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000      0.994 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.994 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000      0.994 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000      0.988 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000      0.994 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.994 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000      0.994 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000      0.994 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.994 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.988 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.994 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000      0.994 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.994 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.994 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.988 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.994 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.994 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.994 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.994 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000      0.994 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.994 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.994 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.988 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0376      0.990 0.996 0.004
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000      0.988 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.994 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.5059      0.872 0.888 0.112
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.994 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.994 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.994 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000      0.994 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000      0.994 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000      0.988 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000      0.988 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.994 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000      0.994 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.994 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000      0.988 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.994 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000      0.994 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000      0.994 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0000      0.994 1.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0000      0.994 1.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000      0.994 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.994 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000      0.994 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.988 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.988 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000      0.994 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000      0.994 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.988 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.6712      0.793 0.176 0.824
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000      0.994 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000      0.994 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0376      0.985 0.004 0.996
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000      0.988 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000      0.994 1.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0000      0.994 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000      0.994 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000      0.994 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000      0.994 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000      0.994 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0000      0.994 1.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000      0.994 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000      0.994 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000      0.994 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000      0.994 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000      0.994 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000      0.994 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     1  0.0000      0.994 1.000 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     1  0.9635      0.363 0.612 0.388
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.0938      0.978 0.012 0.988
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000      0.994 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1  0.0376      0.990 0.996 0.004
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0000      0.994 1.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.0000      0.994 1.000 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000      0.994 1.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000      0.988 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.0000      0.994 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000      0.988 0.000 1.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000      0.988 0.000 1.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000      0.994 1.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000      0.988 0.000 1.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000      0.988 0.000 1.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000      0.994 1.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.0000      0.994 1.000 0.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000      0.988 0.000 1.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.0000      0.994 1.000 0.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0376      0.985 0.004 0.996
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000      0.988 0.000 1.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.0000      0.994 1.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.0000      0.994 1.000 0.000
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000      0.988 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.0000      0.994 1.000 0.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0000      0.994 1.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000      0.994 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0000      0.994 1.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000      0.988 0.000 1.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0000      0.994 1.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     1  0.0000      0.994 1.000 0.000
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.8443      0.632 0.272 0.728
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000      0.994 1.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.0000      0.994 1.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.5519      0.856 0.128 0.872
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000      0.988 0.000 1.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.0000      0.994 1.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1  0.0000      0.994 1.000 0.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000      0.988 0.000 1.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000      0.994 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000      0.988 0.000 1.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000      0.988 0.000 1.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1  0.0000      0.994 1.000 0.000
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000      0.988 0.000 1.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000      0.994 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000      0.988 0.000 1.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.0000      0.994 1.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000      0.994 1.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.0000      0.994 1.000 0.000
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000      0.994 1.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.0000      0.994 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0000      0.994 1.000 0.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0000      0.994 1.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000      0.994 1.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0000      0.994 1.000 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000      0.988 0.000 1.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000      0.988 0.000 1.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.0000      0.994 1.000 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000      0.988 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000      0.994 1.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000      0.994 1.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000      0.988 0.000 1.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000      0.994 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0000      0.994 1.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000      0.988 0.000 1.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000      0.988 0.000 1.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.3274      0.933 0.060 0.940
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000      0.994 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000      0.994 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000      0.994 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000      0.994 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000      0.994 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000      0.988 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.0000      0.994 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000      0.994 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.0000      0.994 1.000 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000      0.994 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.4815      0.882 0.896 0.104
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000      0.994 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000      0.994 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000      0.994 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000      0.994 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000      0.994 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.0000      0.994 1.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000      0.994 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000      0.988 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000      0.988 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0000      0.994 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000      0.994 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000      0.994 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000      0.994 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000      0.994 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000      0.988 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.0000      0.994 1.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.0000      0.994 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.994 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.994 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.3584      0.925 0.068 0.932
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0000      0.994 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000      0.988 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.988 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.988 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000      0.994 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.3733      0.920 0.928 0.072
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000      0.994 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.994 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.994 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000      0.994 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0000      0.994 1.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.994 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.994 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.988 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0376      0.990 0.996 0.004
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000      0.994 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000      0.994 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.988 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0376      0.985 0.004 0.996
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.994 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.988 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.988 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.994 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.994 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.988 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.988 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.1633      0.971 0.976 0.024
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.994 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.994 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.988 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.994 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.988 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.994 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000      0.994 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000      0.994 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.994 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.994 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.988 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.994 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000      0.994 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.994 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.994 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.994 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.994 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000      0.994 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0376      0.990 0.996 0.004
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.994 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.994 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000      0.994 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.994 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.988 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.994 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000      0.994 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.994 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.994 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.994 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.988 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000      0.994 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.6343      0.808 0.840 0.160
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000      0.994 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5842      0.842 0.140 0.860
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000      0.994 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000      0.994 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.994 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.994 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.988 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.994 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0376      0.985 0.004 0.996
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.994 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000      0.994 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.994 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0376      0.990 0.996 0.004
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.994 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000      0.994 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000      0.994 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.994 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.1414      0.975 0.980 0.020
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000      0.994 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000      0.994 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.994 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000      0.994 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.988 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.988 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000      0.994 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.994 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.994 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.994 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.6062     0.7564 0.616 0.000 0.384
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.6079     0.7169 0.388 0.000 0.612
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.2796     0.5064 0.908 0.000 0.092
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.6079     0.7571 0.612 0.000 0.388
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.6079     0.7571 0.612 0.000 0.388
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1163     0.4694 0.972 0.000 0.028
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.9627     0.2654 0.460 0.312 0.228
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9756 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6307    -0.6041 0.512 0.000 0.488
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.5968     0.7484 0.636 0.000 0.364
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.6062     0.7563 0.616 0.000 0.384
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6045     0.7551 0.620 0.000 0.380
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.5180 0.000 0.000 1.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9756 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.6095     0.7558 0.608 0.000 0.392
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.6079     0.7169 0.388 0.000 0.612
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.6079     0.7169 0.388 0.000 0.612
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.6079     0.7571 0.612 0.000 0.388
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.5099 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.5835     0.7066 0.340 0.000 0.660
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9756 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.6095     0.7558 0.608 0.000 0.392
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#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.6079     0.7571 0.612 0.000 0.388
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.6079     0.7169 0.388 0.000 0.612
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000     0.9756 0.000 1.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.9756 0.000 1.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.2200     0.9038 0.056 0.940 0.004
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.6079     0.7571 0.612 0.000 0.388
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.6095     0.7558 0.608 0.000 0.392
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.6079     0.7571 0.612 0.000 0.388
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.6095     0.7558 0.608 0.000 0.392
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000     0.5099 1.000 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.9756 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.6079     0.7169 0.388 0.000 0.612
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000     0.5099 1.000 0.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.4702     0.0131 0.788 0.000 0.212
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.6045     0.7553 0.620 0.000 0.380
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.7075    -0.6225 0.492 0.020 0.488
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.6079     0.7169 0.388 0.000 0.612
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.6079     0.7571 0.612 0.000 0.388
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.6079     0.7571 0.612 0.000 0.388
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0237     0.5077 0.996 0.000 0.004
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.1753     0.5497 0.952 0.000 0.048
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.6079     0.7571 0.612 0.000 0.388
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.6095     0.7558 0.608 0.000 0.392
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000     0.9756 0.000 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0237     0.9721 0.004 0.996 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.6095     0.7558 0.608 0.000 0.392
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.6095     0.7558 0.608 0.000 0.392
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000     0.5099 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.3619     0.2461 0.864 0.000 0.136
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.6079     0.7571 0.612 0.000 0.388
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000     0.9756 0.000 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.6079     0.7571 0.612 0.000 0.388
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.4974     0.6326 0.236 0.000 0.764
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.6079     0.7571 0.612 0.000 0.388
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000     0.5099 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.2356     0.8866 0.072 0.928 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0892     0.5358 0.020 0.000 0.980
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9756 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9756 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9756 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.6079     0.7169 0.388 0.000 0.612
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.1964     0.5438 0.000 0.056 0.944
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000     0.5099 1.000 0.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.5099 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.5099 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.5180 0.000 0.000 1.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.6302    -0.6085 0.480 0.000 0.520
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.3116     0.5938 0.892 0.000 0.108
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000     0.5099 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9756 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.6079     0.7571 0.612 0.000 0.388
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.6307    -0.6187 0.488 0.000 0.512
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5968     0.7455 0.636 0.000 0.364
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9756 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9756 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.5099 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9756 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9756 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.6299    -0.6031 0.476 0.000 0.524
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.6095     0.7558 0.608 0.000 0.392
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9756 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9756 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.6062     0.7166 0.384 0.000 0.616
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     3  0.6168    -0.4954 0.412 0.000 0.588
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.6244     0.6767 0.440 0.000 0.560
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9756 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.1411     0.5222 0.964 0.000 0.036
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9756 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.4654     0.0246 0.792 0.000 0.208
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000     0.5099 1.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.6079     0.7571 0.612 0.000 0.388
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.6079     0.7169 0.388 0.000 0.612
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.5099 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9756 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.1860     0.5619 0.052 0.000 0.948
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.6079     0.7571 0.612 0.000 0.388
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0237     0.5050 0.996 0.000 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.6154     0.7419 0.592 0.000 0.408
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.6079     0.7571 0.612 0.000 0.388
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.6079     0.7571 0.612 0.000 0.388
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6252     0.3449 0.556 0.000 0.444
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.0747     0.5026 0.016 0.000 0.984
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.6079     0.7571 0.612 0.000 0.388
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.6095     0.7558 0.608 0.000 0.392
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.6095     0.7558 0.608 0.000 0.392
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.6095     0.7558 0.608 0.000 0.392
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9756 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.6079     0.7571 0.612 0.000 0.388
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.3116     0.5944 0.892 0.000 0.108
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.5099 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.6095     0.7558 0.608 0.000 0.392
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1643     0.5460 0.956 0.000 0.044
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9756 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.6026     0.7513 0.624 0.000 0.376
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.7348     0.3079 0.176 0.120 0.704
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6079     0.7571 0.612 0.000 0.388
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.4505     0.8053 0.048 0.860 0.092
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6095     0.7558 0.608 0.000 0.392
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.6095     0.7147 0.392 0.000 0.608
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.5099 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4504     0.0627 0.804 0.000 0.196
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9756 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.6079     0.7571 0.612 0.000 0.388
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.2356     0.9007 0.072 0.928 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6079     0.7571 0.612 0.000 0.388
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.6079    -0.4530 0.612 0.000 0.388
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6095     0.7558 0.608 0.000 0.392
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.6079     0.7571 0.612 0.000 0.388
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.6079     0.7571 0.612 0.000 0.388
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.6079     0.7571 0.612 0.000 0.388
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.6079     0.7571 0.612 0.000 0.388
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.5180 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.6079     0.7169 0.388 0.000 0.612
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6095     0.7558 0.608 0.000 0.392
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5254     0.6877 0.736 0.000 0.264
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.6079     0.7571 0.612 0.000 0.388
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4887    -0.0443 0.772 0.000 0.228
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9756 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9756 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2261     0.5753 0.068 0.000 0.932
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.6095     0.7558 0.608 0.000 0.392
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.5254     0.6915 0.736 0.000 0.264
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.6079     0.7571 0.612 0.000 0.388

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0672    0.86026 0.984 0.000 0.008 0.008
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     4  0.5646    0.18153 0.088 0.000 0.204 0.708
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> 03E81178-E971-4E91-8BED-D8273EA1425C     4  0.5174    0.63505 0.368 0.000 0.012 0.620
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4978    0.26402 0.384 0.004 0.612 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.5125    0.31776 0.008 0.000 0.388 0.604
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1118    0.83967 0.964 0.000 0.000 0.036
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0469    0.86602 0.988 0.000 0.000 0.012
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0469    0.86150 0.988 0.000 0.000 0.012
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.4790    0.43244 0.620 0.000 0.000 0.380
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1211    0.82241 0.000 0.000 0.960 0.040
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.1022    0.82762 0.000 0.000 0.968 0.032
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     4  0.4916    0.59325 0.424 0.000 0.000 0.576
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4866    0.42312 0.596 0.000 0.000 0.404
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4804    0.26639 0.384 0.000 0.616 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0779    0.86501 0.980 0.000 0.004 0.016
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1118    0.85618 0.964 0.000 0.000 0.036
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.5028    0.62390 0.400 0.000 0.004 0.596
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1004    0.86100 0.972 0.000 0.004 0.024
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0707    0.86458 0.980 0.000 0.000 0.020
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.4406    0.64987 0.300 0.000 0.000 0.700
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#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.2830    0.87230 0.060 0.900 0.040 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.4855    0.42563 0.600 0.000 0.000 0.400
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     4  0.4790    0.62820 0.380 0.000 0.000 0.620
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     4  0.4866    0.29396 0.000 0.000 0.404 0.596
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     4  0.4866    0.62159 0.404 0.000 0.000 0.596
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     4  0.6055    0.63784 0.240 0.000 0.096 0.664
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.1022    0.85950 0.968 0.000 0.000 0.032
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.1211    0.82241 0.000 0.000 0.960 0.040
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0592    0.86576 0.984 0.000 0.000 0.016
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     4  0.4999    0.46070 0.492 0.000 0.000 0.508
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0707    0.86458 0.980 0.000 0.000 0.020
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.4008    0.72539 0.000 0.756 0.000 0.244
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.1398    0.93077 0.004 0.956 0.040 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.4790    0.43244 0.620 0.000 0.000 0.380
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     4  0.4790    0.62820 0.380 0.000 0.000 0.620
#> C86EBD08-53F2-4972-801A-74970FDD6A62     4  0.0188    0.50120 0.004 0.000 0.000 0.996
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.2773    0.88773 0.000 0.900 0.028 0.072
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.4790    0.43244 0.620 0.000 0.000 0.380
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0707    0.83106 0.020 0.000 0.980 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     4  0.4843    0.62509 0.396 0.000 0.000 0.604
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.2563    0.86679 0.072 0.908 0.020 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.1211    0.82241 0.000 0.000 0.960 0.040
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     4  0.5050    0.61637 0.408 0.000 0.004 0.588
#> B55743F2-4D63-4375-85D3-F58281CFD852     4  0.4790    0.62820 0.380 0.000 0.000 0.620
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     4  0.4790    0.62820 0.380 0.000 0.000 0.620
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4817    0.26168 0.388 0.000 0.612 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4888   -0.10408 0.588 0.000 0.000 0.412
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     4  0.4830    0.62637 0.392 0.000 0.000 0.608
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0336    0.86683 0.992 0.000 0.000 0.008
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.4804    0.26639 0.384 0.000 0.616 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.4925    0.38562 0.572 0.000 0.000 0.428
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0469    0.95319 0.000 0.988 0.012 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0336    0.95464 0.000 0.992 0.000 0.008
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.4989    0.09957 0.472 0.000 0.528 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.3015    0.77278 0.884 0.000 0.092 0.024
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     4  0.5244    0.31647 0.012 0.000 0.388 0.600
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     4  0.5105    0.55675 0.432 0.000 0.004 0.564
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     4  0.6635    0.60916 0.228 0.000 0.152 0.620
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     4  0.4866    0.29396 0.000 0.000 0.404 0.596
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     4  0.4866    0.62159 0.404 0.000 0.000 0.596
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2300    0.79717 0.048 0.000 0.924 0.028
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.1022    0.86016 0.968 0.000 0.000 0.032
#> D365A238-4739-4B54-9608-DC548F21C04E     4  0.3907    0.64679 0.232 0.000 0.000 0.768
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.2125    0.80802 0.920 0.000 0.076 0.004
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0817    0.86336 0.976 0.000 0.000 0.024
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     4  0.6599   -0.05398 0.432 0.000 0.080 0.488
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1716    0.79608 0.064 0.000 0.936 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0707    0.86458 0.980 0.000 0.000 0.020
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.4855    0.42563 0.600 0.000 0.000 0.400
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1716    0.83510 0.936 0.000 0.000 0.064
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.4713    0.05242 0.640 0.000 0.000 0.360
#> 9AF0E82E-E621-437A-8D19-700532B95090     4  0.4193    0.65308 0.268 0.000 0.000 0.732
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0707    0.86116 0.980 0.000 0.020 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     4  0.4996    0.44214 0.484 0.000 0.000 0.516
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.1042    0.85094 0.972 0.000 0.008 0.020
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6903    0.37919 0.112 0.000 0.508 0.380
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.3542    0.79495 0.120 0.852 0.000 0.028
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.4855    0.46586 0.644 0.000 0.004 0.352
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.5435    0.25774 0.016 0.000 0.420 0.564
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     4  0.4855    0.62359 0.400 0.000 0.000 0.600
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.3241    0.86362 0.004 0.884 0.040 0.072
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     4  0.1820    0.47714 0.020 0.000 0.036 0.944
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.1118    0.84856 0.964 0.000 0.036 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4866    0.42312 0.596 0.000 0.000 0.404
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.4761    0.28975 0.000 0.000 0.628 0.372
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.2760    0.74812 0.872 0.000 0.000 0.128
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.2973    0.67947 0.856 0.000 0.000 0.144
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.86726 1.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.0000    0.50147 0.000 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.96093 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.84492 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0469    0.86642 0.988 0.000 0.000 0.012
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.4898   -0.05552 0.416 0.000 0.000 0.584
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0188    0.86687 0.996 0.000 0.000 0.004

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.2612     0.6640 0.868 0.000 0.000 0.124 0.008
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.7875     0.2172 0.088 0.000 0.204 0.308 0.400
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.1768     0.7118 0.072 0.000 0.004 0.000 0.924
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4276     0.4013 0.380 0.000 0.616 0.004 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.1544     0.7349 0.000 0.932 0.000 0.068 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4846     0.3918 0.000 0.000 0.384 0.028 0.588
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1750     0.7069 0.936 0.000 0.000 0.036 0.028
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3876     0.6254 0.684 0.000 0.000 0.000 0.316
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1251     0.7187 0.956 0.000 0.000 0.036 0.008
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4268    -0.0555 0.000 0.556 0.000 0.444 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.5325     0.5606 0.616 0.000 0.000 0.308 0.076
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0510     0.8804 0.000 0.000 0.984 0.000 0.016
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0963     0.7275 0.964 0.000 0.000 0.000 0.036
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.1341     0.6906 0.000 0.000 0.000 0.056 0.944
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0510     0.8804 0.000 0.000 0.984 0.000 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     5  0.5092     0.4053 0.440 0.000 0.000 0.036 0.524
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.7268 1.000 0.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.6009     0.5640 0.580 0.000 0.000 0.240 0.180
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3999     0.4592 0.344 0.000 0.656 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.4717     0.5377 0.660 0.000 0.308 0.004 0.028
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4045     0.6034 0.644 0.000 0.000 0.000 0.356
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.5983     0.5551 0.252 0.000 0.168 0.000 0.580
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#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     4  0.3999     0.6077 0.000 0.344 0.000 0.656 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     5  0.6524     0.6000 0.080 0.000 0.140 0.148 0.632
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.4088     0.5863 0.632 0.000 0.000 0.000 0.368
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.3596     0.6813 0.776 0.000 0.000 0.012 0.212
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0510     0.7681 0.000 0.984 0.016 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.1124     0.7230 0.960 0.000 0.000 0.036 0.004
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.4210     0.1122 0.000 0.000 0.588 0.000 0.412
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     4  0.4219     0.4659 0.000 0.416 0.000 0.584 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     4  0.3990     0.4742 0.308 0.004 0.000 0.688 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0880     0.7231 0.968 0.000 0.000 0.032 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.5699     0.5484 0.584 0.000 0.000 0.308 0.108
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     5  0.4227     0.5869 0.292 0.000 0.000 0.016 0.692
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     5  0.4227     0.3536 0.000 0.000 0.420 0.000 0.580
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     5  0.5065     0.4414 0.420 0.000 0.000 0.036 0.544
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     5  0.1648     0.7136 0.020 0.000 0.040 0.000 0.940
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.4030     0.6066 0.648 0.000 0.000 0.000 0.352
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     5  0.4291     0.3339 0.000 0.000 0.000 0.464 0.536
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0510     0.8804 0.000 0.000 0.984 0.000 0.016
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.2329     0.7102 0.876 0.000 0.000 0.000 0.124
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.0000     0.7030 0.000 0.000 0.000 0.000 1.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.5114    -0.3114 0.492 0.000 0.000 0.036 0.472
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.0000     0.7268 1.000 0.000 0.000 0.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.4118     0.6169 0.660 0.000 0.004 0.000 0.336
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.3491     0.4787 0.000 0.768 0.000 0.228 0.004
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.3837     0.4747 0.308 0.000 0.000 0.692 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.5325     0.5606 0.616 0.000 0.000 0.308 0.076
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000     0.7268 1.000 0.000 0.000 0.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     5  0.1671     0.7099 0.076 0.000 0.000 0.000 0.924
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.3990     0.5255 0.004 0.000 0.000 0.308 0.688
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.3055     0.6606 0.000 0.840 0.016 0.144 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.5213     0.5971 0.640 0.000 0.000 0.284 0.076
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0404     0.8789 0.012 0.000 0.988 0.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.2127     0.7064 0.108 0.000 0.000 0.000 0.892
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.4644    -0.1475 0.000 0.528 0.012 0.460 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.1608     0.7320 0.000 0.928 0.000 0.072 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0510     0.8804 0.000 0.000 0.984 0.000 0.016
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.7060     0.5618 0.120 0.000 0.200 0.108 0.572
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.1671     0.7099 0.076 0.000 0.000 0.000 0.924
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.1671     0.7099 0.076 0.000 0.000 0.000 0.924
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4138     0.4004 0.384 0.000 0.616 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.3661     0.3909 0.276 0.000 0.000 0.000 0.724
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.1908     0.7096 0.092 0.000 0.000 0.000 0.908
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4677     0.6346 0.664 0.000 0.000 0.036 0.300
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1732     0.8001 0.080 0.000 0.920 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.5932     0.5295 0.560 0.000 0.000 0.308 0.132
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.4135     0.6093 0.004 0.340 0.000 0.656 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.0000     0.7030 0.000 0.000 0.000 0.000 1.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.4219     0.0565 0.000 0.584 0.000 0.416 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3837     0.3308 0.000 0.692 0.000 0.000 0.308
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.2605     0.7306 0.148 0.000 0.852 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3796     0.3863 0.000 0.700 0.000 0.300 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.4794     0.5915 0.624 0.000 0.032 0.000 0.344
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.4686     0.4079 0.020 0.000 0.384 0.000 0.596
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.2561     0.6425 0.000 0.856 0.000 0.144 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.3060     0.6810 0.128 0.000 0.024 0.000 0.848
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.4291    -0.1247 0.000 0.536 0.000 0.464 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.1965     0.7113 0.024 0.000 0.052 0.000 0.924
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.3684     0.5514 0.000 0.000 0.000 0.280 0.720
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.3039     0.6830 0.808 0.000 0.000 0.192 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.4227     0.3536 0.000 0.000 0.420 0.000 0.580
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.3039     0.6761 0.192 0.000 0.000 0.000 0.808
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0404     0.7773 0.000 0.988 0.000 0.012 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.1818     0.8388 0.024 0.000 0.932 0.000 0.044
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.4642     0.6126 0.660 0.000 0.000 0.308 0.032
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.0703     0.7129 0.024 0.000 0.000 0.000 0.976
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5811     0.5197 0.604 0.000 0.272 0.120 0.004
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3999     0.6132 0.656 0.000 0.000 0.000 0.344
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.7752     0.2807 0.440 0.000 0.080 0.228 0.252
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1121     0.8556 0.044 0.000 0.956 0.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3983     0.6158 0.660 0.000 0.000 0.000 0.340
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.5699     0.5484 0.584 0.000 0.000 0.308 0.108
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4060     0.6054 0.640 0.000 0.000 0.000 0.360
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2516     0.6598 0.000 0.860 0.000 0.140 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.4836     0.1279 0.628 0.000 0.000 0.036 0.336
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.0794     0.7141 0.028 0.000 0.000 0.000 0.972
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4843     0.6199 0.660 0.000 0.048 0.000 0.292
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2929     0.6064 0.180 0.000 0.000 0.000 0.820
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.1485     0.7145 0.948 0.000 0.000 0.032 0.020
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.7243     0.2572 0.112 0.000 0.460 0.352 0.076
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0162     0.7266 0.996 0.000 0.000 0.004 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.4443     0.4303 0.028 0.744 0.000 0.016 0.212
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5272     0.5645 0.620 0.000 0.000 0.308 0.072
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     5  0.5816     0.3154 0.036 0.000 0.416 0.032 0.516
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     5  0.5059     0.4460 0.416 0.000 0.000 0.036 0.548
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.0000     0.7030 0.000 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.4256     0.4170 0.000 0.436 0.000 0.564 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.7268 1.000 0.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.3837     0.4747 0.308 0.000 0.000 0.692 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.5183     0.5052 0.036 0.000 0.016 0.308 0.640
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0880     0.7228 0.968 0.000 0.032 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0510     0.7255 0.984 0.000 0.000 0.016 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5740     0.5464 0.580 0.000 0.000 0.308 0.112
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0880     0.7230 0.968 0.000 0.000 0.032 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.4278     0.2125 0.000 0.000 0.452 0.000 0.548
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.4565     0.6025 0.664 0.000 0.000 0.308 0.028
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.6958     0.4172 0.572 0.000 0.216 0.080 0.132
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0963     0.7220 0.964 0.000 0.000 0.036 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3837     0.5266 0.000 0.000 0.000 0.308 0.692
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.7842 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1478     0.7392 0.000 0.936 0.000 0.064 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8876 0.000 0.000 1.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0510     0.7272 0.984 0.000 0.000 0.000 0.016
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.5861    -0.2424 0.400 0.000 0.000 0.100 0.500
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2325     0.7226 0.904 0.000 0.000 0.028 0.068

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.1226     0.7632 0.952 0.000 0.000 0.040 0.004 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.9242 0.000 0.000 1.000 0.000 0.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.6994     0.1822 0.004 0.000 0.200 0.116 0.496 0.184
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     6  0.1610     0.6846 0.084 0.000 0.000 0.000 0.000 0.916
#> 78F79407-D49F-4FA2-B09F-0665C502827C     6  0.1610     0.6845 0.084 0.000 0.000 0.000 0.000 0.916
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.3847     0.5264 0.000 0.000 0.000 0.000 0.544 0.456
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2912     0.6720 0.216 0.000 0.784 0.000 0.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3118     0.7217 0.072 0.836 0.000 0.092 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.2823     0.6372 0.000 0.000 0.204 0.000 0.796 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0146     0.7776 0.996 0.000 0.000 0.000 0.000 0.004
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#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.4498     0.3518 0.000 0.640 0.000 0.024 0.016 0.320
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     6  0.7210     0.3184 0.220 0.000 0.000 0.128 0.220 0.432
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     5  0.6856     0.3348 0.256 0.000 0.228 0.068 0.448 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2398     0.6913 0.876 0.000 0.000 0.000 0.104 0.020
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.3499     0.6513 0.000 0.000 0.000 0.000 0.680 0.320
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.3464     0.6291 0.000 0.312 0.000 0.688 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3854     0.1699 0.536 0.000 0.000 0.000 0.000 0.464
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.3221     0.5672 0.264 0.000 0.000 0.736 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0146     0.7776 0.996 0.000 0.000 0.000 0.000 0.004
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.4104     0.4666 0.016 0.000 0.000 0.132 0.772 0.080
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.5745    -0.0265 0.416 0.000 0.168 0.000 0.000 0.416
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0547     0.7747 0.980 0.000 0.000 0.000 0.000 0.020
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.3695     0.3463 0.624 0.000 0.000 0.000 0.000 0.376
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.5492     0.5253 0.028 0.000 0.000 0.132 0.208 0.632
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2562     0.6631 0.828 0.000 0.000 0.000 0.000 0.172
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.9242 0.000 0.000 1.000 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.5580     0.5042 0.000 0.000 0.324 0.000 0.516 0.160
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.6770     0.3093 0.292 0.000 0.000 0.060 0.204 0.444
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.7454     0.4114 0.144 0.000 0.160 0.020 0.212 0.464
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0146     0.7776 0.996 0.000 0.000 0.000 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.5328     0.2622 0.000 0.000 0.000 0.132 0.560 0.308
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8870 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1556     0.8149 0.000 0.920 0.000 0.080 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.9242 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.3828     0.1256 0.440 0.000 0.000 0.000 0.000 0.560
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     6  0.4707     0.3162 0.000 0.000 0.000 0.112 0.216 0.672
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2730     0.6606 0.808 0.000 0.000 0.000 0.000 0.192

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-pam-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "mclust"]
# you can also extract it by
# res = res_list["MAD:mclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.975       0.991         0.3825 0.625   0.625
#> 3 3 0.817           0.858       0.942         0.6543 0.736   0.580
#> 4 4 0.671           0.700       0.792         0.1343 0.851   0.614
#> 5 5 0.628           0.650       0.751         0.0370 0.907   0.678
#> 6 6 0.609           0.495       0.702         0.0492 0.951   0.807

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.6887     0.7711 0.816 0.184
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000     0.9890 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000     0.9890 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9890 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9890 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9890 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.6048     0.8233 0.148 0.852
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9944 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000     0.9890 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9890 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9890 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9890 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000     0.9890 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9944 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000     0.9890 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000     0.9890 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000     0.9890 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9890 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9890 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000     0.9890 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9944 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9890 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9890 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9890 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000     0.9890 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9890 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000     0.9890 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.9890 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9944 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9944 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9890 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.9890 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9890 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9890 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9944 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000     0.9890 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000     0.9890 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9944 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9890 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9890 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9944 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000     0.9890 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000     0.9890 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.9890 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9890 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000     0.9890 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9890 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9944 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000     0.9890 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9944 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.9890 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9944 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000     0.9890 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000     0.9890 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9890 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000     0.9890 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000     0.9890 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000     0.9890 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9944 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.9890 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.9890 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000     0.9890 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000     0.9890 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.9890 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9944 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000     0.9890 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.9890 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000     0.9890 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000     0.9890 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9944 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.9890 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000     0.9890 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000     0.9890 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.9890 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000     0.9890 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.9890 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000     0.9890 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9944 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000     0.9890 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000     0.9944 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000     0.9890 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.8327     0.6368 0.264 0.736
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000     0.9890 1.000 0.000
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#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000     0.9890 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9890 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000     0.9890 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000     0.9890 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9890 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000     0.9890 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000     0.9890 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000     0.9890 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000     0.9890 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000     0.9890 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000     0.9890 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9944 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000     0.9890 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000     0.9890 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9890 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.9890 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9890 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9944 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000     0.9890 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.9996     0.0563 0.512 0.488
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000     0.9890 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.9988     0.0870 0.520 0.480
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000     0.9890 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000     0.9890 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9890 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9890 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9944 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9890 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9944 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.9890 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000     0.9890 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000     0.9890 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.9850     0.2583 0.572 0.428
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.9890 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.9890 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.9890 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000     0.9890 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000     0.9890 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000     0.9890 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000     0.9890 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9890 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9890 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9944 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9944 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000     0.9890 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.9890 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9890 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9890 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0000     0.8904 0.000 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8904 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000     0.8904 0.000 0.000 1.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9344 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9344 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9344 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6235     0.1712 0.000 0.436 0.564
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9736 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.0424     0.8882 0.008 0.000 0.992
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9344 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9344 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9344 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1031     0.8810 0.024 0.000 0.976
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9736 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.5254     0.6546 0.264 0.000 0.736
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1529     0.8719 0.040 0.000 0.960
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1964     0.8940 0.944 0.000 0.056
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9344 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9344 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4931     0.6901 0.232 0.000 0.768
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9736 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9344 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9344 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9344 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8904 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9344 1.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000     0.8904 0.000 0.000 1.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.9344 1.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9736 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9736 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.2625     0.8659 0.916 0.000 0.084
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.6126     0.3289 0.600 0.000 0.400
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9344 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9344 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0592     0.9640 0.000 0.988 0.012
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.0000     0.8904 0.000 0.000 1.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.0000     0.8904 0.000 0.000 1.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9736 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9344 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9344 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9736 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6079     0.3641 0.388 0.000 0.612
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000     0.8904 0.000 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0424     0.9296 0.992 0.000 0.008
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.1031     0.9189 0.976 0.000 0.024
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.1643     0.9042 0.956 0.000 0.044
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9344 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9736 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5216     0.6431 0.260 0.000 0.740
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9736 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.9344 1.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9736 0.000 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.6154     0.3074 0.592 0.000 0.408
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.6235     0.2742 0.436 0.000 0.564
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9344 1.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0000     0.8904 0.000 0.000 1.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.8904 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     3  0.6286     0.1444 0.464 0.000 0.536
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9736 0.000 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.9344 1.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.5138     0.6551 0.748 0.000 0.252
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.4399     0.7597 0.188 0.000 0.812
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.6307     0.0488 0.488 0.000 0.512
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.9344 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9736 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.8904 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.9344 1.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0592     0.9270 0.988 0.000 0.012
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.8904 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9736 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0237     0.9321 0.996 0.000 0.004
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000     0.9344 1.000 0.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.5905     0.4558 0.648 0.000 0.352
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.9344 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.6244     0.1654 0.560 0.000 0.440
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.9344 1.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.5785     0.5003 0.668 0.000 0.332
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9736 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.8904 0.000 0.000 1.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0747     0.9605 0.000 0.984 0.016
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000     0.9344 1.000 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6126     0.2697 0.000 0.400 0.600
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0424     0.9292 0.992 0.000 0.008
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.9344 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.9344 1.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5363     0.6129 0.724 0.000 0.276
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000     0.9344 1.000 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9736 0.000 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9736 0.000 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0237     0.8893 0.004 0.000 0.996
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.5254     0.6325 0.736 0.000 0.264
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000     0.9344 1.000 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9736 0.000 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.5926     0.4470 0.356 0.000 0.644
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.2356     0.8788 0.928 0.000 0.072
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.9344 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.0000     0.8904 0.000 0.000 1.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.0592     0.8868 0.012 0.000 0.988
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     3  0.4555     0.7459 0.200 0.000 0.800
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.4291     0.7580 0.180 0.000 0.820
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.0000     0.8904 0.000 0.000 1.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9736 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9736 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000     0.9344 1.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.5431     0.5985 0.716 0.000 0.284
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9736 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     3  0.0000     0.8904 0.000 0.000 1.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.5327     0.6230 0.272 0.000 0.728
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000     0.9344 1.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000     0.9736 0.000 1.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9736 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     3  0.1031     0.8821 0.024 0.000 0.976
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000     0.8904 0.000 0.000 1.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.2959     0.8346 0.100 0.000 0.900
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.3686     0.8098 0.860 0.000 0.140
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000     0.9344 1.000 0.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0424     0.9297 0.992 0.000 0.008
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#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0000     0.8904 0.000 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     3  0.2959     0.8142 0.000 0.100 0.900
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5560     0.5775 0.300 0.000 0.700
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.0000     0.8904 0.000 0.000 1.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9344 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9344 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9736 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9344 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.4605     0.7454 0.000 0.796 0.204
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6225     0.2024 0.568 0.000 0.432
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0592     0.8869 0.012 0.000 0.988
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000     0.8904 0.000 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.0000     0.8904 0.000 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5363     0.6387 0.276 0.000 0.724
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0892     0.9208 0.980 0.000 0.020
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.0000     0.8904 0.000 0.000 1.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0424     0.8880 0.008 0.000 0.992
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0000     0.8904 0.000 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0000     0.8904 0.000 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000     0.9344 1.000 0.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9344 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9344 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9736 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9736 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8904 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3816     0.7984 0.852 0.000 0.148
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9344 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9344 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0592    0.81520 0.000 0.000 0.984 0.016
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0188    0.81443 0.000 0.000 0.996 0.004
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0188    0.81443 0.000 0.000 0.996 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     4  0.4907    0.77632 0.420 0.000 0.000 0.580
#> 78F79407-D49F-4FA2-B09F-0665C502827C     4  0.4941    0.76001 0.436 0.000 0.000 0.564
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0188    0.76104 0.996 0.000 0.000 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5464    0.55699 0.000 0.228 0.708 0.064
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.5620    0.66501 0.208 0.000 0.708 0.084
#> 53062969-D209-490B-9C9B-5D297625E2AE     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0817    0.75752 0.976 0.000 0.000 0.024
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.4053    0.78892 0.004 0.000 0.768 0.228
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.2089    0.80405 0.048 0.000 0.932 0.020
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4767    0.77794 0.020 0.000 0.724 0.256
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1356    0.75150 0.960 0.000 0.008 0.032
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     4  0.4697    0.79371 0.356 0.000 0.000 0.644
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000    0.76195 1.000 0.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.6197   -0.02140 0.508 0.000 0.440 0.052
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     4  0.4941    0.76001 0.436 0.000 0.000 0.564
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     4  0.4830    0.79368 0.392 0.000 0.000 0.608
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1557    0.82034 0.000 0.000 0.944 0.056
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4804   -0.29767 0.616 0.000 0.000 0.384
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3907    0.78852 0.000 0.000 0.768 0.232
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     4  0.5861    0.64191 0.480 0.000 0.032 0.488
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1406    0.75969 0.960 0.000 0.016 0.024
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3245    0.70459 0.880 0.000 0.056 0.064
#> 904EDF2E-411E-43BD-901D-46129AFA283A     4  0.4679    0.79191 0.352 0.000 0.000 0.648
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1302    0.74439 0.956 0.000 0.000 0.044
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.2644    0.90490 0.000 0.908 0.032 0.060
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.3801    0.80015 0.000 0.000 0.780 0.220
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.2521    0.80778 0.024 0.000 0.912 0.064
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     4  0.4925    0.76944 0.428 0.000 0.000 0.572
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     4  0.4961    0.74749 0.448 0.000 0.000 0.552
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6098    0.46125 0.292 0.000 0.632 0.076
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2814    0.81472 0.000 0.000 0.868 0.132
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     4  0.4467    0.56659 0.172 0.000 0.040 0.788
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0707    0.76096 0.980 0.000 0.000 0.020
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2408    0.71943 0.920 0.000 0.036 0.044
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0921    0.75580 0.972 0.000 0.000 0.028
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.4706    0.59063 0.248 0.000 0.732 0.020
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4981   -0.39623 0.536 0.000 0.000 0.464
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.6748    0.23826 0.328 0.000 0.560 0.112
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.6300    0.66878 0.084 0.000 0.608 0.308
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2149    0.81912 0.000 0.000 0.912 0.088
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0336    0.81361 0.000 0.000 0.992 0.008
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.6728    0.33860 0.596 0.000 0.268 0.136
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0336    0.95910 0.000 0.992 0.000 0.008
#> A22892DE-0AF4-4B63-9513-1D6825059040     4  0.4776    0.79695 0.376 0.000 0.000 0.624
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.1706    0.72913 0.948 0.000 0.016 0.036
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.7763    0.54559 0.264 0.000 0.432 0.304
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.7214    0.07234 0.476 0.000 0.380 0.144
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     4  0.4697    0.79352 0.356 0.000 0.000 0.644
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0336    0.81361 0.000 0.000 0.992 0.008
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4830   -0.08795 0.608 0.000 0.000 0.392
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0817    0.75111 0.976 0.000 0.000 0.024
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0188    0.81443 0.000 0.000 0.996 0.004
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0188    0.76208 0.996 0.000 0.000 0.004
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0188    0.76208 0.996 0.000 0.000 0.004
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.3015    0.68257 0.884 0.000 0.092 0.024
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.6587   -0.10326 0.100 0.000 0.324 0.576
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000    0.76195 1.000 0.000 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.2759    0.71544 0.904 0.000 0.052 0.044
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000    0.81468 0.000 0.000 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.4227    0.82155 0.000 0.820 0.120 0.060
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     4  0.4955    0.75296 0.444 0.000 0.000 0.556
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.6078    0.36902 0.000 0.312 0.620 0.068
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000    0.76195 1.000 0.000 0.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0817    0.75752 0.976 0.000 0.000 0.024
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     4  0.4933    0.76491 0.432 0.000 0.000 0.568
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.4499    0.61027 0.804 0.000 0.072 0.124
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3569    0.56306 0.804 0.000 0.000 0.196
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.1661    0.81087 0.052 0.000 0.944 0.004
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3453    0.69781 0.868 0.000 0.080 0.052
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0817    0.75713 0.976 0.000 0.000 0.024
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.6380   -0.02707 0.500 0.000 0.436 0.064
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.1854    0.75036 0.940 0.000 0.012 0.048
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0921    0.75580 0.972 0.000 0.000 0.028
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.3801    0.80357 0.000 0.000 0.780 0.220
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.5754    0.75804 0.048 0.000 0.636 0.316
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.6898    0.10407 0.524 0.000 0.360 0.116
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.5374    0.75321 0.052 0.000 0.704 0.244
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.0188    0.81443 0.000 0.000 0.996 0.004
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.1118    0.75219 0.964 0.000 0.000 0.036
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.3398    0.69813 0.872 0.000 0.060 0.068
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0188    0.96006 0.000 0.996 0.000 0.004
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     3  0.6071    0.67151 0.196 0.012 0.700 0.092
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.5783    0.62551 0.188 0.000 0.704 0.108
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000    0.76195 1.000 0.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 7139D616-1A15-4288-A9AE-411856A4A76D     3  0.5655    0.66301 0.212 0.000 0.704 0.084
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.1389    0.82011 0.000 0.000 0.952 0.048
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.0817    0.81882 0.000 0.000 0.976 0.024
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     4  0.7072   -0.01757 0.140 0.000 0.336 0.524
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.1118    0.75831 0.964 0.000 0.000 0.036
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000    0.76195 1.000 0.000 0.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     3  0.6022    0.60024 0.260 0.000 0.656 0.084
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     4  0.4776    0.79695 0.376 0.000 0.000 0.624
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     4  0.4830    0.79368 0.392 0.000 0.000 0.608
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     4  0.4925    0.76944 0.428 0.000 0.000 0.572
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     4  0.4925    0.76944 0.428 0.000 0.000 0.572
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     3  0.5366    0.74208 0.040 0.000 0.684 0.276
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.3444    0.81311 0.000 0.000 0.816 0.184
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#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.3837    0.80172 0.000 0.000 0.776 0.224
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.2124    0.79036 0.000 0.008 0.924 0.068
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.3356    0.80638 0.000 0.000 0.824 0.176
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     3  0.7024    0.67636 0.088 0.132 0.680 0.100
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6248    0.53562 0.224 0.000 0.656 0.120
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.5397    0.79514 0.068 0.000 0.720 0.212
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     4  0.4804    0.79620 0.384 0.000 0.000 0.616
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0188    0.76208 0.996 0.000 0.000 0.004
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.96085 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     4  0.4643    0.78796 0.344 0.000 0.000 0.656
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.5394    0.68720 0.000 0.712 0.228 0.060
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.6837    0.46026 0.100 0.000 0.472 0.428
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0336    0.81361 0.000 0.000 0.992 0.008
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1389    0.82045 0.000 0.000 0.952 0.048
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.1890    0.81524 0.000 0.008 0.936 0.056
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5906    0.70901 0.064 0.000 0.644 0.292
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.5435    0.77052 0.420 0.000 0.016 0.564
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.4283    0.79584 0.004 0.000 0.740 0.256
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.4103    0.78712 0.000 0.000 0.744 0.256
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.5417    0.69372 0.180 0.000 0.732 0.088
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0921    0.81874 0.000 0.000 0.972 0.028
#> 835AAE7F-F873-4D11-8845-232D261A38DF     4  0.6233    0.75014 0.388 0.000 0.060 0.552
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     4  0.4661    0.78764 0.348 0.000 0.000 0.652
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1022    0.75159 0.968 0.000 0.000 0.032
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0707    0.95594 0.000 0.980 0.000 0.020
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3311    0.80736 0.000 0.000 0.828 0.172
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.7651    0.49854 0.320 0.000 0.228 0.452
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0188    0.76208 0.996 0.000 0.000 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3873    0.44567 0.772 0.000 0.000 0.228

