cola Report for recount2:TCGA_head_and_neck

Date: 2019-12-26 01:30:50 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 17541 rows and 500 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 = cores)