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.2927   0.544398 0.000 0.000 0.868 0.092 0.040
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.5398   0.420066 0.000 0.000 0.648 0.112 0.240
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5564   0.464085 0.016 0.000 0.676 0.112 0.196
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1341   0.746965 0.944 0.000 0.000 0.000 0.056
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1908   0.723711 0.908 0.000 0.000 0.000 0.092
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.4065   0.861442 0.264 0.000 0.000 0.016 0.720
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.7838   0.127943 0.000 0.180 0.476 0.140 0.204
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0162   0.905333 0.000 0.996 0.000 0.004 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.5689   0.797205 0.000 0.000 0.248 0.616 0.136
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0981   0.736917 0.972 0.000 0.012 0.008 0.008
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.4626   0.798457 0.364 0.000 0.000 0.020 0.616
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1041   0.749042 0.964 0.000 0.004 0.000 0.032
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1281   0.580222 0.032 0.000 0.956 0.000 0.012
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1671   0.901371 0.000 0.924 0.000 0.076 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.7499   0.283321 0.252 0.000 0.500 0.100 0.148
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1314   0.572319 0.012 0.000 0.960 0.012 0.016
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     5  0.4483   0.834053 0.308 0.000 0.008 0.012 0.672
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1410   0.747290 0.940 0.000 0.000 0.000 0.060
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.4106   0.858837 0.256 0.000 0.000 0.020 0.724
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.7879   0.365654 0.252 0.000 0.240 0.088 0.420
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000   0.905355 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2074   0.721772 0.896 0.000 0.000 0.000 0.104
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0703   0.747467 0.976 0.000 0.000 0.000 0.024
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0854   0.742269 0.976 0.000 0.004 0.008 0.012
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3477   0.553404 0.000 0.000 0.824 0.040 0.136
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.4150   0.179131 0.612 0.000 0.000 0.000 0.388
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0000   0.575629 0.000 0.000 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.3575   0.667285 0.824 0.000 0.056 0.000 0.120
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0703   0.901180 0.000 0.976 0.000 0.024 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0162   0.905333 0.000 0.996 0.000 0.004 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4486   0.857875 0.256 0.000 0.020 0.012 0.712
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.5811   0.808519 0.272 0.000 0.052 0.044 0.632
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0794   0.747684 0.972 0.000 0.000 0.000 0.028
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.4219   0.744066 0.416 0.000 0.000 0.000 0.584
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0963   0.895872 0.000 0.964 0.000 0.036 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.1471   0.570349 0.024 0.000 0.952 0.020 0.004
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.5204   0.570726 0.000 0.000 0.368 0.580 0.052
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000   0.905355 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1121   0.749095 0.956 0.000 0.000 0.000 0.044
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.3074   0.652980 0.804 0.000 0.000 0.000 0.196
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.2690   0.882367 0.000 0.844 0.000 0.156 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.5525   0.127527 0.240 0.000 0.636 0.000 0.124
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1493   0.577145 0.000 0.000 0.948 0.024 0.028
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4288   0.508698 0.720 0.000 0.256 0.008 0.016
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.4387   0.818650 0.348 0.000 0.000 0.012 0.640
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.5351   0.636838 0.380 0.000 0.060 0.000 0.560
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.4366   0.839948 0.320 0.000 0.000 0.016 0.664
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0404   0.903835 0.000 0.988 0.000 0.012 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.5288   0.165490 0.244 0.000 0.656 0.000 0.100
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.3242   0.860687 0.000 0.784 0.000 0.216 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3424   0.483140 0.760 0.000 0.000 0.000 0.240
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000   0.905355 0.000 1.000 0.000 0.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.4481   0.166296 0.576 0.000 0.416 0.000 0.008
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.5071   0.324950 0.272 0.000 0.672 0.040 0.016
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000   0.742383 1.000 0.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2597   0.571283 0.000 0.000 0.884 0.024 0.092
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.5398   0.416810 0.000 0.000 0.648 0.112 0.240
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.7362   0.603315 0.264 0.000 0.172 0.068 0.496
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000   0.905355 0.000 1.000 0.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0703   0.746894 0.976 0.000 0.000 0.000 0.024
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.4167   0.853289 0.252 0.000 0.000 0.024 0.724
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.6064  -0.185360 0.032 0.000 0.496 0.052 0.420
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.7016  -0.299257 0.304 0.000 0.388 0.008 0.300
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0510   0.746395 0.984 0.000 0.000 0.000 0.016
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0510   0.903020 0.000 0.984 0.000 0.016 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.5398   0.416810 0.000 0.000 0.648 0.112 0.240
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3932   0.176761 0.672 0.000 0.000 0.000 0.328
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.3861   0.861965 0.264 0.000 0.000 0.008 0.728
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.5167   0.440716 0.000 0.000 0.668 0.092 0.240
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.2074   0.895448 0.000 0.896 0.000 0.104 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.3689   0.859420 0.256 0.000 0.000 0.004 0.740
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.3766   0.861003 0.268 0.000 0.000 0.004 0.728
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.5451   0.799804 0.256 0.000 0.064 0.020 0.660
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0794   0.750405 0.972 0.000 0.000 0.000 0.028
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     3  0.4994   0.124810 0.464 0.000 0.512 0.008 0.016
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.4106   0.858837 0.256 0.000 0.000 0.020 0.724
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.4896   0.841333 0.252 0.000 0.032 0.020 0.696
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0703   0.901180 0.000 0.976 0.000 0.024 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5205   0.440256 0.000 0.000 0.672 0.104 0.224
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.3837   0.789889 0.000 0.692 0.000 0.308 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.2127   0.723340 0.892 0.000 0.000 0.000 0.108
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.8264  -0.022564 0.000 0.236 0.380 0.144 0.240
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.3689   0.859420 0.256 0.000 0.000 0.004 0.740
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.4238   0.801373 0.368 0.000 0.000 0.004 0.628
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.1671   0.740772 0.924 0.000 0.000 0.000 0.076
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     5  0.6198   0.739705 0.272 0.000 0.128 0.016 0.584
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4268  -0.372071 0.556 0.000 0.000 0.000 0.444
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.1544   0.902748 0.000 0.932 0.000 0.068 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.2471   0.887874 0.000 0.864 0.000 0.136 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.6881   0.138529 0.168 0.000 0.588 0.076 0.168
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.5929   0.673354 0.308 0.000 0.116 0.004 0.572
#> D47D0936-826F-4D54-9225-F71B95357438     5  0.4218   0.831398 0.332 0.000 0.000 0.008 0.660
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.3242   0.860687 0.000 0.784 0.000 0.216 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.7997  -0.184227 0.252 0.000 0.388 0.092 0.268
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.3942   0.861438 0.260 0.000 0.012 0.000 0.728
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.4626   0.798457 0.364 0.000 0.000 0.020 0.616
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.0613   0.573178 0.004 0.000 0.984 0.008 0.004
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     3  0.3189   0.506327 0.056 0.000 0.868 0.012 0.064
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.8171   0.388414 0.224 0.000 0.160 0.200 0.416
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.2452   0.534148 0.084 0.000 0.896 0.004 0.016
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.6060   0.414914 0.020 0.000 0.616 0.120 0.244
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0703   0.901180 0.000 0.976 0.000 0.024 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0703   0.901180 0.000 0.976 0.000 0.024 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     5  0.4651   0.790814 0.372 0.000 0.000 0.020 0.608
#> 7822EA86-35A1-4285-9429-2B63111B9885     5  0.5439   0.807577 0.276 0.000 0.076 0.008 0.640
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000   0.905355 0.000 1.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     4  0.5778   0.788385 0.000 0.016 0.256 0.632 0.096
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.3213   0.459272 0.144 0.000 0.836 0.004 0.016
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     5  0.3861   0.861360 0.264 0.000 0.000 0.008 0.728
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.3242   0.860687 0.000 0.784 0.000 0.216 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0609   0.902199 0.000 0.980 0.000 0.020 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     4  0.6727   0.729115 0.024 0.000 0.260 0.536 0.180
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.4028   0.525789 0.000 0.000 0.776 0.048 0.176
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.3642   0.554689 0.004 0.000 0.824 0.048 0.124
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.5567   0.105149 0.532 0.000 0.412 0.040 0.016
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#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.3835   0.861122 0.260 0.000 0.000 0.008 0.732
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.5497   0.291871 0.592 0.000 0.348 0.040 0.020
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.4975   0.828870 0.272 0.000 0.040 0.012 0.676
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.4616   0.839568 0.288 0.000 0.036 0.000 0.676
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.3074   0.868965 0.000 0.804 0.000 0.196 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.4262   0.672659 0.440 0.000 0.000 0.000 0.560
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.3143   0.642378 0.796 0.000 0.000 0.000 0.204
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3534   0.858272 0.256 0.000 0.000 0.000 0.744
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.4054   0.635116 0.788 0.000 0.140 0.000 0.072
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.4906   0.278894 0.316 0.000 0.648 0.020 0.016
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3336   0.540847 0.772 0.000 0.000 0.000 0.228
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0510   0.747692 0.984 0.000 0.000 0.000 0.016
#> 02ABB64E-768B-4999-A899-EEE573D5F186     5  0.6786   0.239175 0.384 0.000 0.224 0.004 0.388
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     3  0.6596  -0.150192 0.100 0.000 0.472 0.032 0.396
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5289   0.108256 0.596 0.000 0.064 0.000 0.340
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.8389   0.096975 0.268 0.000 0.328 0.148 0.256
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1908   0.730708 0.908 0.000 0.000 0.000 0.092
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.1197   0.904271 0.000 0.952 0.000 0.048 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.5439   0.147614 0.556 0.000 0.392 0.040 0.012
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     3  0.4951   0.240559 0.000 0.000 0.704 0.196 0.100
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.4157   0.861113 0.264 0.000 0.000 0.020 0.716
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.3796   0.328437 0.700 0.000 0.000 0.000 0.300
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.4331   0.765874 0.400 0.000 0.000 0.004 0.596
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0703   0.901180 0.000 0.976 0.000 0.024 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.0162   0.574308 0.000 0.000 0.996 0.004 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.6084   0.362805 0.000 0.012 0.604 0.144 0.240
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0854   0.577807 0.004 0.000 0.976 0.008 0.012
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.5951   0.752942 0.000 0.044 0.228 0.648 0.080
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4305   0.377747 0.200 0.000 0.748 0.000 0.052
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.2946   0.508327 0.000 0.000 0.868 0.088 0.044
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1270   0.741827 0.948 0.000 0.000 0.000 0.052
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.4157   0.861113 0.264 0.000 0.000 0.020 0.716
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.3143   0.866050 0.000 0.796 0.000 0.204 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0510   0.746395 0.984 0.000 0.000 0.000 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.4508   0.743037 0.000 0.648 0.020 0.332 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.4852   0.211990 0.380 0.000 0.596 0.008 0.016
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.5550   0.416591 0.004 0.000 0.644 0.112 0.240
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.2067   0.571057 0.000 0.000 0.920 0.048 0.032
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.3758   0.513191 0.000 0.056 0.824 0.112 0.008
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.5046   0.335090 0.256 0.000 0.684 0.044 0.016
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.3257   0.693000 0.844 0.000 0.028 0.004 0.124
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.2251   0.555973 0.052 0.000 0.916 0.024 0.008
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0404   0.572551 0.000 0.000 0.988 0.012 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     4  0.5446   0.772141 0.000 0.000 0.272 0.628 0.100
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4532   0.542079 0.020 0.000 0.764 0.048 0.168
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3882   0.605727 0.788 0.000 0.168 0.000 0.044
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.1121   0.743339 0.956 0.000 0.000 0.000 0.044
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.4047   0.823119 0.320 0.000 0.000 0.004 0.676
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0609   0.902199 0.000 0.980 0.000 0.020 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0162   0.905030 0.000 0.996 0.000 0.004 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1557   0.580364 0.000 0.000 0.940 0.008 0.052
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5436   0.298918 0.588 0.000 0.356 0.040 0.016
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.3715   0.859371 0.260 0.000 0.000 0.004 0.736
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3990   0.317670 0.688 0.000 0.000 0.004 0.308

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0146   0.436763 0.000 0.000 0.996 0.004 0.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4780   0.047663 0.012 0.000 0.644 0.056 0.000 0.288
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.5566  -0.082079 0.096 0.000 0.552 0.020 0.000 0.332
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3528   0.705277 0.700 0.000 0.000 0.000 0.296 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3728   0.671454 0.652 0.000 0.000 0.000 0.344 0.004
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.2605   0.650319 0.028 0.000 0.000 0.108 0.864 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6150  -0.215701 0.020 0.188 0.528 0.004 0.000 0.260
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0146   0.807442 0.000 0.996 0.000 0.000 0.000 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.5402   0.658928 0.060 0.000 0.128 0.676 0.136 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3733   0.692563 0.764 0.000 0.004 0.008 0.204 0.020
#> B710293C-41D3-4A2E-8104-5402F91DD859     5  0.4302   0.560255 0.156 0.000 0.000 0.116 0.728 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3288   0.701409 0.724 0.000 0.000 0.000 0.276 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2231   0.440347 0.028 0.000 0.908 0.048 0.000 0.016
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1957   0.795359 0.000 0.888 0.000 0.000 0.000 0.112
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.6201  -0.115863 0.308 0.000 0.488 0.024 0.000 0.180
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3698   0.442994 0.028 0.000 0.788 0.164 0.020 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     5  0.5173   0.540399 0.172 0.000 0.000 0.188 0.636 0.004
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3288   0.707686 0.724 0.000 0.000 0.000 0.276 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.2398   0.648867 0.020 0.000 0.000 0.104 0.876 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.5825   0.070788 0.056 0.000 0.064 0.356 0.524 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3986   0.636277 0.608 0.000 0.000 0.004 0.384 0.004
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3508   0.700528 0.704 0.000 0.000 0.000 0.292 0.004
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3259   0.699562 0.772 0.000 0.000 0.000 0.216 0.012
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3295   0.339655 0.000 0.000 0.816 0.056 0.000 0.128
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.3995   0.267611 0.516 0.000 0.000 0.000 0.480 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0508   0.443599 0.012 0.000 0.984 0.004 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5260   0.472053 0.640 0.000 0.044 0.048 0.264 0.004
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0713   0.799589 0.000 0.972 0.000 0.000 0.000 0.028
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.2737   0.662703 0.024 0.000 0.060 0.036 0.880 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.4824   0.517936 0.060 0.000 0.016 0.268 0.656 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.3221   0.707300 0.736 0.000 0.000 0.000 0.264 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.3457   0.494560 0.232 0.000 0.000 0.016 0.752 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0146   0.806997 0.000 0.996 0.000 0.004 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.5354   0.359702 0.160 0.000 0.680 0.084 0.000 0.076
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.4832   0.459142 0.008 0.000 0.324 0.612 0.056 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3619   0.694558 0.680 0.000 0.000 0.000 0.316 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.3961   0.489491 0.556 0.000 0.000 0.000 0.440 0.004
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.3428   0.732690 0.000 0.696 0.000 0.000 0.000 0.304
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.7651  -0.167206 0.168 0.000 0.348 0.212 0.268 0.004
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0790   0.441479 0.000 0.000 0.968 0.032 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4826   0.644243 0.724 0.000 0.036 0.076 0.160 0.004
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.4286   0.627362 0.108 0.000 0.000 0.164 0.728 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     5  0.4296   0.312535 0.348 0.000 0.004 0.016 0.628 0.004
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.3612   0.615558 0.100 0.000 0.000 0.104 0.796 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0363   0.806192 0.000 0.988 0.000 0.000 0.000 0.012
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.7026  -0.035589 0.128 0.000 0.452 0.148 0.272 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.3843   0.656127 0.000 0.548 0.000 0.000 0.000 0.452
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4204   0.435035 0.540 0.000 0.000 0.008 0.448 0.004
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0363   0.808601 0.000 0.988 0.000 0.000 0.000 0.012
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.6049  -0.035055 0.508 0.000 0.364 0.044 0.076 0.008
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.6755   0.065251 0.356 0.000 0.428 0.096 0.000 0.120
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3245   0.703747 0.764 0.000 0.000 0.000 0.228 0.008
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0363   0.433899 0.000 0.000 0.988 0.000 0.000 0.012
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.3646   0.056769 0.004 0.000 0.700 0.004 0.000 0.292
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.6293   0.208850 0.096 0.000 0.076 0.316 0.512 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3405   0.706290 0.724 0.000 0.000 0.000 0.272 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.2502   0.672304 0.020 0.000 0.012 0.084 0.884 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.7037  -0.223949 0.080 0.000 0.376 0.204 0.340 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     4  0.7558   0.232627 0.224 0.000 0.164 0.332 0.280 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.3244   0.707193 0.732 0.000 0.000 0.000 0.268 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0260   0.807001 0.000 0.992 0.000 0.000 0.000 0.008
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.3508   0.060823 0.000 0.000 0.704 0.004 0.000 0.292
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     5  0.3989  -0.199641 0.468 0.000 0.000 0.000 0.528 0.004
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.3278   0.651766 0.040 0.000 0.000 0.152 0.808 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.4045   0.102020 0.000 0.000 0.696 0.036 0.000 0.268
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.3101   0.755133 0.000 0.756 0.000 0.000 0.000 0.244
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     5  0.2655   0.662835 0.096 0.000 0.012 0.020 0.872 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     5  0.1176   0.667383 0.024 0.000 0.000 0.020 0.956 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.4798   0.493507 0.096 0.000 0.000 0.236 0.664 0.004
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3266   0.706884 0.728 0.000 0.000 0.000 0.272 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.6782  -0.285392 0.416 0.000 0.380 0.144 0.044 0.016
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.2480   0.648703 0.024 0.000 0.000 0.104 0.872 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.2920   0.606943 0.008 0.000 0.004 0.168 0.820 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0713   0.799589 0.000 0.972 0.000 0.000 0.000 0.028
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.2909   0.331423 0.000 0.000 0.836 0.028 0.000 0.136
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.3937   0.672001 0.000 0.572 0.004 0.000 0.000 0.424
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.3955   0.566179 0.560 0.000 0.000 0.000 0.436 0.004
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.6433   0.095837 0.020 0.172 0.400 0.008 0.000 0.400
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     5  0.2875   0.654374 0.096 0.000 0.000 0.052 0.852 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     5  0.2930   0.617392 0.124 0.000 0.000 0.036 0.840 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3769   0.665032 0.640 0.000 0.000 0.000 0.356 0.004
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#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     5  0.2706   0.619172 0.008 0.000 0.000 0.160 0.832 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.3717   0.695615 0.000 0.616 0.000 0.000 0.000 0.384
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.5894   0.000405 0.008 0.000 0.548 0.140 0.012 0.292
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0146   0.808273 0.000 0.996 0.000 0.000 0.000 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0713   0.799589 0.000 0.972 0.000 0.000 0.000 0.028
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     5  0.4651   0.576474 0.172 0.000 0.000 0.124 0.700 0.004
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.2520   0.305522 0.000 0.000 0.844 0.004 0.000 0.152
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.3525   0.610960 0.068 0.000 0.000 0.120 0.808 0.004
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.2066   0.662414 0.024 0.000 0.000 0.072 0.904 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.2398   0.648867 0.020 0.000 0.000 0.104 0.876 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1657   0.448540 0.016 0.000 0.928 0.056 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0405   0.442800 0.008 0.000 0.988 0.004 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     5  0.5868  -0.015207 0.020 0.000 0.124 0.356 0.500 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.1549   0.666598 0.044 0.000 0.000 0.020 0.936 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.6787   0.184704 0.308 0.000 0.480 0.120 0.008 0.084
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.2118   0.366043 0.000 0.000 0.888 0.008 0.000 0.104
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.6588  -0.509560 0.448 0.000 0.192 0.028 0.008 0.324
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.3843   0.656127 0.000 0.548 0.000 0.000 0.000 0.452
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0146   0.807326 0.000 0.996 0.004 0.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     5  0.3872  -0.139230 0.392 0.000 0.000 0.000 0.604 0.004
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.3288   0.744395 0.000 0.724 0.000 0.000 0.000 0.276
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.1152   0.785737 0.000 0.952 0.044 0.004 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     5  0.5121  -0.091066 0.440 0.000 0.008 0.060 0.492 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3565   0.702651 0.692 0.000 0.000 0.000 0.304 0.004
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.3151   0.753668 0.000 0.748 0.000 0.000 0.000 0.252
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0260   0.806110 0.000 0.992 0.000 0.000 0.000 0.008
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.2619   0.392051 0.000 0.008 0.880 0.040 0.000 0.072
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     5  0.3297   0.637388 0.068 0.000 0.000 0.112 0.820 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     5  0.2888   0.670153 0.056 0.000 0.000 0.092 0.852 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.2846   0.669229 0.060 0.000 0.000 0.084 0.856 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.3838   0.657906 0.000 0.552 0.000 0.000 0.000 0.448
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     5  0.2726   0.647491 0.032 0.000 0.000 0.112 0.856 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.2030   0.660691 0.028 0.000 0.000 0.064 0.908 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.4669   0.399275 0.772 0.000 0.072 0.036 0.036 0.084
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.4765   0.517137 0.112 0.000 0.000 0.204 0.680 0.004
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     5  0.3635   0.659067 0.068 0.000 0.008 0.120 0.804 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.3782   0.681026 0.000 0.588 0.000 0.000 0.000 0.412
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     5  0.3104   0.551633 0.184 0.000 0.000 0.016 0.800 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.3982   0.354121 0.536 0.000 0.000 0.000 0.460 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3297   0.608470 0.068 0.000 0.000 0.112 0.820 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.4675   0.527399 0.616 0.000 0.036 0.000 0.336 0.012
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     3  0.6578   0.086382 0.396 0.000 0.420 0.128 0.008 0.048
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3728   0.671402 0.652 0.000 0.000 0.000 0.344 0.004
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.3071   0.680628 0.804 0.000 0.016 0.000 0.180 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     5  0.6650   0.209462 0.376 0.000 0.092 0.108 0.424 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     3  0.7625  -0.167695 0.244 0.000 0.312 0.176 0.268 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5513   0.149844 0.472 0.000 0.024 0.056 0.444 0.004
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.6750   0.167197 0.320 0.000 0.248 0.032 0.004 0.396
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.3684   0.564715 0.664 0.000 0.000 0.000 0.332 0.004
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2178   0.789609 0.000 0.868 0.000 0.000 0.000 0.132
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.6088   0.200952 0.656 0.000 0.120 0.092 0.032 0.100
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     3  0.5398   0.050129 0.028 0.000 0.524 0.392 0.056 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     5  0.2771   0.646449 0.032 0.000 0.000 0.116 0.852 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     5  0.3864  -0.305689 0.480 0.000 0.000 0.000 0.520 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.3572   0.525283 0.204 0.000 0.000 0.032 0.764 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0713   0.799589 0.000 0.972 0.000 0.000 0.000 0.028
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.2575   0.449783 0.024 0.000 0.872 0.100 0.000 0.004
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.4622  -0.138999 0.020 0.004 0.564 0.008 0.000 0.404
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.3726   0.373185 0.092 0.000 0.812 0.024 0.000 0.072
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.4189   0.687096 0.004 0.028 0.148 0.772 0.048 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.7380   0.044372 0.224 0.000 0.432 0.172 0.168 0.004
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4380   0.349464 0.024 0.000 0.652 0.312 0.012 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3565   0.690140 0.692 0.000 0.000 0.000 0.304 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.2558   0.648533 0.028 0.000 0.000 0.104 0.868 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.3620   0.707064 0.000 0.648 0.000 0.000 0.000 0.352
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3198   0.707491 0.740 0.000 0.000 0.000 0.260 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.4389   0.630948 0.000 0.528 0.024 0.000 0.000 0.448
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.6992   0.141776 0.320 0.000 0.452 0.156 0.036 0.036
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.4556   0.021906 0.032 0.000 0.652 0.016 0.000 0.300
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000   0.438417 0.000 0.000 1.000 0.000 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     3  0.5860   0.361983 0.120 0.036 0.664 0.140 0.000 0.040
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.6837   0.121627 0.308 0.000 0.456 0.116 0.000 0.120
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4046   0.464674 0.620 0.000 0.000 0.004 0.368 0.008
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.6155   0.307418 0.208 0.000 0.596 0.116 0.004 0.076
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2988   0.447332 0.024 0.000 0.824 0.152 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     4  0.3841   0.702322 0.000 0.000 0.168 0.764 0.068 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4447   0.306905 0.092 0.000 0.744 0.020 0.000 0.144
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5241   0.551505 0.648 0.000 0.140 0.008 0.200 0.004
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.3508   0.696122 0.704 0.000 0.000 0.000 0.292 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3342   0.549866 0.228 0.000 0.000 0.012 0.760 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0547   0.802426 0.000 0.980 0.000 0.000 0.000 0.020
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000   0.807583 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1398   0.435689 0.000 0.000 0.940 0.052 0.000 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4794   0.474606 0.760 0.000 0.020 0.088 0.060 0.072
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.2095   0.665607 0.076 0.000 0.004 0.016 0.904 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.3727   0.609553 0.612 0.000 0.000 0.000 0.388 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-mclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


MAD:NMF*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "NMF"]
# you can also extract it by
# res = res_list["MAD:NMF"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.946           0.948       0.979         0.4589 0.542   0.542
#> 3 3 0.827           0.861       0.942         0.3917 0.767   0.590
#> 4 4 0.777           0.813       0.912         0.0855 0.886   0.712
#> 5 5 0.851           0.839       0.898         0.0860 0.856   0.594
#> 6 6 0.827           0.724       0.882         0.0527 0.949   0.802

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000    0.96994 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000    0.98178 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.6343    0.80877 0.840 0.160
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.98178 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.98178 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000    0.98178 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000    0.96994 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.96994 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000    0.98178 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000    0.98178 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.98178 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000    0.98178 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000    0.98178 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.96994 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000    0.98178 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0938    0.97135 0.988 0.012
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000    0.98178 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000    0.98178 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000    0.98178 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000    0.98178 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.96994 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.98178 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000    0.98178 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.98178 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000    0.98178 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000    0.98178 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.6247    0.81064 0.844 0.156
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000    0.98178 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.96994 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.96994 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000    0.98178 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000    0.98178 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.98178 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000    0.98178 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.96994 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.9552    0.40895 0.376 0.624
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.9286    0.46459 0.656 0.344
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.96994 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000    0.98178 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000    0.98178 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.96994 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000    0.98178 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     2  0.0000    0.96994 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000    0.98178 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000    0.98178 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000    0.98178 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000    0.98178 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.96994 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000    0.98178 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.96994 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000    0.98178 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000    0.96994 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000    0.98178 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000    0.98178 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000    0.98178 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     2  0.0000    0.96994 0.000 1.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.6343    0.80592 0.840 0.160
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000    0.98178 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000    0.96994 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000    0.98178 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000    0.98178 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.7453    0.72564 0.788 0.212
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000    0.98178 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000    0.98178 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.96994 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     2  0.9661    0.36523 0.392 0.608
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000    0.98178 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000    0.98178 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.6343    0.80581 0.840 0.160
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000    0.96994 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000    0.98178 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000    0.98178 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000    0.98178 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000    0.98178 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000    0.98178 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000    0.98178 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000    0.98178 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000    0.96994 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     2  0.0000    0.96994 0.000 1.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000    0.96994 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000    0.98178 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.0000    0.96994 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000    0.98178 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000    0.98178 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000    0.98178 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000    0.98178 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000    0.98178 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000    0.96994 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000    0.96994 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000    0.98178 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000    0.98178 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000    0.98178 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000    0.96994 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000    0.98178 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000    0.98178 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000    0.98178 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.0000    0.96994 0.000 1.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.8608    0.59805 0.716 0.284
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.1414    0.96402 0.980 0.020
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000    0.98178 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.1184    0.96803 0.984 0.016
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000    0.96994 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000    0.96994 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000    0.98178 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000    0.98178 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000    0.96994 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000    0.96994 0.000 1.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000    0.98178 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000    0.98178 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000    0.96994 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000    0.96994 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.9580    0.37304 0.620 0.380
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.5629    0.84340 0.868 0.132
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000    0.98178 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000    0.98178 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000    0.98178 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000    0.98178 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.6438    0.79764 0.836 0.164
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000    0.98178 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000    0.98178 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000    0.98178 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000    0.98178 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000    0.98178 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000    0.98178 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.4022    0.89785 0.080 0.920
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.0000    0.96994 0.000 1.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.0000    0.96994 0.000 1.000
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000    0.98178 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     2  0.7376    0.74135 0.208 0.792
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.0000    0.98178 1.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     2  0.9732    0.34370 0.404 0.596
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000    0.98178 1.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000    0.96994 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.0000    0.98178 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000    0.96994 0.000 1.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000    0.96994 0.000 1.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000    0.98178 1.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000    0.96994 0.000 1.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000    0.96994 0.000 1.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000    0.98178 1.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1  0.0000    0.98178 1.000 0.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000    0.96994 0.000 1.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1  0.0000    0.98178 1.000 0.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0000    0.96994 0.000 1.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000    0.96994 0.000 1.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1  0.0000    0.98178 1.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1  0.1184    0.96785 0.984 0.016
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2  0.0000    0.96994 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1  0.0000    0.98178 1.000 0.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1  0.0000    0.98178 1.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1  0.0000    0.98178 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0000    0.98178 1.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000    0.96994 0.000 1.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0000    0.98178 1.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     2  0.0000    0.96994 0.000 1.000
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2  0.0000    0.96994 0.000 1.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000    0.98178 1.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.0000    0.98178 1.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2  0.0000    0.96994 0.000 1.000
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000    0.96994 0.000 1.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.0000    0.98178 1.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1  0.0376    0.97833 0.996 0.004
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000    0.96994 0.000 1.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000    0.98178 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000    0.96994 0.000 1.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000    0.96994 0.000 1.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     2  0.3879    0.90167 0.076 0.924
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000    0.96994 0.000 1.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.0000    0.98178 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000    0.96994 0.000 1.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.0000    0.98178 1.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000    0.98178 1.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     2  0.4161    0.89451 0.084 0.916
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000    0.98178 1.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.0000    0.98178 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1  0.0000    0.98178 1.000 0.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0000    0.98178 1.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000    0.98178 1.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1  0.0000    0.98178 1.000 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000    0.96994 0.000 1.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000    0.96994 0.000 1.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.9998   -0.00254 0.508 0.492
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2  0.0000    0.96994 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000    0.98178 1.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000    0.98178 1.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000    0.96994 0.000 1.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000    0.98178 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1  0.0000    0.98178 1.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000    0.96994 0.000 1.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000    0.96994 0.000 1.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000    0.96994 0.000 1.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0000    0.98178 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0000    0.98178 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000    0.98178 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.0000    0.98178 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000    0.98178 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.96994 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.0000    0.98178 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000    0.98178 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     2  0.9850    0.27431 0.428 0.572
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000    0.98178 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.0000    0.96994 0.000 1.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.0000    0.98178 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000    0.98178 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000    0.98178 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000    0.98178 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000    0.98178 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.7299    0.74751 0.204 0.796
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.0000    0.98178 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.0000    0.96994 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000    0.96994 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.1633    0.96036 0.976 0.024
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000    0.98178 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000    0.98178 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000    0.98178 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000    0.98178 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.0000    0.96994 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     2  0.0000    0.96994 0.000 1.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     2  0.0000    0.96994 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.98178 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000    0.98178 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000    0.96994 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0000    0.98178 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.96994 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.96994 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.96994 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000    0.98178 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     2  0.0000    0.96994 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000    0.98178 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.98178 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000    0.98178 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000    0.98178 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     2  0.9209    0.50230 0.336 0.664
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000    0.98178 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000    0.98178 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.96994 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000    0.98178 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.1414    0.96394 0.980 0.020
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000    0.98178 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.96994 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000    0.96994 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000    0.98178 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.96994 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.96994 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000    0.98178 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000    0.98178 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.96994 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.96994 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     2  0.0000    0.96994 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000    0.98178 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000    0.98178 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000    0.96994 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000    0.98178 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.96994 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.98178 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000    0.98178 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0000    0.98178 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000    0.98178 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000    0.98178 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000    0.96994 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000    0.98178 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000    0.98178 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000    0.98178 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000    0.98178 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0672    0.97483 0.992 0.008
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.98178 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0000    0.98178 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000    0.98178 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000    0.98178 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000    0.98178 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000    0.98178 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000    0.98178 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.96994 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000    0.98178 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0938    0.96005 0.012 0.988
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000    0.98178 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000    0.98178 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.98178 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.96994 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.6438    0.80225 0.164 0.836
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000    0.96994 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000    0.96994 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000    0.96994 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000    0.98178 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.7815    0.70528 0.232 0.768
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.98178 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.98178 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.96994 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.98178 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000    0.96994 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000    0.98178 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000    0.98178 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     2  0.0000    0.96994 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000    0.96994 0.000 1.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.98178 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000    0.98178 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.0000    0.96994 0.000 1.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.9635    0.36076 0.612 0.388
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.6343    0.80755 0.160 0.840
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6531    0.79466 0.832 0.168
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000    0.98178 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.98178 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000    0.98178 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.96994 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.96994 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6343    0.80463 0.840 0.160
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000    0.98178 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000    0.98178 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000    0.98178 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.2448     0.8412 0.000 0.076 0.924
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.8937 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0475     0.8947 0.004 0.004 0.992
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9401 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9401 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9401 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.0424     0.8926 0.000 0.008 0.992
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9568 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.1525     0.9116 0.964 0.032 0.004
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.6308    -0.0504 0.508 0.000 0.492
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9401 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9401 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0237     0.8949 0.004 0.000 0.996
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9568 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0424     0.8952 0.008 0.000 0.992
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1529     0.8801 0.040 0.000 0.960
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5835     0.4664 0.660 0.000 0.340
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9401 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9401 1.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3412     0.8279 0.876 0.000 0.124
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9568 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9401 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9401 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3038     0.8521 0.896 0.000 0.104
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.8937 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9401 1.000 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0237     0.8936 0.000 0.004 0.996
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5785     0.5376 0.332 0.000 0.668
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9568 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9568 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9401 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0237     0.9374 0.996 0.000 0.004
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9401 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9401 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0424     0.9516 0.000 0.992 0.008
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.1031     0.8855 0.000 0.024 0.976
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5926     0.4483 0.644 0.356 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9568 0.000 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9401 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9401 1.000 0.000 0.000
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#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.6140     0.3657 0.404 0.000 0.596
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#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000     0.9401 1.000 0.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000     0.9401 1.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.6516     0.0368 0.004 0.516 0.480
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.5926     0.4283 0.644 0.000 0.356
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.2448     0.8882 0.000 0.924 0.076
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.1753     0.9202 0.000 0.952 0.048
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0424     0.8952 0.008 0.000 0.992
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.4605     0.7469 0.204 0.000 0.796
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000     0.9401 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000     0.9401 1.000 0.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000     0.9401 1.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.5497     0.5403 0.000 0.292 0.708
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0424     0.8926 0.000 0.008 0.992
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000     0.8937 0.000 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.9401 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000     0.9401 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0000     0.9568 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0424     0.8952 0.008 0.000 0.992
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9568 0.000 1.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9568 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9568 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.3619     0.8145 0.864 0.000 0.136
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0237     0.8936 0.000 0.004 0.996
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0000     0.9401 1.000 0.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.9401 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.9401 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.0237     0.8949 0.004 0.000 0.996
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.0237     0.8936 0.000 0.004 0.996
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0237     0.9372 0.996 0.004 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000     0.9401 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9568 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.6654     0.0923 0.536 0.008 0.456
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0475     0.8947 0.004 0.004 0.992
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0424     0.8952 0.008 0.000 0.992
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0424     0.9532 0.000 0.992 0.008
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9568 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9401 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9568 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9568 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.6095     0.3266 0.608 0.000 0.392
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.4452     0.7407 0.808 0.000 0.192
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9568 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9568 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.5363     0.5928 0.000 0.276 0.724
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.9401 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000     0.9401 1.000 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9568 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000     0.9401 1.000 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9568 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.9401 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0000     0.9401 1.000 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0424     0.8952 0.008 0.000 0.992
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.2625     0.8715 0.916 0.000 0.084
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9401 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000     0.9568 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000     0.9401 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0237     0.9377 0.996 0.000 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9401 1.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.3816     0.8106 0.148 0.000 0.852
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5631     0.7357 0.792 0.044 0.164
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9401 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.2066     0.8694 0.060 0.000 0.940
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.1860     0.9018 0.948 0.000 0.052
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0237     0.9375 0.996 0.004 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.1289     0.9182 0.968 0.000 0.032
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0424     0.8952 0.008 0.000 0.992
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1964     0.8977 0.944 0.000 0.056
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000     0.9568 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.0424     0.8952 0.008 0.000 0.992
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0424     0.9532 0.000 0.992 0.008
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9401 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0592     0.9326 0.988 0.000 0.012
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9401 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9568 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     3  0.1411     0.8755 0.000 0.036 0.964
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0237     0.8936 0.000 0.004 0.996
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0000     0.8937 0.000 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9568 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.2625     0.8563 0.084 0.000 0.916
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.9322     0.1457 0.164 0.392 0.444
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9401 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9401 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9568 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9401 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.5706     0.5183 0.000 0.680 0.320
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.4931     0.7105 0.232 0.000 0.768
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0424     0.8952 0.008 0.000 0.992
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000     0.8937 0.000 0.000 1.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9568 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.0424     0.8952 0.008 0.000 0.992
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.5058     0.6612 0.756 0.000 0.244
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.2356     0.8915 0.000 0.928 0.072
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000     0.8937 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.1529     0.9172 0.040 0.960 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0475     0.8947 0.004 0.004 0.992
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.1031     0.8893 0.024 0.000 0.976
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9401 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9401 1.000 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9568 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9568 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000     0.8937 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.3752     0.8132 0.144 0.000 0.856
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9401 1.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9401 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2799     0.7433 0.000 0.008 0.108 0.884
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     4  0.4761     0.3957 0.000 0.000 0.372 0.628
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000     0.8429 0.000 0.000 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0336     0.9257 0.992 0.000 0.008 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.0707     0.8435 0.000 0.000 0.980 0.020
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.3626     0.7645 0.812 0.000 0.004 0.184
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.5453     0.3620 0.388 0.000 0.592 0.020
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0188     0.9273 0.996 0.000 0.000 0.004
#> B055A70B-3003-47CB-BDAA-6378C000BF24     4  0.4679     0.4137 0.000 0.000 0.352 0.648
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0469     0.8439 0.000 0.000 0.988 0.012
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     4  0.2888     0.7258 0.004 0.000 0.124 0.872
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5356     0.6751 0.728 0.000 0.072 0.200
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0188     0.9272 0.996 0.000 0.004 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3813     0.7991 0.828 0.000 0.024 0.148
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4837     0.4474 0.648 0.000 0.348 0.004
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     4  0.2704     0.7287 0.000 0.000 0.124 0.876
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0188     0.9272 0.996 0.000 0.004 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4522     0.5480 0.000 0.000 0.680 0.320
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.6124     0.4951 0.640 0.000 0.276 0.084
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0188     0.9271 0.996 0.004 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.4933     0.2531 0.568 0.000 0.000 0.432
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0188     0.9411 0.000 0.996 0.004 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.3737     0.7188 0.004 0.136 0.840 0.020
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     2  0.5628     0.2348 0.420 0.556 0.024 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0469     0.9364 0.000 0.988 0.012 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0336     0.9257 0.992 0.000 0.008 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.1211     0.9192 0.000 0.960 0.000 0.040
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     4  0.7526     0.2009 0.372 0.000 0.188 0.440
#> 6D3CC3AC-618B-414A-B640-169C735A6568     4  0.2345     0.7402 0.000 0.000 0.100 0.900
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0707     0.9204 0.980 0.000 0.000 0.020
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.3801     0.7353 0.780 0.000 0.000 0.220
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.1792     0.8853 0.932 0.000 0.068 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     4  0.4423     0.6703 0.036 0.000 0.176 0.788
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.3649     0.6759 0.000 0.204 0.000 0.796
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0188     0.9273 0.996 0.000 0.000 0.004
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0592     0.9339 0.000 0.984 0.016 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.4972     0.1982 0.000 0.000 0.544 0.456
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.0817     0.8434 0.000 0.000 0.976 0.024
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     3  0.4163     0.6401 0.188 0.000 0.792 0.020
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     4  0.4994     0.0153 0.000 0.000 0.480 0.520
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#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.1474     0.9072 0.000 0.948 0.052 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.1867     0.7631 0.000 0.072 0.000 0.928
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0000     0.8429 0.000 0.000 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.6737     0.2167 0.420 0.000 0.488 0.092
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0895     0.9185 0.976 0.004 0.020 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.4509     0.6077 0.000 0.708 0.288 0.004
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0188     0.8431 0.000 0.000 0.996 0.004
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.4948     0.2245 0.000 0.000 0.560 0.440
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.0336     0.9398 0.000 0.992 0.000 0.008
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.4405     0.7091 0.048 0.000 0.800 0.152
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.3758     0.8166 0.848 0.000 0.104 0.048
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.3942     0.6640 0.000 0.000 0.764 0.236
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0895     0.9193 0.976 0.000 0.004 0.020
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     4  0.4406     0.5149 0.000 0.000 0.300 0.700
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4697     0.4654 0.000 0.000 0.644 0.356
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.2469     0.8392 0.892 0.108 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     3  0.5290     0.4436 0.324 0.012 0.656 0.008
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.2408     0.8046 0.000 0.000 0.896 0.104
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0000     0.8429 0.000 0.000 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.2530     0.7465 0.000 0.112 0.000 0.888
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0336     0.9394 0.000 0.992 0.000 0.008
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.5670     0.6630 0.720 0.000 0.152 0.128
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.3486     0.7542 0.812 0.000 0.188 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     4  0.3032     0.7295 0.000 0.008 0.124 0.868
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.2081     0.8773 0.916 0.000 0.000 0.084
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0336     0.9258 0.992 0.000 0.000 0.008
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0188     0.9412 0.000 0.996 0.000 0.004
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0188     0.9272 0.996 0.000 0.004 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0592     0.8441 0.000 0.000 0.984 0.016
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.4046     0.8010 0.828 0.000 0.048 0.124
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.2704     0.8256 0.000 0.876 0.000 0.124
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0707     0.9205 0.980 0.000 0.000 0.020
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0817     0.8411 0.024 0.000 0.976 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.2094     0.8987 0.940 0.024 0.012 0.024
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.3224     0.7478 0.120 0.000 0.864 0.016
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.2149     0.8776 0.912 0.000 0.000 0.088
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0469     0.9230 0.988 0.012 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0469     0.9240 0.988 0.000 0.012 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000     0.8429 0.000 0.000 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2530     0.8448 0.888 0.000 0.112 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0188     0.9412 0.000 0.996 0.000 0.004
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.1042     0.8446 0.008 0.000 0.972 0.020
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.2466     0.7559 0.004 0.096 0.000 0.900
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0188     0.9273 0.996 0.000 0.004 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.2973     0.7129 0.000 0.000 0.144 0.856
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0188     0.8431 0.000 0.000 0.996 0.004
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.0817     0.8434 0.000 0.000 0.976 0.024
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.7498     0.2046 0.492 0.000 0.292 0.216
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.0469     0.7665 0.000 0.012 0.000 0.988
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0921     0.9271 0.000 0.972 0.000 0.028
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9284 1.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.0592     0.7677 0.000 0.016 0.000 0.984
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.4663     0.6525 0.148 0.000 0.064 0.788
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.8429 0.000 0.000 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.3610     0.7157 0.000 0.000 0.800 0.200
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     3  0.0817     0.8434 0.000 0.000 0.976 0.024
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.4961     0.1976 0.552 0.000 0.448 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.3128     0.8288 0.004 0.864 0.128 0.004
#> CE6B6871-3ED3-44DE-A777-7558D4429057     4  0.2149     0.7459 0.000 0.000 0.088 0.912
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.4999     0.7101 0.100 0.792 0.012 0.096
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0592     0.8441 0.000 0.000 0.984 0.016
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.2222     0.8295 0.016 0.000 0.924 0.060
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0188     0.9273 0.996 0.000 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0188     0.9272 0.996 0.000 0.004 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9428 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     4  0.2281     0.7422 0.000 0.000 0.096 0.904
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.1520     0.8397 0.024 0.000 0.956 0.020
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0188     0.9272 0.996 0.000 0.004 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9284 1.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1117    0.82783 0.000 0.016 0.000 0.964 0.020
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0671    0.91661 0.000 0.000 0.980 0.016 0.004
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.5253    0.61509 0.000 0.020 0.304 0.036 0.640
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     5  0.4402    0.58341 0.000 0.008 0.292 0.012 0.688
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.5492    0.47855 0.312 0.000 0.076 0.608 0.004
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4576    0.39800 0.608 0.000 0.000 0.016 0.376
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0290    0.94127 0.992 0.000 0.000 0.000 0.008
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1270    0.91939 0.000 0.000 0.948 0.052 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4383    0.22540 0.000 0.572 0.004 0.424 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.1205    0.84069 0.000 0.000 0.040 0.004 0.956
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1732    0.91374 0.000 0.000 0.920 0.080 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0798    0.92037 0.016 0.000 0.976 0.008 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0451    0.93987 0.988 0.000 0.000 0.004 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.1965    0.88760 0.096 0.000 0.904 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0162    0.94285 0.996 0.000 0.000 0.000 0.004
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2536    0.83953 0.868 0.000 0.000 0.004 0.128
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1478    0.91847 0.000 0.000 0.936 0.064 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0963    0.92498 0.964 0.000 0.036 0.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2426    0.90770 0.000 0.000 0.900 0.064 0.036
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.2020    0.88401 0.100 0.000 0.900 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     4  0.4503    0.57110 0.256 0.000 0.040 0.704 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0510    0.93718 0.984 0.000 0.016 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     5  0.4632    0.37743 0.004 0.376 0.000 0.012 0.608
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.6137    0.51926 0.644 0.240 0.064 0.036 0.016
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.1412    0.88968 0.000 0.952 0.008 0.036 0.004
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0162    0.94276 0.996 0.000 0.004 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.3177    0.72424 0.000 0.208 0.000 0.792 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.2079    0.91955 0.020 0.000 0.916 0.064 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2179    0.89681 0.000 0.000 0.888 0.112 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3535    0.80817 0.832 0.000 0.000 0.080 0.088
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2300    0.91730 0.040 0.000 0.908 0.052 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0162    0.94276 0.996 0.000 0.004 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0794    0.91876 0.000 0.000 0.972 0.028 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.1357    0.83583 0.000 0.048 0.004 0.948 0.000
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#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.2179    0.85172 0.888 0.000 0.000 0.000 0.112
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.2209    0.91949 0.032 0.000 0.912 0.056 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.3480    0.64498 0.752 0.000 0.000 0.248 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.3631    0.72106 0.792 0.192 0.004 0.008 0.004
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     2  0.4987    0.72273 0.100 0.776 0.052 0.060 0.012
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.1270    0.91324 0.052 0.000 0.948 0.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0290    0.94120 0.992 0.000 0.000 0.000 0.008
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     4  0.1410    0.83226 0.000 0.060 0.000 0.940 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.1988    0.90279 0.048 0.000 0.928 0.016 0.008
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.2989    0.83199 0.000 0.880 0.068 0.036 0.016
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     4  0.1331    0.83555 0.000 0.040 0.008 0.952 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     5  0.2511    0.82647 0.000 0.000 0.080 0.028 0.892
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     5  0.4857    0.44701 0.324 0.000 0.000 0.040 0.636
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.1671    0.88413 0.924 0.000 0.076 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.3478    0.82601 0.852 0.004 0.096 0.032 0.016
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.3232    0.82283 0.000 0.872 0.056 0.036 0.036
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     5  0.2554    0.82877 0.000 0.000 0.072 0.036 0.892
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.1205    0.91937 0.000 0.000 0.956 0.040 0.004
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.1267    0.89693 0.000 0.960 0.012 0.024 0.004
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.1630    0.88378 0.000 0.004 0.944 0.036 0.016
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.1608    0.90426 0.072 0.000 0.928 0.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0324    0.90991 0.000 0.000 0.992 0.004 0.004
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.1205    0.92068 0.956 0.000 0.040 0.000 0.004
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1732    0.91374 0.000 0.000 0.920 0.080 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.2331    0.90829 0.000 0.000 0.900 0.080 0.020
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1121    0.91341 0.956 0.044 0.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0162    0.94276 0.996 0.000 0.004 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4546    0.52754 0.668 0.028 0.000 0.000 0.304
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.1668    0.91751 0.000 0.000 0.940 0.032 0.028
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.2959    0.81684 0.000 0.000 0.100 0.036 0.864
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.1197    0.83555 0.000 0.048 0.000 0.952 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0162    0.91474 0.000 0.996 0.004 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0794    0.90184 0.000 0.972 0.000 0.028 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     3  0.2230    0.86710 0.116 0.000 0.884 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0290    0.94137 0.992 0.000 0.008 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.1851    0.91075 0.000 0.000 0.912 0.088 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0609    0.93445 0.980 0.000 0.020 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.1965    0.88760 0.096 0.000 0.904 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0162    0.91455 0.000 0.996 0.000 0.004 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0510    0.93743 0.984 0.000 0.016 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.2605    0.78863 0.000 0.852 0.000 0.148 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0162    0.94276 0.996 0.000 0.004 0.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.1732    0.90007 0.080 0.000 0.920 0.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0955    0.90094 0.000 0.968 0.004 0.028 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2280    0.86301 0.120 0.000 0.880 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0579    0.93844 0.984 0.000 0.008 0.000 0.008
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     5  0.5181    0.60559 0.080 0.000 0.268 0.000 0.652
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.1748    0.91152 0.944 0.016 0.004 0.008 0.028
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.5921    0.12422 0.088 0.000 0.452 0.004 0.456
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.1792    0.89775 0.084 0.000 0.916 0.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0992    0.92566 0.968 0.024 0.000 0.008 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0963    0.92212 0.964 0.000 0.036 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.2850    0.81964 0.000 0.000 0.092 0.036 0.872
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.1478    0.83065 0.000 0.064 0.000 0.936 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4294    0.04489 0.532 0.000 0.468 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0162    0.91446 0.000 0.996 0.000 0.004 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.1732    0.79656 0.000 0.000 0.000 0.920 0.080
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.2793    0.82129 0.000 0.000 0.088 0.036 0.876
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0324    0.91281 0.004 0.992 0.000 0.004 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0981    0.90911 0.012 0.000 0.972 0.008 0.008
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.3612    0.55550 0.000 0.000 0.268 0.732 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.4440    0.08086 0.000 0.528 0.004 0.468 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0609    0.93479 0.980 0.000 0.000 0.000 0.020
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.1267    0.83114 0.000 0.024 0.012 0.960 0.004
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     4  0.5324    0.46924 0.304 0.000 0.040 0.636 0.020
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.2959    0.81684 0.000 0.000 0.100 0.036 0.864
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     5  0.2863    0.80380 0.000 0.000 0.064 0.060 0.876
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0162    0.91455 0.000 0.996 0.000 0.004 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.6212    0.40461 0.600 0.000 0.092 0.036 0.272
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     5  0.3394    0.73615 0.020 0.152 0.000 0.004 0.824
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2020    0.90430 0.000 0.000 0.900 0.100 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1934    0.88795 0.004 0.052 0.928 0.016 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.3705    0.75258 0.012 0.000 0.788 0.008 0.192
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0162    0.94285 0.996 0.000 0.000 0.000 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0703    0.93304 0.976 0.000 0.024 0.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.91613 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1965    0.90667 0.000 0.000 0.904 0.096 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     5  0.0566    0.84147 0.000 0.000 0.004 0.012 0.984
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000    0.94425 1.000 0.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2941    0.68374 0.000 0.000 0.000 0.780 0.220 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0260    0.97489 0.000 0.000 0.992 0.000 0.008 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.5877   -0.24677 0.000 0.000 0.200 0.000 0.428 0.372
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000    0.86105 1.000 0.000 0.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1957    0.79513 0.888 0.000 0.000 0.000 0.112 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.3782    0.33295 0.588 0.000 0.000 0.000 0.412 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     6  0.4977    0.42623 0.000 0.084 0.300 0.000 0.004 0.612
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.89841 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.3404    0.25167 0.016 0.000 0.000 0.224 0.760 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3098    0.73979 0.836 0.000 0.000 0.040 0.004 0.120
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3136    0.65959 0.768 0.000 0.000 0.004 0.228 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0146    0.86106 0.996 0.000 0.000 0.000 0.004 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000    0.97651 0.000 0.000 1.000 0.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.4052    0.41304 0.000 0.628 0.000 0.356 0.016 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.0146    0.75314 0.000 0.000 0.000 0.000 0.004 0.996
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000    0.97651 0.000 0.000 1.000 0.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0146    0.97628 0.004 0.000 0.996 0.000 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2234    0.78022 0.872 0.000 0.000 0.004 0.124 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.2219    0.77932 0.864 0.000 0.000 0.000 0.136 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0260    0.97504 0.008 0.000 0.992 0.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.89841 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0260    0.86101 0.992 0.000 0.000 0.000 0.008 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0146    0.86106 0.996 0.000 0.000 0.000 0.004 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4764    0.42935 0.628 0.000 0.000 0.000 0.080 0.292
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0260    0.97489 0.000 0.000 0.992 0.000 0.008 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.1267    0.84238 0.940 0.000 0.000 0.000 0.060 0.000
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#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0622    0.96964 0.000 0.012 0.980 0.000 0.008 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.0000    0.75367 0.000 0.000 0.000 0.000 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.1082    0.95166 0.004 0.000 0.956 0.000 0.000 0.040
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0146    0.86062 0.996 0.000 0.000 0.000 0.004 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.1204    0.84305 0.944 0.000 0.000 0.000 0.056 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.89841 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.89841 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.97651 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     6  0.1564    0.73361 0.024 0.000 0.000 0.000 0.040 0.936
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.3607    0.47807 0.652 0.000 0.000 0.000 0.348 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1082    0.84596 0.956 0.000 0.000 0.004 0.040 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-NMF-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-NMF-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "hclust"]
# you can also extract it by
# res = res_list["ATC:hclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.407           0.742       0.867         0.3639 0.667   0.667
#> 3 3 0.291           0.531       0.749         0.5793 0.617   0.467
#> 4 4 0.345           0.478       0.693         0.1365 0.772   0.522
#> 5 5 0.452           0.473       0.674         0.0834 0.759   0.446
#> 6 6 0.522           0.452       0.674         0.0455 0.882   0.684

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.9922     0.3143 0.552 0.448
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     2  0.0376     0.8310 0.004 0.996
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.9129     0.6191 0.672 0.328
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1633     0.8429 0.976 0.024
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1184     0.8417 0.984 0.016
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.7219     0.7680 0.800 0.200
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.9358     0.5645 0.648 0.352
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     1  0.0000     0.8376 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.9323     0.5851 0.652 0.348
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.7219     0.7697 0.800 0.200
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3274     0.8429 0.940 0.060
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4939     0.8312 0.892 0.108
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.5842     0.8128 0.860 0.140
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     1  0.0000     0.8376 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     2  0.0000     0.8313 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.9580     0.5212 0.620 0.380
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     2  0.6973     0.7488 0.188 0.812
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2778     0.8438 0.952 0.048
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     2  0.9775     0.2551 0.412 0.588
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.1184     0.8415 0.984 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     1  0.0000     0.8376 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.5408     0.8236 0.876 0.124
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4562     0.8352 0.904 0.096
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.3733     0.8412 0.928 0.072
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.9996     0.2018 0.512 0.488
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     2  0.6531     0.7645 0.168 0.832
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.9460     0.5542 0.636 0.364
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.9795     0.4376 0.584 0.416
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     1  0.0000     0.8376 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     1  0.0000     0.8376 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.8376 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.8376 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.8376 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.9881     0.3814 0.564 0.436
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.7674     0.7398 0.776 0.224
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2603     0.8439 0.956 0.044
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.9393     0.5634 0.644 0.356
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.7815     0.6952 0.232 0.768
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.5737     0.8153 0.864 0.136
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.9983     0.2443 0.524 0.476
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     1  0.0000     0.8376 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.2948     0.8437 0.948 0.052
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.9608     0.5136 0.616 0.384
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4690     0.8344 0.900 0.100
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.9522     0.5387 0.628 0.372
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.9580     0.5216 0.620 0.380
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2948     0.8433 0.948 0.052
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     1  0.0000     0.8376 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.9427     0.5617 0.640 0.360
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     1  0.0000     0.8376 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3114     0.8435 0.944 0.056
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.7815     0.6952 0.232 0.768
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.9491     0.5457 0.632 0.368
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2236     0.8439 0.964 0.036
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.5737     0.8153 0.864 0.136
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.3879     0.8419 0.924 0.076
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     2  0.0000     0.8313 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000     0.8376 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     1  0.9977     0.2153 0.528 0.472
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.3114     0.8429 0.944 0.056
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.3879     0.8407 0.924 0.076
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000     0.8376 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.3274     0.8426 0.940 0.060
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.4161     0.8390 0.916 0.084
#> 131213AD-0313-4DF1-B013-CE67ED262C37     1  0.0000     0.8376 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     2  0.0000     0.8313 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3584     0.8414 0.932 0.068
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.6148     0.8067 0.848 0.152
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     2  0.0376     0.8310 0.004 0.996
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     1  0.0000     0.8376 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     2  0.4690     0.8048 0.100 0.900
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     2  0.8386     0.6379 0.268 0.732
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.9522     0.5375 0.628 0.372
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.6048     0.8108 0.852 0.148
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4939     0.8312 0.892 0.108
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.8327     0.7026 0.736 0.264
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.3879     0.8406 0.924 0.076
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     1  0.0000     0.8376 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     2  0.4431     0.8079 0.092 0.908
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.9775     0.2937 0.412 0.588
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.9087     0.6211 0.676 0.324
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.0000     0.8313 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     2  0.5294     0.7946 0.120 0.880
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.5519     0.8194 0.872 0.128
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.5519     0.8194 0.872 0.128
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000     0.8376 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0376     0.8389 0.996 0.004
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     1  0.0000     0.8376 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.7815     0.6952 0.232 0.768
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.9087     0.6255 0.676 0.324
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.8144     0.7179 0.748 0.252
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.8386     0.6997 0.732 0.268
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     1  0.0000     0.8376 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.9580     0.5209 0.620 0.380
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.8376 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.8376 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.2603     0.8439 0.956 0.044
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.2603     0.8438 0.956 0.044
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.6148     0.8071 0.848 0.152
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.9460     0.5542 0.636 0.364
#> 00439565-02CE-4BF5-956D-7078B51C0947     2  0.0376     0.8307 0.004 0.996
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     1  0.0000     0.8376 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     1  0.0000     0.8376 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0938     0.8405 0.988 0.012
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#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4431     0.8356 0.908 0.092
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4298     0.8376 0.912 0.088
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.5178     0.8253 0.884 0.116
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     1  0.0000     0.8376 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000     0.8376 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000     0.8313 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5178     0.8258 0.884 0.116
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.0000     0.8376 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     2  0.6973     0.7489 0.188 0.812
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.5842     0.8076 0.860 0.140
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0376     0.8384 0.996 0.004
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.8909     0.6462 0.692 0.308
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     1  0.0000     0.8376 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.5408     0.8233 0.876 0.124
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.3584     0.8392 0.932 0.068
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4562     0.8357 0.904 0.096
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     2  0.0000     0.8313 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.5737     0.8153 0.864 0.136
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0000     0.8376 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0672     0.8399 0.992 0.008
#> 6752EED9-7990-433F-A206-D5398C396471     2  0.0000     0.8313 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.2778     0.8434 0.952 0.048
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.9635     0.5043 0.612 0.388
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.8327     0.7043 0.736 0.264
#> 1ABBEF80-508F-4247-B43D-3E549372113B     2  0.8081     0.6783 0.248 0.752
#> 835AAE7F-F873-4D11-8845-232D261A38DF     2  0.4431     0.8079 0.092 0.908
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0376     0.8384 0.996 0.004
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     2  0.0000     0.8313 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     1  0.1184     0.8411 0.984 0.016
#> 26DABC83-DB30-452F-9BE2-366760CB138E     1  0.6048     0.8019 0.852 0.148
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     2  0.7219     0.7357 0.200 0.800
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.2603     0.8436 0.956 0.044
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     2  0.8386     0.6425 0.268 0.732
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.8376 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.6954    0.41058 0.720 0.084 0.196
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4796    0.82504 0.220 0.000 0.780
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.4636    0.65920 0.848 0.116 0.036
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     2  0.5988    0.53358 0.368 0.632 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     2  0.5431    0.65834 0.284 0.716 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.5138    0.53118 0.748 0.252 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.4807    0.61209 0.848 0.060 0.092
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2496    0.74153 0.068 0.928 0.004
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.3370    0.67117 0.904 0.072 0.024
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.5692    0.50723 0.724 0.268 0.008
#> B710293C-41D3-4A2E-8104-5402F91DD859     2  0.6302    0.22290 0.480 0.520 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.6140    0.23200 0.596 0.404 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.6359    0.35032 0.628 0.364 0.008
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0237    0.72909 0.004 0.996 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.4062    0.83803 0.164 0.000 0.836
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.2187    0.64906 0.948 0.028 0.024
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.6302   -0.41740 0.520 0.000 0.480
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     2  0.6140    0.44754 0.404 0.596 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.5803    0.32693 0.736 0.016 0.248
#> C204D355-B876-4341-A111-36D48CBDD2A8     2  0.5529    0.64103 0.296 0.704 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.3965    0.75065 0.132 0.860 0.008
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.6180    0.19209 0.584 0.416 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.6244    0.10430 0.560 0.440 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.6267    0.05186 0.548 0.452 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.4059    0.53416 0.860 0.012 0.128
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.6305    0.49398 0.484 0.000 0.516
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.2527    0.66228 0.936 0.044 0.020
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.2651    0.61549 0.928 0.012 0.060
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1643    0.74028 0.044 0.956 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0424    0.73117 0.008 0.992 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     2  0.4002    0.74949 0.160 0.840 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     2  0.3686    0.75109 0.140 0.860 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     2  0.3816    0.74936 0.148 0.852 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2866    0.60438 0.916 0.008 0.076
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.5524    0.59459 0.796 0.164 0.040
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.6307    0.20234 0.488 0.512 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.4479    0.66240 0.860 0.096 0.044
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.7919    0.56250 0.380 0.064 0.556
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.5810    0.39302 0.664 0.336 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.4209    0.55521 0.860 0.020 0.120
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.72660 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     2  0.6274    0.30650 0.456 0.544 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.2318    0.64701 0.944 0.028 0.028
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.6192    0.18370 0.580 0.420 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.2434    0.65639 0.940 0.036 0.024
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.1905    0.65114 0.956 0.028 0.016
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     2  0.6274    0.30108 0.456 0.544 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.72660 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.2846    0.66672 0.924 0.056 0.020
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1529    0.73944 0.040 0.960 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     2  0.6274    0.30817 0.456 0.544 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.7919    0.56250 0.380 0.064 0.556
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.2031    0.65746 0.952 0.032 0.016
#> F941890E-AB33-478F-8C97-1C785DD9428F     2  0.6079    0.48788 0.388 0.612 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.5810    0.39302 0.664 0.336 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.6267    0.05014 0.548 0.452 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.1529    0.82261 0.040 0.000 0.960
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     2  0.3686    0.75109 0.140 0.860 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     1  0.7596    0.33695 0.672 0.100 0.228
#> A22892DE-0AF4-4B63-9513-1D6825059040     2  0.6280    0.28706 0.460 0.540 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.6260    0.06571 0.552 0.448 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.3941    0.75034 0.156 0.844 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     2  0.6308    0.17505 0.492 0.508 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.6225    0.13355 0.568 0.432 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.1529    0.74064 0.040 0.960 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.1529    0.82261 0.040 0.000 0.960
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     2  0.6305    0.20334 0.484 0.516 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.5650    0.44121 0.688 0.312 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.4931    0.81840 0.232 0.000 0.768
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0237    0.72909 0.004 0.996 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.6180    0.62922 0.416 0.000 0.584
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.6111   -0.17065 0.604 0.000 0.396
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.2176    0.65497 0.948 0.032 0.020
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.6275    0.36961 0.644 0.348 0.008
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.6154    0.22359 0.592 0.408 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.4110    0.62775 0.844 0.152 0.004
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.6260    0.06225 0.552 0.448 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.3030    0.73139 0.092 0.904 0.004
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5926    0.71674 0.356 0.000 0.644
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     1  0.8440   -0.18099 0.492 0.088 0.420
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.3293    0.66390 0.900 0.088 0.012
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.1529    0.82261 0.040 0.000 0.960
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.6168    0.63076 0.412 0.000 0.588
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.5859    0.37639 0.656 0.344 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.5859    0.37639 0.656 0.344 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     2  0.4235    0.74198 0.176 0.824 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     2  0.4887    0.71222 0.228 0.772 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0237    0.72909 0.004 0.996 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     3  0.7919    0.56250 0.380 0.064 0.556
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.4519    0.65802 0.852 0.116 0.032
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.4968    0.60800 0.800 0.188 0.012
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.4047    0.63104 0.848 0.148 0.004
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1289    0.73608 0.032 0.968 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.1919    0.64802 0.956 0.024 0.020
#> D587A993-3C47-4D4C-B744-59169D4F7451     2  0.3686    0.75109 0.140 0.860 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     2  0.3816    0.74936 0.148 0.852 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.6307    0.20234 0.488 0.512 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     2  0.6154    0.43523 0.408 0.592 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.5859    0.38663 0.656 0.344 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.2527    0.66228 0.936 0.044 0.020
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.3619    0.83746 0.136 0.000 0.864
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.1643    0.74028 0.044 0.956 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.2496    0.74153 0.068 0.928 0.004
#> D9096909-1439-462D-B69C-CAD1BF4F420C     2  0.5785    0.59258 0.332 0.668 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.5012    0.58922 0.788 0.204 0.008
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.1753    0.74035 0.048 0.952 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.2878    0.75376 0.096 0.904 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.4342    0.56539 0.856 0.024 0.120
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.6225    0.12487 0.568 0.432 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.6849    0.49615 0.380 0.600 0.020
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000    0.72660 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.1643    0.74482 0.044 0.956 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.4796    0.82504 0.220 0.000 0.780
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.4750    0.82652 0.216 0.000 0.784
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     2  0.6260    0.34097 0.448 0.552 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.2527    0.63986 0.936 0.020 0.044
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     3  0.5706    0.74670 0.320 0.000 0.680
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     2  0.5016    0.70174 0.240 0.760 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     2  0.4504    0.73230 0.196 0.804 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     2  0.3816    0.74936 0.148 0.852 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     3  0.6309    0.45896 0.496 0.000 0.504
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.6460   -0.32129 0.556 0.004 0.440
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.5115    0.61070 0.796 0.188 0.016
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.5905    0.36406 0.648 0.352 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.6082    0.64396 0.296 0.692 0.012
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.6849    0.49615 0.380 0.600 0.020
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     1  0.7388    0.39658 0.692 0.100 0.208
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.6302   -0.07349 0.520 0.480 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.1529    0.82261 0.040 0.000 0.960
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     3  0.3816    0.83916 0.148 0.000 0.852
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#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.6204    0.16615 0.576 0.424 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.1529    0.82261 0.040 0.000 0.960
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6632    0.27772 0.596 0.392 0.012
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.3340    0.75593 0.120 0.880 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     2  0.4452    0.73401 0.192 0.808 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.2066    0.82740 0.060 0.000 0.940
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.6252    0.34044 0.444 0.556 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.2187    0.64368 0.948 0.024 0.028
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5008    0.61634 0.804 0.180 0.016
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.6587   -0.28022 0.568 0.008 0.424
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.6154    0.64224 0.408 0.000 0.592
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     2  0.4002    0.74575 0.160 0.840 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.4452    0.83323 0.192 0.000 0.808
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2537    0.73282 0.080 0.920 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     1  0.6906    0.39950 0.644 0.324 0.032
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6286   -0.40315 0.536 0.000 0.464
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     2  0.6079    0.48568 0.388 0.612 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.6675   -0.18606 0.584 0.012 0.404
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     2  0.3941    0.74782 0.156 0.844 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5228     0.5732 0.120 0.000 0.124 0.756
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.5186     0.6701 0.164 0.000 0.752 0.084
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5397     0.4630 0.708 0.044 0.004 0.244
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.5326     0.1635 0.604 0.380 0.000 0.016
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.5682    -0.1586 0.520 0.456 0.000 0.024
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4901     0.5862 0.780 0.108 0.000 0.112
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.5421     0.5372 0.308 0.008 0.020 0.664
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2670     0.6987 0.052 0.908 0.000 0.040
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5692     0.4187 0.680 0.036 0.012 0.272
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4793     0.5993 0.800 0.112 0.008 0.080
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.4826     0.4499 0.716 0.264 0.000 0.020
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.4755     0.5741 0.760 0.200 0.000 0.040
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.5775     0.5845 0.696 0.212 0.000 0.092
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0188     0.7044 0.004 0.996 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.4224     0.6786 0.144 0.000 0.812 0.044
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.4508     0.4120 0.744 0.004 0.008 0.244
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.7714     0.3184 0.332 0.000 0.432 0.236
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.5543     0.2625 0.612 0.360 0.000 0.028
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.7591    -0.0822 0.500 0.004 0.204 0.292
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.5493    -0.1163 0.528 0.456 0.000 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.4181     0.6947 0.128 0.820 0.000 0.052
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.5325     0.5677 0.728 0.204 0.000 0.068
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4137     0.5552 0.780 0.208 0.000 0.012
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4678     0.5335 0.744 0.232 0.000 0.024
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.6285     0.1917 0.624 0.000 0.092 0.284
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.7634     0.3894 0.300 0.000 0.464 0.236
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.5024     0.4305 0.724 0.020 0.008 0.248
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5427     0.3522 0.704 0.004 0.044 0.248
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1833     0.7054 0.032 0.944 0.000 0.024
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0469     0.7077 0.012 0.988 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     2  0.5536     0.5102 0.384 0.592 0.000 0.024
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     2  0.5482     0.5302 0.368 0.608 0.000 0.024
#> 904EDF2E-411E-43BD-901D-46129AFA283A     2  0.5510     0.5173 0.376 0.600 0.000 0.024
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.5498     0.3133 0.680 0.000 0.048 0.272
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     4  0.5021     0.6541 0.180 0.064 0.000 0.756
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.5062     0.4485 0.692 0.284 0.000 0.024
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.6582     0.2466 0.560 0.052 0.016 0.372
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.5600     0.1938 0.020 0.000 0.512 0.468
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.3749     0.6165 0.840 0.128 0.000 0.032
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.6104     0.2598 0.664 0.000 0.104 0.232
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.7022 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.5003     0.3992 0.676 0.308 0.000 0.016
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.4664     0.4023 0.736 0.004 0.012 0.248
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.4655     0.5644 0.760 0.208 0.000 0.032
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4429     0.4333 0.764 0.004 0.012 0.220
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4302     0.4244 0.756 0.004 0.004 0.236
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.4988     0.4072 0.692 0.288 0.000 0.020
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.7022 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.4862     0.4526 0.744 0.020 0.008 0.228
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1733     0.7051 0.028 0.948 0.000 0.024
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.4908     0.4108 0.692 0.292 0.000 0.016
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.5600     0.1938 0.020 0.000 0.512 0.468
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.4374     0.4362 0.760 0.008 0.004 0.228
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.5523     0.1912 0.596 0.380 0.000 0.024
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.3749     0.6165 0.840 0.128 0.000 0.032
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.5227     0.5195 0.704 0.256 0.000 0.040
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.6266 0.000 0.000 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     2  0.5482     0.5302 0.368 0.608 0.000 0.024
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.4849     0.5223 0.064 0.000 0.164 0.772
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.4963     0.4110 0.696 0.284 0.000 0.020
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.5170     0.5353 0.724 0.228 0.000 0.048
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.5523     0.5187 0.380 0.596 0.000 0.024
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.4868     0.4686 0.720 0.256 0.000 0.024
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.4764     0.5533 0.748 0.220 0.000 0.032
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.1724     0.7054 0.032 0.948 0.000 0.020
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.6266 0.000 0.000 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.4720     0.4538 0.720 0.264 0.000 0.016
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.4440     0.6180 0.804 0.136 0.000 0.060
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.5334     0.6646 0.172 0.000 0.740 0.088
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0188     0.7044 0.004 0.996 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.7324     0.4952 0.240 0.000 0.532 0.228
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.7843    -0.4243 0.388 0.000 0.344 0.268
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.4582     0.4254 0.748 0.008 0.008 0.236
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3880     0.6130 0.836 0.136 0.008 0.020
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4669     0.5729 0.764 0.200 0.000 0.036
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.5160     0.5359 0.748 0.072 0.000 0.180
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.4635     0.5381 0.756 0.216 0.000 0.028
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.3463     0.6583 0.040 0.864 0.000 0.096
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.6834     0.5629 0.224 0.000 0.600 0.176
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.5331     0.1919 0.024 0.000 0.332 0.644
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4540     0.4921 0.772 0.032 0.000 0.196
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0000     0.6266 0.000 0.000 1.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.7267     0.5007 0.248 0.000 0.540 0.212
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.3552     0.6136 0.848 0.128 0.000 0.024
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3552     0.6136 0.848 0.128 0.000 0.024
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     2  0.5592     0.4712 0.404 0.572 0.000 0.024
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     2  0.5597     0.3384 0.464 0.516 0.000 0.020
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0188     0.7044 0.004 0.996 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     3  0.5600     0.1938 0.020 0.000 0.512 0.468
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.5366     0.4667 0.712 0.044 0.004 0.240
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.5869     0.5350 0.704 0.096 0.004 0.196
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.4037     0.5409 0.824 0.040 0.000 0.136
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1411     0.7027 0.020 0.960 0.000 0.020
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.4508     0.4119 0.744 0.004 0.008 0.244
#> D587A993-3C47-4D4C-B744-59169D4F7451     2  0.5482     0.5302 0.368 0.608 0.000 0.024
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     2  0.5510     0.5173 0.376 0.600 0.000 0.024
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.5062     0.4485 0.692 0.284 0.000 0.024
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.5436     0.2673 0.620 0.356 0.000 0.024
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.5292     0.6076 0.744 0.168 0.000 0.088
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.5024     0.4305 0.724 0.020 0.008 0.248
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.3547     0.6611 0.064 0.000 0.864 0.072
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.1833     0.7054 0.032 0.944 0.000 0.024
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.2670     0.6987 0.052 0.908 0.000 0.040
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.5611     0.0430 0.564 0.412 0.000 0.024
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.5183     0.5565 0.764 0.084 0.004 0.148
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.1936     0.7038 0.032 0.940 0.000 0.028
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.4936     0.6207 0.280 0.700 0.000 0.020
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.6381     0.2353 0.628 0.004 0.088 0.280
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.4540     0.5560 0.772 0.196 0.000 0.032
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.7550     0.3008 0.204 0.464 0.000 0.332
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.7022 0.000 1.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.4284     0.6783 0.200 0.780 0.000 0.020
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.5186     0.6701 0.164 0.000 0.752 0.084
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.5165     0.6707 0.168 0.000 0.752 0.080
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.5206     0.3875 0.668 0.308 0.000 0.024
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.4854     0.4005 0.732 0.004 0.020 0.244
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     3  0.6583     0.5936 0.192 0.000 0.632 0.176
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     2  0.5774     0.3217 0.464 0.508 0.000 0.028
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     2  0.5643     0.4276 0.428 0.548 0.000 0.024
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     2  0.5510     0.5173 0.376 0.600 0.000 0.024
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     3  0.7641     0.3630 0.324 0.000 0.452 0.224
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     3  0.7867     0.2751 0.316 0.000 0.392 0.292
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.5950     0.5390 0.708 0.100 0.008 0.184
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.3606     0.6117 0.844 0.132 0.000 0.024
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.7002     0.4404 0.352 0.520 0.000 0.128
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.7550     0.3008 0.204 0.464 0.000 0.332
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     4  0.5253     0.5672 0.092 0.008 0.132 0.768
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.4434     0.5064 0.756 0.228 0.000 0.016
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.0000     0.6266 0.000 0.000 1.000 0.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     3  0.3658     0.6765 0.144 0.000 0.836 0.020
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.5279     0.5403 0.716 0.232 0.000 0.052
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     2  0.5510     0.5173 0.376 0.600 0.000 0.024
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     3  0.5600     0.1938 0.020 0.000 0.512 0.468
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     3  0.7816     0.2813 0.340 0.000 0.400 0.260
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     4  0.4874     0.6550 0.180 0.056 0.000 0.764
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000     0.7022 0.000 1.000 0.000 0.000
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#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.7022 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.4713     0.6021 0.776 0.172 0.000 0.052
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.6928     0.1836 0.116 0.372 0.000 0.512
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.4728     0.5589 0.752 0.216 0.000 0.032
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.6266 0.000 0.000 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6797     0.5157 0.616 0.232 0.004 0.148
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.4857     0.6221 0.284 0.700 0.000 0.016
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     2  0.5716     0.4360 0.420 0.552 0.000 0.028
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.1004     0.6395 0.024 0.000 0.972 0.004
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5110     0.3506 0.656 0.328 0.000 0.016
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.4747     0.4018 0.736 0.004 0.016 0.244
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5883     0.5284 0.700 0.092 0.004 0.204
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.7896     0.2431 0.312 0.000 0.376 0.312
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.7274     0.4990 0.240 0.000 0.540 0.220
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     2  0.5548     0.4970 0.388 0.588 0.000 0.024
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.4701     0.6755 0.164 0.000 0.780 0.056
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2660     0.6875 0.036 0.908 0.000 0.056
#> 26DABC83-DB30-452F-9BE2-366760CB138E     4  0.6635     0.5364 0.152 0.228 0.000 0.620
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.7814     0.3073 0.304 0.000 0.416 0.280
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.5600     0.2144 0.596 0.376 0.000 0.028
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.7869    -0.4432 0.368 0.000 0.356 0.276
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     2  0.5536     0.5027 0.384 0.592 0.000 0.024

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5544   0.508060 0.028 0.000 0.204 0.684 0.084
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.4595   0.546267 0.004 0.000 0.488 0.004 0.504
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5121  -0.248675 0.500 0.004 0.468 0.028 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3387   0.634201 0.836 0.132 0.024 0.008 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4419   0.602541 0.760 0.188 0.032 0.020 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.3944   0.328365 0.720 0.004 0.272 0.004 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.6538   0.192983 0.152 0.000 0.396 0.444 0.008
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2610   0.839480 0.028 0.892 0.004 0.076 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.5184   0.402556 0.456 0.004 0.508 0.032 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4164   0.403569 0.728 0.012 0.252 0.008 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2589   0.636568 0.900 0.048 0.044 0.008 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3646   0.581608 0.816 0.036 0.144 0.004 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.4882   0.516077 0.736 0.048 0.188 0.028 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0324   0.874270 0.004 0.992 0.004 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.4219   0.627280 0.000 0.000 0.416 0.000 0.584
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4648   0.437157 0.464 0.000 0.524 0.012 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.5537   0.307185 0.112 0.000 0.660 0.008 0.220
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3976   0.636103 0.812 0.124 0.048 0.016 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.4782   0.575943 0.236 0.000 0.708 0.008 0.048
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.4405   0.609490 0.752 0.200 0.036 0.012 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.4716   0.728933 0.112 0.772 0.028 0.088 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3635   0.595248 0.824 0.036 0.132 0.008 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3192   0.615261 0.848 0.040 0.112 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2850   0.619317 0.872 0.036 0.092 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.5192   0.561266 0.324 0.000 0.628 0.020 0.028
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.5386   0.210551 0.088 0.000 0.664 0.008 0.240
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4907   0.394736 0.484 0.000 0.492 0.024 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4574   0.507350 0.412 0.000 0.576 0.012 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1774   0.857092 0.016 0.932 0.000 0.052 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0671   0.868358 0.016 0.980 0.004 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.5146   0.436885 0.636 0.316 0.032 0.016 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.5299   0.410895 0.616 0.332 0.032 0.020 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.5251   0.433391 0.628 0.320 0.032 0.020 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.4527   0.517345 0.392 0.000 0.596 0.012 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     4  0.4869   0.612229 0.084 0.044 0.104 0.768 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3759   0.637612 0.828 0.084 0.080 0.008 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.6493   0.414542 0.380 0.016 0.480 0.124 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     5  0.6219   0.131315 0.000 0.000 0.144 0.384 0.472
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2852   0.521589 0.828 0.000 0.172 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.4789   0.542791 0.368 0.000 0.608 0.004 0.020
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0162   0.874845 0.004 0.996 0.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.3384   0.644236 0.852 0.084 0.056 0.008 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.4894   0.449134 0.456 0.000 0.520 0.024 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3467   0.593544 0.832 0.036 0.128 0.004 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4659   0.397125 0.488 0.000 0.500 0.012 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.4656   0.411150 0.480 0.000 0.508 0.012 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2838   0.641300 0.884 0.072 0.036 0.008 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0162   0.874845 0.004 0.996 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.4658  -0.361531 0.504 0.000 0.484 0.012 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1862   0.859437 0.016 0.932 0.004 0.048 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2900   0.641817 0.884 0.064 0.040 0.012 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     5  0.6219   0.131315 0.000 0.000 0.144 0.384 0.472
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.4659  -0.393651 0.496 0.000 0.492 0.012 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4509   0.627090 0.772 0.152 0.056 0.020 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2852   0.521589 0.828 0.000 0.172 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.4537   0.612074 0.784 0.072 0.116 0.028 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     5  0.0162   0.697487 0.000 0.000 0.000 0.004 0.996
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5299   0.410895 0.616 0.332 0.032 0.020 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.5226   0.479230 0.008 0.000 0.164 0.704 0.124
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2339   0.637997 0.912 0.052 0.028 0.008 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2854   0.619109 0.880 0.028 0.084 0.008 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.5224   0.410035 0.620 0.332 0.028 0.020 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.2772   0.637703 0.892 0.044 0.052 0.012 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2984   0.610143 0.860 0.032 0.108 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.1701   0.859186 0.016 0.936 0.000 0.048 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     5  0.0162   0.697487 0.000 0.000 0.000 0.004 0.996
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2362   0.634628 0.912 0.040 0.040 0.008 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.3422   0.481012 0.792 0.004 0.200 0.004 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.4596  -0.544498 0.004 0.000 0.500 0.004 0.492
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0324   0.874270 0.004 0.992 0.004 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.4622  -0.045495 0.024 0.000 0.700 0.012 0.264
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.4799   0.424531 0.120 0.000 0.756 0.016 0.108
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4656   0.406661 0.480 0.000 0.508 0.012 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3280   0.537548 0.812 0.012 0.176 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3602   0.585006 0.820 0.036 0.140 0.004 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.4288   0.016605 0.612 0.000 0.384 0.004 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.2206   0.615908 0.912 0.016 0.068 0.004 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.2881   0.802892 0.012 0.860 0.004 0.124 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5037  -0.242378 0.024 0.000 0.612 0.012 0.352
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.6040   0.177816 0.000 0.000 0.152 0.556 0.292
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4610  -0.214385 0.556 0.000 0.432 0.012 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.0162   0.697487 0.000 0.000 0.000 0.004 0.996
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.4864  -0.039195 0.036 0.000 0.672 0.008 0.284
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.2773   0.530445 0.836 0.000 0.164 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2773   0.530445 0.836 0.000 0.164 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5025   0.481643 0.664 0.288 0.028 0.020 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4565   0.552172 0.720 0.240 0.024 0.016 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0324   0.874270 0.004 0.992 0.004 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     5  0.6219   0.131315 0.000 0.000 0.144 0.384 0.472
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.5119  -0.235758 0.504 0.004 0.464 0.028 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.4841   0.069813 0.600 0.008 0.376 0.016 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.4288   0.008496 0.612 0.000 0.384 0.004 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1525   0.864598 0.012 0.948 0.004 0.036 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.4650   0.431733 0.468 0.000 0.520 0.012 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.5299   0.410895 0.616 0.332 0.032 0.020 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.5251   0.433391 0.628 0.320 0.032 0.020 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.3759   0.637612 0.828 0.084 0.080 0.008 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.4410   0.629224 0.792 0.124 0.044 0.040 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.4141   0.490458 0.768 0.020 0.196 0.016 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.4907   0.394736 0.484 0.000 0.492 0.024 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     5  0.3756   0.664756 0.000 0.000 0.248 0.008 0.744
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.1774   0.857092 0.016 0.932 0.000 0.052 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.2610   0.839480 0.028 0.892 0.004 0.076 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.3716   0.622794 0.812 0.152 0.024 0.012 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.4353   0.168557 0.660 0.004 0.328 0.008 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.1943   0.855577 0.020 0.924 0.000 0.056 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.5497   0.126947 0.488 0.464 0.028 0.020 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.5560   0.538679 0.364 0.000 0.576 0.024 0.036
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.2116   0.606570 0.912 0.008 0.076 0.004 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.7249   0.076080 0.204 0.348 0.032 0.416 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0162   0.874845 0.004 0.996 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.5383   0.322122 0.356 0.592 0.032 0.020 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     5  0.4595   0.546267 0.004 0.000 0.488 0.004 0.504
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     5  0.4596   0.545175 0.004 0.000 0.492 0.004 0.500
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.3745   0.641172 0.832 0.088 0.068 0.012 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     3  0.4637   0.451448 0.452 0.000 0.536 0.012 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     3  0.4657  -0.328524 0.008 0.000 0.604 0.008 0.380
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.5139   0.547312 0.692 0.240 0.036 0.032 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.4681   0.508029 0.692 0.272 0.020 0.016 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.5251   0.433391 0.628 0.320 0.032 0.020 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     3  0.5821   0.250445 0.120 0.000 0.620 0.008 0.252
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     3  0.5647   0.296280 0.084 0.000 0.696 0.048 0.172
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#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.4656  -0.338539 0.508 0.000 0.480 0.012 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5067   0.498948 0.668 0.280 0.028 0.024 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3538   0.633447 0.832 0.128 0.028 0.012 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.4921  -0.118210 0.036 0.000 0.640 0.004 0.320
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.6088   0.465964 0.380 0.000 0.492 0.128 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4945   0.534073 0.688 0.260 0.032 0.020 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4915   0.510873 0.684 0.268 0.028 0.020 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.4227   0.622351 0.000 0.000 0.420 0.000 0.580
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.4659   0.385036 0.488 0.000 0.500 0.012 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     4  0.4936   0.607302 0.068 0.092 0.072 0.768 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2970   0.523226 0.828 0.000 0.168 0.004 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.4792   0.516740 0.248 0.704 0.028 0.020 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.3106   0.587649 0.844 0.024 0.132 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2237   0.610021 0.904 0.008 0.084 0.004 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2648   0.543916 0.848 0.000 0.152 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2976   0.797126 0.012 0.852 0.004 0.132 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5623   0.206588 0.512 0.432 0.032 0.024 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.0162   0.697487 0.000 0.000 0.000 0.004 0.996
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6338   0.492592 0.648 0.076 0.160 0.116 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5383   0.322122 0.356 0.592 0.032 0.020 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5713   0.193550 0.100 0.000 0.620 0.008 0.272
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.8164   0.145936 0.408 0.240 0.208 0.144 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4848   0.499446 0.684 0.272 0.028 0.016 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4510  -0.171834 0.560 0.000 0.432 0.008 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0162   0.874845 0.004 0.996 0.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.3277   0.556746 0.832 0.012 0.148 0.008 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.6143   0.329766 0.076 0.284 0.040 0.600 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3420   0.598068 0.836 0.036 0.124 0.004 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0162   0.697487 0.000 0.000 0.000 0.004 0.996
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6191   0.482671 0.652 0.072 0.188 0.088 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.5715   0.125248 0.480 0.460 0.032 0.028 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5008   0.493468 0.668 0.284 0.024 0.024 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.1671   0.701246 0.000 0.000 0.076 0.000 0.924
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4247   0.632144 0.808 0.100 0.056 0.036 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.4641   0.449432 0.456 0.000 0.532 0.012 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.4893   0.016129 0.580 0.008 0.396 0.016 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.5842   0.308336 0.088 0.000 0.688 0.064 0.160
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4906  -0.041104 0.036 0.000 0.664 0.008 0.292
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.5104   0.455048 0.648 0.304 0.028 0.020 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.4278   0.583953 0.000 0.000 0.452 0.000 0.548
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2452   0.839293 0.016 0.896 0.004 0.084 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     4  0.5739   0.548099 0.076 0.188 0.052 0.684 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.4899   0.276943 0.064 0.000 0.736 0.020 0.180
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4067   0.632548 0.804 0.132 0.048 0.016 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.5504   0.403018 0.132 0.000 0.704 0.028 0.136
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.5180   0.455389 0.644 0.304 0.032 0.020 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.4584    0.54456 0.032 0.000 0.104 0.028 0.772 0.064
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4754    0.08906 0.004 0.000 0.576 0.020 0.016 0.384
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5296    0.29086 0.588 0.000 0.324 0.056 0.032 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3794    0.52046 0.744 0.040 0.000 0.216 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4499    0.43095 0.652 0.060 0.000 0.288 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4046    0.53802 0.752 0.000 0.176 0.068 0.004 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     5  0.6992    0.21671 0.144 0.000 0.304 0.116 0.436 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2487    0.78514 0.004 0.892 0.008 0.068 0.028 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5451    0.19464 0.540 0.000 0.368 0.064 0.028 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.3293    0.55613 0.812 0.000 0.140 0.048 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2685    0.59169 0.852 0.008 0.008 0.132 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.3292    0.60910 0.844 0.008 0.056 0.084 0.008 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.4470    0.58869 0.752 0.008 0.108 0.120 0.012 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0146    0.82933 0.000 0.996 0.000 0.004 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.4459   -0.13296 0.000 0.000 0.516 0.020 0.004 0.460
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.5049    0.18460 0.548 0.000 0.384 0.060 0.008 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.4984    0.57962 0.124 0.000 0.728 0.020 0.024 0.104
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4081    0.52918 0.740 0.028 0.008 0.216 0.008 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.4138    0.46422 0.276 0.000 0.692 0.020 0.012 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.4579    0.45249 0.660 0.060 0.004 0.276 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.4647    0.60142 0.044 0.740 0.012 0.168 0.036 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3670    0.61799 0.808 0.012 0.080 0.100 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2452    0.61951 0.884 0.004 0.028 0.084 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2476    0.61196 0.880 0.004 0.024 0.092 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.5220    0.22160 0.388 0.000 0.540 0.048 0.024 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.4873    0.56687 0.092 0.000 0.740 0.016 0.032 0.120
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.5096    0.23399 0.568 0.000 0.364 0.048 0.020 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.5124    0.02874 0.488 0.000 0.444 0.060 0.008 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1672    0.80641 0.000 0.932 0.004 0.048 0.016 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0806    0.81095 0.008 0.972 0.000 0.020 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.5432    0.20160 0.480 0.120 0.000 0.400 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.5458    0.18969 0.480 0.124 0.000 0.396 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.5358    0.21923 0.496 0.112 0.000 0.392 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.5035   -0.01702 0.472 0.000 0.468 0.052 0.008 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     5  0.5279    0.35350 0.048 0.036 0.020 0.224 0.672 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3223    0.58896 0.824 0.020 0.008 0.144 0.004 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.6570    0.02403 0.452 0.000 0.344 0.064 0.140 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     5  0.5608    0.22487 0.000 0.000 0.092 0.016 0.468 0.424
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1779    0.60666 0.920 0.000 0.064 0.016 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.4816    0.11433 0.436 0.000 0.516 0.044 0.004 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.3229    0.58025 0.804 0.020 0.004 0.172 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.5202    0.17404 0.540 0.000 0.388 0.052 0.020 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3269    0.60921 0.844 0.008 0.048 0.092 0.008 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4851    0.22870 0.576 0.000 0.364 0.056 0.004 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.4880    0.20612 0.564 0.000 0.376 0.056 0.004 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2830    0.57757 0.836 0.020 0.000 0.144 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.4776    0.25361 0.588 0.000 0.356 0.052 0.004 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1707    0.80805 0.000 0.928 0.004 0.056 0.012 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2958    0.58650 0.824 0.008 0.008 0.160 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     5  0.5608    0.22487 0.000 0.000 0.092 0.016 0.468 0.424
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.4818    0.24685 0.588 0.000 0.352 0.056 0.004 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.4720    0.49764 0.704 0.056 0.012 0.216 0.012 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1779    0.60666 0.920 0.000 0.064 0.016 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.3816    0.59546 0.796 0.016 0.028 0.148 0.012 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.5458    0.18969 0.480 0.124 0.000 0.396 0.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     5  0.3796    0.54518 0.000 0.000 0.068 0.028 0.808 0.096
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2692    0.57962 0.840 0.012 0.000 0.148 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2540    0.61594 0.872 0.004 0.020 0.104 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.5537    0.18929 0.476 0.136 0.000 0.388 0.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.2825    0.59868 0.844 0.008 0.012 0.136 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2670    0.61655 0.872 0.004 0.040 0.084 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.1605    0.80922 0.000 0.936 0.004 0.044 0.016 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2573    0.59371 0.856 0.004 0.008 0.132 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.2595    0.59434 0.872 0.000 0.084 0.044 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.4866    0.12132 0.004 0.000 0.584 0.020 0.024 0.368
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0146    0.82933 0.000 0.996 0.000 0.004 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.4145    0.49612 0.024 0.000 0.800 0.036 0.036 0.104
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.4086    0.55578 0.144 0.000 0.784 0.024 0.036 0.012
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.4963    0.22033 0.568 0.000 0.368 0.056 0.008 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.2384    0.61080 0.884 0.000 0.084 0.032 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.3231    0.60945 0.848 0.008 0.052 0.084 0.008 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.4159    0.42925 0.704 0.000 0.252 0.040 0.004 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.1866    0.61348 0.908 0.000 0.008 0.084 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.2998    0.75049 0.000 0.852 0.004 0.076 0.068 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5288    0.40473 0.040 0.000 0.668 0.028 0.032 0.232
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     5  0.7181    0.35743 0.000 0.000 0.124 0.196 0.432 0.248
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.4596    0.33475 0.640 0.000 0.304 0.052 0.004 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.4415    0.49707 0.036 0.000 0.772 0.028 0.028 0.136
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.1594    0.61003 0.932 0.000 0.052 0.016 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.1594    0.61003 0.932 0.000 0.052 0.016 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.5144    0.27721 0.536 0.092 0.000 0.372 0.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.4724    0.35498 0.592 0.060 0.000 0.348 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0146    0.82933 0.000 0.996 0.000 0.004 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     5  0.5608    0.22487 0.000 0.000 0.092 0.016 0.468 0.424
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.5243    0.29702 0.592 0.000 0.324 0.052 0.032 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.4772    0.43043 0.672 0.000 0.248 0.064 0.016 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.4088    0.42835 0.716 0.000 0.240 0.040 0.004 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1442    0.81523 0.000 0.944 0.004 0.040 0.012 0.000
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#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.4736    0.32224 0.624 0.000 0.312 0.060 0.004 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.3874    0.58437 0.780 0.016 0.020 0.172 0.012 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.6004   -0.03863 0.392 0.236 0.000 0.372 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.4139    0.42705 0.700 0.000 0.260 0.036 0.004 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.4601    0.60385 0.020 0.748 0.008 0.116 0.108 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1616    0.61847 0.932 0.000 0.048 0.020 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.5956   -0.00572 0.456 0.000 0.420 0.064 0.060 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0260    0.82776 0.000 0.992 0.000 0.008 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.5863   -0.11827 0.000 0.456 0.008 0.152 0.384 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.4138    0.46422 0.276 0.000 0.692 0.020 0.012 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.3935    0.63385 0.044 0.792 0.004 0.136 0.024 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.3254    0.60626 0.816 0.000 0.048 0.136 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.4886    0.00263 0.468 0.000 0.480 0.048 0.004 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     5  0.4656    0.39063 0.044 0.012 0.016 0.220 0.708 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.5523    0.12371 0.516 0.000 0.392 0.056 0.036 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.4107    0.48681 0.700 0.044 0.000 0.256 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.5035   -0.00409 0.472 0.000 0.468 0.052 0.008 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.5724    0.23138 0.160 0.648 0.008 0.140 0.044 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.4920    0.17167 0.544 0.000 0.396 0.056 0.004 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.4499    0.43095 0.652 0.060 0.000 0.288 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.4915    0.18955 0.000 0.000 0.620 0.032 0.032 0.316
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.4283    0.57211 0.072 0.000 0.796 0.020 0.040 0.072
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.4776    0.25020 0.588 0.000 0.356 0.052 0.004 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.3709    0.53653 0.756 0.040 0.000 0.204 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.3813    0.64467 0.044 0.804 0.004 0.124 0.024 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.5024    0.06571 0.440 0.000 0.500 0.052 0.008 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.4734    0.14120 0.000 0.000 0.604 0.032 0.016 0.348
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.4513    0.37955 0.676 0.000 0.264 0.052 0.008 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.4806    0.26574 0.592 0.000 0.348 0.056 0.004 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5407    0.28417 0.536 0.112 0.000 0.348 0.004 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.3727    0.52348 0.748 0.036 0.000 0.216 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.4599    0.47573 0.028 0.000 0.748 0.028 0.032 0.164
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.6670   -0.03027 0.436 0.000 0.360 0.096 0.108 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5375    0.32713 0.564 0.100 0.004 0.328 0.004 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.5025    0.31483 0.560 0.084 0.000 0.356 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.4456   -0.12543 0.000 0.000 0.520 0.020 0.004 0.456
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.4851    0.23348 0.576 0.000 0.364 0.056 0.004 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     5  0.5422    0.30054 0.028 0.088 0.016 0.200 0.668 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1682    0.60769 0.928 0.000 0.052 0.020 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.5467   -0.17722 0.152 0.544 0.000 0.304 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2278    0.62098 0.900 0.004 0.044 0.052 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.2176    0.61709 0.896 0.000 0.024 0.080 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1549    0.61555 0.936 0.000 0.044 0.020 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.3104    0.74360 0.000 0.844 0.004 0.084 0.068 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.6129   -0.05475 0.384 0.236 0.000 0.376 0.004 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6097    0.46251 0.640 0.028 0.076 0.172 0.084 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.5983   -0.31367 0.232 0.412 0.000 0.356 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5172    0.55816 0.104 0.000 0.708 0.020 0.024 0.144
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.8006   -0.27387 0.356 0.136 0.120 0.324 0.064 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.4879    0.29343 0.544 0.064 0.000 0.392 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.4486    0.35887 0.656 0.000 0.292 0.048 0.004 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.83017 0.000 1.000 0.000 0.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2629    0.62296 0.872 0.000 0.068 0.060 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.6755    0.43862 0.016 0.172 0.048 0.504 0.260 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3190    0.61002 0.844 0.008 0.044 0.100 0.004 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.0000    0.83624 0.000 0.000 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.5913    0.49386 0.656 0.028 0.096 0.164 0.056 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.6217   -0.14214 0.364 0.280 0.000 0.352 0.004 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5508    0.26033 0.520 0.108 0.000 0.364 0.008 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.1908    0.78418 0.000 0.000 0.096 0.004 0.000 0.900
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4092    0.53849 0.756 0.028 0.008 0.192 0.016 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.5021    0.16838 0.540 0.000 0.396 0.056 0.008 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.4804    0.41682 0.660 0.000 0.264 0.060 0.016 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.4882    0.54480 0.092 0.000 0.752 0.024 0.088 0.044
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.4383    0.50332 0.032 0.000 0.772 0.028 0.028 0.140
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.5211    0.25011 0.516 0.096 0.000 0.388 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.4734   -0.00621 0.000 0.000 0.548 0.028 0.012 0.412
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2340    0.79187 0.000 0.896 0.004 0.056 0.044 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     5  0.6475    0.04799 0.028 0.176 0.024 0.224 0.548 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.4605    0.56524 0.084 0.000 0.772 0.024 0.036 0.084
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4187    0.51654 0.724 0.028 0.008 0.232 0.008 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.4329    0.55912 0.148 0.000 0.768 0.016 0.048 0.020
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.5290    0.23652 0.504 0.104 0.000 0.392 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-hclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "kmeans"]
# you can also extract it by
# res = res_list["ATC:kmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.734           0.924       0.962         0.4667 0.526   0.526
#> 3 3 0.984           0.958       0.983         0.2779 0.627   0.424
#> 4 4 0.735           0.858       0.902         0.1988 0.768   0.484
#> 5 5 0.812           0.831       0.902         0.0691 0.947   0.812
#> 6 6 0.746           0.591       0.789         0.0471 0.984   0.936

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0000     0.9429 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000     0.9429 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     2  0.9393     0.4301 0.356 0.644
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     2  0.0000     0.9695 0.000 1.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     2  0.0000     0.9695 0.000 1.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     2  0.1843     0.9473 0.028 0.972
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.0000     0.9429 1.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0376     0.9684 0.004 0.996
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5946     0.8688 0.856 0.144
#> 53062969-D209-490B-9C9B-5D297625E2AE     2  0.6343     0.8072 0.160 0.840
#> B710293C-41D3-4A2E-8104-5402F91DD859     2  0.0000     0.9695 0.000 1.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     2  0.2043     0.9438 0.032 0.968
#> B055A70B-3003-47CB-BDAA-6378C000BF24     2  0.7674     0.7123 0.224 0.776
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0376     0.9684 0.004 0.996
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000     0.9429 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.5946     0.8688 0.856 0.144
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#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0376     0.9684 0.004 0.996
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1  0.0376     0.9430 0.996 0.004
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1  0.0376     0.9430 0.996 0.004
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1  0.1184     0.9397 0.984 0.016
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     2  0.8144     0.6639 0.252 0.748
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     2  0.6048     0.8224 0.148 0.852
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0376     0.9684 0.004 0.996
#> 344B9631-AAA5-4302-8747-D584345D9131     1  0.6148     0.8599 0.848 0.152
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     2  0.0000     0.9695 0.000 1.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     2  0.0000     0.9695 0.000 1.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     2  0.0000     0.9695 0.000 1.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1  0.0000     0.9429 1.000 0.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.5408     0.8838 0.876 0.124
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.0376     0.9430 0.996 0.004
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     2  0.0000     0.9695 0.000 1.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1  0.0376     0.9430 0.996 0.004
#> 331A9160-D730-45DD-A985-C6CAC03035ED     2  0.0000     0.9695 0.000 1.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.0000     0.9695 0.000 1.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.4939     0.8938 0.892 0.108
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     1  0.0000     0.9429 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0376     0.9684 0.004 0.996
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1  0.0000     0.9429 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.5946     0.8688 0.856 0.144
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     2  0.0000     0.9695 0.000 1.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1  0.0000     0.9429 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     2  0.0000     0.9695 0.000 1.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     1  0.0000     0.9429 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1  0.0000     0.9429 1.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.5629     0.8763 0.868 0.132
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     2  0.0000     0.9695 0.000 1.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     2  0.0000     0.9695 0.000 1.000
#> B2088466-FA5D-491C-9982-99B33683E66F     1  0.0000     0.9429 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1  0.0000     0.9429 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     1  0.0376     0.9426 0.996 0.004
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0376     0.9684 0.004 0.996
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0376     0.9684 0.004 0.996
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.5946     0.8688 0.856 0.144
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.0000     0.9429 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1  0.0376     0.9430 0.996 0.004
#> B55743F2-4D63-4375-85D3-F58281CFD852     2  0.0000     0.9695 0.000 1.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     2  0.0000     0.9695 0.000 1.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     2  0.0000     0.9695 0.000 1.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     2  0.0000     0.9695 0.000 1.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     2  0.0000     0.9695 0.000 1.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.5946     0.8688 0.856 0.144
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0376     0.9684 0.004 0.996
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     2  0.0000     0.9695 0.000 1.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.5946     0.8688 0.856 0.144
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1  0.0000     0.9429 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0376     0.9684 0.004 0.996
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0376     0.9684 0.004 0.996
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.1184     0.9397 0.984 0.016
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0376     0.9684 0.004 0.996
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000     0.9695 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     2  0.0000     0.9695 0.000 1.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.5629     0.8783 0.868 0.132
#> CE539000-92D7-4622-9C8D-BC6E01310681     1  0.6887     0.8146 0.816 0.184
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0376     0.9684 0.004 0.996
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     2  0.7139     0.7561 0.196 0.804
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     2  0.0000     0.9695 0.000 1.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0376     0.9430 0.996 0.004
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0376     0.9684 0.004 0.996
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.5842     0.8721 0.860 0.140
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0376     0.9684 0.004 0.996
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     2  0.0000     0.9695 0.000 1.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.0376     0.9430 0.996 0.004
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1  0.0376     0.9430 0.996 0.004
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.5519     0.8812 0.872 0.128
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     2  0.0000     0.9695 0.000 1.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0376     0.9684 0.004 0.996
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.5629     0.8783 0.868 0.132
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1  0.0376     0.9430 0.996 0.004
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.9988     0.1437 0.520 0.480
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.5946     0.8688 0.856 0.144
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     2  0.0000     0.9695 0.000 1.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     2  0.0000     0.9695 0.000 1.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.0376     0.9430 0.996 0.004
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5946     0.8688 0.856 0.144
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     2  0.0000     0.9695 0.000 1.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     2  0.0000     0.9695 0.000 1.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1  0.0000     0.9429 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.5946     0.8688 0.856 0.144
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0376     0.9684 0.004 0.996
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     2  0.6247     0.8121 0.156 0.844
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0000     0.9695 0.000 1.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     2  0.0000     0.9695 0.000 1.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     2  0.0000     0.9695 0.000 1.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     2  0.0000     0.9695 0.000 1.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0376     0.9684 0.004 0.996
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.0000     0.9695 0.000 1.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1  0.0000     0.9429 1.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0376     0.9684 0.004 0.996
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000     0.9695 0.000 1.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0376     0.9430 0.996 0.004
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.5059     0.8689 0.112 0.888
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     2  0.0000     0.9695 0.000 1.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.5946     0.8688 0.856 0.144
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0376     0.9684 0.004 0.996
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     2  0.5946     0.8274 0.144 0.856
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0376     0.9684 0.004 0.996
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     2  0.0000     0.9695 0.000 1.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.0000     0.9429 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     2  0.9358     0.4553 0.352 0.648
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0376     0.9684 0.004 0.996
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     2  0.0000     0.9695 0.000 1.000
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0000     0.9429 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.0000     0.9695 0.000 1.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.5946     0.8688 0.856 0.144
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     2  0.6247     0.8121 0.156 0.844
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.0000     0.9429 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0376     0.9430 0.996 0.004
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     2  0.0000     0.9695 0.000 1.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0376     0.9430 0.996 0.004
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0376     0.9684 0.004 0.996
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0376     0.9684 0.004 0.996
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000     0.9429 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     2  0.0000     0.9695 0.000 1.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0376     0.9430 0.996 0.004
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     2  0.0000     0.9695 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0000      0.965 0.000 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000      0.965 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.994 1.000 0.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.994 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.994 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.994 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2625      0.874 0.084 0.000 0.916
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.959 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.994 1.000 0.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.994 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.994 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.994 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.994 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.959 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0000      0.965 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.994 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.4654      0.718 0.208 0.000 0.792
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.994 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.4842      0.697 0.224 0.000 0.776
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000      0.994 1.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.959 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000      0.994 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.994 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.994 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.5291      0.641 0.268 0.000 0.732
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.0000      0.965 0.000 0.000 1.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000      0.994 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.994 1.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.959 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.959 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000      0.994 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000      0.994 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000      0.994 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.994 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.959 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000      0.994 1.000 0.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.994 1.000 0.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.0000      0.965 0.000 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.994 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.994 1.000 0.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.959 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000      0.994 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.994 1.000 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000      0.994 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.994 1.000 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.994 1.000 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000      0.994 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.959 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.994 1.000 0.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.959 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000      0.994 1.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.0000      0.965 0.000 0.000 1.000
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#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.994 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     3  0.0000      0.965 0.000 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000      0.965 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     3  0.4483      0.807 0.128 0.024 0.848
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.959 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.959 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000      0.994 1.000 0.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.5882      0.440 0.652 0.000 0.348
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     3  0.0000      0.965 0.000 0.000 1.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000      0.994 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000      0.994 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000      0.994 1.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0000      0.994 1.000 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     2  0.4887      0.695 0.228 0.772 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0000      0.994 1.000 0.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.959 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000      0.994 1.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.0000      0.994 1.000 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0000      0.965 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.959 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.959 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.0000      0.994 1.000 0.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.959 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.959 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000      0.994 1.000 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000      0.994 1.000 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000      0.959 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.959 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.0000      0.994 1.000 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.994 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000      0.994 1.000 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.959 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0000      0.994 1.000 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.959 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.994 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.0000      0.965 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0000      0.965 0.000 0.000 1.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000      0.994 1.000 0.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.994 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.959 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000      0.994 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.0000      0.965 0.000 0.000 1.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0000      0.994 1.000 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0000      0.994 1.000 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.994 1.000 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.994 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.0000      0.965 0.000 0.000 1.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.0000      0.994 1.000 0.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.994 1.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.994 1.000 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000      0.965 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000      0.994 1.000 0.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.959 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000      0.994 1.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0000      0.959 0.000 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.994 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000      0.994 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000      0.994 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.959 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.5216      0.653 0.260 0.740 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000      0.965 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000      0.994 1.000 0.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.959 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000      0.965 0.000 0.000 1.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000      0.994 1.000 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.994 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000      0.994 1.000 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.959 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000      0.994 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.959 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.994 1.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000      0.965 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0000      0.994 1.000 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.959 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4002      0.800 0.840 0.160 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.0000      0.965 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000      0.994 1.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000      0.994 1.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0000      0.994 1.000 0.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0000      0.965 0.000 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.0000      0.965 0.000 0.000 1.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.994 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.0000      0.965 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.959 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.959 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000      0.965 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.994 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.1860      0.910 0.052 0.000 0.948
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.994 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.2892     0.6963 0.000 0.036 0.896 0.068
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.1118     0.8200 0.036 0.000 0.964 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     3  0.4855     0.5365 0.400 0.000 0.600 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.1356     0.7640 0.000 0.008 0.960 0.032
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.2530     0.8708 0.112 0.000 0.888 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.3610     0.8333 0.200 0.000 0.800 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     3  0.4164     0.7633 0.264 0.000 0.736 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.3243     0.8505 0.088 0.000 0.876 0.036
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.3439     0.8361 0.084 0.000 0.868 0.048
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1182     0.8019 0.016 0.000 0.968 0.016
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.4994    -0.0397 0.000 0.000 0.520 0.480
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.5000    -0.2410 0.504 0.000 0.496 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.1211     0.9534 0.960 0.000 0.040 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0592     0.9387 0.984 0.000 0.016 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0336     0.9327 0.992 0.000 0.008 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0817     0.9484 0.000 0.976 0.024 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.1022     0.8166 0.032 0.000 0.968 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.2714     0.8629 0.000 0.004 0.112 0.884
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     3  0.2921     0.8793 0.140 0.000 0.860 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.1022     0.8166 0.032 0.000 0.968 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.1118     0.9542 0.036 0.964 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0707     0.9509 0.000 0.980 0.020 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.2469     0.8667 0.000 0.000 0.108 0.892
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     3  0.4331     0.7325 0.288 0.000 0.712 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.4103     0.6220 0.744 0.000 0.256 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0592     0.9387 0.984 0.000 0.016 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     3  0.6949    -0.1123 0.000 0.408 0.480 0.112
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.2976     0.7846 0.872 0.120 0.008 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     3  0.4830     0.5542 0.392 0.000 0.608 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0592     0.9505 0.000 0.984 0.016 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.3569     0.8368 0.196 0.000 0.804 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.2011     0.7293 0.000 0.000 0.920 0.080
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.2868     0.8809 0.136 0.000 0.864 0.000
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#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.1118     0.9542 0.036 0.964 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.1118     0.9542 0.036 0.964 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0895     0.8059 0.020 0.000 0.976 0.004
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.1716     0.9357 0.936 0.000 0.064 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.1389     0.9519 0.952 0.000 0.048 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.2921     0.8794 0.140 0.000 0.860 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.2888     0.7830 0.872 0.124 0.004 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0592     0.9505 0.000 0.984 0.016 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.3837     0.6815 0.776 0.000 0.224 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.2589     0.8723 0.116 0.000 0.884 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.4382     0.6584 0.000 0.704 0.296 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.1118     0.9542 0.036 0.964 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.2760     0.8782 0.128 0.000 0.872 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0817     0.9484 0.000 0.976 0.024 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     4  0.2281     0.8629 0.000 0.000 0.096 0.904
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     4  0.4941     0.3111 0.000 0.000 0.436 0.564
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.1118     0.9542 0.036 0.964 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     4  0.0817     0.9054 0.000 0.000 0.024 0.976
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.2921     0.8794 0.140 0.000 0.860 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0336     0.9327 0.992 0.000 0.008 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     4  0.3688     0.7486 0.000 0.000 0.208 0.792
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0336     0.9327 0.992 0.000 0.008 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2814     0.8651 0.000 0.868 0.132 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.2921     0.8794 0.140 0.000 0.860 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.3448     0.8167 0.168 0.828 0.004 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.2589     0.8705 0.884 0.000 0.116 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.2859     0.7963 0.880 0.112 0.008 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     3  0.4328     0.6635 0.244 0.008 0.748 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4998    -0.0881 0.000 0.000 0.512 0.488
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.1118     0.8200 0.036 0.000 0.964 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     3  0.4277     0.7433 0.280 0.000 0.720 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.3196     0.8666 0.008 0.856 0.136 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.1022     0.8166 0.032 0.000 0.968 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.1489     0.9531 0.044 0.952 0.004 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0336     0.9200 0.992 0.000 0.008 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1389     0.9531 0.952 0.000 0.048 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2868     0.8809 0.136 0.000 0.864 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.2081     0.8553 0.084 0.000 0.916 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.3569     0.8189 0.000 0.000 0.196 0.804
#> 835AAE7F-F873-4D11-8845-232D261A38DF     4  0.4992     0.1761 0.000 0.000 0.476 0.524
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0592     0.9387 0.984 0.000 0.016 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.0000     0.9162 0.000 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0707     0.9497 0.000 0.980 0.020 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2281     0.7142 0.000 0.000 0.904 0.096
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.1302     0.9553 0.956 0.000 0.044 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.1452     0.7839 0.008 0.000 0.956 0.036
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1302     0.9553 0.956 0.000 0.044 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2773     0.7684 0.000 0.000 0.164 0.836 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.0510     0.9283 0.000 0.000 0.000 0.016 0.984
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.2813     0.7266 0.000 0.000 0.832 0.168 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2358     0.9125 0.888 0.000 0.008 0.104 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1331     0.9280 0.952 0.000 0.008 0.040 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     3  0.4855     0.6510 0.168 0.000 0.720 0.112 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.3177     0.7314 0.000 0.000 0.208 0.792 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.1851     0.9251 0.000 0.912 0.000 0.088 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.3477     0.7708 0.056 0.000 0.832 0.112 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2522     0.9089 0.880 0.000 0.012 0.108 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     3  0.3849     0.7503 0.080 0.000 0.808 0.112 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.0510     0.9283 0.000 0.000 0.000 0.016 0.984
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0162     0.8422 0.000 0.000 0.996 0.004 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.1331     0.9285 0.952 0.000 0.008 0.040 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.1478     0.8101 0.000 0.000 0.936 0.064 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2020     0.9190 0.000 0.900 0.000 0.100 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.3427     0.8760 0.836 0.000 0.056 0.108 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2358     0.9126 0.888 0.000 0.008 0.104 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2522     0.9089 0.880 0.000 0.012 0.108 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1908     0.7872 0.000 0.000 0.908 0.092 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.5600     0.3270 0.000 0.000 0.588 0.096 0.316
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.5122     0.6127 0.200 0.000 0.688 0.112 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0290     0.8431 0.000 0.000 0.992 0.008 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.1410     0.9353 0.000 0.940 0.000 0.060 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0451     0.9270 0.988 0.000 0.008 0.004 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.0162     0.8432 0.000 0.000 0.996 0.004 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.2471     0.8920 0.000 0.864 0.000 0.136 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1408     0.9282 0.948 0.000 0.008 0.044 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.1270     0.8222 0.000 0.000 0.948 0.052 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.3274     0.6901 0.000 0.000 0.000 0.780 0.220
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     3  0.2574     0.8009 0.012 0.000 0.876 0.112 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.0162     0.8422 0.000 0.000 0.996 0.004 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9402 0.000 1.000 0.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0451     0.9288 0.988 0.000 0.008 0.004 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0609     0.8372 0.000 0.000 0.980 0.020 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0798     0.9296 0.976 0.000 0.008 0.016 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.1608     0.8282 0.000 0.000 0.928 0.072 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2522     0.9089 0.880 0.000 0.012 0.108 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0609     0.9411 0.000 0.980 0.000 0.020 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1478     0.9321 0.000 0.936 0.000 0.064 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2249     0.9155 0.896 0.000 0.008 0.096 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.3424     0.6750 0.000 0.000 0.000 0.760 0.240
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0880     0.8390 0.000 0.000 0.968 0.032 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.1557     0.9276 0.940 0.000 0.008 0.052 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     3  0.3670     0.7609 0.068 0.000 0.820 0.112 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.3055     0.8810 0.864 0.000 0.072 0.064 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0693     0.9245 0.980 0.000 0.008 0.012 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.2685     0.7914 0.000 0.028 0.092 0.880 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2522     0.9089 0.880 0.000 0.012 0.108 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.2358     0.9125 0.888 0.000 0.008 0.104 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0693     0.9159 0.980 0.008 0.000 0.012 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.3141     0.8899 0.852 0.000 0.040 0.108 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     3  0.4406     0.7014 0.128 0.000 0.764 0.108 0.000
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#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.0912     0.9104 0.972 0.016 0.000 0.012 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.0162     0.8422 0.000 0.000 0.996 0.004 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.3756     0.7160 0.008 0.744 0.000 0.248 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.0162     0.8432 0.000 0.000 0.996 0.004 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.2358     0.9125 0.888 0.000 0.008 0.104 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.1557     0.9272 0.940 0.000 0.008 0.052 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     4  0.4057     0.7687 0.000 0.000 0.120 0.792 0.088
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     4  0.4316     0.7535 0.000 0.000 0.108 0.772 0.120
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.4256     0.1692 0.000 0.000 0.564 0.436 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.2411     0.9108 0.884 0.000 0.008 0.108 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.1956     0.9228 0.916 0.000 0.008 0.076 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     4  0.2471     0.7834 0.000 0.000 0.136 0.864 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     4  0.2280     0.7891 0.000 0.000 0.120 0.880 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0609     0.9411 0.000 0.980 0.000 0.020 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0510     0.9411 0.000 0.984 0.000 0.016 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0162     0.8422 0.000 0.000 0.996 0.004 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.4088     0.3740 0.000 0.000 0.632 0.368 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.0510     0.9283 0.000 0.000 0.000 0.016 0.984
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.5250     0.6429 0.668 0.000 0.224 0.108 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.5076     0.6807 0.692 0.000 0.200 0.108 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1768     0.8261 0.004 0.000 0.924 0.072 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0693     0.9245 0.980 0.000 0.008 0.012 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.1106     0.9074 0.964 0.024 0.000 0.012 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     3  0.1478     0.8301 0.000 0.000 0.936 0.064 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.1410     0.9354 0.000 0.940 0.000 0.060 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5578     0.5441 0.616 0.000 0.272 0.112 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.3210     0.8082 0.000 0.788 0.000 0.212 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.0609     0.8365 0.000 0.000 0.980 0.020 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0566     0.9395 0.012 0.984 0.000 0.004 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.3558     0.8685 0.828 0.000 0.064 0.108 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.0703     0.8408 0.000 0.000 0.976 0.024 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     4  0.3043     0.7846 0.000 0.056 0.080 0.864 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0609     0.9411 0.000 0.980 0.000 0.020 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0290     0.8423 0.000 0.000 0.992 0.008 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.1331     0.9278 0.952 0.000 0.008 0.040 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.2843     0.8864 0.008 0.848 0.000 0.144 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.1331     0.9280 0.952 0.000 0.008 0.040 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.3702     0.7659 0.000 0.000 0.096 0.084 0.820
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.5696     0.2576 0.000 0.000 0.560 0.096 0.344
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0609     0.9411 0.000 0.980 0.000 0.020 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.2351     0.8652 0.000 0.000 0.016 0.088 0.896
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.2011     0.8189 0.004 0.000 0.908 0.088 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000     0.8429 0.000 0.000 1.000 0.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.2411     0.9108 0.884 0.000 0.008 0.108 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.5433     0.4194 0.000 0.000 0.288 0.092 0.620
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.0162     0.8429 0.000 0.000 0.996 0.004 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0898     0.9297 0.972 0.000 0.008 0.020 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0579     0.9260 0.984 0.000 0.008 0.008 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.0510     0.9283 0.000 0.000 0.000 0.016 0.984
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.0404     0.8429 0.000 0.000 0.988 0.012 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     4  0.3242     0.6425 0.000 0.216 0.000 0.784 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     3  0.2574     0.8009 0.012 0.000 0.876 0.112 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.3318     0.7126 0.180 0.808 0.000 0.012 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2522     0.9096 0.880 0.000 0.012 0.108 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.3912     0.8424 0.804 0.000 0.088 0.108 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     3  0.5535     0.5054 0.272 0.000 0.620 0.108 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2074     0.9166 0.000 0.896 0.000 0.104 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0807     0.9133 0.976 0.012 0.000 0.012 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.5312     0.5517 0.248 0.000 0.100 0.652 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.2248     0.8511 0.088 0.900 0.000 0.012 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5584     0.3350 0.000 0.000 0.592 0.096 0.312
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.2424     0.7581 0.000 0.000 0.868 0.132 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1331     0.9280 0.952 0.000 0.008 0.040 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.1410     0.8315 0.000 0.000 0.940 0.060 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0290     0.9397 0.008 0.992 0.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     3  0.4016     0.7390 0.092 0.000 0.796 0.112 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.3424     0.6342 0.000 0.240 0.000 0.760 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.2361     0.9139 0.892 0.000 0.012 0.096 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.3966     0.4529 0.000 0.000 0.664 0.336 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.1408     0.9081 0.044 0.948 0.000 0.008 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0404     0.9200 0.988 0.000 0.000 0.012 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.0000     0.9288 0.000 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.1764     0.9257 0.928 0.000 0.008 0.064 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0162     0.8429 0.000 0.000 0.996 0.004 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0794     0.8345 0.000 0.000 0.972 0.028 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.6041     0.3629 0.000 0.000 0.128 0.516 0.356
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5616     0.2220 0.000 0.000 0.552 0.084 0.364
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0579     0.9279 0.984 0.000 0.008 0.008 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.0510     0.9283 0.000 0.000 0.000 0.016 0.984
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2074     0.9166 0.000 0.896 0.000 0.104 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.3210     0.8082 0.000 0.788 0.000 0.212 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3262     0.7279 0.000 0.000 0.840 0.124 0.036
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0579     0.9283 0.984 0.000 0.008 0.008 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.2074     0.7774 0.000 0.000 0.896 0.104 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0451     0.9270 0.988 0.000 0.008 0.004 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1003    0.84630 0.000 0.000 0.016 0.964 0.020 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     6  0.2312    0.84095 0.000 0.000 0.000 0.012 0.112 0.876
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.3962    0.63547 0.000 0.000 0.764 0.116 0.120 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3659    0.46319 0.636 0.000 0.000 0.000 0.364 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3448    0.55491 0.716 0.000 0.000 0.004 0.280 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     3  0.5479   -0.57284 0.108 0.000 0.472 0.004 0.416 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.2325    0.81719 0.000 0.000 0.048 0.892 0.060 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.2954    0.82985 0.000 0.844 0.000 0.048 0.108 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.1007    0.69909 0.000 0.000 0.956 0.000 0.044 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.4410   -0.24585 0.028 0.000 0.560 0.000 0.412 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3737    0.41316 0.608 0.000 0.000 0.000 0.392 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     3  0.4829   -0.39854 0.056 0.000 0.520 0.000 0.424 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1327    0.69549 0.000 0.000 0.936 0.000 0.064 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.1910    0.84725 0.000 0.892 0.000 0.000 0.108 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.2218    0.84216 0.000 0.000 0.000 0.012 0.104 0.884
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1075    0.69840 0.000 0.000 0.952 0.000 0.048 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.2320    0.67475 0.000 0.000 0.864 0.004 0.132 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2178    0.67011 0.868 0.000 0.000 0.000 0.132 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.4271    0.57893 0.000 0.000 0.696 0.060 0.244 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0291    0.69358 0.992 0.000 0.000 0.004 0.004 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.3196    0.82206 0.000 0.828 0.000 0.064 0.108 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.5587   -0.18443 0.476 0.000 0.124 0.004 0.396 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3717    0.43076 0.616 0.000 0.000 0.000 0.384 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4494    0.26139 0.544 0.000 0.032 0.000 0.424 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3481    0.64989 0.000 0.000 0.792 0.048 0.160 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.6589    0.32431 0.000 0.000 0.528 0.104 0.236 0.132
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.5478   -0.57108 0.124 0.000 0.452 0.000 0.424 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0547    0.70119 0.000 0.000 0.980 0.000 0.020 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.2558    0.83953 0.000 0.868 0.000 0.028 0.104 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.1910    0.84725 0.000 0.892 0.000 0.000 0.108 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0260    0.69040 0.992 0.000 0.000 0.000 0.008 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0632    0.69313 0.976 0.000 0.000 0.000 0.024 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1075    0.69357 0.952 0.000 0.000 0.000 0.048 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.1267    0.69799 0.000 0.000 0.940 0.000 0.060 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4277    0.74569 0.000 0.732 0.000 0.144 0.124 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2562    0.66030 0.828 0.000 0.000 0.000 0.172 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.2954    0.68328 0.000 0.000 0.844 0.048 0.108 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.1049    0.84749 0.000 0.000 0.000 0.960 0.008 0.032
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     3  0.4018   -0.17567 0.008 0.000 0.580 0.000 0.412 0.000
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#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.0000    0.84058 0.000 0.000 0.000 0.000 0.000 1.000
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#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.1967    0.69492 0.000 0.000 0.904 0.012 0.084 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.7482    0.11183 0.000 0.000 0.240 0.372 0.228 0.160
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#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.3252    0.81988 0.000 0.824 0.000 0.068 0.108 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.4587    0.68580 0.000 0.688 0.000 0.204 0.108 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.4592    0.54449 0.000 0.000 0.664 0.080 0.256 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0865    0.69675 0.964 0.000 0.000 0.000 0.036 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.4769    0.53183 0.000 0.000 0.656 0.104 0.240 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1007    0.69430 0.956 0.000 0.000 0.000 0.044 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-kmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-kmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:skmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "skmeans"]
# you can also extract it by
# res = res_list["ATC:skmeans"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 4.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.988       0.995         0.5011 0.499   0.499
#> 3 3 0.968           0.929       0.973         0.3233 0.741   0.527
#> 4 4 0.963           0.938       0.974         0.1280 0.809   0.511
#> 5 5 0.892           0.877       0.930         0.0656 0.892   0.615
#> 6 6 0.827           0.805       0.880         0.0351 0.952   0.772

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3

There is also optional best \(k\) = 2 3 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.0000      0.993 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000      0.993 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0000      0.993 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     2  0.0000      0.997 0.000 1.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     2  0.0000      0.997 0.000 1.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.7219      0.749 0.800 0.200
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     1  0.0000      0.993 1.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.997 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.993 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000      0.993 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     2  0.0000      0.997 0.000 1.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.993 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.993 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000      0.997 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0000      0.993 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.993 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000      0.993 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     2  0.0000      0.997 0.000 1.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000      0.993 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     2  0.0000      0.997 0.000 1.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000      0.997 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     2  0.0000      0.997 0.000 1.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     2  0.0000      0.997 0.000 1.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     2  0.0000      0.997 0.000 1.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000      0.993 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000      0.993 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     2  0.0000      0.997 0.000 1.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000      0.993 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000      0.997 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000      0.997 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     2  0.0000      0.997 0.000 1.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     2  0.0000      0.997 0.000 1.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     2  0.0000      0.997 0.000 1.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000      0.993 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000      0.997 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.0000      0.997 0.000 1.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.0000      0.993 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     1  0.0000      0.993 1.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000      0.993 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000      0.993 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000      0.997 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     2  0.0000      0.997 0.000 1.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.0000      0.993 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     2  0.0000      0.997 0.000 1.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000      0.993 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000      0.993 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     2  0.0000      0.997 0.000 1.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000      0.997 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000      0.993 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000      0.997 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     2  0.0000      0.997 0.000 1.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     1  0.0000      0.993 1.000 0.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000      0.993 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     2  0.0000      0.997 0.000 1.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000      0.993 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     2  0.0000      0.997 0.000 1.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.0000      0.993 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     2  0.0000      0.997 0.000 1.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     1  0.0000      0.993 1.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     2  0.0000      0.997 0.000 1.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     2  0.0000      0.997 0.000 1.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.0000      0.997 0.000 1.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     2  0.0000      0.997 0.000 1.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000      0.993 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000      0.997 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1  0.0000      0.993 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     2  0.0000      0.997 0.000 1.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000      0.993 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000      0.993 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000      0.997 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000      0.993 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000      0.993 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000      0.993 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     2  0.8763      0.577 0.296 0.704
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     2  0.0000      0.997 0.000 1.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000      0.993 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     2  0.0000      0.997 0.000 1.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000      0.997 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.0000      0.993 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     1  0.0000      0.993 1.000 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000      0.993 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1  0.0000      0.993 1.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000      0.993 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000      0.993 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000      0.993 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     2  0.0000      0.997 0.000 1.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     2  0.0000      0.997 0.000 1.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000      0.997 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     1  0.0000      0.993 1.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.993 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     2  0.0672      0.989 0.008 0.992
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000      0.993 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000      0.997 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000      0.993 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     2  0.0000      0.997 0.000 1.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     2  0.0000      0.997 0.000 1.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.0000      0.997 0.000 1.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     2  0.0000      0.997 0.000 1.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     2  0.0000      0.997 0.000 1.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.1184      0.977 0.984 0.016
#> 00439565-02CE-4BF5-956D-7078B51C0947     1  0.0000      0.993 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000      0.997 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000      0.997 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     2  0.0000      0.997 0.000 1.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0000      0.993 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000      0.997 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000      0.997 0.000 1.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0000      0.993 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     2  0.0000      0.997 0.000 1.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000      0.997 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000      0.997 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.0000      0.997 0.000 1.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1  0.0000      0.993 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1  0.0000      0.993 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     2  0.0000      0.997 0.000 1.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0000      0.993 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.0000      0.993 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     2  0.0000      0.997 0.000 1.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     2  0.0000      0.997 0.000 1.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     2  0.0000      0.997 0.000 1.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.0000      0.993 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.0000      0.993 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000      0.993 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     2  0.0000      0.997 0.000 1.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.0000      0.997 0.000 1.000
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#> 4938E366-C740-4C9C-9358-FF37997DC9EF     2  0.0000      0.997 0.000 1.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000      0.993 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     2  0.0000      0.997 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0000   0.960315 0.000 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000   0.960315 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0424   0.953183 0.000 0.008 0.992
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000   0.976032 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000   0.976032 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000   0.976032 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.0000   0.960315 0.000 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000   0.978877 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.0000   0.960315 0.000 0.000 1.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000   0.976032 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000   0.976032 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000   0.976032 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.5968   0.450511 0.364 0.000 0.636
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000   0.978877 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0000   0.960315 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000   0.960315 0.000 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000   0.960315 0.000 0.000 1.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000   0.976032 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.0000   0.960315 0.000 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000   0.976032 1.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000   0.978877 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000   0.976032 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000   0.976032 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000   0.976032 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000   0.960315 0.000 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.0000   0.960315 0.000 0.000 1.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000   0.976032 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0000   0.960315 0.000 0.000 1.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000   0.978877 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000   0.978877 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000   0.976032 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000   0.976032 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000   0.976032 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.4555   0.740389 0.200 0.000 0.800
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000   0.978877 0.000 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     2  0.6062   0.385929 0.384 0.616 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.0000   0.960315 0.000 0.000 1.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.0000   0.960315 0.000 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000   0.976032 1.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.0000   0.960315 0.000 0.000 1.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000   0.978877 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000   0.976032 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0000   0.960315 0.000 0.000 1.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000   0.976032 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.4452   0.739198 0.808 0.000 0.192
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.0000   0.960315 0.000 0.000 1.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000   0.976032 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000   0.978877 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.0000   0.960315 0.000 0.000 1.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000   0.978877 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000   0.976032 1.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.0000   0.960315 0.000 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.6126   0.363475 0.400 0.000 0.600
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000   0.976032 1.000 0.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000   0.976032 1.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     2  0.0000   0.978877 0.000 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000   0.960315 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000   0.976032 1.000 0.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.6309  -0.010731 0.000 0.504 0.496
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000   0.976032 1.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000   0.976032 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.0000   0.978877 0.000 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000   0.976032 1.000 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000   0.976032 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000   0.978877 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000   0.960315 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000   0.976032 1.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000   0.976032 1.000 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000   0.960315 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000   0.978877 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.0000   0.960315 0.000 0.000 1.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.0000   0.960315 0.000 0.000 1.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0000   0.960315 0.000 0.000 1.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000   0.976032 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000   0.976032 1.000 0.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.6274   0.108033 0.544 0.000 0.456
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000   0.976032 1.000 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000   0.978877 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000   0.960315 0.000 0.000 1.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     3  0.0000   0.960315 0.000 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.1289   0.943519 0.968 0.000 0.032
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0000   0.960315 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.0000   0.960315 0.000 0.000 1.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000   0.976032 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000   0.976032 1.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000   0.976032 1.000 0.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000   0.976032 1.000 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000   0.978877 0.000 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     3  0.0000   0.960315 0.000 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0000   0.960315 0.000 0.000 1.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000   0.976032 1.000 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000   0.976032 1.000 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000   0.978877 0.000 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.6154   0.342590 0.408 0.000 0.592
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000   0.976032 1.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000   0.976032 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     2  0.0592   0.969338 0.012 0.988 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     2  0.2625   0.902443 0.084 0.916 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000   0.976032 1.000 0.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000   0.976032 1.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.0000   0.960315 0.000 0.000 1.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000   0.978877 0.000 1.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000   0.978877 0.000 1.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000   0.976032 1.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     3  0.6302   0.114236 0.480 0.000 0.520
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000   0.978877 0.000 1.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.0000   0.978877 0.000 1.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000   0.960315 0.000 0.000 1.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0000   0.976032 1.000 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0000   0.978877 0.000 1.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000   0.978877 0.000 1.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     2  0.1860   0.934867 0.052 0.948 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000   0.960315 0.000 0.000 1.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.0000   0.960315 0.000 0.000 1.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0000   0.976032 1.000 0.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     3  0.0000   0.960315 0.000 0.000 1.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     3  0.0000   0.960315 0.000 0.000 1.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     2  0.2066   0.927407 0.060 0.940 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000   0.976032 1.000 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0000   0.976032 1.000 0.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     3  0.0000   0.960315 0.000 0.000 1.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     3  0.0000   0.960315 0.000 0.000 1.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     3  0.3412   0.837184 0.124 0.000 0.876
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000   0.976032 1.000 0.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.0000   0.978877 0.000 1.000 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.0000   0.978877 0.000 1.000 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.4346   0.761170 0.000 0.816 0.184
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000   0.976032 1.000 0.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.0000   0.960315 0.000 0.000 1.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     3  0.0000   0.960315 0.000 0.000 1.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     2  0.4121   0.795942 0.168 0.832 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0000   0.976032 1.000 0.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     3  0.0000   0.960315 0.000 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     3  0.0000   0.960315 0.000 0.000 1.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.0000   0.978877 0.000 1.000 0.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0000   0.978877 0.000 1.000 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.0000   0.976032 1.000 0.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0000   0.978877 0.000 1.000 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.0000   0.978877 0.000 1.000 0.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1  0.0000   0.976032 1.000 0.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     3  0.0000   0.960315 0.000 0.000 1.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2  0.0000   0.978877 0.000 1.000 0.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     3  0.0000   0.960315 0.000 0.000 1.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2  0.0000   0.978877 0.000 1.000 0.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2  0.0000   0.978877 0.000 1.000 0.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     3  0.0000   0.960315 0.000 0.000 1.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     3  0.0000   0.960315 0.000 0.000 1.000
#> B04E2E50-0A6E-4224-A825-1714D12E5669     3  0.0000   0.960315 0.000 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     3  0.0000   0.960315 0.000 0.000 1.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     3  0.0000   0.960315 0.000 0.000 1.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     3  0.5988   0.441491 0.368 0.000 0.632
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1  0.0000   0.976032 1.000 0.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2  0.0000   0.978877 0.000 1.000 0.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1  0.0000   0.976032 1.000 0.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     2  0.0000   0.978877 0.000 1.000 0.000
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     3  0.0000   0.960315 0.000 0.000 1.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1  0.0000   0.976032 1.000 0.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1  0.0000   0.976032 1.000 0.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     3  0.0000   0.960315 0.000 0.000 1.000
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2  0.0000   0.978877 0.000 1.000 0.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1  0.0000   0.976032 1.000 0.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     3  0.0000   0.960315 0.000 0.000 1.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2  0.0000   0.978877 0.000 1.000 0.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1  0.0000   0.976032 1.000 0.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2  0.0000   0.978877 0.000 1.000 0.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2  0.0000   0.978877 0.000 1.000 0.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     2  0.0000   0.978877 0.000 1.000 0.000
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2  0.0000   0.978877 0.000 1.000 0.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1  0.5882   0.433176 0.652 0.348 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2  0.0000   0.978877 0.000 1.000 0.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1  0.0000   0.976032 1.000 0.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1  0.0000   0.976032 1.000 0.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     2  0.1964   0.931244 0.056 0.944 0.000
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000   0.976032 1.000 0.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1  0.6305   0.000576 0.516 0.000 0.484
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     3  0.0000   0.960315 0.000 0.000 1.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1  0.0000   0.976032 1.000 0.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.0000   0.976032 1.000 0.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     3  0.0000   0.960315 0.000 0.000 1.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000   0.978877 0.000 1.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000   0.978877 0.000 1.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     2  0.1860   0.935079 0.052 0.948 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     3  0.0000   0.960315 0.000 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000   0.976032 1.000 0.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.0000   0.976032 1.000 0.000 0.000
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#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     3  0.0000   0.960315 0.000 0.000 1.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000   0.978877 0.000 1.000 0.000
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#> BE38240A-F7C2-439F-9AAE-51C8A340F310     3  0.0000   0.960315 0.000 0.000 1.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     3  0.0000   0.960315 0.000 0.000 1.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     3  0.0000   0.960315 0.000 0.000 1.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     3  0.0000   0.960315 0.000 0.000 1.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0000   0.976032 1.000 0.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000   0.978877 0.000 1.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.0000   0.960315 0.000 0.000 1.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000   0.976032 1.000 0.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     2  0.0000   0.978877 0.000 1.000 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000   0.976032 1.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.0000   0.960315 0.000 0.000 1.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     3  0.0000   0.960315 0.000 0.000 1.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     3  0.0000   0.960315 0.000 0.000 1.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000   0.976032 1.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     3  0.0000   0.960315 0.000 0.000 1.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000   0.976032 1.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.0000   0.978877 0.000 1.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     3  0.0000   0.960315 0.000 0.000 1.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     3  0.0000   0.960315 0.000 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000   0.978877 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0000   0.960315 0.000 0.000 1.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     3  0.5650   0.557734 0.312 0.000 0.688
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000   0.976032 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     3  0.0000   0.960315 0.000 0.000 1.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000   0.976032 1.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.0000   0.960315 0.000 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0000   0.960315 0.000 0.000 1.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000   0.960315 0.000 0.000 1.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000   0.976032 1.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000   0.976032 1.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     3  0.0000   0.960315 0.000 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000   0.960315 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     3  0.1753   0.915324 0.000 0.048 0.952
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000   0.978877 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000   0.978877 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.0000   0.960315 0.000 0.000 1.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000   0.960315 0.000 0.000 1.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     3  0.0000   0.960315 0.000 0.000 1.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0000   0.976032 1.000 0.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0000   0.976032 1.000 0.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.0000   0.976032 1.000 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.5968   0.423406 0.636 0.364 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     2  0.3752   0.831010 0.144 0.856 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     3  0.6307   0.091361 0.488 0.000 0.512
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000   0.978877 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000   0.976032 1.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0000   0.960315 0.000 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0000   0.960315 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000   0.978877 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000   0.978877 0.000 1.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.0000   0.960315 0.000 0.000 1.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000   0.978877 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000   0.978877 0.000 1.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000   0.976032 1.000 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.5926   0.468292 0.356 0.000 0.644
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0000   0.978877 0.000 1.000 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000   0.978877 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0000   0.960315 0.000 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000   0.976032 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.0000   0.960315 0.000 0.000 1.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000   0.978877 0.000 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     3  0.0000   0.960315 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000   0.978877 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000   0.976032 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.0000   0.960315 0.000 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0000   0.960315 0.000 0.000 1.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.0000   0.960315 0.000 0.000 1.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000   0.976032 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000   0.978877 0.000 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.0000   0.960315 0.000 0.000 1.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.0000   0.960315 0.000 0.000 1.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.6079   0.345046 0.612 0.000 0.388
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.0000   0.960315 0.000 0.000 1.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0747   0.960431 0.984 0.016 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000   0.976032 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.0000   0.960315 0.000 0.000 1.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.0000   0.960315 0.000 0.000 1.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000   0.976032 1.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000   0.976032 1.000 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000   0.960315 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.0000   0.960315 0.000 0.000 1.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000   0.978877 0.000 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0000   0.976032 1.000 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     2  0.0000   0.978877 0.000 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000   0.976032 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000   0.976032 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000   0.976032 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000   0.978877 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     2  0.0000   0.978877 0.000 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000   0.960315 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000   0.978877 0.000 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000   0.978877 0.000 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000   0.960315 0.000 0.000 1.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.6111   0.343244 0.000 0.396 0.604
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000   0.976032 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.6274   0.201437 0.456 0.000 0.544
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000   0.978877 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000   0.976032 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000   0.978877 0.000 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000   0.976032 1.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000   0.960315 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0892   0.942752 0.000 0.020 0.980
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000   0.978877 0.000 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     2  0.1753   0.938529 0.048 0.952 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.0000   0.960315 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.0000   0.978877 0.000 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0000   0.960315 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0000   0.960315 0.000 0.000 1.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0000   0.960315 0.000 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.0000   0.960315 0.000 0.000 1.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000   0.976032 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.0000   0.960315 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000   0.978877 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000   0.978877 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000   0.960315 0.000 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000   0.976032 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.0000   0.960315 0.000 0.000 1.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000   0.976032 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4941      0.227 0.564 0.000 0.000 0.436
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.3172      0.807 0.000 0.000 0.160 0.840
#> 53062969-D209-490B-9C9B-5D297625E2AE     4  0.3444      0.772 0.184 0.000 0.000 0.816
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.2921      0.831 0.140 0.000 0.000 0.860
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#> C1411CDA-814D-4E21-8929-C0F77858828F     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     4  0.4134      0.648 0.000 0.000 0.260 0.740
#> 627BC251-D217-4955-B718-6B9D6DEA1756     4  0.0188      0.972 0.004 0.000 0.000 0.996
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1  0.4072      0.668 0.748 0.000 0.000 0.252
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1  0.1557      0.903 0.944 0.000 0.000 0.056
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     3  0.0921      0.966 0.000 0.000 0.972 0.028
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     4  0.0188      0.972 0.004 0.000 0.000 0.996
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.4134      0.650 0.740 0.260 0.000 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     4  0.2149      0.894 0.000 0.000 0.088 0.912
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     2  0.0188      0.974 0.004 0.996 0.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     3  0.2408      0.881 0.000 0.104 0.896 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0469      0.940 0.988 0.000 0.000 0.012
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.0921      0.928 0.972 0.000 0.000 0.028
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     4  0.0188      0.972 0.004 0.000 0.000 0.996
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.4585      0.494 0.000 0.000 0.668 0.332
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.4761      0.440 0.628 0.000 0.000 0.372
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0188      0.974 0.000 0.996 0.004 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.4898      0.310 0.584 0.416 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4250      0.629 0.724 0.000 0.000 0.276
#> EFE5A302-D138-4044-A301-5C5FD1C24836     4  0.0188      0.972 0.004 0.000 0.000 0.996
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3726      0.725 0.788 0.212 0.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.4977      0.151 0.000 0.540 0.460 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     4  0.0188      0.972 0.004 0.000 0.000 0.996
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     2  0.4250      0.602 0.276 0.724 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     4  0.0000      0.975 0.000 0.000 0.000 1.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.1716      0.928 0.000 0.000 0.936 0.064
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000      0.978 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.948 1.000 0.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.0000      0.993 0.000 0.000 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000      0.948 1.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.1341     0.9425 0.056 0.000 0.000 0.000 0.944
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.0000     0.9628 0.000 0.000 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.1502     0.9409 0.056 0.000 0.004 0.000 0.940
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4161     0.5458 0.608 0.000 0.000 0.392 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3684     0.7299 0.720 0.000 0.000 0.280 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2074     0.8429 0.920 0.000 0.036 0.044 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     5  0.1341     0.9425 0.056 0.000 0.000 0.000 0.944
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9928 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.1197     0.8805 0.000 0.000 0.952 0.000 0.048
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1628     0.8231 0.936 0.000 0.056 0.008 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2929     0.8282 0.820 0.000 0.000 0.180 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1628     0.8231 0.936 0.000 0.056 0.008 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0000     0.9010 0.000 0.000 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0162     0.9918 0.000 0.996 0.000 0.004 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.0000     0.9628 0.000 0.000 0.000 0.000 1.000
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#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     5  0.2516     0.8338 0.000 0.000 0.140 0.000 0.860
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.0290     0.9305 0.008 0.000 0.000 0.992 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     5  0.0000     0.9628 0.000 0.000 0.000 0.000 1.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     4  0.2020     0.8403 0.100 0.000 0.000 0.900 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     4  0.3122     0.8314 0.000 0.000 0.020 0.804 0.000 0.176
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.4039     0.3352 0.568 0.000 0.000 0.008 0.424 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.3883     0.5460 0.656 0.000 0.000 0.012 0.332 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2545     0.7846 0.892 0.000 0.028 0.052 0.028 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.2854     0.8540 0.000 0.000 0.000 0.792 0.000 0.208
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.2979     0.7840 0.004 0.000 0.852 0.056 0.000 0.088
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2679     0.7290 0.864 0.000 0.040 0.096 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2300     0.7783 0.856 0.000 0.000 0.000 0.144 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2122     0.7537 0.900 0.000 0.024 0.076 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.1349     0.8025 0.000 0.000 0.940 0.056 0.000 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0291     0.9789 0.000 0.992 0.000 0.004 0.004 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1141     0.8047 0.000 0.000 0.948 0.052 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1285     0.8067 0.000 0.000 0.944 0.004 0.000 0.052
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     5  0.0458     0.8822 0.016 0.000 0.000 0.000 0.984 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     6  0.2609     0.8286 0.000 0.000 0.036 0.096 0.000 0.868
#> C204D355-B876-4341-A111-36D48CBDD2A8     5  0.1196     0.8785 0.040 0.000 0.000 0.008 0.952 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0972     0.8039 0.964 0.000 0.000 0.008 0.028 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2750     0.7908 0.844 0.000 0.000 0.020 0.136 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2234     0.7900 0.872 0.000 0.000 0.004 0.124 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.3523     0.6662 0.000 0.000 0.780 0.040 0.000 0.180
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     6  0.0777     0.9133 0.000 0.000 0.004 0.024 0.000 0.972
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4895     0.4844 0.316 0.000 0.616 0.056 0.012 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0622     0.8159 0.012 0.000 0.980 0.008 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0291     0.9789 0.000 0.992 0.000 0.004 0.004 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.0692     0.8818 0.020 0.000 0.000 0.004 0.976 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     5  0.1462     0.8744 0.056 0.000 0.000 0.008 0.936 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     5  0.2743     0.7842 0.164 0.000 0.000 0.008 0.828 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.3425     0.7968 0.084 0.000 0.836 0.048 0.000 0.032
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     5  0.0436     0.8825 0.004 0.004 0.000 0.004 0.988 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.3163     0.8171 0.000 0.000 0.004 0.764 0.000 0.232
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2404     0.7394 0.884 0.000 0.036 0.080 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     6  0.4124     0.6900 0.000 0.000 0.120 0.132 0.000 0.748
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     5  0.1918     0.8598 0.088 0.000 0.000 0.008 0.904 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.3383     0.5916 0.000 0.000 0.728 0.268 0.000 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     5  0.2558     0.8042 0.156 0.000 0.000 0.004 0.840 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.1010     0.8095 0.004 0.000 0.960 0.036 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.3821     0.7783 0.024 0.000 0.804 0.100 0.000 0.072
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.3259     0.7165 0.772 0.000 0.000 0.012 0.216 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1914     0.8149 0.016 0.000 0.920 0.056 0.000 0.008
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2416     0.7709 0.844 0.000 0.000 0.000 0.156 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1049     0.8115 0.008 0.000 0.960 0.032 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     5  0.0291     0.8816 0.004 0.000 0.000 0.004 0.992 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2039     0.7547 0.904 0.000 0.020 0.076 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     5  0.3683     0.7079 0.000 0.004 0.160 0.052 0.784 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.0692     0.8820 0.020 0.000 0.000 0.004 0.976 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.3190     0.8558 0.000 0.008 0.000 0.772 0.000 0.220
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0790     0.8038 0.968 0.000 0.000 0.000 0.032 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.4229     0.2881 0.548 0.000 0.000 0.016 0.436 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     5  0.1349     0.8460 0.000 0.056 0.000 0.004 0.940 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     5  0.5328     0.2471 0.368 0.000 0.072 0.016 0.544 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1838     0.7622 0.916 0.000 0.016 0.068 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2416     0.7709 0.844 0.000 0.000 0.000 0.156 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.5086     0.4780 0.364 0.000 0.548 0.088 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0405     0.9767 0.000 0.988 0.000 0.004 0.008 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     6  0.1124     0.9032 0.000 0.000 0.008 0.036 0.000 0.956
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     6  0.2563     0.8382 0.000 0.000 0.052 0.072 0.000 0.876
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0692     0.8121 0.004 0.000 0.976 0.020 0.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.2039     0.7670 0.908 0.000 0.016 0.072 0.004 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.2003     0.8016 0.912 0.000 0.000 0.044 0.044 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     3  0.5792     0.6182 0.240 0.000 0.580 0.156 0.000 0.024
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.4224     0.5617 0.660 0.000 0.016 0.012 0.312 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.5103    -0.0286 0.532 0.000 0.392 0.072 0.000 0.004
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     6  0.0260     0.9233 0.000 0.000 0.000 0.008 0.000 0.992
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.1895     0.7600 0.912 0.000 0.016 0.072 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2006     0.7556 0.904 0.000 0.016 0.080 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     5  0.1398     0.8756 0.052 0.000 0.000 0.008 0.940 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     5  0.2389     0.8307 0.128 0.000 0.000 0.008 0.864 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0291     0.9789 0.000 0.992 0.000 0.004 0.004 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     6  0.5070     0.3616 0.000 0.000 0.316 0.100 0.000 0.584
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3370     0.7768 0.828 0.000 0.008 0.092 0.072 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4595     0.6633 0.248 0.000 0.668 0.084 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.1075     0.8059 0.000 0.000 0.952 0.048 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.0146     0.8820 0.004 0.000 0.000 0.000 0.996 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     5  0.3445     0.6434 0.260 0.000 0.000 0.008 0.732 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     5  0.0603     0.8742 0.000 0.016 0.000 0.004 0.980 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     5  0.0260     0.8805 0.000 0.000 0.000 0.008 0.992 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     5  0.2346     0.8356 0.124 0.000 0.000 0.008 0.868 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.1204     0.8034 0.000 0.000 0.944 0.056 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.3945     0.4367 0.612 0.000 0.000 0.008 0.380 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     3  0.2074     0.8158 0.048 0.000 0.912 0.036 0.000 0.004
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     5  0.0777     0.8680 0.000 0.024 0.000 0.004 0.972 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.1863     0.8035 0.000 0.000 0.920 0.036 0.000 0.044
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.1218     0.8033 0.956 0.000 0.004 0.012 0.028 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.0405     0.9767 0.000 0.988 0.000 0.004 0.008 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     5  0.0146     0.8806 0.000 0.000 0.000 0.004 0.996 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     5  0.2513     0.8186 0.140 0.000 0.000 0.008 0.852 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     3  0.2891     0.8056 0.032 0.000 0.872 0.060 0.000 0.036
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     6  0.0692     0.9156 0.000 0.000 0.004 0.020 0.000 0.976
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     5  0.0146     0.8806 0.000 0.000 0.000 0.004 0.996 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.2882     0.7503 0.812 0.000 0.000 0.008 0.180 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     5  0.3512     0.6202 0.272 0.000 0.000 0.008 0.720 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     6  0.1088     0.9052 0.000 0.000 0.016 0.024 0.000 0.960
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     6  0.0547     0.9288 0.000 0.000 0.000 0.020 0.000 0.980
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.7309    -0.0654 0.392 0.000 0.236 0.120 0.000 0.252
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0692     0.8006 0.976 0.000 0.000 0.004 0.020 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     5  0.0622     0.8765 0.000 0.012 0.000 0.008 0.980 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     4  0.3868     0.1058 0.000 0.492 0.000 0.508 0.000 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     4  0.3470     0.8522 0.000 0.028 0.000 0.772 0.000 0.200
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.1957     0.7931 0.888 0.000 0.000 0.000 0.112 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     6  0.0458     0.9284 0.000 0.000 0.000 0.016 0.000 0.984
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     5  0.1515     0.8597 0.000 0.008 0.028 0.020 0.944 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     5  0.1643     0.8698 0.068 0.000 0.000 0.008 0.924 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     4  0.2996     0.8557 0.000 0.000 0.000 0.772 0.000 0.228
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     6  0.0146     0.9247 0.000 0.000 0.000 0.004 0.000 0.996
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#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     5  0.1196     0.8785 0.040 0.000 0.000 0.008 0.952 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.5368     0.6947 0.184 0.000 0.652 0.136 0.000 0.028
#> 20EB9CC6-EABB-438A-9030-E766459996D1     4  0.3515     0.5266 0.000 0.324 0.000 0.676 0.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2618     0.7302 0.872 0.000 0.052 0.076 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     5  0.0935     0.8619 0.000 0.032 0.000 0.004 0.964 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2197     0.8062 0.900 0.000 0.000 0.044 0.056 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0935     0.8042 0.964 0.000 0.000 0.004 0.032 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1082     0.7798 0.956 0.000 0.004 0.040 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     5  0.0858     0.8651 0.000 0.028 0.000 0.004 0.968 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.4931     0.5258 0.000 0.648 0.000 0.216 0.136 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.3890     0.2757 0.000 0.400 0.000 0.004 0.596 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.3868     0.0743 0.000 0.000 0.508 0.492 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.3073     0.7275 0.788 0.000 0.000 0.008 0.204 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.5884     0.5919 0.260 0.000 0.560 0.156 0.000 0.024
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0692     0.9664 0.000 0.976 0.000 0.004 0.020 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.2680     0.7275 0.868 0.000 0.056 0.076 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.1333     0.9363 0.000 0.944 0.000 0.048 0.008 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     5  0.2053     0.8510 0.108 0.000 0.000 0.004 0.888 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     4  0.3496     0.8214 0.000 0.000 0.052 0.804 0.004 0.140
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0508     0.9737 0.000 0.984 0.000 0.004 0.012 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     5  0.0146     0.8806 0.000 0.000 0.000 0.004 0.996 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     5  0.1958     0.7960 0.000 0.100 0.000 0.004 0.896 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.1141     0.8047 0.000 0.000 0.948 0.052 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     4  0.3352     0.7403 0.000 0.000 0.072 0.816 0.000 0.112
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.0632     0.9290 0.000 0.000 0.000 0.024 0.000 0.976
#> 835AAE7F-F873-4D11-8845-232D261A38DF     6  0.2309     0.8446 0.000 0.000 0.084 0.028 0.000 0.888
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     5  0.3804     0.4898 0.336 0.000 0.000 0.008 0.656 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     6  0.0260     0.9233 0.000 0.000 0.000 0.008 0.000 0.992
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9816 0.000 1.000 0.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     6  0.3200     0.7174 0.000 0.000 0.196 0.016 0.000 0.788
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     5  0.1398     0.8759 0.052 0.000 0.000 0.008 0.940 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     6  0.0146     0.9248 0.000 0.000 0.000 0.004 0.000 0.996
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     5  0.3271     0.6914 0.232 0.000 0.000 0.008 0.760 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-skmeans-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:pam

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "pam"]
# you can also extract it by
# res = res_list["ATC:pam"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.490           0.888       0.898         0.4421 0.544   0.544
#> 3 3 0.690           0.857       0.920         0.3486 0.824   0.681
#> 4 4 0.641           0.677       0.865         0.1741 0.815   0.570
#> 5 5 0.688           0.707       0.840         0.1039 0.852   0.554
#> 6 6 0.697           0.642       0.804         0.0274 0.972   0.877

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000      0.952 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     2  0.0000      0.952 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.7056      0.913 0.808 0.192
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.7056      0.913 0.808 0.192
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.7056      0.913 0.808 0.192
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.7056      0.913 0.808 0.192
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.7056      0.782 0.192 0.808
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     1  0.0000      0.837 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     2  0.2423      0.912 0.040 0.960
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.7056      0.913 0.808 0.192
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.7056      0.913 0.808 0.192
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.7056      0.913 0.808 0.192
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.7056      0.913 0.808 0.192
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     1  0.0000      0.837 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     2  0.0000      0.952 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     2  0.0000      0.952 0.000 1.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     2  0.0000      0.952 0.000 1.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.7056      0.913 0.808 0.192
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     2  0.0000      0.952 0.000 1.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.7056      0.913 0.808 0.192
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     1  0.0000      0.837 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.7056      0.913 0.808 0.192
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.7056      0.913 0.808 0.192
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.7056      0.913 0.808 0.192
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     2  0.0000      0.952 0.000 1.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     2  0.0000      0.952 0.000 1.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.7056      0.913 0.808 0.192
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     2  0.1414      0.934 0.020 0.980
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     1  0.0000      0.837 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     1  0.0000      0.837 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.7056      0.913 0.808 0.192
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.7056      0.913 0.808 0.192
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.7056      0.913 0.808 0.192
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     2  0.0000      0.952 0.000 1.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     1  0.0000      0.837 1.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.7056      0.913 0.808 0.192
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     2  0.6247      0.745 0.156 0.844
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.7056      0.782 0.192 0.808
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.7056      0.913 0.808 0.192
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     2  0.0000      0.952 0.000 1.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     1  0.0000      0.837 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.7056      0.913 0.808 0.192
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.8813      0.790 0.700 0.300
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.7056      0.913 0.808 0.192
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.7056      0.913 0.808 0.192
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     2  0.0000      0.952 0.000 1.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.7056      0.913 0.808 0.192
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     1  0.0000      0.837 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     2  0.9996     -0.312 0.488 0.512
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     1  0.0000      0.837 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.7056      0.913 0.808 0.192
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.7056      0.782 0.192 0.808
#> B507E82F-6680-497B-A014-033EDD7A2E03     2  0.0672      0.945 0.008 0.992
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.7056      0.913 0.808 0.192
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.7056      0.913 0.808 0.192
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.7056      0.913 0.808 0.192
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     2  0.0000      0.952 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.7056      0.913 0.808 0.192
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.7056      0.782 0.192 0.808
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.7056      0.913 0.808 0.192
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.7056      0.913 0.808 0.192
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.1414      0.845 0.980 0.020
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.7056      0.913 0.808 0.192
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.7056      0.913 0.808 0.192
#> 131213AD-0313-4DF1-B013-CE67ED262C37     1  0.0000      0.837 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     2  0.0000      0.952 0.000 1.000
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#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.7056      0.913 0.808 0.192
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     2  0.0000      0.952 0.000 1.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     1  0.0672      0.833 0.992 0.008
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     1  0.0000      0.837 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.7056      0.913 0.808 0.192
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.7056      0.913 0.808 0.192
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     2  0.0000      0.952 0.000 1.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     1  0.0000      0.837 1.000 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     2  0.0000      0.952 0.000 1.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     1  0.0000      0.837 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.7056      0.913 0.808 0.192
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     2  0.0000      0.952 0.000 1.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     2  0.0000      0.952 0.000 1.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     2  0.0000      0.952 0.000 1.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.7056      0.913 0.808 0.192
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     1  0.0000      0.837 1.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     2  0.0000      0.952 0.000 1.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     2  0.0000      0.952 0.000 1.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.7056      0.913 0.808 0.192
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     2  0.0000      0.952 0.000 1.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0376      0.838 0.996 0.004
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.7056      0.913 0.808 0.192
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     2  0.0000      0.952 0.000 1.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.9552      0.660 0.624 0.376
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.7056      0.913 0.808 0.192
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.7056      0.913 0.808 0.192
#> CCDB0290-91DA-4089-84A6-4434BA028D30     2  0.0000      0.952 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     2  0.0000      0.952 0.000 1.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     1  0.0000      0.837 1.000 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.7056      0.913 0.808 0.192
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.0000      0.837 1.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.7056      0.913 0.808 0.192
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.7056      0.913 0.808 0.192
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.7056      0.913 0.808 0.192
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     1  0.0000      0.837 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.7056      0.913 0.808 0.192
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000      0.952 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.7056      0.913 0.808 0.192
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.0000      0.837 1.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     2  0.0000      0.952 0.000 1.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.7056      0.913 0.808 0.192
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.7056      0.913 0.808 0.192
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     2  0.0000      0.952 0.000 1.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     1  0.0000      0.837 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.7056      0.913 0.808 0.192
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.0000      0.837 1.000 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.7056      0.913 0.808 0.192
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     2  0.0000      0.952 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.7139      0.910 0.804 0.196
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.0000      0.837 1.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.7056      0.913 0.808 0.192
#> 6752EED9-7990-433F-A206-D5398C396471     2  0.0000      0.952 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.7056      0.913 0.808 0.192
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.8763      0.796 0.704 0.296
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.7602      0.887 0.780 0.220
#> 1ABBEF80-508F-4247-B43D-3E549372113B     2  0.0000      0.952 0.000 1.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     2  0.0000      0.952 0.000 1.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.7056      0.913 0.808 0.192
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     2  0.0000      0.952 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     1  0.0000      0.837 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     1  0.0000      0.837 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     2  0.0000      0.952 0.000 1.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.7056      0.913 0.808 0.192
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     2  0.0000      0.952 0.000 1.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.7056      0.913 0.808 0.192

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.5397     0.7971 0.280 0.000 0.720
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0000     0.7843 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0424     0.9400 0.992 0.000 0.008
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9473 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9473 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9473 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.6226     0.6268 0.028 0.252 0.720
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3116     0.8767 0.108 0.892 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.5760     0.7360 0.328 0.000 0.672
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9473 1.000 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9473 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9473 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000     0.9473 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9671 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0000     0.7843 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.5397     0.7971 0.280 0.000 0.720
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.5397     0.7971 0.280 0.000 0.720
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9473 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.5397     0.7971 0.280 0.000 0.720
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000     0.9473 1.000 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2356     0.9125 0.072 0.928 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9473 1.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9473 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9473 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.5397     0.7971 0.280 0.000 0.720
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.4002     0.8038 0.160 0.000 0.840
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000     0.9473 1.000 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.5560     0.7750 0.300 0.000 0.700
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9671 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9671 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9473 1.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.9473 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9473 1.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.5397     0.7971 0.280 0.000 0.720
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4452     0.7729 0.192 0.808 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0000     0.9473 1.000 0.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.6252     0.5058 0.444 0.000 0.556
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.5138     0.6157 0.000 0.252 0.748
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0237     0.9437 0.996 0.000 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.5397     0.7971 0.280 0.000 0.720
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9671 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000     0.9473 1.000 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.3267     0.8088 0.884 0.000 0.116
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.9473 1.000 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9473 1.000 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.5397     0.7971 0.280 0.000 0.720
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9473 1.000 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9671 0.000 1.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.5465     0.4504 0.712 0.000 0.288
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9671 0.000 1.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.9473 1.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     3  0.0000     0.7843 0.000 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5529     0.7802 0.296 0.000 0.704
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000     0.9473 1.000 0.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9473 1.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0000     0.9473 1.000 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0000     0.7843 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000     0.9473 1.000 0.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     3  0.6274     0.2129 0.000 0.456 0.544
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.9473 1.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.9473 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.4931     0.6577 0.768 0.232 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000     0.9473 1.000 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.9473 1.000 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9671 0.000 1.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.0000     0.7843 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.9473 1.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000     0.9473 1.000 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.0000     0.7843 0.000 0.000 1.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9671 0.000 1.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.5397     0.7971 0.280 0.000 0.720
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.5397     0.7971 0.280 0.000 0.720
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.5465     0.7894 0.288 0.000 0.712
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.9473 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000     0.9473 1.000 0.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.2066     0.8835 0.940 0.000 0.060
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000     0.9473 1.000 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9671 0.000 1.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.0000     0.7843 0.000 0.000 1.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     3  0.0000     0.7843 0.000 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     3  0.5706     0.7477 0.320 0.000 0.680
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.0000     0.7843 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     3  0.0000     0.7843 0.000 0.000 1.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.9473 1.000 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.9473 1.000 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000     0.9473 1.000 0.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000     0.9473 1.000 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9671 0.000 1.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     3  0.5138     0.6157 0.000 0.252 0.748
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.5621     0.7648 0.308 0.000 0.692
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000     0.9473 1.000 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000     0.9473 1.000 0.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9671 0.000 1.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.1031     0.9237 0.976 0.000 0.024
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.9473 1.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.9473 1.000 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0000     0.9473 1.000 0.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0000     0.9473 1.000 0.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000     0.9473 1.000 0.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000     0.9473 1.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.0000     0.7843 0.000 0.000 1.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9671 0.000 1.000 0.000
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#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.4291     0.7034 0.820 0.000 0.180
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000     0.9473 1.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000     0.9473 1.000 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.0000     0.7843 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.5397     0.7971 0.280 0.000 0.720
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2066     0.9238 0.060 0.940 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.0424     0.9400 0.992 0.000 0.008
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.5988     0.4131 0.632 0.368 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.0000     0.9473 1.000 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.9473 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.9473 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9671 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000     0.9473 1.000 0.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.0000     0.7843 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.0000     0.9473 1.000 0.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.6126     0.3350 0.600 0.400 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.5291     0.8007 0.268 0.000 0.732
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.0000     0.9473 1.000 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9473 1.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.5397     0.7971 0.280 0.000 0.720
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9671 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9473 1.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.5178     0.6157 0.744 0.256 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.9473 1.000 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.7843 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.0237     0.9437 0.996 0.000 0.004
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.5178     0.6157 0.744 0.256 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.9473 1.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.0000     0.7843 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.0000     0.9473 1.000 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.2959     0.8309 0.900 0.000 0.100
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0424     0.9397 0.992 0.000 0.008
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.0592     0.7860 0.012 0.000 0.988
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.5178     0.8035 0.256 0.000 0.744
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9473 1.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.0000     0.7843 0.000 0.000 1.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9671 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9671 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.5397     0.7971 0.280 0.000 0.720
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.9473 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.5397     0.7971 0.280 0.000 0.720
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9473 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     1  0.4761     0.4067 0.628 0.000 0.372 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.3569     0.7121 0.804 0.000 0.196 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.4855     0.3605 0.600 0.000 0.400 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.4916     0.3782 0.576 0.000 0.424 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4012     0.5637 0.204 0.004 0.788 0.004
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3323     0.8443 0.064 0.876 0.060 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.1389     0.7523 0.048 0.000 0.952 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.4977     0.2810 0.540 0.000 0.460 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3610     0.6729 0.800 0.000 0.200 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2149     0.7684 0.912 0.000 0.088 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2921     0.7022 0.140 0.000 0.860 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.1389     0.8689 0.000 0.000 0.048 0.952
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2530     0.7480 0.888 0.000 0.112 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.1211     0.7367 0.000 0.000 0.960 0.040
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3649     0.6670 0.796 0.000 0.204 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2675     0.8742 0.044 0.908 0.048 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.4996     0.1465 0.516 0.000 0.484 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.2081     0.7698 0.916 0.000 0.084 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.4977     0.2349 0.540 0.000 0.460 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.4679     0.1312 0.000 0.000 0.648 0.352
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.2973     0.7490 0.856 0.000 0.144 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.0188     0.7648 0.004 0.000 0.996 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4731     0.7380 0.160 0.780 0.060 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.0188     0.7946 0.996 0.000 0.004 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.1302     0.7618 0.044 0.000 0.956 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.6193     0.6853 0.000 0.180 0.148 0.672
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     3  0.4981    -0.0706 0.464 0.000 0.536 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.4776     0.4087 0.624 0.000 0.376 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2704     0.7273 0.124 0.000 0.876 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.2081     0.7698 0.916 0.000 0.084 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3486     0.6732 0.188 0.000 0.812 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.4955     0.2661 0.556 0.000 0.444 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1302     0.7620 0.044 0.000 0.956 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.3074     0.7198 0.848 0.000 0.152 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.2216     0.8626 0.000 0.000 0.092 0.908
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0817     0.7916 0.976 0.000 0.024 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     3  0.4985    -0.0841 0.468 0.000 0.532 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.1792     0.7773 0.932 0.000 0.068 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3907     0.7055 0.000 0.768 0.232 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2647     0.7435 0.880 0.000 0.120 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.4955     0.2661 0.556 0.000 0.444 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.3801     0.6499 0.780 0.000 0.220 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.4998     0.1731 0.512 0.000 0.488 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.3610     0.6729 0.800 0.000 0.200 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.4977     0.2349 0.540 0.000 0.460 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     4  0.4855     0.5686 0.000 0.000 0.400 0.600
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.1389     0.7293 0.000 0.000 0.952 0.048
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.4948     0.2951 0.560 0.000 0.440 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0188     0.7636 0.004 0.000 0.996 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.2868     0.7440 0.864 0.000 0.136 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.2081     0.7698 0.916 0.000 0.084 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     3  0.2814     0.7100 0.132 0.000 0.868 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.4955     0.2661 0.556 0.000 0.444 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     4  0.4804     0.5969 0.000 0.000 0.384 0.616
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.2760     0.8495 0.000 0.000 0.128 0.872
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     3  0.4746     0.3047 0.368 0.000 0.632 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     4  0.3569     0.8065 0.000 0.000 0.196 0.804
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     3  0.4985    -0.0841 0.468 0.000 0.532 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.3024     0.7359 0.852 0.000 0.148 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     3  0.7790    -0.3058 0.024 0.132 0.468 0.376
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.0592     0.7650 0.016 0.000 0.984 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.5000     0.1040 0.500 0.000 0.500 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4304     0.5304 0.284 0.000 0.716 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.2921     0.7092 0.140 0.000 0.860 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.4730     0.4311 0.636 0.000 0.364 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0592     0.7930 0.984 0.000 0.016 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3219     0.7106 0.836 0.000 0.164 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.3528     0.6476 0.192 0.000 0.808 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     4  0.2281     0.8616 0.000 0.000 0.096 0.904
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     3  0.4985    -0.0388 0.468 0.000 0.532 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.4977     0.2202 0.540 0.000 0.460 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     1  0.3610     0.6478 0.800 0.200 0.000 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     4  0.4624     0.6434 0.000 0.000 0.340 0.660
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#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.2281     0.7403 0.096 0.000 0.904 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4730     0.4311 0.636 0.000 0.364 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.2919     0.8632 0.044 0.896 0.060 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2589     0.7563 0.884 0.000 0.116 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.2469     0.7348 0.892 0.108 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4406     0.5852 0.700 0.000 0.300 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4961     0.2579 0.552 0.000 0.448 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     3  0.4985    -0.0841 0.468 0.000 0.532 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.2081     0.7698 0.916 0.000 0.084 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.2704     0.7225 0.876 0.124 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.3024     0.6160 0.000 0.000 0.852 0.148
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.2081     0.7698 0.916 0.000 0.084 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     3  0.4981    -0.0706 0.464 0.000 0.536 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.2266     0.7686 0.912 0.004 0.084 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1867     0.7757 0.928 0.000 0.072 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4999    -0.1563 0.492 0.000 0.508 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.2266     0.7686 0.912 0.004 0.084 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.0000     0.8694 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4977     0.2848 0.540 0.000 0.460 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2589     0.7245 0.116 0.000 0.884 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3764     0.6030 0.216 0.000 0.784 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.4948     0.5076 0.000 0.000 0.440 0.560
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.3123     0.6047 0.000 0.000 0.844 0.156
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.7951 1.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     4  0.1792     0.8670 0.000 0.000 0.068 0.932
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9326 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1489     0.9019 0.004 0.952 0.044 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2814     0.6373 0.000 0.000 0.868 0.132
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4679     0.4543 0.648 0.000 0.352 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.0000     0.7641 0.000 0.000 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.7951 1.000 0.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.4404    0.51015 0.252 0.000 0.036 0.712 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.0162    0.88827 0.000 0.000 0.000 0.004 0.996
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.2583    0.75829 0.864 0.000 0.132 0.004 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0404    0.81607 0.988 0.000 0.012 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     3  0.3612    0.46097 0.268 0.000 0.732 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     3  0.4287   -0.37341 0.460 0.000 0.540 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     4  0.0880    0.74336 0.000 0.000 0.032 0.968 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3579    0.82362 0.084 0.840 0.068 0.008 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.1597    0.70844 0.048 0.000 0.940 0.012 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     3  0.3730    0.61422 0.288 0.000 0.712 0.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2230    0.80667 0.884 0.000 0.116 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2020    0.77578 0.900 0.000 0.100 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.3635    0.67460 0.004 0.000 0.748 0.248 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.4060    0.45801 0.000 0.000 0.000 0.360 0.640
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3480    0.67265 0.000 0.000 0.752 0.248 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     4  0.0880    0.74859 0.000 0.000 0.032 0.968 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0963    0.81413 0.964 0.000 0.036 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     4  0.1121    0.74735 0.000 0.000 0.044 0.956 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3508    0.74843 0.748 0.000 0.252 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.2899    0.86113 0.036 0.880 0.076 0.008 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     3  0.1965    0.69065 0.096 0.000 0.904 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1732    0.78720 0.920 0.000 0.080 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     3  0.3895    0.64402 0.320 0.000 0.680 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     4  0.0880    0.74859 0.000 0.000 0.032 0.968 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     4  0.0992    0.74739 0.000 0.000 0.024 0.968 0.008
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.2127    0.77298 0.892 0.000 0.108 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3336    0.68386 0.000 0.000 0.772 0.228 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.2605    0.79438 0.852 0.000 0.148 0.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.3274    0.76776 0.780 0.000 0.220 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     3  0.3895    0.61321 0.000 0.000 0.680 0.320 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4724    0.71117 0.168 0.744 0.080 0.008 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.3305    0.76589 0.776 0.000 0.224 0.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.3336    0.68386 0.000 0.000 0.772 0.228 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.4641    0.53234 0.000 0.172 0.004 0.744 0.080
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     3  0.3395    0.64815 0.236 0.000 0.764 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     4  0.1121    0.74729 0.000 0.000 0.044 0.956 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0510    0.92868 0.000 0.984 0.000 0.016 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.4297   -0.21115 0.472 0.000 0.528 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.3635    0.67306 0.004 0.000 0.748 0.248 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1732    0.78720 0.920 0.000 0.080 0.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3359    0.71592 0.052 0.000 0.840 0.108 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     4  0.4273   -0.02634 0.000 0.000 0.448 0.552 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     3  0.2230    0.68461 0.116 0.000 0.884 0.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.3336    0.68386 0.000 0.000 0.772 0.228 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0290    0.92833 0.000 0.992 0.000 0.008 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1121    0.80619 0.956 0.000 0.044 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     5  0.4182    0.49775 0.000 0.000 0.004 0.352 0.644
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.3480    0.67265 0.000 0.000 0.752 0.248 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0963    0.80835 0.964 0.000 0.036 0.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     3  0.3480    0.64561 0.248 0.000 0.752 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.1270    0.80543 0.948 0.000 0.052 0.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.3210    0.77075 0.788 0.000 0.212 0.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     4  0.5201    0.17178 0.000 0.424 0.044 0.532 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1608    0.81022 0.928 0.000 0.072 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     3  0.2230    0.68461 0.116 0.000 0.884 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.3612    0.73214 0.732 0.000 0.268 0.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     3  0.3177    0.68679 0.208 0.000 0.792 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0290    0.92914 0.000 0.992 0.000 0.008 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0794    0.81129 0.972 0.000 0.028 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.1908    0.69810 0.092 0.000 0.908 0.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     4  0.3612    0.51260 0.000 0.000 0.000 0.732 0.268
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     4  0.1478    0.74373 0.000 0.000 0.064 0.936 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     4  0.4114    0.61729 0.164 0.000 0.060 0.776 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.4268    0.58972 0.008 0.000 0.648 0.344 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3684    0.57636 0.720 0.000 0.280 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.1908    0.78052 0.908 0.000 0.092 0.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     3  0.3336    0.68386 0.000 0.000 0.772 0.228 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     3  0.2179    0.68654 0.112 0.000 0.888 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0290    0.92914 0.000 0.992 0.000 0.008 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     4  0.3837    0.44873 0.000 0.000 0.000 0.692 0.308
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.4118    0.36618 0.000 0.000 0.004 0.660 0.336
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     3  0.2069    0.69420 0.076 0.000 0.912 0.012 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     4  0.3612    0.48503 0.000 0.000 0.000 0.732 0.268
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     3  0.3508    0.64541 0.252 0.000 0.748 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.4045    0.37906 0.644 0.000 0.356 0.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.3305    0.76589 0.776 0.000 0.224 0.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.3210    0.77075 0.788 0.000 0.212 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0290    0.92833 0.000 0.992 0.000 0.008 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     4  0.4952    0.56106 0.020 0.116 0.004 0.756 0.104
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     4  0.3242    0.67333 0.012 0.000 0.172 0.816 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     3  0.1608    0.69992 0.072 0.000 0.928 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4678    0.69931 0.064 0.000 0.712 0.224 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0510    0.92868 0.000 0.984 0.000 0.016 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.3756    0.67619 0.008 0.000 0.744 0.248 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.3305    0.76589 0.776 0.000 0.224 0.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.4192    0.53349 0.596 0.000 0.404 0.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.0404    0.81385 0.988 0.000 0.012 0.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3730    0.71770 0.712 0.000 0.288 0.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.6135    0.54305 0.192 0.000 0.560 0.248 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     5  0.3983    0.51409 0.000 0.000 0.000 0.340 0.660
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0162    0.92961 0.000 0.996 0.000 0.004 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0290    0.92914 0.000 0.992 0.000 0.008 0.000
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#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0162    0.92962 0.000 0.996 0.000 0.004 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.2624    0.71952 0.012 0.000 0.872 0.116 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.3999    0.64095 0.656 0.000 0.344 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     4  0.0963    0.74783 0.000 0.000 0.036 0.964 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     1  0.3745    0.73399 0.828 0.096 0.068 0.008 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     3  0.3074    0.65879 0.000 0.000 0.804 0.196 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0290    0.92833 0.000 0.992 0.000 0.008 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.3305    0.76589 0.776 0.000 0.224 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     4  0.2773    0.63983 0.000 0.000 0.000 0.836 0.164
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     4  0.3534    0.50244 0.000 0.000 0.000 0.744 0.256
#> 54504893-92C5-4328-85A8-2A882680B5E0     3  0.3932    0.60893 0.000 0.000 0.672 0.328 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.3305    0.76589 0.776 0.000 0.224 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.0290    0.92914 0.000 0.992 0.000 0.008 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     4  0.3707    0.47070 0.000 0.000 0.284 0.716 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.4060    0.47026 0.000 0.000 0.000 0.360 0.640
#> D365A238-4739-4B54-9608-DC548F21C04E     3  0.3895    0.57597 0.320 0.000 0.680 0.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     3  0.3636    0.65830 0.000 0.000 0.728 0.272 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0290    0.81462 0.992 0.000 0.008 0.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     3  0.4219    0.00426 0.416 0.000 0.584 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     4  0.0794    0.73956 0.000 0.000 0.000 0.972 0.028
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.3480    0.67265 0.000 0.000 0.752 0.248 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0290    0.81684 0.992 0.000 0.008 0.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.4201    0.52566 0.592 0.000 0.408 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     3  0.3305    0.68593 0.000 0.000 0.776 0.224 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.3282    0.84847 0.044 0.860 0.084 0.012 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2773    0.72433 0.836 0.000 0.164 0.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.2377    0.75228 0.872 0.128 0.000 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.3707    0.55720 0.716 0.000 0.284 0.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     3  0.1965    0.69315 0.096 0.000 0.904 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     3  0.3366    0.65231 0.232 0.000 0.768 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0290    0.92914 0.000 0.992 0.000 0.008 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.1732    0.78720 0.920 0.000 0.080 0.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.5500    0.69408 0.648 0.140 0.212 0.000 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     4  0.0510    0.74760 0.000 0.000 0.016 0.984 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.1908    0.78052 0.908 0.000 0.092 0.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     3  0.3424    0.67762 0.000 0.000 0.760 0.240 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0290    0.92833 0.000 0.992 0.000 0.008 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     3  0.1043    0.71328 0.040 0.000 0.960 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.2193    0.77765 0.900 0.000 0.092 0.008 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1544    0.79417 0.932 0.000 0.068 0.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.3561    0.63443 0.260 0.000 0.740 0.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1732    0.78720 0.920 0.000 0.080 0.000 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.0000    0.88981 0.000 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4283    0.02979 0.544 0.000 0.456 0.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3480    0.67265 0.000 0.000 0.752 0.248 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.0324    0.71054 0.004 0.000 0.992 0.004 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.3508    0.50932 0.000 0.000 0.000 0.748 0.252
#> 835AAE7F-F873-4D11-8845-232D261A38DF     4  0.0880    0.74859 0.000 0.000 0.032 0.968 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.81580 1.000 0.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.3661    0.62456 0.000 0.000 0.000 0.276 0.724
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.92962 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.1894    0.88324 0.000 0.920 0.072 0.008 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     4  0.0510    0.74760 0.000 0.000 0.016 0.984 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.4150    0.56567 0.612 0.000 0.388 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.0510    0.74760 0.000 0.000 0.016 0.984 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0404    0.81607 0.988 0.000 0.012 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     3  0.5942    0.36560 0.260 0.220 0.512 0.000 0.008 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     6  0.0146    0.86098 0.000 0.000 0.004 0.000 0.000 0.996
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.1714    0.78134 0.908 0.000 0.000 0.000 0.092 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0363    0.81514 0.988 0.000 0.000 0.000 0.012 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     5  0.3244    0.42740 0.268 0.000 0.000 0.000 0.732 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     5  0.3864   -0.39692 0.480 0.000 0.000 0.000 0.520 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2346    0.69157 0.000 0.124 0.868 0.000 0.008 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.3590    0.49167 0.188 0.776 0.000 0.004 0.032 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.0993    0.73145 0.024 0.000 0.012 0.000 0.964 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     5  0.3309    0.63648 0.280 0.000 0.000 0.000 0.720 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2092    0.80891 0.876 0.000 0.000 0.000 0.124 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1204    0.79297 0.944 0.000 0.000 0.000 0.056 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     5  0.3221    0.68924 0.000 0.000 0.264 0.000 0.736 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.3851    0.58007 0.000 0.540 0.000 0.460 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.3747    0.38810 0.000 0.000 0.396 0.000 0.000 0.604
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     5  0.3244    0.68637 0.000 0.000 0.268 0.000 0.732 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.0260    0.72876 0.000 0.000 0.992 0.000 0.008 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0790    0.81534 0.968 0.000 0.000 0.000 0.032 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     3  0.0865    0.72426 0.000 0.000 0.964 0.000 0.036 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3151    0.76148 0.748 0.000 0.000 0.000 0.252 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.4038    0.65650 0.060 0.780 0.000 0.136 0.024 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     5  0.1204    0.71998 0.056 0.000 0.000 0.000 0.944 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     5  0.3330    0.66756 0.284 0.000 0.000 0.000 0.716 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0260    0.72876 0.000 0.000 0.992 0.000 0.008 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     3  0.0260    0.72876 0.000 0.000 0.992 0.000 0.008 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.1327    0.79203 0.936 0.000 0.000 0.000 0.064 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     5  0.2996    0.71133 0.000 0.000 0.228 0.000 0.772 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.3843    0.58792 0.000 0.548 0.000 0.452 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.3847    0.58498 0.000 0.544 0.000 0.456 0.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.2378    0.79816 0.848 0.000 0.000 0.000 0.152 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.2912    0.77858 0.784 0.000 0.000 0.000 0.216 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     5  0.3288    0.68360 0.000 0.000 0.276 0.000 0.724 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.3978    0.37407 0.268 0.700 0.000 0.000 0.032 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2941    0.77697 0.780 0.000 0.000 0.000 0.220 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.2969    0.71224 0.000 0.000 0.224 0.000 0.776 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     3  0.5088    0.36251 0.000 0.412 0.516 0.000 0.004 0.068
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     5  0.2996    0.67178 0.228 0.000 0.000 0.000 0.772 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     3  0.0790    0.72542 0.000 0.000 0.968 0.000 0.032 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     4  0.2664    0.56955 0.000 0.184 0.000 0.816 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     5  0.3857   -0.24927 0.468 0.000 0.000 0.000 0.532 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     5  0.3360    0.68940 0.004 0.000 0.264 0.000 0.732 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     5  0.2983    0.73090 0.032 0.000 0.136 0.000 0.832 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     3  0.3860   -0.13562 0.000 0.000 0.528 0.000 0.472 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     5  0.1387    0.71693 0.068 0.000 0.000 0.000 0.932 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.3847    0.58498 0.000 0.544 0.000 0.456 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     5  0.2969    0.71224 0.000 0.000 0.224 0.000 0.776 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.0146    0.68235 0.000 0.004 0.000 0.996 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0865    0.81002 0.964 0.000 0.000 0.000 0.036 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     6  0.5426    0.56240 0.000 0.220 0.180 0.000 0.004 0.596
#> B507E82F-6680-497B-A014-033EDD7A2E03     5  0.3244    0.68821 0.000 0.000 0.268 0.000 0.732 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0458    0.81109 0.984 0.000 0.000 0.000 0.016 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     5  0.3023    0.66926 0.232 0.000 0.000 0.000 0.768 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.1075    0.80529 0.952 0.000 0.000 0.000 0.048 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.2854    0.78090 0.792 0.000 0.000 0.000 0.208 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.3699    0.09204 0.000 0.660 0.336 0.000 0.004 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.1387    0.81475 0.932 0.000 0.000 0.000 0.068 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.1387    0.71693 0.068 0.000 0.000 0.000 0.932 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.3244    0.74907 0.732 0.000 0.000 0.000 0.268 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     5  0.2697    0.70856 0.188 0.000 0.000 0.000 0.812 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.2941    0.69926 0.000 0.780 0.000 0.220 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0713    0.81159 0.972 0.000 0.000 0.000 0.028 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     5  0.1327    0.72145 0.064 0.000 0.000 0.000 0.936 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.3076    0.51922 0.000 0.000 0.760 0.000 0.000 0.240
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.3857   -0.48599 0.000 0.468 0.000 0.532 0.000 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     3  0.1267    0.71803 0.000 0.000 0.940 0.000 0.060 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     3  0.3516    0.59502 0.164 0.000 0.788 0.000 0.048 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     5  0.3684    0.62623 0.004 0.000 0.332 0.000 0.664 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.3330    0.53872 0.716 0.000 0.000 0.000 0.284 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     5  0.2969    0.71224 0.000 0.000 0.224 0.000 0.776 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     5  0.1387    0.71693 0.068 0.000 0.000 0.000 0.932 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.2941    0.69926 0.000 0.780 0.000 0.220 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.3428    0.42003 0.000 0.000 0.696 0.000 0.000 0.304
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#> 8ACBD428-7713-48D9-810A-43C9CD191A73     3  0.3081    0.62719 0.000 0.220 0.776 0.000 0.004 0.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.3290    0.47270 0.000 0.004 0.744 0.000 0.000 0.252
#> DD51C17C-300F-44A4-955A-C9BC85417842     5  0.3266    0.68826 0.000 0.000 0.272 0.000 0.728 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.3101    0.76566 0.756 0.000 0.000 0.000 0.244 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.2730    0.78709 0.808 0.000 0.000 0.000 0.192 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     3  0.3890    0.46715 0.000 0.400 0.596 0.000 0.004 0.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.1176    0.53381 0.000 0.956 0.020 0.000 0.024 0.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.3847    0.58498 0.000 0.544 0.000 0.456 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     4  0.3868   -0.54147 0.000 0.496 0.000 0.504 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     3  0.3862    0.18994 0.004 0.000 0.608 0.000 0.388 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.1141    0.71297 0.000 0.000 0.948 0.000 0.052 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     6  0.3175    0.65408 0.000 0.000 0.256 0.000 0.000 0.744
#> B55743F2-4D63-4375-85D3-F58281CFD852     5  0.1327    0.71854 0.064 0.000 0.000 0.000 0.936 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     5  0.1387    0.71693 0.068 0.000 0.000 0.000 0.932 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.5990   -0.00358 0.440 0.000 0.264 0.000 0.296 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.2854    0.78090 0.792 0.000 0.000 0.000 0.208 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.2883    0.77989 0.788 0.000 0.000 0.000 0.212 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     5  0.2969    0.71224 0.000 0.000 0.224 0.000 0.776 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.2969    0.69870 0.000 0.776 0.000 0.224 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1204    0.79297 0.944 0.000 0.000 0.000 0.056 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     5  0.2969    0.71224 0.000 0.000 0.224 0.000 0.776 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     4  0.0000    0.68332 0.000 0.000 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.4100    0.62802 0.004 0.600 0.000 0.388 0.008 0.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     3  0.3136    0.56600 0.004 0.000 0.768 0.000 0.228 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     4  0.0000    0.68332 0.000 0.000 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     1  0.4945    0.69838 0.668 0.100 0.000 0.012 0.220 0.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     5  0.1663    0.70455 0.088 0.000 0.000 0.000 0.912 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     3  0.3867   -0.23438 0.000 0.000 0.512 0.000 0.488 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0891    0.54314 0.000 0.968 0.008 0.000 0.024 0.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.3828    0.59792 0.000 0.560 0.000 0.440 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     5  0.2312    0.74299 0.012 0.000 0.112 0.000 0.876 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.3592    0.66305 0.656 0.000 0.000 0.000 0.344 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     3  0.0260    0.72876 0.000 0.000 0.992 0.000 0.008 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     1  0.4134    0.53399 0.656 0.316 0.000 0.000 0.028 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     5  0.2300    0.71364 0.000 0.000 0.144 0.000 0.856 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     4  0.0000    0.68332 0.000 0.000 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.2941    0.77697 0.780 0.000 0.000 0.000 0.220 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.2416    0.61855 0.000 0.000 0.844 0.000 0.000 0.156
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.3175    0.46785 0.000 0.000 0.744 0.000 0.000 0.256
#> 54504893-92C5-4328-85A8-2A882680B5E0     5  0.3428    0.66382 0.000 0.000 0.304 0.000 0.696 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.2941    0.77697 0.780 0.000 0.000 0.000 0.220 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.2969    0.69870 0.000 0.776 0.000 0.224 0.000 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     3  0.3330    0.43766 0.000 0.000 0.716 0.000 0.284 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     6  0.3717    0.44541 0.000 0.000 0.384 0.000 0.000 0.616
#> D365A238-4739-4B54-9608-DC548F21C04E     5  0.3515    0.59479 0.324 0.000 0.000 0.000 0.676 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     5  0.3076    0.70652 0.000 0.000 0.240 0.000 0.760 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.0363    0.81128 0.988 0.000 0.000 0.000 0.012 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     5  0.3782   -0.04580 0.412 0.000 0.000 0.000 0.588 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.0260    0.72702 0.000 0.000 0.992 0.000 0.000 0.008
#> 02ABB64E-768B-4999-A899-EEE573D5F186     5  0.3221    0.68924 0.000 0.000 0.264 0.000 0.736 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.0260    0.81560 0.992 0.000 0.000 0.000 0.008 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.3782    0.54719 0.588 0.000 0.000 0.000 0.412 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     5  0.2969    0.71367 0.000 0.000 0.224 0.000 0.776 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0146    0.56130 0.000 0.996 0.000 0.000 0.004 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2340    0.72936 0.852 0.000 0.000 0.000 0.148 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.3866   -0.11168 0.516 0.000 0.000 0.484 0.000 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.3330    0.53537 0.716 0.000 0.000 0.000 0.284 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     5  0.1387    0.71713 0.068 0.000 0.000 0.000 0.932 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     5  0.2941    0.67561 0.220 0.000 0.000 0.000 0.780 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.2941    0.69926 0.000 0.780 0.000 0.220 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.5190    0.65467 0.640 0.008 0.000 0.144 0.208 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.0000    0.72823 0.000 0.000 1.000 0.000 0.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     5  0.3198    0.69430 0.000 0.000 0.260 0.000 0.740 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.0000    0.68332 0.000 0.000 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     5  0.0790    0.73396 0.032 0.000 0.000 0.000 0.968 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     1  0.1285    0.79304 0.944 0.000 0.000 0.004 0.052 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1075    0.79718 0.952 0.000 0.000 0.000 0.048 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     5  0.3151    0.65746 0.252 0.000 0.000 0.000 0.748 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     1  0.1141    0.79489 0.948 0.000 0.000 0.000 0.052 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     6  0.0000    0.86208 0.000 0.000 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.3823    0.08602 0.564 0.000 0.000 0.000 0.436 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     5  0.3244    0.68821 0.000 0.000 0.268 0.000 0.732 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     5  0.0291    0.73210 0.004 0.000 0.004 0.000 0.992 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.3151    0.47519 0.000 0.000 0.748 0.000 0.000 0.252
#> 835AAE7F-F873-4D11-8845-232D261A38DF     3  0.0260    0.72876 0.000 0.000 0.992 0.000 0.008 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000    0.81419 1.000 0.000 0.000 0.000 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     6  0.3409    0.59541 0.000 0.000 0.300 0.000 0.000 0.700
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.3765    0.62227 0.000 0.596 0.000 0.404 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.2513    0.66872 0.000 0.852 0.000 0.140 0.008 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0000    0.72823 0.000 0.000 1.000 0.000 0.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3737    0.58538 0.608 0.000 0.000 0.000 0.392 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     3  0.0000    0.72823 0.000 0.000 1.000 0.000 0.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0363    0.81514 0.988 0.000 0.000 0.000 0.012 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-pam-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "mclust"]
# you can also extract it by
# res = res_list["ATC:mclust"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.985       0.994         0.3808 0.621   0.621
#> 3 3 0.583           0.737       0.867         0.4920 0.847   0.754
#> 4 4 0.628           0.689       0.838         0.0804 0.859   0.722
#> 5 5 0.694           0.785       0.868         0.1170 0.910   0.783
#> 6 6 0.647           0.638       0.807         0.0741 0.924   0.781

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2   0.242      0.953 0.040 0.960
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1   0.000      0.995 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1   0.000      0.995 1.000 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1   0.000      0.995 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1   0.000      0.995 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1   0.000      0.995 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2   0.993      0.172 0.452 0.548
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2   0.000      0.992 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1   0.000      0.995 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1   0.000      0.995 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1   0.000      0.995 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1   0.000      0.995 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1   0.000      0.995 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2   0.000      0.992 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1   0.000      0.995 1.000 0.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1   0.000      0.995 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1   0.000      0.995 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1   0.000      0.995 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1   0.000      0.995 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1   0.000      0.995 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2   0.000      0.992 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1   0.000      0.995 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1   0.000      0.995 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1   0.000      0.995 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1   0.000      0.995 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1   0.000      0.995 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1   0.000      0.995 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1   0.000      0.995 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2   0.000      0.992 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2   0.000      0.992 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1   0.000      0.995 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1   0.000      0.995 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1   0.000      0.995 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1   0.000      0.995 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2   0.000      0.992 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1   0.000      0.995 1.000 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1   0.000      0.995 1.000 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2   0.000      0.992 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1   0.000      0.995 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1   0.000      0.995 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2   0.000      0.992 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1   0.000      0.995 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1   0.000      0.995 1.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1   0.000      0.995 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1   0.000      0.995 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1   0.000      0.995 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1   0.000      0.995 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2   0.000      0.992 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1   0.000      0.995 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2   0.000      0.992 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1   0.000      0.995 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2   0.000      0.992 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1   0.000      0.995 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1   0.000      0.995 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1   0.000      0.995 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1   0.000      0.995 1.000 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1   0.000      0.995 1.000 0.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1   0.000      0.995 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2   0.000      0.992 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1   0.000      0.995 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1   0.000      0.995 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     1   0.000      0.995 1.000 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1   0.000      0.995 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1   0.000      0.995 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2   0.000      0.992 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     1   0.000      0.995 1.000 0.000
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1   0.000      0.995 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1   0.000      0.995 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1   0.000      0.995 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2   0.000      0.992 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1   0.000      0.995 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1   0.000      0.995 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1   0.000      0.995 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1   0.000      0.995 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1   0.000      0.995 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1   0.000      0.995 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1   0.000      0.995 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2   0.000      0.992 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1   0.000      0.995 1.000 0.000
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2   0.000      0.992 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1   0.000      0.995 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     1   0.000      0.995 1.000 0.000
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1   0.000      0.995 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1   0.000      0.995 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1   0.000      0.995 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1   0.000      0.995 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1   0.000      0.995 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2   0.000      0.992 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2   0.000      0.992 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1   0.000      0.995 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1   0.000      0.995 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1   0.000      0.995 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2   0.000      0.992 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1   0.000      0.995 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1   0.000      0.995 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1   0.000      0.995 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1   0.000      0.995 1.000 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1   0.000      0.995 1.000 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1   0.000      0.995 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1   0.000      0.995 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     1   0.000      0.995 1.000 0.000
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2   0.000      0.992 0.000 1.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2   0.000      0.992 0.000 1.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1   0.000      0.995 1.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1   0.000      0.995 1.000 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2   0.000      0.992 0.000 1.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     1   0.000      0.995 1.000 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1   0.000      0.995 1.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1   0.000      0.995 1.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2   0.000      0.992 0.000 1.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2   0.000      0.992 0.000 1.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1   0.000      0.995 1.000 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     1   0.000      0.995 1.000 0.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     1   0.000      0.995 1.000 0.000
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1   0.000      0.995 1.000 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1   0.000      0.995 1.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1   0.000      0.995 1.000 0.000
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1   0.000      0.995 1.000 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1   0.000      0.995 1.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1   0.000      0.995 1.000 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1   0.000      0.995 1.000 0.000
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1   0.000      0.995 1.000 0.000
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1   0.000      0.995 1.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1   0.000      0.995 1.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     1   0.000      0.995 1.000 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2   0.000      0.992 0.000 1.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2   0.000      0.992 0.000 1.000
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1   0.000      0.995 1.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     1   0.000      0.995 1.000 0.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1   0.000      0.995 1.000 0.000
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1   0.000      0.995 1.000 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1   0.000      0.995 1.000 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2   0.000      0.992 0.000 1.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1   0.000      0.995 1.000 0.000
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2   0.000      0.992 0.000 1.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2   0.000      0.992 0.000 1.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1   0.000      0.995 1.000 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2   0.000      0.992 0.000 1.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2   0.000      0.992 0.000 1.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     1   0.000      0.995 1.000 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     1   0.000      0.995 1.000 0.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     2   0.000      0.992 0.000 1.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     1   0.000      0.995 1.000 0.000
#> 0DC723D0-7C68-4495-A4B9-2DF2FF19AB14     2   0.000      0.992 0.000 1.000
#> 7540005F-57E0-4E2E-A8A2-BEF2B0F333B1     2   0.000      0.992 0.000 1.000
#> EB1DDB14-4076-4C2C-B911-390C17C21486     1   0.000      0.995 1.000 0.000
#> 9EA70EC4-8BA0-4E3D-B3CB-A68D19E89868     1   0.000      0.995 1.000 0.000
#> B04E2E50-0A6E-4224-A825-1714D12E5669     2   0.000      0.992 0.000 1.000
#> B0BF5E01-536D-40FF-9C24-CBBD611E2FC2     1   0.000      0.995 1.000 0.000
#> 7B6B1788-B297-4442-B6BE-B7CE8754491E     1   0.000      0.995 1.000 0.000
#> A090D00C-34DF-4906-A517-4803C4C9A332     1   0.000      0.995 1.000 0.000
#> 340D44A6-9BEA-412C-9973-D9ABD6692255     1   0.000      0.995 1.000 0.000
#> E8D0D1E7-E5A8-4014-80C1-0245F90F4358     2   0.000      0.992 0.000 1.000
#> 19EA1494-8572-40E1-B9BB-3739F47B607D     1   0.000      0.995 1.000 0.000
#> 1C1B4793-8DAF-4763-BA4D-C4E869A4ED35     1   0.000      0.995 1.000 0.000
#> 45BF59B3-95BD-4196-ABAA-4C4F0DB38572     2   0.000      0.992 0.000 1.000
#> 47B5A2A7-7E13-4558-99D2-067F5075C6A4     1   0.000      0.995 1.000 0.000
#> E94638E8-CB51-4FBB-8BCB-4BFD7A812291     1   0.000      0.995 1.000 0.000
#> A17352A8-0D3C-4545-8136-7DAE2FB0E102     2   0.327      0.932 0.060 0.940
#> B18A6F95-D4ED-416B-B5A1-9A4934865D0D     2   0.000      0.992 0.000 1.000
#> 33E92C5F-0C42-4549-AD5B-0A064182A272     1   0.000      0.995 1.000 0.000
#> E041B375-3E60-4F18-A6EF-D1C249E3B8EE     1   0.000      0.995 1.000 0.000
#> EDF90AF6-6C64-4BD2-AADF-8D7D188650B2     2   0.000      0.992 0.000 1.000
#> 569320D2-316C-4E2D-B7B3-D7D5C4DAD42D     1   0.000      0.995 1.000 0.000
#> AFFB223D-DAE9-4567-9EF2-8E4DF9D8782D     2   0.000      0.992 0.000 1.000
#> 56FC9454-0A6A-4CC3-95C4-BE0E0D0BAFCE     2   0.000      0.992 0.000 1.000
#> 43226365-FAEF-46C5-AF1B-5C6C2BED84FF     1   0.000      0.995 1.000 0.000
#> 1536110A-B42A-4A84-9474-9895321FDCE9     2   0.000      0.992 0.000 1.000
#> 812255DD-536B-4216-90B1-27D5AB339BE2     1   0.000      0.995 1.000 0.000
#> 5D4563D6-68B7-4C9D-A3F4-AA7D45D5112C     2   0.000      0.992 0.000 1.000
#> BAA39781-DB94-473C-98B1-FA6CD3E1C67A     1   0.000      0.995 1.000 0.000
#> C1411CDA-814D-4E21-8929-C0F77858828F     1   0.000      0.995 1.000 0.000
#> EFE2F248-C13E-4E8D-9153-8C903848AC4A     1   0.000      0.995 1.000 0.000
#> D3939C84-D1D6-4060-9F91-AEB222A9BDD5     1   0.000      0.995 1.000 0.000
#> EABD2987-8C1E-49E5-94AF-C0BDE5335A48     1   0.000      0.995 1.000 0.000
#> F4BE2ABE-2CEB-4A6A-B8EC-0355F8C63B9B     1   0.000      0.995 1.000 0.000
#> 627BC251-D217-4955-B718-6B9D6DEA1756     1   0.000      0.995 1.000 0.000
#> 31B54613-A20E-4039-BB8B-9B52104CE418     1   0.000      0.995 1.000 0.000
#> 3F292B7C-A535-4DBD-BC20-CB4F85A1C94B     1   0.000      0.995 1.000 0.000
#> BEA2A5EB-EEA9-4F31-AC38-810E04CE124B     2   0.000      0.992 0.000 1.000
#> 99D84D46-19DA-43F1-B639-DCE9953F1529     2   0.000      0.992 0.000 1.000
#> 4588817E-1068-4A78-86B6-4674A0112DDA     1   0.000      0.995 1.000 0.000
#> 6AC633BD-BEC1-4750-94E3-378972DAB6B3     2   0.000      0.992 0.000 1.000
#> 09E17C6E-7EDE-4DDF-B5ED-2521AF870C9A     1   0.000      0.995 1.000 0.000
#> 58D9C750-26A2-4B7C-84C4-13D7AFB4C5EA     1   0.000      0.995 1.000 0.000
#> DF28E138-E222-4F77-9B61-69E601CA7E60     2   0.000      0.992 0.000 1.000
#> FEA489A8-E423-4266-AADA-9BAAB29AB94B     1   0.000      0.995 1.000 0.000
#> F3FCC207-15CD-41EA-A3EF-F5D2C12AC373     1   0.000      0.995 1.000 0.000
#> 53DD7AFB-A258-4643-A501-BACC95D17A50     2   0.000      0.992 0.000 1.000
#> D850B2A1-1F8A-4A44-A0CF-8D9DD4A1889A     2   0.000      0.992 0.000 1.000
#> B3F746DC-E487-4305-9F30-825D1520E8FD     2   0.000      0.992 0.000 1.000
#> BE38240A-F7C2-439F-9AAE-51C8A340F310     1   0.000      0.995 1.000 0.000
#> A9022D9E-1D30-49EE-8552-1364A8027F34     1   0.000      0.995 1.000 0.000
#> 0E8A56EE-D9A2-48A5-B793-A358BE1E4EFA     1   0.000      0.995 1.000 0.000
#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1   0.000      0.995 1.000 0.000
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1   0.000      0.995 1.000 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2   0.000      0.992 0.000 1.000
#> 344B9631-AAA5-4302-8747-D584345D9131     1   0.000      0.995 1.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1   0.000      0.995 1.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1   0.000      0.995 1.000 0.000
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1   0.000      0.995 1.000 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     1   0.000      0.995 1.000 0.000
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1   0.000      0.995 1.000 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1   0.000      0.995 1.000 0.000
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1   0.000      0.995 1.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     1   0.000      0.995 1.000 0.000
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1   0.000      0.995 1.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1   0.000      0.995 1.000 0.000
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1   0.000      0.995 1.000 0.000
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2   0.000      0.992 0.000 1.000
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2   0.000      0.992 0.000 1.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     1   0.000      0.995 1.000 0.000
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1   0.000      0.995 1.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1   0.000      0.995 1.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     1   0.000      0.995 1.000 0.000
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1   0.000      0.995 1.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2   0.000      0.992 0.000 1.000
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     1   0.000      0.995 1.000 0.000
#> DD51C17C-300F-44A4-955A-C9BC85417842     1   0.000      0.995 1.000 0.000
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1   0.000      0.995 1.000 0.000
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1   0.000      0.995 1.000 0.000
#> B2088466-FA5D-491C-9982-99B33683E66F     2   0.000      0.992 0.000 1.000
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     1   0.000      0.995 1.000 0.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2   0.000      0.992 0.000 1.000
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2   0.000      0.992 0.000 1.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2   0.000      0.992 0.000 1.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1   0.000      0.995 1.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1   0.000      0.995 1.000 0.000
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     1   0.000      0.995 1.000 0.000
#> B55743F2-4D63-4375-85D3-F58281CFD852     1   0.000      0.995 1.000 0.000
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1   0.000      0.995 1.000 0.000
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1   0.000      0.995 1.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1   0.000      0.995 1.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1   0.000      0.995 1.000 0.000
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1   0.000      0.995 1.000 0.000
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2   0.000      0.992 0.000 1.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1   0.000      0.995 1.000 0.000
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1   0.000      0.995 1.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     1   0.000      0.995 1.000 0.000
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2   0.000      0.992 0.000 1.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2   0.000      0.992 0.000 1.000
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1   0.000      0.995 1.000 0.000
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2   0.000      0.992 0.000 1.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2   0.000      0.992 0.000 1.000
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1   0.000      0.995 1.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1   0.000      0.995 1.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2   0.000      0.992 0.000 1.000
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2   0.000      0.992 0.000 1.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1   0.000      0.995 1.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1   0.000      0.995 1.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1   0.000      0.995 1.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2   0.000      0.992 0.000 1.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1   0.000      0.995 1.000 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2   0.000      0.992 0.000 1.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1   0.000      0.995 1.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1   0.000      0.995 1.000 0.000
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     1   0.000      0.995 1.000 0.000
#> 54504893-92C5-4328-85A8-2A882680B5E0     1   0.000      0.995 1.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1   0.000      0.995 1.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2   0.000      0.992 0.000 1.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1   0.000      0.995 1.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     1   0.000      0.995 1.000 0.000
#> D365A238-4739-4B54-9608-DC548F21C04E     1   0.000      0.995 1.000 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1   0.000      0.995 1.000 0.000
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1   0.000      0.995 1.000 0.000
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1   0.000      0.995 1.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1   0.000      0.995 1.000 0.000
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1   0.000      0.995 1.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1   0.000      0.995 1.000 0.000
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1   0.000      0.995 1.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     1   0.000      0.995 1.000 0.000
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1   0.000      0.995 1.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2   0.000      0.992 0.000 1.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1   0.000      0.995 1.000 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1   0.994      0.153 0.544 0.456
#> 9AF0E82E-E621-437A-8D19-700532B95090     1   0.000      0.995 1.000 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1   0.000      0.995 1.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1   0.000      0.995 1.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2   0.000      0.992 0.000 1.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1   0.000      0.995 1.000 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     1   0.891      0.551 0.692 0.308
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1   0.000      0.995 1.000 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1   0.932      0.462 0.652 0.348
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1   0.000      0.995 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1   0.000      0.995 1.000 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1   0.000      0.995 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1   0.000      0.995 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2   0.000      0.992 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1   0.000      0.995 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2   0.000      0.992 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1   0.000      0.995 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1   0.000      0.995 1.000 0.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1   0.000      0.995 1.000 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2   0.358      0.923 0.068 0.932
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1   0.000      0.995 1.000 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     1   0.000      0.995 1.000 0.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1   0.000      0.995 1.000 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1   0.000      0.995 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1   0.000      0.995 1.000 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1   0.000      0.995 1.000 0.000
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1   0.000      0.995 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1   0.000      0.995 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1   0.000      0.995 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2   0.000      0.992 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2   0.000      0.992 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1   0.000      0.995 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1   0.000      0.995 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1   0.000      0.995 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1   0.000      0.995 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.7075     0.1446 0.020 0.496 0.484
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4002     0.7196 0.160 0.000 0.840
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5835     0.5732 0.660 0.000 0.340
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.8104 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1289     0.8006 0.968 0.000 0.032
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0592     0.8080 0.988 0.000 0.012
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.9247     0.2085 0.156 0.392 0.452
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9208 0.000 1.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.5363     0.6740 0.724 0.000 0.276
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.2356     0.7749 0.928 0.000 0.072
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.8104 1.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0592     0.8114 0.988 0.000 0.012
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.5733     0.6179 0.676 0.000 0.324
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9208 0.000 1.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.1289     0.7648 0.032 0.000 0.968
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.5926     0.5685 0.644 0.000 0.356
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4504     0.7362 0.804 0.000 0.196
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.3619     0.7721 0.864 0.000 0.136
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.6062     0.3956 0.616 0.000 0.384
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.3116     0.7846 0.892 0.000 0.108
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9208 0.000 1.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0892     0.8055 0.980 0.000 0.020
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.8104 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.8104 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.6079     0.5043 0.612 0.000 0.388
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.6026     0.3902 0.624 0.000 0.376
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.5926     0.5685 0.644 0.000 0.356
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.8104 1.000 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9208 0.000 1.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9208 0.000 1.000 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.3941     0.7600 0.844 0.000 0.156
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.8104 1.000 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1411     0.8087 0.964 0.000 0.036
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.8104 1.000 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0237     0.9193 0.000 0.996 0.004
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.5138     0.6942 0.748 0.000 0.252
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5733     0.6096 0.676 0.000 0.324
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.4750     0.7730 0.000 0.784 0.216
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2165     0.7810 0.936 0.000 0.064
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.2448     0.7715 0.924 0.000 0.076
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9208 0.000 1.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.4702     0.7277 0.788 0.000 0.212
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.6204     0.4174 0.576 0.000 0.424
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.3038     0.7868 0.896 0.000 0.104
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#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.1529     0.7968 0.960 0.000 0.040
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     2  0.6111     0.5492 0.000 0.604 0.396
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000     0.9208 0.000 1.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     3  0.2066     0.7755 0.060 0.000 0.940
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0000     0.8104 1.000 0.000 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000     0.8104 1.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     3  0.2537     0.7793 0.080 0.000 0.920
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0747     0.8112 0.984 0.000 0.016
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.4178     0.8110 0.000 0.828 0.172
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     3  0.0237     0.7462 0.004 0.000 0.996
#> DD51C17C-300F-44A4-955A-C9BC85417842     1  0.6235     0.3829 0.564 0.000 0.436
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.0237     0.8097 0.996 0.000 0.004
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.3816     0.7651 0.852 0.000 0.148
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.3192     0.8568 0.000 0.888 0.112
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     3  0.0000     0.7429 0.000 0.000 1.000
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.2959     0.8652 0.000 0.900 0.100
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000     0.9208 0.000 1.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000     0.9208 0.000 1.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0000     0.8104 1.000 0.000 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     1  0.6252     0.3594 0.556 0.000 0.444
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     3  0.6026     0.5182 0.376 0.000 0.624
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.0892     0.8055 0.980 0.000 0.020
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.1964     0.7868 0.944 0.000 0.056
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     1  0.5905     0.5754 0.648 0.000 0.352
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     1  0.5905     0.5754 0.648 0.000 0.352
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4452     0.7410 0.808 0.000 0.192
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.2356     0.7749 0.928 0.000 0.072
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000     0.9208 0.000 1.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.5058     0.7013 0.756 0.000 0.244
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     1  0.6095     0.4952 0.608 0.000 0.392
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     3  0.2261     0.7773 0.068 0.000 0.932
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000     0.9208 0.000 1.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.1031     0.9098 0.000 0.976 0.024
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.5560     0.6055 0.700 0.000 0.300
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000     0.9208 0.000 1.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.8556     0.2260 0.256 0.596 0.148
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.0000     0.8104 1.000 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.2356     0.7749 0.928 0.000 0.072
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.2448     0.8816 0.000 0.924 0.076
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000     0.9208 0.000 1.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     1  0.5926     0.5685 0.644 0.000 0.356
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0000     0.8104 1.000 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.0000     0.8104 1.000 0.000 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0892     0.9116 0.000 0.980 0.020
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.1289     0.8013 0.968 0.000 0.032
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000     0.9208 0.000 1.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0000     0.8104 1.000 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     3  0.6244     0.3526 0.440 0.000 0.560
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.6126     0.3517 0.400 0.000 0.600
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.0000     0.8104 1.000 0.000 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0000     0.8104 1.000 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.2261     0.8861 0.000 0.932 0.068
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0000     0.8104 1.000 0.000 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.5926     0.5313 0.356 0.000 0.644
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0237     0.8097 0.996 0.000 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.1529     0.7970 0.960 0.000 0.040
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.5098     0.6975 0.752 0.000 0.248
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000     0.8104 1.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     3  0.6305     0.0102 0.484 0.000 0.516
#> 02ABB64E-768B-4999-A899-EEE573D5F186     1  0.5926     0.5685 0.644 0.000 0.356
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.5098     0.6975 0.752 0.000 0.248
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0424     0.8112 0.992 0.000 0.008
#> CCDB0290-91DA-4089-84A6-4434BA028D30     3  0.2625     0.7794 0.084 0.000 0.916
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.2165     0.7810 0.936 0.000 0.064
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0424     0.9176 0.000 0.992 0.008
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.2356     0.7979 0.928 0.000 0.072
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.6420     0.6342 0.688 0.024 0.288
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.1860     0.7894 0.948 0.000 0.052
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000     0.8104 1.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000     0.8104 1.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.9208 0.000 1.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5216     0.6874 0.740 0.000 0.260
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     3  0.1289     0.7125 0.000 0.032 0.968
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5988     0.5212 0.632 0.000 0.368
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.7250     0.5894 0.656 0.056 0.288
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.6291     0.3110 0.532 0.000 0.468
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     1  0.6204     0.4174 0.576 0.000 0.424
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.1411     0.7987 0.964 0.000 0.036
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.2356     0.7749 0.928 0.000 0.072
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9208 0.000 1.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0747     0.8069 0.984 0.000 0.016
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.2959     0.8652 0.000 0.900 0.100
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.5098     0.6975 0.752 0.000 0.248
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     3  0.0000     0.7429 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     1  0.6215     0.4109 0.572 0.000 0.428
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.9851    -0.2558 0.296 0.420 0.284
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5291     0.6805 0.732 0.000 0.268
#> 6752EED9-7990-433F-A206-D5398C396471     3  0.2625     0.7794 0.084 0.000 0.916
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5291     0.6805 0.732 0.000 0.268
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.6180     0.4357 0.584 0.000 0.416
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5291     0.6805 0.732 0.000 0.268
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.3482     0.7689 0.128 0.000 0.872
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3551     0.7648 0.868 0.000 0.132
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2165     0.7810 0.936 0.000 0.064
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.4931     0.6891 0.232 0.000 0.768
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9208 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9208 0.000 1.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.6308     0.1934 0.508 0.000 0.492
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.8104 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.5968     0.4634 0.636 0.000 0.364
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.8104 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.6795   -0.07554 0.000 0.472 0.096 0.432
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.2944   -0.14146 0.004 0.000 0.868 0.128
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.4852    0.68818 0.776 0.000 0.152 0.072
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1256    0.82786 0.964 0.000 0.008 0.028
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0779    0.83211 0.980 0.000 0.004 0.016
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.5840   -0.02729 0.044 0.144 0.748 0.064
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4964    0.51108 0.716 0.000 0.256 0.028
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0188    0.83108 0.996 0.000 0.000 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0817    0.82782 0.976 0.000 0.024 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.5137   -0.33411 0.544 0.000 0.452 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.4898    0.70789 0.000 0.000 0.416 0.584
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.4888    0.63182 0.412 0.000 0.588 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4331    0.34471 0.712 0.000 0.288 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4093    0.75919 0.832 0.000 0.072 0.096
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.6834    0.28878 0.600 0.000 0.176 0.224
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.1798    0.82414 0.944 0.000 0.040 0.016
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0672    0.83115 0.984 0.000 0.008 0.008
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1635    0.82222 0.948 0.000 0.008 0.044
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.4543    0.66938 0.324 0.000 0.676 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.6889    0.26727 0.592 0.000 0.232 0.176
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.4898    0.62758 0.416 0.000 0.584 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0336    0.82978 0.992 0.000 0.008 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0188    0.91917 0.000 0.996 0.004 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4297    0.74780 0.820 0.000 0.084 0.096
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.1398    0.82047 0.956 0.000 0.040 0.004
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.1059    0.83065 0.972 0.000 0.012 0.016
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0336    0.82901 0.992 0.000 0.008 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.1716    0.87512 0.000 0.936 0.064 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.2775    0.79736 0.896 0.000 0.084 0.020
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5576    0.61859 0.720 0.000 0.184 0.096
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.6650    0.08022 0.000 0.432 0.084 0.484
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1256    0.82732 0.964 0.000 0.028 0.008
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.4406    0.34146 0.700 0.000 0.300 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.4500    0.66418 0.316 0.000 0.684 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1109    0.82628 0.968 0.000 0.028 0.004
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.4996    0.53955 0.484 0.000 0.516 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0188    0.83127 0.996 0.000 0.004 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.2266    0.79610 0.912 0.000 0.084 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     4  0.6646    0.09559 0.000 0.428 0.084 0.488
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.5168    0.51507 0.496 0.000 0.500 0.004
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.2578    0.81005 0.912 0.000 0.052 0.036
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.4866    0.63286 0.404 0.000 0.596 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     4  0.4804    0.72748 0.000 0.000 0.384 0.616
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#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     4  0.6089    0.45462 0.000 0.280 0.080 0.640
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0592    0.91184 0.000 0.984 0.016 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     4  0.4356    0.76712 0.000 0.000 0.292 0.708
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.0336    0.82901 0.992 0.000 0.008 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     4  0.4356    0.76712 0.000 0.000 0.292 0.708
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     2  0.6391    0.35837 0.000 0.604 0.304 0.092
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     4  0.4916    0.70715 0.000 0.000 0.424 0.576
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.5453    0.64702 0.304 0.000 0.660 0.036
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.1151    0.82892 0.968 0.000 0.008 0.024
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.4362    0.74518 0.816 0.000 0.088 0.096
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.3754    0.79099 0.000 0.852 0.084 0.064
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     4  0.4730    0.73760 0.000 0.000 0.364 0.636
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.3485    0.80140 0.000 0.856 0.116 0.028
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.0188    0.83008 0.996 0.000 0.004 0.000
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.4426    0.49509 0.204 0.000 0.772 0.024
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     3  0.7762    0.05977 0.380 0.000 0.384 0.236
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.2198    0.80712 0.920 0.000 0.008 0.072
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.2342    0.80294 0.912 0.000 0.008 0.080
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.4916    0.61736 0.424 0.000 0.576 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.4907    0.62087 0.420 0.000 0.580 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.4549    0.73179 0.804 0.000 0.100 0.096
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.0592    0.83138 0.984 0.000 0.000 0.016
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.1890    0.80919 0.936 0.000 0.056 0.008
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.4624    0.67178 0.340 0.000 0.660 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     4  0.4356    0.76712 0.000 0.000 0.292 0.708
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2593    0.84042 0.000 0.892 0.004 0.104
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.6402    0.40468 0.624 0.000 0.108 0.268
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.5352    0.59232 0.140 0.760 0.092 0.008
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.1389    0.80621 0.952 0.000 0.048 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.2342    0.85097 0.000 0.912 0.080 0.008
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.4877    0.63204 0.408 0.000 0.592 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0469    0.83047 0.988 0.000 0.012 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.1302    0.81044 0.956 0.000 0.044 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.1305    0.89838 0.000 0.960 0.004 0.036
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.0469    0.82983 0.988 0.000 0.012 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     1  0.7450    0.02276 0.508 0.000 0.264 0.228
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     3  0.7344    0.14006 0.380 0.000 0.460 0.160
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1211    0.81252 0.960 0.000 0.040 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.2081    0.85691 0.000 0.916 0.084 0.000
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.0188    0.82995 0.996 0.000 0.004 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     3  0.7543    0.12220 0.392 0.000 0.420 0.188
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.0336    0.83123 0.992 0.000 0.008 0.000
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.0469    0.83158 0.988 0.000 0.000 0.012
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.2473    0.80301 0.908 0.000 0.080 0.012
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     1  0.6621    0.02661 0.508 0.000 0.408 0.084
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.4941    0.59974 0.436 0.000 0.564 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.2179    0.80576 0.924 0.000 0.064 0.012
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0937    0.83156 0.976 0.000 0.012 0.012
#> CCDB0290-91DA-4089-84A6-4434BA028D30     4  0.4356    0.76524 0.000 0.000 0.292 0.708
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.1970    0.87567 0.000 0.932 0.060 0.008
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.1022    0.82573 0.968 0.000 0.032 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.6072    0.63478 0.740 0.080 0.128 0.052
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2412    0.80177 0.908 0.000 0.008 0.084
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.3876    0.76108 0.836 0.000 0.124 0.040
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.2546    0.68781 0.000 0.008 0.092 0.900
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.5337    0.52957 0.696 0.000 0.260 0.044
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.6197    0.64248 0.732 0.052 0.128 0.088
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.5929    0.40227 0.640 0.000 0.296 0.064
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.4500    0.66418 0.316 0.000 0.684 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0672    0.83117 0.984 0.000 0.008 0.008
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0469    0.83158 0.988 0.000 0.000 0.012
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000    0.83049 1.000 0.000 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.3324    0.80250 0.000 0.852 0.136 0.012
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.1902    0.80808 0.932 0.000 0.064 0.004
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     4  0.4356    0.76712 0.000 0.000 0.292 0.708
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.5639    0.65344 0.324 0.000 0.636 0.040
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.4147    0.75944 0.068 0.844 0.076 0.012
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.4487    0.73684 0.808 0.000 0.100 0.092
#> 6752EED9-7990-433F-A206-D5398C396471     4  0.4356    0.76712 0.000 0.000 0.292 0.708
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.4700    0.71918 0.792 0.000 0.124 0.084
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.4643    0.67015 0.344 0.000 0.656 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.4700    0.71918 0.792 0.000 0.124 0.084
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.7854   -0.10948 0.304 0.000 0.400 0.296
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3984    0.70387 0.828 0.000 0.132 0.040
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0336    0.83124 0.992 0.000 0.008 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.7905   -0.27002 0.368 0.000 0.312 0.320
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000    0.92099 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.5169    0.61362 0.272 0.000 0.696 0.032
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0927    0.83005 0.976 0.000 0.008 0.016
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.6301    0.40553 0.636 0.000 0.260 0.104
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1256    0.82786 0.964 0.000 0.008 0.028

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.5296    0.79866 0.000 0.180 0.000 0.676 0.144
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.4675    0.47996 0.004 0.000 0.248 0.044 0.704
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.5163    0.77325 0.732 0.000 0.024 0.128 0.116
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2546    0.85688 0.904 0.000 0.012 0.036 0.048
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0968    0.87030 0.972 0.000 0.012 0.012 0.004
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4404    0.54155 0.000 0.112 0.792 0.024 0.072
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.6225    0.65975 0.648 0.000 0.184 0.060 0.108
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1153    0.86945 0.964 0.000 0.004 0.008 0.024
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0162    0.86755 0.996 0.000 0.004 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.1200    0.86920 0.964 0.000 0.016 0.012 0.008
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.6085    0.33280 0.372 0.000 0.528 0.016 0.084
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0290    0.96161 0.000 0.992 0.000 0.008 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.1638    0.71490 0.004 0.000 0.000 0.064 0.932
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.1043    0.73937 0.040 0.000 0.960 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.5401    0.17165 0.536 0.000 0.404 0.000 0.060
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.4657    0.79616 0.768 0.000 0.016 0.104 0.112
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     5  0.5901    0.23751 0.356 0.000 0.016 0.072 0.556
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0609    0.86918 0.980 0.000 0.020 0.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.3224    0.84373 0.864 0.000 0.012 0.044 0.080
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2228    0.74149 0.044 0.000 0.920 0.016 0.020
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     5  0.4150    0.58016 0.140 0.000 0.004 0.068 0.788
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.0609    0.73026 0.020 0.000 0.980 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.1485    0.85874 0.948 0.000 0.032 0.020 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0290    0.96161 0.000 0.992 0.000 0.008 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.4657    0.79616 0.768 0.000 0.016 0.104 0.112
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0290    0.86784 0.992 0.000 0.008 0.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.1469    0.85830 0.948 0.000 0.036 0.016 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.5154    0.78554 0.752 0.000 0.068 0.080 0.100
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.5519    0.76052 0.712 0.000 0.040 0.124 0.124
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     4  0.4351    0.87558 0.000 0.132 0.000 0.768 0.100
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0566    0.86629 0.984 0.000 0.004 0.012 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.3299    0.83997 0.848 0.000 0.004 0.040 0.108
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.3707    0.55557 0.716 0.000 0.284 0.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0932    0.73174 0.020 0.000 0.972 0.004 0.004
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1471    0.86783 0.952 0.000 0.020 0.004 0.024
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3274    0.64461 0.220 0.000 0.780 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2522    0.85584 0.896 0.000 0.004 0.024 0.076
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0693    0.86831 0.980 0.000 0.012 0.008 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.3495    0.84710 0.852 0.000 0.020 0.048 0.080
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
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#> 51667574-318E-4BDB-8F42-8512A4C1B84F     1  0.5426    0.71202 0.680 0.000 0.016 0.088 0.216
#> B0A442C9-67E4-4534-8A5C-D6D73F42358C     1  0.0693    0.86498 0.980 0.000 0.012 0.008 0.000
#> 25A5BC09-0D88-4385-87AF-997F9018522D     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 344B9631-AAA5-4302-8747-D584345D9131     3  0.4305    0.18966 0.488 0.000 0.512 0.000 0.000
#> 1C3795AD-6306-4892-95F5-92DF3375D46A     1  0.0162    0.86847 0.996 0.000 0.004 0.000 0.000
#> 17BB221D-8BF9-4391-83DD-423AE1E03651     1  0.5152    0.77663 0.736 0.000 0.028 0.128 0.108
#> 297611E9-9555-4BCA-A723-02E846ACC23A     1  0.0290    0.86943 0.992 0.000 0.000 0.008 0.000
#> AD7FF180-1EAC-4783-8A62-E9626B96DD9F     5  0.4668    0.50721 0.000 0.008 0.048 0.220 0.724
#> FD544083-9BD5-4036-BD81-0352B67CC45C     1  0.2513    0.80305 0.876 0.000 0.116 0.008 0.000
#> 879A74D5-5B29-418D-A0F4-8E88D6384008     1  0.1538    0.86160 0.948 0.000 0.036 0.008 0.008
#> 43CD982C-13C0-4A52-803A-9A3A3FAE09BC     1  0.0290    0.86706 0.992 0.000 0.008 0.000 0.000
#> DCD0313D-5206-4111-8743-A8A0227257D9     5  0.1243    0.72798 0.028 0.000 0.004 0.008 0.960
#> 331A9160-D730-45DD-A985-C6CAC03035ED     1  0.0162    0.86755 0.996 0.000 0.004 0.000 0.000
#> 9EEECA0E-530D-4724-B016-A716F0782148     1  0.6623    0.66318 0.628 0.000 0.140 0.128 0.104
#> B3073976-CA3F-4115-9243-8C2D9E1B975D     1  0.2879    0.85362 0.880 0.000 0.008 0.032 0.080
#> 77B3C9B4-1A7F-41BB-A37D-01EF80E933CC     4  0.3631    0.88254 0.000 0.072 0.000 0.824 0.104
#> C0C26822-2E9F-4FB0-81D4-575027C8B71C     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> F1FCE328-2B3B-499A-888D-0E66A017E8B0     5  0.2230    0.67788 0.000 0.000 0.000 0.116 0.884
#> F069DAD6-F1EB-42F7-8252-F3F6EC46CC3E     1  0.1568    0.85681 0.944 0.000 0.036 0.020 0.000
#> 99CC822E-8C98-4EEC-BB58-AEF76A0B5332     1  0.0162    0.86755 0.996 0.000 0.004 0.000 0.000
#> C86EBD08-53F2-4972-801A-74970FDD6A62     5  0.2127    0.68272 0.000 0.000 0.000 0.108 0.892
#> F07326F2-C1D6-4D5A-9693-25C3A04B0EC2     1  0.0162    0.86856 0.996 0.000 0.004 0.000 0.000
#> 8ACBD428-7713-48D9-810A-43C9CD191A73     4  0.5355    0.85699 0.000 0.124 0.016 0.704 0.156
#> 3D3501B4-1A43-4FA7-90A2-CCEBF66BFD4A     5  0.2677    0.67746 0.000 0.000 0.016 0.112 0.872
#> DD51C17C-300F-44A4-955A-C9BC85417842     3  0.3118    0.67036 0.008 0.004 0.860 0.016 0.112
#> 58FF391C-1D83-426C-8F92-C15F78F56C95     1  0.1518    0.86565 0.952 0.000 0.012 0.020 0.016
#> ACE65C6E-2B10-4972-91B4-9199DD4B179D     1  0.4657    0.79616 0.768 0.000 0.016 0.104 0.112
#> B2088466-FA5D-491C-9982-99B33683E66F     2  0.5602    0.25820 0.000 0.620 0.008 0.288 0.084
#> D47AF416-1687-4FE0-A235-8815B6E8EB0B     5  0.2179    0.68081 0.000 0.000 0.000 0.112 0.888
#> 4DCAD07F-CC43-46F6-B2F3-EDBF3EDD1045     2  0.2177    0.85985 0.000 0.908 0.008 0.004 0.080
#> AAAE0BD9-63FC-4A0E-A27E-447B634BAD99     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> BC471AA1-52CF-4CEE-9866-34CE91404F45     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 81D3EE3F-AC11-404F-8092-307F0DC12198     1  0.1356    0.86632 0.956 0.000 0.012 0.028 0.004
#> 8C02026C-C25E-406B-B8B8-A1A82362AE79     3  0.1412    0.70240 0.004 0.000 0.952 0.008 0.036
#> 6A005F2A-A0C1-4CA4-B15B-96B08F013874     5  0.1195    0.72809 0.028 0.000 0.000 0.012 0.960
#> B55743F2-4D63-4375-85D3-F58281CFD852     1  0.3883    0.82354 0.820 0.000 0.012 0.060 0.108
#> 24F98393-C817-4D0E-A7DB-05D2B5C71F40     1  0.4048    0.82207 0.812 0.000 0.016 0.064 0.108
#> 2C2AEF1D-4112-4EC7-9027-5E3FD26E8802     3  0.1341    0.74289 0.056 0.000 0.944 0.000 0.000
#> 8BAC3CB5-2987-4349-8AE8-B83DDD16CA3C     3  0.2648    0.69676 0.152 0.000 0.848 0.000 0.000
#> ED9C74E6-92FC-4E58-8FCE-1761DEA0C977     1  0.5111    0.77901 0.740 0.000 0.028 0.120 0.112
#> BA732ED4-F6BA-404E-BA3C-CA558FAD866A     1  0.3628    0.83701 0.836 0.000 0.012 0.048 0.104
#> E750385A-12D9-4A88-B4DF-C1306B5EF3B7     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 6B1DC5E4-5F82-4395-913F-6AEDB5B63188     1  0.4473    0.78516 0.772 0.000 0.160 0.024 0.044
#> A7C12D37-FD50-4674-A054-1774F4E5C3B3     3  0.0609    0.73026 0.020 0.000 0.980 0.000 0.000
#> 2155C764-2063-4D9C-9ACD-96AA73475F5E     5  0.2127    0.68272 0.000 0.000 0.000 0.108 0.892
#> DE23CC15-A95E-4119-9B3C-8EEC45900D11     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 5DB1DCAD-638E-48A4-9F40-3D6268FDEC33     2  0.2248    0.87850 0.000 0.900 0.000 0.088 0.012
#> 34AF0341-73D7-4080-AAEB-4C1541C2569F     1  0.5682    0.59863 0.616 0.000 0.016 0.072 0.296
#> B60D4235-44AF-4BA4-98C0-BCCDC28E90B9     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> CF463D89-2C9F-4257-BF04-8BC1CD40EA7D     2  0.2426    0.87023 0.008 0.908 0.064 0.016 0.004
#> EF6C8165-484A-4530-AEDF-93DCC4A8455D     1  0.1121    0.86310 0.956 0.000 0.044 0.000 0.000
#> B9F6B5E4-4D10-49B8-A8FE-8F33C5A62CBF     1  0.0968    0.86991 0.972 0.000 0.004 0.012 0.012
#> CE539000-92D7-4622-9C8D-BC6E01310681     2  0.0833    0.94649 0.000 0.976 0.004 0.004 0.016
#> D3BBC405-A22A-4009-ABF6-96FEEE653051     2  0.0290    0.96161 0.000 0.992 0.000 0.008 0.000
#> 0B3C86BD-0D20-4408-9BE3-05658729505F     3  0.0963    0.73830 0.036 0.000 0.964 0.000 0.000
#> 9B9C5071-7C3F-416C-B91C-6F5966747F54     1  0.0290    0.86738 0.992 0.000 0.008 0.000 0.000
#> A9469A4A-C5F9-4681-A916-A26F0B4307BA     1  0.2929    0.76215 0.840 0.000 0.152 0.008 0.000
#> A31B57E4-E30B-4A1B-829D-1B47D9CEC041     2  0.0609    0.95704 0.000 0.980 0.000 0.020 0.000
#> 647255CE-F84A-4070-B3FD-D8ACA32C4D09     1  0.1399    0.86037 0.952 0.000 0.028 0.020 0.000
#> 8F5E9F02-51D7-410E-B8B7-22737F2F095A     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 8074A7F6-2FDE-4578-B71C-01C542D468FE     1  0.0162    0.86847 0.996 0.000 0.004 0.000 0.000
#> 2A946F17-F245-409E-A019-C60CDA18DC7D     5  0.1800    0.70701 0.048 0.000 0.000 0.020 0.932
#> 0878C381-47F9-4786-82C2-94AC840BEDCB     5  0.1753    0.71104 0.032 0.000 0.000 0.032 0.936
#> 54504893-92C5-4328-85A8-2A882680B5E0     1  0.1493    0.85833 0.948 0.000 0.028 0.024 0.000
#> 0A27D1BE-E5DD-459A-A51F-6D8AAF7CFEB4     1  0.0404    0.86842 0.988 0.000 0.012 0.000 0.000
#> 89ED5A3E-CAC0-4AB4-B858-A3CD8F34DBD5     2  0.1862    0.90788 0.000 0.932 0.048 0.004 0.016
#> ACEEB0A5-AADB-4EF9-8710-4BAF95522CEA     1  0.1399    0.86037 0.952 0.000 0.028 0.020 0.000
#> 02C74D81-5976-4252-BC6C-B10E934DECA2     5  0.1300    0.72116 0.028 0.000 0.000 0.016 0.956
#> D365A238-4739-4B54-9608-DC548F21C04E     1  0.1059    0.86972 0.968 0.000 0.008 0.020 0.004
#> F70F7ED5-A3B7-4210-95AD-DEFA0A565F06     1  0.1739    0.86723 0.940 0.000 0.004 0.024 0.032
#> A92C23A9-BC25-4025-9501-6D5FF8E2A502     1  0.4943    0.78691 0.768 0.000 0.088 0.072 0.072
#> ECE9BBF4-840E-47A6-8378-0B6C4A2369D3     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> 38749490-0FCF-4B33-9EBC-8F86C2D9E4AF     5  0.4330    0.56665 0.164 0.000 0.044 0.016 0.776
#> 02ABB64E-768B-4999-A899-EEE573D5F186     3  0.0703    0.73322 0.024 0.000 0.976 0.000 0.000
#> C1C467A8-18B1-4C3F-AC45-33359ED6FDC4     1  0.4528    0.75066 0.756 0.000 0.172 0.064 0.008
#> 78B2E4A1-9DAE-404F-AB47-1896450EF254     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> CCDB0290-91DA-4089-84A6-4434BA028D30     5  0.1732    0.70002 0.000 0.000 0.000 0.080 0.920
#> D5041E80-20A0-4C1A-9AC1-2394F6DB6E92     1  0.1074    0.86547 0.968 0.000 0.016 0.012 0.004
#> 20EB9CC6-EABB-438A-9030-E766459996D1     2  0.0880    0.94984 0.000 0.968 0.000 0.032 0.000
#> 73E99110-9A7C-4F73-98C5-79D22CB06230     1  0.3663    0.76130 0.776 0.000 0.208 0.016 0.000
#> FAD8A464-9BC3-4ED9-9517-B18D36514325     1  0.8758    0.12488 0.388 0.320 0.080 0.112 0.100
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4048    0.82207 0.812 0.000 0.016 0.064 0.108
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.0162    0.86755 0.996 0.000 0.004 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.0703    0.86705 0.976 0.000 0.024 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     1  0.5744    0.75063 0.708 0.000 0.100 0.092 0.100
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     4  0.3141    0.81434 0.000 0.016 0.000 0.832 0.152
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     1  0.6354    0.70900 0.660 0.004 0.076 0.128 0.132
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     1  0.7766    0.59760 0.584 0.100 0.080 0.128 0.108
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     5  0.5483    0.30435 0.332 0.000 0.048 0.016 0.604
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.1278    0.73326 0.020 0.000 0.960 0.016 0.004
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000    0.86789 1.000 0.000 0.000 0.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.3141    0.84556 0.860 0.000 0.004 0.040 0.096
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000    0.96201 0.000 1.000 0.000 0.000 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0579    0.86585 0.984 0.000 0.008 0.008 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.2678    0.84442 0.000 0.880 0.100 0.004 0.016
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.3629    0.84064 0.848 0.000 0.056 0.028 0.068
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.2179    0.68081 0.000 0.000 0.000 0.112 0.888
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.4361    0.64739 0.160 0.000 0.776 0.048 0.016
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.3381    0.81053 0.016 0.864 0.064 0.052 0.004
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.5199    0.77354 0.732 0.000 0.028 0.128 0.112
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.2020    0.68837 0.000 0.000 0.000 0.100 0.900
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.5325    0.76746 0.724 0.000 0.032 0.128 0.116
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0609    0.73026 0.020 0.000 0.980 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.5116    0.77644 0.736 0.000 0.024 0.128 0.112
#> 1ABBEF80-508F-4247-B43D-3E549372113B     5  0.0404    0.71971 0.000 0.000 0.000 0.012 0.988
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5203    0.72468 0.708 0.000 0.140 0.008 0.144
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0162    0.86755 0.996 0.000 0.004 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     5  0.1211    0.72727 0.024 0.000 0.000 0.016 0.960
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0510    0.95991 0.000 0.984 0.000 0.016 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.1405    0.73270 0.020 0.000 0.956 0.016 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0404    0.86842 0.988 0.000 0.012 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.6207    0.19930 0.464 0.000 0.016 0.088 0.432
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.2149    0.86157 0.924 0.000 0.012 0.028 0.036

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.3725    0.76379 0.000 0.128 0.000 0.804 0.040 0.028
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     6  0.4347    0.47770 0.000 0.000 0.288 0.004 0.040 0.668
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.4195    0.60862 0.440 0.000 0.004 0.000 0.548 0.008
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.3317    0.66077 0.808 0.000 0.156 0.000 0.032 0.004
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2669    0.68219 0.836 0.000 0.156 0.000 0.008 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0547    0.71516 0.980 0.000 0.000 0.000 0.020 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.3364    0.53281 0.024 0.000 0.820 0.140 0.012 0.004
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0891    0.88976 0.000 0.968 0.000 0.008 0.024 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.4393    0.36760 0.704 0.000 0.224 0.000 0.068 0.004
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.1714    0.67116 0.908 0.000 0.000 0.000 0.092 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.3025    0.67753 0.820 0.000 0.156 0.000 0.024 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0291    0.71751 0.992 0.000 0.000 0.004 0.004 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.4076    0.52922 0.428 0.000 0.564 0.000 0.004 0.004
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.2794    0.88293 0.000 0.860 0.000 0.060 0.080 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.1116    0.70160 0.000 0.000 0.008 0.004 0.028 0.960
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.2597    0.76324 0.176 0.000 0.824 0.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.4174    0.13843 0.628 0.000 0.352 0.000 0.016 0.004
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.5659    0.01834 0.552 0.000 0.156 0.000 0.284 0.008
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     6  0.6277    0.00868 0.364 0.000 0.008 0.000 0.260 0.368
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.2980    0.67429 0.808 0.000 0.180 0.000 0.012 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.1398    0.89047 0.000 0.940 0.000 0.008 0.052 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2768    0.67669 0.832 0.000 0.156 0.000 0.012 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4706    0.51300 0.696 0.000 0.156 0.000 0.144 0.004
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0458    0.71633 0.984 0.000 0.000 0.000 0.016 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2527    0.76133 0.168 0.000 0.832 0.000 0.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     6  0.4513    0.58610 0.152 0.000 0.008 0.000 0.116 0.724
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2562    0.76236 0.172 0.000 0.828 0.000 0.000 0.000
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#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.2527    0.75995 0.168 0.000 0.832 0.000 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.4204   -0.44706 0.540 0.000 0.008 0.000 0.448 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     6  0.1542    0.71119 0.004 0.000 0.008 0.000 0.052 0.936
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.4715    0.46206 0.696 0.000 0.040 0.000 0.040 0.224
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2945    0.67740 0.824 0.000 0.156 0.000 0.020 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     6  0.1845    0.70900 0.004 0.000 0.008 0.000 0.072 0.916
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.2910    0.88017 0.000 0.852 0.000 0.068 0.080 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.2794    0.88318 0.000 0.860 0.000 0.060 0.080 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.2810    0.75227 0.156 0.000 0.832 0.000 0.008 0.004
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.3025    0.66935 0.820 0.000 0.156 0.000 0.024 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     6  0.6235    0.09354 0.352 0.000 0.008 0.000 0.244 0.396
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.4520    0.55256 0.716 0.000 0.156 0.000 0.124 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-mclust-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.


ATC:NMF*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "NMF"]
# you can also extract it by
# res = res_list["ATC:NMF"]

A summary of res and all the functions that can be applied to it:

res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 17469 rows and 309 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)
#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.946           0.943       0.976         0.4424 0.565   0.565
#> 3 3 0.668           0.785       0.899         0.1376 0.889   0.806
#> 4 4 0.520           0.726       0.840         0.3757 0.750   0.507
#> 5 5 0.676           0.729       0.856         0.1038 0.856   0.574
#> 6 6 0.659           0.584       0.785         0.0518 0.927   0.712

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)
#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#>                                      class entropy silhouette    p1    p2
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0000     0.9784 0.000 1.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     1  0.0000     0.9739 1.000 0.000
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.2603     0.9358 0.956 0.044
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000     0.9739 1.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000     0.9739 1.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000     0.9739 1.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.0000     0.9784 0.000 1.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.9784 0.000 1.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000     0.9739 1.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0000     0.9739 1.000 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0000     0.9739 1.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000     0.9739 1.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000     0.9739 1.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.0000     0.9784 0.000 1.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     1  0.0376     0.9707 0.996 0.004
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000     0.9739 1.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.0000     0.9739 1.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000     0.9739 1.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.0000     0.9739 1.000 0.000
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0000     0.9739 1.000 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.9784 0.000 1.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0000     0.9739 1.000 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000     0.9739 1.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000     0.9739 1.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0000     0.9739 1.000 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.0000     0.9739 1.000 0.000
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0000     0.9739 1.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0000     0.9739 1.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.9784 0.000 1.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.0000     0.9784 0.000 1.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0000     0.9739 1.000 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0000     0.9739 1.000 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0000     0.9739 1.000 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0000     0.9739 1.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.0000     0.9784 0.000 1.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1184     0.9609 0.984 0.016
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.7056     0.7620 0.808 0.192
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.9784 0.000 1.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0000     0.9739 1.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0000     0.9739 1.000 0.000
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.0000     0.9784 0.000 1.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0000     0.9739 1.000 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.3733     0.9098 0.928 0.072
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0000     0.9739 1.000 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0000     0.9739 1.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0000     0.9739 1.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0000     0.9739 1.000 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.9784 0.000 1.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0000     0.9739 1.000 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0000     0.9784 0.000 1.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0000     0.9739 1.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0000     0.9784 0.000 1.000
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0000     0.9739 1.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0000     0.9739 1.000 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0000     0.9739 1.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.2603     0.9356 0.956 0.044
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     1  0.9044     0.5310 0.680 0.320
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0000     0.9739 1.000 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.9784 0.000 1.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0000     0.9739 1.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000     0.9739 1.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.6247     0.8100 0.156 0.844
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0000     0.9739 1.000 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0000     0.9739 1.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.9784 0.000 1.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     2  0.9286     0.4783 0.344 0.656
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0000     0.9739 1.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0000     0.9739 1.000 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     1  0.0000     0.9739 1.000 0.000
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.0000     0.9784 0.000 1.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0000     0.9739 1.000 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0000     0.9739 1.000 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0000     0.9739 1.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000     0.9739 1.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0000     0.9739 1.000 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0000     0.9739 1.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000     0.9739 1.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0000     0.9784 0.000 1.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     1  0.9996     0.0454 0.512 0.488
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0000     0.9784 0.000 1.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0000     0.9739 1.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     2  0.6048     0.8213 0.148 0.852
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.0000     0.9739 1.000 0.000
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0000     0.9739 1.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0000     0.9739 1.000 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0000     0.9739 1.000 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000     0.9739 1.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.0000     0.9784 0.000 1.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.9784 0.000 1.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000     0.9739 1.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000     0.9739 1.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0000     0.9739 1.000 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.0000     0.9784 0.000 1.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0000     0.9739 1.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0000     0.9739 1.000 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0000     0.9739 1.000 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.8207     0.6620 0.744 0.256
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.7056     0.7617 0.808 0.192
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0000     0.9739 1.000 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000     0.9739 1.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     2  0.0376     0.9754 0.004 0.996
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000     0.9784 0.000 1.000
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#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     2  0.0000     0.9784 0.000 1.000
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     2  0.0000     0.9784 0.000 1.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     2  0.0938     0.9691 0.012 0.988
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     1  0.0000     0.9739 1.000 0.000
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     2  0.3274     0.9265 0.060 0.940
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0000     0.9739 1.000 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0000     0.9739 1.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     2  0.0000     0.9784 0.000 1.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0000     0.9739 1.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     2  0.0000     0.9784 0.000 1.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     1  0.0000     0.9739 1.000 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     1  0.9522     0.4094 0.628 0.372
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     2  0.0938     0.9691 0.012 0.988
#> C98275CD-C39A-4E14-A731-4F3EB7396665     2  0.0376     0.9755 0.004 0.996
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     1  0.3274     0.9199 0.940 0.060
#> 6752EED9-7990-433F-A206-D5398C396471     1  0.0376     0.9707 0.996 0.004
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     1  0.9522     0.4221 0.628 0.372
#> CE6B6871-3ED3-44DE-A777-7558D4429057     1  0.0000     0.9739 1.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0376     0.9708 0.996 0.004
#> 1ABBEF80-508F-4247-B43D-3E549372113B     1  0.9998     0.0290 0.508 0.492
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.0000     0.9739 1.000 0.000
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0000     0.9739 1.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.0000     0.9739 1.000 0.000
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.9784 0.000 1.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.9784 0.000 1.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0000     0.9739 1.000 0.000
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000     0.9739 1.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0000     0.9739 1.000 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0000     0.9739 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.0237      0.604 0.000 0.996 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.0424      0.837 0.008 0.000 0.992
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     1  0.0424      0.939 0.992 0.008 0.000
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.0000      0.943 1.000 0.000 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.0000      0.943 1.000 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.0000      0.943 1.000 0.000 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     2  0.5859      0.664 0.344 0.656 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.4235      0.657 0.176 0.824 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     1  0.0000      0.943 1.000 0.000 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0237      0.942 0.996 0.000 0.004
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.0237      0.941 0.996 0.004 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0000      0.943 1.000 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     1  0.0000      0.943 1.000 0.000 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.3192      0.642 0.112 0.888 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     3  0.0237      0.839 0.004 0.000 0.996
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     1  0.0000      0.943 1.000 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     1  0.1860      0.901 0.948 0.000 0.052
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.0000      0.943 1.000 0.000 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.5098      0.658 0.752 0.000 0.248
#> C204D355-B876-4341-A111-36D48CBDD2A8     1  0.0237      0.941 0.996 0.004 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0424      0.613 0.008 0.992 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.0237      0.942 0.996 0.000 0.004
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0000      0.943 1.000 0.000 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0000      0.943 1.000 0.000 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     1  0.0424      0.941 0.992 0.000 0.008
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.5178      0.644 0.744 0.000 0.256
#> 2B5DD791-7692-4721-9519-7D7D49B52570     1  0.0237      0.941 0.996 0.004 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     1  0.0237      0.942 0.996 0.000 0.004
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0237      0.611 0.004 0.996 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.5968      0.659 0.364 0.636 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.0237      0.941 0.996 0.004 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     1  0.0237      0.941 0.996 0.004 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.0237      0.941 0.996 0.004 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.0424      0.941 0.992 0.000 0.008
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.5835      0.665 0.340 0.660 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     1  0.1411      0.909 0.964 0.036 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     1  0.1031      0.923 0.976 0.024 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0237      0.604 0.000 0.996 0.004
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0237      0.942 0.996 0.000 0.004
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0747      0.935 0.984 0.000 0.016
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.5706      0.667 0.320 0.680 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     1  0.0237      0.941 0.996 0.004 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     1  0.3192      0.803 0.888 0.112 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.0237      0.941 0.996 0.004 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     1  0.0237      0.942 0.996 0.000 0.004
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.0424      0.941 0.992 0.000 0.008
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.0237      0.942 0.996 0.000 0.004
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0592      0.615 0.012 0.988 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     1  0.0237      0.942 0.996 0.000 0.004
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.0237      0.611 0.004 0.996 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0237      0.941 0.996 0.004 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0592      0.596 0.000 0.988 0.012
#> B507E82F-6680-497B-A014-033EDD7A2E03     1  0.0424      0.941 0.992 0.000 0.008
#> F941890E-AB33-478F-8C97-1C785DD9428F     1  0.0237      0.941 0.996 0.004 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0237      0.942 0.996 0.000 0.004
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     1  0.0747      0.931 0.984 0.016 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     3  0.0237      0.839 0.000 0.004 0.996
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     1  0.0237      0.941 0.996 0.004 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0237      0.604 0.000 0.996 0.004
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0237      0.942 0.996 0.000 0.004
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.0000      0.943 1.000 0.000 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     2  0.6260      0.547 0.448 0.552 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     1  0.0237      0.941 0.996 0.004 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0237      0.942 0.996 0.000 0.004
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0237      0.611 0.004 0.996 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     3  0.4002      0.782 0.000 0.160 0.840
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0237      0.941 0.996 0.004 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     1  0.0237      0.942 0.996 0.000 0.004
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.4654      0.611 0.208 0.000 0.792
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.6111      0.634 0.396 0.604 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.0424      0.941 0.992 0.000 0.008
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0424      0.941 0.992 0.000 0.008
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     1  0.0424      0.941 0.992 0.000 0.008
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0000      0.943 1.000 0.000 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.0237      0.941 0.996 0.004 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0424      0.941 0.992 0.000 0.008
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     1  0.0000      0.943 1.000 0.000 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0237      0.611 0.004 0.996 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.5360      0.555 0.220 0.012 0.768
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0237      0.604 0.000 0.996 0.004
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.0237      0.942 0.996 0.000 0.004
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     3  0.1643      0.828 0.000 0.044 0.956
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.6244      0.224 0.560 0.000 0.440
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0237      0.942 0.996 0.000 0.004
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0424      0.941 0.992 0.000 0.008
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     1  0.0237      0.941 0.996 0.004 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     1  0.0000      0.943 1.000 0.000 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.5835      0.665 0.340 0.660 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0237      0.604 0.000 0.996 0.004
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     1  0.0000      0.943 1.000 0.000 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.0000      0.943 1.000 0.000 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     1  0.0237      0.942 0.996 0.000 0.004
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.1411      0.622 0.036 0.964 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     1  0.0237      0.942 0.996 0.000 0.004
#> D587A993-3C47-4D4C-B744-59169D4F7451     1  0.0237      0.941 0.996 0.004 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.0237      0.941 0.996 0.004 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     1  0.4555      0.639 0.800 0.200 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.3482      0.778 0.872 0.128 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.0237      0.941 0.996 0.004 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     1  0.0000      0.943 1.000 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     3  0.6126      0.624 0.000 0.400 0.600
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0237      0.611 0.004 0.996 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0237      0.611 0.004 0.996 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0237      0.941 0.996 0.004 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     1  0.0237      0.942 0.996 0.000 0.004
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0237      0.611 0.004 0.996 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     2  0.6252      0.556 0.444 0.556 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     1  0.0424      0.941 0.992 0.000 0.008
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.0237      0.942 0.996 0.000 0.004
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     2  0.6111      0.633 0.396 0.604 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0237      0.611 0.004 0.996 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     1  0.1031      0.923 0.976 0.024 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     3  0.0000      0.839 0.000 0.000 1.000
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     3  0.3619      0.712 0.136 0.000 0.864
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     1  0.0237      0.941 0.996 0.004 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.0424      0.941 0.992 0.000 0.008
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.5363      0.598 0.724 0.000 0.276
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     1  0.0592      0.935 0.988 0.012 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0000      0.943 1.000 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.0237      0.941 0.996 0.004 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.6168      0.299 0.588 0.000 0.412
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.5497      0.586 0.708 0.000 0.292
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.0000      0.943 1.000 0.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.0000      0.943 1.000 0.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     2  0.6280      0.519 0.460 0.540 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     2  0.5650      0.668 0.312 0.688 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.0475      0.608 0.004 0.992 0.004
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0000      0.943 1.000 0.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     3  0.0747      0.837 0.000 0.016 0.984
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     3  0.0237      0.839 0.004 0.000 0.996
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     1  0.0237      0.941 0.996 0.004 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.0237      0.941 0.996 0.004 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0592      0.596 0.000 0.988 0.012
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.5058      0.665 0.756 0.000 0.244
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     2  0.4178      0.657 0.172 0.828 0.000
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#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     1  0.0237      0.941 0.996 0.004 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     3  0.6180      0.222 0.416 0.000 0.584
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.5733      0.511 0.676 0.000 0.324
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0237      0.941 0.996 0.004 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     3  0.0424      0.837 0.008 0.000 0.992
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000      0.607 0.000 1.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0237      0.611 0.004 0.996 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     1  0.0424      0.941 0.992 0.000 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     1  0.0000      0.943 1.000 0.000 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.0892      0.932 0.980 0.000 0.020
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0237      0.941 0.996 0.004 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     2  0.5883     0.7120 0.128 0.700 0.172 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     4  0.1452     0.8425 0.008 0.000 0.036 0.956
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     3  0.4334     0.6773 0.160 0.004 0.804 0.032
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.1867     0.8237 0.928 0.000 0.072 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.2814     0.8373 0.868 0.000 0.132 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1389     0.8335 0.952 0.000 0.048 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2760     0.7308 0.000 0.128 0.872 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     3  0.2973     0.7285 0.144 0.000 0.856 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0469     0.8104 0.988 0.000 0.012 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.2814     0.8378 0.868 0.000 0.132 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.2011     0.7888 0.080 0.000 0.920 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     2  0.3853     0.7793 0.020 0.820 0.160 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     4  0.0000     0.8529 0.000 0.000 0.000 1.000
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.3444     0.7368 0.184 0.000 0.816 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.4248     0.6878 0.220 0.000 0.768 0.012
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     1  0.2216     0.7530 0.908 0.000 0.092 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.2401     0.7547 0.904 0.000 0.004 0.092
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.0817     0.7793 0.024 0.000 0.976 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.2647     0.8408 0.880 0.000 0.120 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.0817     0.8046 0.976 0.000 0.024 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.2149     0.8430 0.912 0.000 0.088 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.2011     0.7877 0.080 0.000 0.920 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.1389     0.8128 0.952 0.000 0.000 0.048
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.2973     0.7706 0.144 0.000 0.856 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.4948     0.1541 0.440 0.000 0.560 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     2  0.5346     0.7379 0.076 0.732 0.192 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     1  0.2345     0.7449 0.900 0.000 0.100 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     3  0.1474     0.7871 0.052 0.000 0.948 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4643     0.5905 0.656 0.000 0.344 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2921     0.8344 0.860 0.000 0.140 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.3942     0.6878 0.000 0.764 0.236 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     3  0.3224     0.7517 0.120 0.016 0.864 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     3  0.3306     0.6910 0.156 0.004 0.840 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.2704     0.8421 0.876 0.000 0.124 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.2843     0.8438 0.892 0.000 0.088 0.020
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.4164     0.7305 0.000 0.736 0.264 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.2011     0.7891 0.080 0.000 0.920 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2216     0.7866 0.092 0.000 0.908 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.1716     0.8394 0.936 0.000 0.064 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.3569     0.7241 0.196 0.000 0.804 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1118     0.8299 0.964 0.000 0.036 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.1211     0.7824 0.040 0.000 0.960 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.1474     0.8156 0.000 0.948 0.052 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.0188     0.8131 0.000 0.996 0.000 0.004
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.3649     0.7141 0.204 0.000 0.796 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     3  0.3837     0.6951 0.224 0.000 0.776 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.0336     0.7731 0.008 0.000 0.992 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     4  0.0000     0.8529 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     3  0.1302     0.7811 0.044 0.000 0.956 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.4304     0.7111 0.716 0.000 0.284 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     3  0.6317     0.3999 0.116 0.240 0.644 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.2281     0.7886 0.096 0.000 0.904 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     4  0.2281     0.8227 0.000 0.096 0.000 0.904
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4008     0.6648 0.244 0.000 0.756 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     4  0.4638     0.6819 0.044 0.000 0.180 0.776
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     2  0.6390     0.6774 0.132 0.644 0.224 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.1118     0.7978 0.964 0.000 0.036 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.0469     0.8104 0.988 0.000 0.012 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.3266     0.7536 0.168 0.000 0.832 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0469     0.8104 0.988 0.000 0.012 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.4746     0.5070 0.632 0.000 0.368 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.2530     0.8425 0.888 0.000 0.112 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     3  0.2469     0.7906 0.108 0.000 0.892 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0336     0.8171 0.000 0.992 0.008 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     4  0.3853     0.7306 0.020 0.000 0.160 0.820
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.0188     0.8140 0.000 0.996 0.004 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.2704     0.8400 0.876 0.000 0.124 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     4  0.0707     0.8497 0.000 0.020 0.000 0.980
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.2704     0.7251 0.876 0.000 0.000 0.124
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.2760     0.8384 0.872 0.000 0.128 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0592     0.8085 0.984 0.000 0.016 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     3  0.3688     0.7292 0.208 0.000 0.792 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.3688     0.7327 0.208 0.000 0.792 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     2  0.6240     0.6878 0.136 0.664 0.200 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     3  0.3074     0.7337 0.152 0.000 0.848 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.2345     0.8361 0.900 0.000 0.100 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.3444     0.7388 0.184 0.000 0.816 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.4134     0.7297 0.000 0.740 0.260 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.2973     0.7709 0.144 0.000 0.856 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     3  0.4999     0.2088 0.492 0.000 0.508 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.3907     0.7570 0.768 0.000 0.232 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     3  0.5432     0.6204 0.216 0.068 0.716 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     1  0.4868     0.5672 0.748 0.040 0.212 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.4250     0.6669 0.724 0.000 0.276 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.2973     0.7711 0.144 0.000 0.856 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     4  0.3224     0.8067 0.016 0.120 0.000 0.864
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0707     0.8177 0.000 0.980 0.020 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.2760     0.8389 0.872 0.000 0.128 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     3  0.2647     0.7852 0.120 0.000 0.880 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0336     0.8169 0.000 0.992 0.008 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     3  0.6673     0.3254 0.140 0.252 0.608 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.3311     0.7482 0.172 0.000 0.828 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.3942     0.7560 0.764 0.000 0.236 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     3  0.5940     0.4815 0.120 0.188 0.692 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0592     0.8181 0.000 0.984 0.016 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     3  0.4158     0.6737 0.224 0.008 0.768 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     4  0.2515     0.8233 0.012 0.004 0.072 0.912
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     4  0.3117     0.7915 0.092 0.000 0.028 0.880
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     3  0.3400     0.7619 0.180 0.000 0.820 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.3123     0.8263 0.844 0.000 0.156 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.1118     0.8161 0.964 0.000 0.000 0.036
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     3  0.5292     0.2393 0.480 0.008 0.512 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.2704     0.8404 0.876 0.000 0.124 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.3801     0.7719 0.780 0.000 0.220 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.2868     0.7957 0.864 0.000 0.000 0.136
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     1  0.3074     0.6930 0.848 0.000 0.000 0.152
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.2814     0.8386 0.868 0.000 0.132 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.2760     0.8384 0.872 0.000 0.128 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.3088     0.7814 0.060 0.052 0.888 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     3  0.2345     0.7254 0.000 0.100 0.900 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     2  0.4436     0.7544 0.020 0.764 0.216 0.000
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.2345     0.8434 0.900 0.000 0.100 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     4  0.0000     0.8529 0.000 0.000 0.000 1.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     4  0.4543     0.4532 0.324 0.000 0.000 0.676
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     3  0.1902     0.7901 0.064 0.004 0.932 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.4103     0.6257 0.744 0.000 0.256 0.000
#> 41D88C3E-5848-4B09-8A77-EAE6AC4EC6B0     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> BDF79CC0-00C7-49C1-900B-AB065A733B17     1  0.1792     0.7942 0.932 0.000 0.000 0.068
#> A894D686-BFC7-4AEE-A794-DBE718C6B6F6     3  0.4933     0.0153 0.000 0.432 0.568 0.000
#> 0712029E-3765-4272-BE5B-B6C8BCCC0F0F     2  0.0707     0.8179 0.000 0.980 0.020 0.000
#> 7B051855-9B09-4887-9BC0-9F077537938E     1  0.2589     0.8427 0.884 0.000 0.116 0.000
#> EF357C46-5C3C-4F51-9383-FF7694D07B97     2  0.0707     0.8183 0.000 0.980 0.020 0.000
#> 9492A322-37CA-4582-AC68-66B5D80778AF     2  0.4643     0.6315 0.000 0.656 0.344 0.000
#> 993399A4-1B9F-4258-B2D0-155AD58A2E82     3  0.4877     0.3471 0.408 0.000 0.592 0.000
#> 7B7DC93D-5494-4E69-BE07-2967887182F9     4  0.0000     0.8529 0.000 0.000 0.000 1.000
#> 29BCBA51-2580-473D-9CF7-BEDBD0DBAD1B     3  0.6976     0.1034 0.136 0.320 0.544 0.000
#> 40855647-E942-4F32-90B7-BEB921929BFB     3  0.2216     0.7878 0.092 0.000 0.908 0.000
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#> 6752EED9-7990-433F-A206-D5398C396471     4  0.0000     0.8529 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     3  0.5810     0.5930 0.276 0.064 0.660 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.3172     0.7576 0.160 0.000 0.840 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     3  0.3300     0.6888 0.144 0.008 0.848 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.4932     0.6843 0.240 0.000 0.032 0.728
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3552     0.8344 0.848 0.000 0.128 0.024
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.2216     0.8435 0.908 0.000 0.092 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4477     0.5826 0.688 0.000 0.000 0.312
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8152 0.000 1.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.3161     0.7771 0.124 0.000 0.864 0.012
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     3  0.3486     0.7336 0.188 0.000 0.812 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     1  0.3464     0.7153 0.860 0.000 0.032 0.108
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.0921     0.8025 0.972 0.000 0.028 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     4  0.1517     0.8090 0.004 0.028 0.012 0.952 0.004
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     5  0.3586     0.6193 0.000 0.000 0.264 0.000 0.736
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     4  0.1442     0.8115 0.004 0.000 0.032 0.952 0.012
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.2179     0.8232 0.896 0.000 0.004 0.100 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1270     0.8588 0.948 0.000 0.052 0.000 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.2522     0.8283 0.880 0.000 0.012 0.108 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.2193     0.8036 0.044 0.008 0.920 0.028 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0451     0.8821 0.008 0.988 0.000 0.004 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     4  0.4537     0.3967 0.012 0.000 0.396 0.592 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0880     0.8526 0.968 0.000 0.000 0.032 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1270     0.8588 0.948 0.000 0.052 0.000 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     1  0.0671     0.8604 0.980 0.000 0.016 0.004 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0807     0.8167 0.012 0.000 0.976 0.012 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     4  0.3759     0.6955 0.000 0.220 0.016 0.764 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     5  0.1357     0.8271 0.048 0.000 0.004 0.000 0.948
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0794     0.8175 0.028 0.000 0.972 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1410     0.8111 0.060 0.000 0.940 0.000 0.000
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     4  0.3491     0.6279 0.228 0.000 0.004 0.768 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.3051     0.8047 0.852 0.000 0.000 0.120 0.028
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.2753     0.7508 0.008 0.000 0.856 0.136 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1282     0.8617 0.952 0.000 0.044 0.004 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.1544     0.8402 0.932 0.000 0.000 0.068 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.1386     0.8634 0.952 0.000 0.032 0.016 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.0290     0.8119 0.000 0.000 0.992 0.008 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.2047     0.8485 0.928 0.000 0.012 0.040 0.020
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.1041     0.8189 0.032 0.000 0.964 0.004 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3837     0.5132 0.308 0.000 0.692 0.000 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0162     0.8849 0.000 0.996 0.000 0.004 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     4  0.2624     0.7889 0.000 0.116 0.012 0.872 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     4  0.3730     0.5501 0.288 0.000 0.000 0.712 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     3  0.4213     0.4724 0.012 0.000 0.680 0.308 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     1  0.4386     0.7341 0.764 0.000 0.096 0.140 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.2852     0.7809 0.828 0.000 0.172 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.4036     0.7530 0.052 0.804 0.132 0.012 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     4  0.4665     0.6186 0.048 0.000 0.260 0.692 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     4  0.1892     0.8113 0.004 0.000 0.080 0.916 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.0794     0.8610 0.972 0.000 0.028 0.000 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.1082     0.8618 0.964 0.000 0.028 0.000 0.008
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.6322     0.0768 0.004 0.480 0.140 0.376 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.0671     0.8177 0.016 0.000 0.980 0.004 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.0798     0.8150 0.008 0.000 0.976 0.016 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     1  0.2677     0.8120 0.872 0.000 0.016 0.112 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.1041     0.8173 0.032 0.000 0.964 0.004 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.1197     0.8611 0.952 0.000 0.048 0.000 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.1877     0.8485 0.924 0.000 0.012 0.064 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0162     0.8850 0.000 0.996 0.004 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.2732     0.7260 0.000 0.000 0.840 0.160 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     2  0.4025     0.5628 0.000 0.700 0.008 0.292 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.1043     0.8604 0.960 0.000 0.040 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.1251     0.8669 0.000 0.956 0.000 0.008 0.036
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1608     0.8007 0.072 0.000 0.928 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     4  0.2659     0.8086 0.052 0.000 0.060 0.888 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.1043     0.8609 0.960 0.000 0.040 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.2513     0.7642 0.008 0.000 0.876 0.116 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     5  0.0000     0.8538 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     4  0.4632     0.2423 0.012 0.000 0.448 0.540 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.2488     0.8120 0.000 0.872 0.004 0.124 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0609     0.8608 0.980 0.000 0.020 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     1  0.5663     0.3764 0.548 0.000 0.088 0.364 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.3644     0.8005 0.024 0.048 0.084 0.844 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.1117     0.8188 0.016 0.000 0.964 0.020 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.1043     0.8609 0.960 0.000 0.040 0.000 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     5  0.1205     0.8397 0.000 0.040 0.004 0.000 0.956
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.1197     0.8596 0.952 0.000 0.048 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.2848     0.7481 0.156 0.000 0.840 0.004 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     5  0.4443     0.1442 0.004 0.000 0.472 0.000 0.524
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     4  0.3008     0.8001 0.004 0.092 0.036 0.868 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.2891     0.7623 0.824 0.000 0.000 0.176 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.2230     0.8192 0.884 0.000 0.000 0.116 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0898     0.8183 0.020 0.000 0.972 0.008 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0880     0.8532 0.968 0.000 0.000 0.032 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     1  0.5854     0.4216 0.600 0.000 0.240 0.160 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0703     0.8611 0.976 0.000 0.024 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     3  0.3420     0.7900 0.076 0.000 0.840 0.084 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.0324     0.8849 0.000 0.992 0.004 0.004 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.4473     0.1787 0.008 0.000 0.580 0.000 0.412
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     2  0.1168     0.8724 0.000 0.960 0.008 0.032 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.1478     0.8587 0.936 0.000 0.064 0.000 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     5  0.0510     0.8497 0.000 0.016 0.000 0.000 0.984
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.4406     0.7137 0.764 0.000 0.000 0.128 0.108
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0404     0.8596 0.988 0.000 0.012 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.0703     0.8526 0.976 0.000 0.000 0.024 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     3  0.2873     0.7740 0.128 0.000 0.856 0.016 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.3639     0.7627 0.144 0.000 0.812 0.044 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     4  0.1124     0.8105 0.000 0.036 0.004 0.960 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     4  0.4755     0.6461 0.060 0.000 0.244 0.696 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     1  0.3536     0.7887 0.812 0.000 0.032 0.156 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.1892     0.8030 0.080 0.000 0.916 0.004 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     4  0.5812     0.1846 0.000 0.432 0.092 0.476 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0609     0.8178 0.020 0.000 0.980 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     4  0.1331     0.8048 0.040 0.000 0.008 0.952 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.3242     0.8138 0.844 0.000 0.040 0.116 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     4  0.0404     0.8089 0.012 0.000 0.000 0.988 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.1901     0.7974 0.056 0.004 0.012 0.928 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.3558     0.8127 0.828 0.000 0.064 0.108 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.0671     0.8174 0.016 0.000 0.980 0.004 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     5  0.2354     0.8175 0.000 0.012 0.008 0.076 0.904
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0162     0.8849 0.000 0.996 0.000 0.004 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.1121     0.8601 0.956 0.000 0.044 0.000 0.000
#> 7822EA86-35A1-4285-9429-2B63111B9885     3  0.2574     0.7757 0.012 0.000 0.876 0.112 0.000
#> 6FD0CFC8-AC8D-4CF1-8C33-833AD98A30EF     2  0.0162     0.8849 0.000 0.996 0.000 0.004 0.000
#> A451F278-5E83-4BC6-9B15-3AA2117B99B6     4  0.0727     0.8111 0.012 0.004 0.004 0.980 0.000
#> 6EC25686-4547-459C-9E01-7EDF8DAECE35     3  0.0703     0.8176 0.024 0.000 0.976 0.000 0.000
#> 5D2F1EEA-2BA8-4C3A-8436-544EE1D23E7E     1  0.3612     0.6593 0.732 0.000 0.268 0.000 0.000
#> 675A4293-A4CE-4307-B00B-DFC4D44A87C6     4  0.2439     0.7986 0.000 0.004 0.120 0.876 0.000
#> 6FBE0AEF-476A-42B2-A857-846CF1ED92B6     2  0.0807     0.8823 0.000 0.976 0.012 0.012 0.000
#> 7139D616-1A15-4288-A9AE-411856A4A76D     4  0.1211     0.8114 0.016 0.000 0.024 0.960 0.000
#> 46D7F8C1-D5C5-40CC-BEF5-2E590A847BD9     5  0.3480     0.6429 0.000 0.000 0.248 0.000 0.752
#> 984C44D3-4F5F-44C9-BCD9-C991EBC1FCB8     5  0.3452     0.6411 0.000 0.000 0.244 0.000 0.756
#> 83FE52E0-2DC2-4580-8BB2-FBCBEE4AC240     3  0.4996     0.6760 0.128 0.000 0.708 0.164 0.000
#> 0923F9CB-DF6F-4BAA-A5F8-0F83CE60D1ED     1  0.3684     0.6429 0.720 0.000 0.280 0.000 0.000
#> 1DEB5206-78CC-4EB5-BCD5-85A6A5B4E273     1  0.1682     0.8516 0.944 0.000 0.012 0.032 0.012
#> E4DB18DA-EB0C-4B2F-9566-7F72222B16D4     4  0.0898     0.8085 0.020 0.000 0.008 0.972 0.000
#> F7456312-1309-4B2F-875D-0F90CDF3EC35     1  0.0880     0.8608 0.968 0.000 0.032 0.000 0.000
#> 9A25E5D8-0706-4960-A76B-BCD0AC93E4FA     1  0.2304     0.8511 0.908 0.000 0.044 0.048 0.000
#> 5A41FE8F-FFB3-4B87-BF11-A570C184096D     1  0.1341     0.8460 0.944 0.000 0.000 0.000 0.056
#> 33F84E63-3F6C-4867-ADB1-A0DF39F1295B     5  0.6360     0.1576 0.388 0.000 0.000 0.164 0.448
#> D6A644F5-D1D0-4A8D-94C4-EE6C3ECE7430     1  0.1608     0.8535 0.928 0.000 0.072 0.000 0.000
#> 2A5848CC-A9A2-4AA8-A752-321273E62CF0     1  0.1197     0.8596 0.952 0.000 0.048 0.000 0.000
#> 7CA6358B-FC8A-4675-B092-9E061038FC83     3  0.3916     0.5826 0.012 0.000 0.732 0.256 0.000
#> A4C2F4BC-5C62-4B1F-9AB8-46D9468EF523     3  0.4510     0.0688 0.000 0.008 0.560 0.432 0.000
#> 8AF4EB7F-418D-4CC9-A9B8-A93A4C1A173B     4  0.1857     0.8080 0.000 0.060 0.008 0.928 0.004
#> E5048887-70C8-468F-881E-2EC55F6E6F3B     1  0.0290     0.8587 0.992 0.000 0.008 0.000 0.000
#> 1BADCC7C-C4D8-4C34-9534-59D622C7A2A2     5  0.0000     0.8538 0.000 0.000 0.000 0.000 1.000
#> 02CE7DF7-64BD-4297-A240-A5B9EE8771D3     1  0.4101     0.5336 0.664 0.000 0.004 0.000 0.332
#> CBF6E96A-F56C-4C87-B851-D319930BAAB8     3  0.3932     0.4291 0.000 0.000 0.672 0.328 0.000
#> 48F6B774-CFD2-4DDF-B7A2-696596413C3F     1  0.4948     0.2045 0.536 0.000 0.028 0.436 0.000
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#> FAD8A464-9BC3-4ED9-9517-B18D36514325     4  0.3007     0.7999 0.028 0.004 0.104 0.864 0.000
#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.2852     0.7691 0.828 0.000 0.000 0.172 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4074     0.4744 0.636 0.000 0.364 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1792     0.8460 0.916 0.000 0.084 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.3146     0.7777 0.028 0.000 0.128 0.844 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     5  0.1732     0.8165 0.000 0.080 0.000 0.000 0.920
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.0613     0.8097 0.004 0.004 0.008 0.984 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     4  0.1243     0.8111 0.004 0.028 0.008 0.960 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.6410     0.1579 0.184 0.000 0.476 0.000 0.340
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     3  0.1704     0.7981 0.004 0.000 0.928 0.068 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.0324     0.8576 0.992 0.000 0.004 0.004 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0162     0.8577 0.996 0.000 0.004 0.000 0.000
#> B5C9EA22-F758-4BD2-BD1F-282EC1078AED     4  0.2278     0.8165 0.008 0.032 0.044 0.916 0.000
#> 3F08AE92-3EFD-4D7F-8C5C-BFB3621F0CD6     1  0.0880     0.8609 0.968 0.000 0.032 0.000 0.000
#> 8F0D43F1-2199-4DBB-9B16-1E5F2CED2FEC     4  0.7270     0.1474 0.020 0.284 0.336 0.360 0.000
#> 54BABD8B-EA9F-4875-8594-2179B38C73BD     3  0.1872     0.8124 0.020 0.000 0.928 0.052 0.000
#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     5  0.0000     0.8538 0.000 0.000 0.000 0.000 1.000
#> F93D26E2-4B45-495D-BC8E-5B592F8FDABF     3  0.3857     0.4715 0.000 0.000 0.688 0.312 0.000
#> C98275CD-C39A-4E14-A731-4F3EB7396665     4  0.2897     0.8120 0.052 0.040 0.020 0.888 0.000
#> 354DC705-216E-42F0-B29E-C1F8D6C9489A     4  0.0404     0.8079 0.012 0.000 0.000 0.988 0.000
#> 6752EED9-7990-433F-A206-D5398C396471     5  0.0000     0.8538 0.000 0.000 0.000 0.000 1.000
#> C3E94C5D-68C4-400C-B7CB-38C42E9D5FFF     4  0.1074     0.8126 0.012 0.004 0.016 0.968 0.000
#> CE6B6871-3ED3-44DE-A777-7558D4429057     3  0.0703     0.8176 0.024 0.000 0.976 0.000 0.000
#> A06E7D1E-E432-4A4C-8BB0-314304F96EDF     4  0.2411     0.7984 0.008 0.000 0.108 0.884 0.000
#> 1ABBEF80-508F-4247-B43D-3E549372113B     4  0.4528     0.1198 0.008 0.000 0.000 0.548 0.444
#> 835AAE7F-F873-4D11-8845-232D261A38DF     1  0.3690     0.7187 0.764 0.000 0.224 0.000 0.012
#> E98A0460-6529-4DBA-8542-1B98801D7A7D     1  0.0404     0.8595 0.988 0.000 0.012 0.000 0.000
#> 06A9CBF8-01D0-4720-BCE8-83F0E77C862F     1  0.4126     0.4350 0.620 0.000 0.000 0.000 0.380
#> 206865A9-A67C-49A6-93AD-55D06E777559     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 26DABC83-DB30-452F-9BE2-366760CB138E     2  0.0000     0.8846 0.000 1.000 0.000 0.000 0.000
#> 9DD5272A-2D6E-4774-83E3-0CD761EDE926     3  0.0854     0.8139 0.012 0.000 0.976 0.004 0.008
#> 4938E366-C740-4C9C-9358-FF37997DC9EF     4  0.5470     0.5205 0.092 0.000 0.296 0.612 0.000
#> E2DA59C4-A47C-41E3-BC55-2D00C6EC17FB     4  0.3612     0.5692 0.268 0.000 0.000 0.732 0.000
#> 37349E62-0BFB-4FEA-81D0-2AB7E7625B0D     1  0.1732     0.8367 0.920 0.000 0.000 0.080 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 7826AE44-B03A-4528-9CB5-7421E592AE36     5  0.3868   -0.22278 0.000 0.000 0.000 0.492 0.508 0.000
#> 0DC2197B-2FEA-48EB-953E-8E44E1933757     3  0.4191    0.29396 0.004 0.000 0.596 0.012 0.000 0.388
#> 87ABB098-8C1E-4677-8C31-48B71EFE41C7     5  0.2884    0.59204 0.000 0.000 0.008 0.164 0.824 0.004
#> EC0154E7-7A27-4535-83AE-6B379E99A93C     1  0.6049    0.20794 0.468 0.000 0.012 0.340 0.180 0.000
#> 78F79407-D49F-4FA2-B09F-0665C502827C     1  0.1059    0.80979 0.964 0.000 0.016 0.004 0.016 0.000
#> 03E81178-E971-4E91-8BED-D8273EA1425C     1  0.1524    0.80036 0.932 0.000 0.000 0.008 0.060 0.000
#> 62FCAEFF-16D8-4019-84B6-18EC3A88BC32     3  0.4941    0.53213 0.008 0.032 0.624 0.316 0.020 0.000
#> 722C1284-5983-4CC1-B19C-214C2DE6F8A6     2  0.0363    0.86366 0.000 0.988 0.000 0.012 0.000 0.000
#> 54E42A64-B350-4A94-8FED-C9BC1872660E     5  0.4227    0.32631 0.004 0.000 0.344 0.020 0.632 0.000
#> 53062969-D209-490B-9C9B-5D297625E2AE     1  0.0508    0.80712 0.984 0.000 0.000 0.012 0.004 0.000
#> B710293C-41D3-4A2E-8104-5402F91DD859     1  0.1080    0.80705 0.960 0.000 0.032 0.004 0.004 0.000
#> 73CB1D05-7AE4-457D-B4EF-25AC5C1F2132     4  0.4328   -0.10005 0.460 0.000 0.020 0.520 0.000 0.000
#> B055A70B-3003-47CB-BDAA-6378C000BF24     3  0.0508    0.73317 0.000 0.000 0.984 0.012 0.004 0.000
#> 46C3A870-E37A-42CB-8C0C-6ACACEAC1ADC     5  0.3328    0.50383 0.000 0.192 0.008 0.012 0.788 0.000
#> E8E6270E-F26D-4F2E-A63E-7885BDE05FDB     6  0.1082    0.82397 0.040 0.000 0.000 0.004 0.000 0.956
#> C4A5EBA2-9091-4D12-BDC8-B84B122022B9     3  0.0820    0.73891 0.016 0.000 0.972 0.012 0.000 0.000
#> 5B1839C4-549D-41D1-B559-3C6D2A1528CE     3  0.1890    0.74096 0.024 0.000 0.924 0.044 0.000 0.008
#> A0DF05EB-DC44-4492-9A8A-F278F7B0C266     5  0.4032    0.22082 0.420 0.000 0.000 0.008 0.572 0.000
#> B5182F49-70F2-45B7-82DE-C6DA68145EEA     1  0.3706    0.68941 0.780 0.000 0.000 0.008 0.172 0.040
#> C204D355-B876-4341-A111-36D48CBDD2A8     3  0.4593    0.56943 0.004 0.000 0.704 0.112 0.180 0.000
#> 7B070AAA-EF97-4D3B-AA19-EEC170C7927D     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> 05A8A881-F8EE-48A2-B11C-A08D7D80CE18     1  0.1592    0.80332 0.940 0.000 0.032 0.008 0.020 0.000
#> BA59EF50-CFE9-456D-B1B6-67D0945004F6     1  0.4181    0.59946 0.700 0.000 0.000 0.248 0.052 0.000
#> AD97B334-E034-4D33-A4D5-48C32D5D521C     1  0.0436    0.80704 0.988 0.000 0.004 0.004 0.004 0.000
#> 51DA2568-32EA-4668-9876-4B6E7CA68860     3  0.1088    0.72440 0.000 0.000 0.960 0.024 0.016 0.000
#> 78C26A05-2084-494D-83D3-C52C1B800F4C     1  0.1881    0.79897 0.928 0.000 0.008 0.020 0.040 0.004
#> 2B5DD791-7692-4721-9519-7D7D49B52570     3  0.3156    0.69124 0.020 0.000 0.800 0.180 0.000 0.000
#> C0BBE26A-79C8-4392-9978-7C420B3786B5     3  0.3341    0.64620 0.208 0.000 0.776 0.012 0.004 0.000
#> F35A8359-3A7A-414F-8A5C-D278F3B45387     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> 8C9BA49C-1270-491D-A234-AE1B1C0609BA     5  0.2531    0.57703 0.004 0.128 0.000 0.008 0.860 0.000
#> CA104B57-B160-4148-8A0A-D34BB3E8D88A     5  0.4631    0.33269 0.352 0.000 0.000 0.052 0.596 0.000
#> 877E18A5-6A7A-4E29-9871-DC7EA14A5F27     3  0.4919    0.37280 0.024 0.000 0.616 0.040 0.320 0.000
#> 904EDF2E-411E-43BD-901D-46129AFA283A     4  0.6816    0.00844 0.360 0.000 0.056 0.380 0.204 0.000
#> FD9F5A9B-2BEB-4D31-9A2D-8D4B4ECBB478     1  0.3725    0.48576 0.676 0.000 0.316 0.008 0.000 0.000
#> 2E206314-9928-456E-B7C6-893DC0E3C7C2     2  0.5465    0.38849 0.020 0.544 0.080 0.356 0.000 0.000
#> 913DB655-2C7F-4369-83DE-9257F04CF39B     5  0.5851    0.33194 0.032 0.004 0.080 0.384 0.500 0.000
#> 72B5B724-FEB5-43BD-83F6-2E2152DDD800     5  0.1821    0.60952 0.008 0.000 0.040 0.024 0.928 0.000
#> 920B547C-6898-446C-AAAF-F4ED96E40AAB     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> 847F796A-8CD6-4013-A0FB-26F4FC3EAF0D     1  0.1578    0.79937 0.936 0.000 0.012 0.048 0.004 0.000
#> C4D64E7A-33F7-4CFC-9FD3-D6AA3D8EFAA7     1  0.0982    0.80929 0.968 0.000 0.004 0.020 0.004 0.004
#> EABA0B17-8E19-48C5-BF62-2A45C9632807     2  0.6544    0.25622 0.000 0.500 0.072 0.144 0.284 0.000
#> 7263CBA8-CE37-4531-A795-9324C6D2A672     3  0.1391    0.73434 0.000 0.000 0.944 0.040 0.016 0.000
#> 6D3CC3AC-618B-414A-B640-169C735A6568     3  0.2762    0.60963 0.000 0.000 0.804 0.196 0.000 0.000
#> 710C05C7-F9CE-45FA-A8CC-29DE2903E04F     4  0.3314    0.37206 0.224 0.000 0.000 0.764 0.012 0.000
#> 3D631A56-2C55-48EA-A667-BA46023C9D50     3  0.0914    0.73418 0.016 0.000 0.968 0.016 0.000 0.000
#> F1C65F64-AF05-4875-B7E4-60FFF56A3F46     1  0.1983    0.79318 0.916 0.000 0.060 0.012 0.012 0.000
#> E5DF76E7-A765-4E07-B87A-06168BF66C5F     1  0.2209    0.78980 0.900 0.000 0.024 0.004 0.072 0.000
#> 5C8C8A6E-40D4-4F82-AC3D-90CFDEE15C0A     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> 0117CBB9-1BF9-48B1-BE6E-A9A770FF8721     3  0.3572    0.61345 0.000 0.000 0.764 0.032 0.204 0.000
#> 31EF66E5-419A-44C3-BB2A-B69B52FFCECC     4  0.6096    0.35619 0.000 0.312 0.008 0.460 0.220 0.000
#> C149CEF5-61F3-4B53-B8A9-8244B673EBD0     1  0.0508    0.80731 0.984 0.000 0.012 0.004 0.000 0.000
#> 0AF351D0-4EC5-4275-AA0A-4FA2AF8A9C85     2  0.3333    0.73421 0.000 0.820 0.000 0.032 0.012 0.136
#> B507E82F-6680-497B-A014-033EDD7A2E03     3  0.1219    0.73908 0.048 0.000 0.948 0.004 0.000 0.000
#> F941890E-AB33-478F-8C97-1C785DD9428F     5  0.4601    0.34650 0.028 0.000 0.004 0.472 0.496 0.000
#> 7987E019-8FED-469B-A6C1-34EE430A60C3     1  0.0622    0.80762 0.980 0.000 0.012 0.008 0.000 0.000
#> 76084AA6-19BF-4605-B6A1-73F1D4BADAF9     3  0.3062    0.67056 0.000 0.000 0.824 0.144 0.032 0.000
#> 329807F7-E0D4-4F53-94E8-E4080E90CB47     6  0.0000    0.84977 0.000 0.000 0.000 0.000 0.000 1.000
#> 1B6505FF-C1A7-4DD0-9827-41A0A3A28F3E     5  0.5001    0.42333 0.040 0.000 0.252 0.048 0.660 0.000
#> 49778E92-B5D3-4AD9-A1AF-3B722D631B96     2  0.4020    0.53568 0.000 0.692 0.000 0.032 0.276 0.000
#> A22892DE-0AF4-4B63-9513-1D6825059040     1  0.0146    0.80663 0.996 0.000 0.004 0.000 0.000 0.000
#> 6D77ECAE-A715-4ADD-97D8-A916DC31A4EA     5  0.5417    0.30579 0.336 0.000 0.068 0.028 0.568 0.000
#> 09758B6F-1B2D-4AED-8913-696097069409     4  0.4914    0.33426 0.004 0.028 0.020 0.588 0.360 0.000
#> 8B709DB4-0B28-42F1-A7C5-106F5809BEA2     3  0.1666    0.73737 0.036 0.000 0.936 0.020 0.008 0.000
#> F2B356FA-79CD-4867-8ABF-84C90A493A75     1  0.0881    0.80743 0.972 0.000 0.012 0.008 0.008 0.000
#> 131213AD-0313-4DF1-B013-CE67ED262C37     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> D94F7E81-0F60-473B-AD4A-0AC13508BDE2     6  0.0405    0.84852 0.000 0.008 0.000 0.000 0.004 0.988
#> 29C17355-D646-48DA-9E54-7B6DD85DD610     1  0.0632    0.80716 0.976 0.000 0.024 0.000 0.000 0.000
#> B8BD866A-2A7C-45C3-96BB-9AB892D26AE5     3  0.4710    0.65801 0.164 0.000 0.708 0.116 0.012 0.000
#> 13EFD045-AD61-41EE-9896-67BFA4FC8C09     3  0.2871    0.63283 0.000 0.000 0.804 0.004 0.000 0.192
#> 2655F609-B3BB-4D01-B421-D5F4B1232EC8     5  0.2745    0.59134 0.004 0.072 0.020 0.024 0.880 0.000
#> 04BC7A52-C67F-42CB-8672-D3C51A20F2BA     1  0.4187    0.63216 0.736 0.000 0.000 0.096 0.168 0.000
#> 45472BD4-DBDB-41FE-B0E3-2440880E1DE6     1  0.3402    0.72137 0.820 0.000 0.004 0.072 0.104 0.000
#> B87FFFCD-CB57-4ACD-9C74-AB188984BBB2     3  0.0725    0.73412 0.012 0.000 0.976 0.012 0.000 0.000
#> 5271374C-13CD-4BFE-AC6D-C95AFE491322     1  0.0891    0.80640 0.968 0.000 0.000 0.024 0.008 0.000
#> E3372ACE-C7C8-43E5-B30A-1F2D662D8170     4  0.2758    0.41136 0.080 0.000 0.036 0.872 0.012 0.000
#> B08DF564-E4D0-4540-8160-93B3981DF1D8     1  0.0820    0.80913 0.972 0.000 0.012 0.016 0.000 0.000
#> 61A7D1B9-FC5A-4B9C-989F-936CDA948C27     3  0.5279    0.64282 0.100 0.000 0.692 0.072 0.136 0.000
#> 74E768C1-8766-46AC-AAB4-D79E5049F76A     2  0.1141    0.84834 0.000 0.948 0.000 0.052 0.000 0.000
#> 0CEA28F0-D7F0-4EB7-A23F-0C5CA6245971     3  0.3647    0.39554 0.000 0.000 0.640 0.000 0.000 0.360
#> 95C4EFF6-147C-48EC-A2C1-16B8F12AEEF2     4  0.4179    0.04716 0.000 0.472 0.000 0.516 0.012 0.000
#> C9A78BEA-D455-4F5E-8B7B-19BCB42887E7     1  0.3025    0.75060 0.844 0.000 0.120 0.016 0.020 0.000
#> DB970740-9AC1-4C10-9658-8A77B1C390DD     6  0.0508    0.84638 0.000 0.012 0.000 0.004 0.000 0.984
#> 883FBD37-0CA0-4562-8925-72ACC1EE93D9     1  0.5346    0.53031 0.652 0.000 0.000 0.024 0.168 0.156
#> 9FE1D006-49F2-471E-91E6-AF0414C24479     1  0.0909    0.80782 0.968 0.000 0.020 0.012 0.000 0.000
#> 11816CC6-8C8B-49C0-99EE-896377BCFCCD     1  0.2581    0.76116 0.860 0.000 0.000 0.120 0.020 0.000
#> 063FC5C8-4318-4ECC-9CA0-1976CBC8ACB6     3  0.5604    0.57434 0.228 0.000 0.624 0.104 0.044 0.000
#> E0F085CC-B90D-4FDE-B60E-C613971BAA00     3  0.5248    0.61718 0.208 0.000 0.668 0.068 0.056 0.000
#> 62361DA2-E4EE-46DA-BB1F-C51DCA9307CC     5  0.2145    0.59843 0.000 0.028 0.000 0.072 0.900 0.000
#> 1BA16D48-B09E-4699-A1AD-2FFECE4F3CDB     2  0.0146    0.86460 0.000 0.996 0.000 0.004 0.000 0.000
#> 3E4F14E9-60AE-4F17-9BA7-2A02E908204A     5  0.5114    0.33911 0.012 0.000 0.052 0.444 0.492 0.000
#> 79226DD7-BC85-4B8E-BFF8-B1E073129D34     5  0.4958    0.15744 0.424 0.000 0.036 0.016 0.524 0.000
#> D47D0936-826F-4D54-9225-F71B95357438     3  0.4553    0.67524 0.072 0.000 0.728 0.176 0.024 0.000
#> 0AE02B91-574C-4165-BA39-E9D7C1A870A2     2  0.5512   -0.06387 0.000 0.460 0.032 0.056 0.452 0.000
#> DED8E9DF-CEFE-45ED-9374-EF9925A135C4     3  0.0000    0.73198 0.000 0.000 1.000 0.000 0.000 0.000
#> D587A993-3C47-4D4C-B744-59169D4F7451     5  0.0964    0.60643 0.016 0.000 0.004 0.012 0.968 0.000
#> 6BCA24E6-440F-42C5-ABE5-66C37B713A39     1  0.4628    0.60976 0.712 0.000 0.024 0.064 0.200 0.000
#> 86A5EDFB-9D06-4FED-BF57-F8D74A68E156     5  0.2266    0.57668 0.012 0.000 0.000 0.108 0.880 0.000
#> B9BD5134-2F6A-4454-8F83-69B63F9AE114     4  0.4580    0.24658 0.028 0.000 0.004 0.528 0.440 0.000
#> 082DA9E1-A40D-482B-8E21-A93BA97185F0     1  0.7223    0.04884 0.440 0.000 0.224 0.152 0.184 0.000
#> 16A8343A-1203-44FB-9F03-05CC7C71B4CC     3  0.1501    0.73134 0.000 0.000 0.924 0.076 0.000 0.000
#> 00439565-02CE-4BF5-956D-7078B51C0947     6  0.2462    0.74557 0.000 0.004 0.000 0.004 0.132 0.860
#> 7B2BD361-2BF1-4E97-BC08-457F5A9C2682     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> C1D8439A-D527-47F6-ADC1-25867B65DA21     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> D9096909-1439-462D-B69C-CAD1BF4F420C     1  0.0363    0.80712 0.988 0.000 0.012 0.000 0.000 0.000
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#> 9AF0E82E-E621-437A-8D19-700532B95090     1  0.4719    0.48711 0.644 0.000 0.000 0.084 0.272 0.000
#> 27DA48F3-4FC1-41A3-8E49-5B25F1CCFF07     1  0.4095   -0.01612 0.512 0.000 0.480 0.008 0.000 0.000
#> EFE5A302-D138-4044-A301-5C5FD1C24836     1  0.1858    0.78010 0.904 0.000 0.092 0.004 0.000 0.000
#> D3E866AC-D66A-4C07-9F47-89AF460320DE     2  0.0000    0.86575 0.000 1.000 0.000 0.000 0.000 0.000
#> 89C45456-9392-4EB3-9A82-A130B6702AAF     4  0.5020    0.36489 0.008 0.000 0.080 0.616 0.296 0.000
#> 8FF5C8FC-2565-49BE-9EE0-91A84A85AB2A     6  0.1700    0.80667 0.000 0.080 0.000 0.004 0.000 0.916
#> 846DF088-75D5-49CF-BDDC-27E735A08DCA     4  0.4224    0.18348 0.008 0.000 0.004 0.512 0.476 0.000
#> EA3A19E1-7ADE-47B6-A35A-71290967147A     5  0.0820    0.60647 0.012 0.000 0.000 0.016 0.972 0.000
#> B2C43D0C-732B-4C54-938F-D3C9FDA880DA     3  0.4336    0.65162 0.084 0.000 0.772 0.012 0.016 0.116
#> EEC856B5-9B7F-488D-975E-CE2FF7072879     4  0.4399    0.17795 0.000 0.000 0.460 0.516 0.024 0.000
#> 8A68C417-09CC-4FA1-BFEB-EB4B738853A4     1  0.2513    0.75134 0.852 0.000 0.000 0.140 0.008 0.000
#> C5DF1A0D-952C-44E2-BF83-ED57177EF60E     1  0.0972    0.80888 0.964 0.000 0.008 0.028 0.000 0.000
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#> C149B6F8-03DC-4907-920A-F3318B8D2A1E     6  0.0000    0.84977 0.000 0.000 0.000 0.000 0.000 1.000
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Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-NMF-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-NMF-collect-classes

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

Session info

sessionInfo()
#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: CentOS Linux 7 (Core)
#> 
#> Matrix products: default
#> BLAS:   /usr/lib64/libblas.so.3.4.2
#> LAPACK: /usr/lib64/liblapack.so.3.4.2
#> 
#> locale:
#>  [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=en_GB.UTF-8       
#>  [4] LC_COLLATE=en_GB.UTF-8     LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
#>  [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
#> [10] LC_TELEPHONE=C             LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] grid      stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] genefilter_1.66.0    ComplexHeatmap_2.3.1 markdown_1.1         knitr_1.26          
#> [5] GetoptLong_0.1.7     cola_1.3.2          
#> 
#> loaded via a namespace (and not attached):
#>  [1] circlize_0.4.8       shape_1.4.4          xfun_0.11            slam_0.1-46         
#>  [5] lattice_0.20-38      splines_3.6.0        colorspace_1.4-1     vctrs_0.2.0         
#>  [9] stats4_3.6.0         blob_1.2.0           XML_3.98-1.20        survival_2.44-1.1   
#> [13] rlang_0.4.2          pillar_1.4.2         DBI_1.0.0            BiocGenerics_0.30.0 
#> [17] bit64_0.9-7          RColorBrewer_1.1-2   matrixStats_0.55.0   stringr_1.4.0       
#> [21] GlobalOptions_0.1.1  evaluate_0.14        memoise_1.1.0        Biobase_2.44.0      
#> [25] IRanges_2.18.3       parallel_3.6.0       AnnotationDbi_1.46.1 highr_0.8           
#> [29] Rcpp_1.0.3           xtable_1.8-4         backports_1.1.5      S4Vectors_0.22.1    
#> [33] annotate_1.62.0      skmeans_0.2-11       bit_1.1-14           microbenchmark_1.4-7
#> [37] brew_1.0-6           impute_1.58.0        rjson_0.2.20         png_0.1-7           
#> [41] digest_0.6.23        stringi_1.4.3        polyclip_1.10-0      clue_0.3-57         
#> [45] tools_3.6.0          bitops_1.0-6         magrittr_1.5         eulerr_6.0.0        
#> [49] RCurl_1.95-4.12      RSQLite_2.1.4        tibble_2.1.3         cluster_2.1.0       
#> [53] crayon_1.3.4         pkgconfig_2.0.3      zeallot_0.1.0        Matrix_1.2-17       
#> [57] xml2_1.2.2           httr_1.4.1           R6_2.4.1             mclust_5.4.5        
#> [61] compiler_3.6.0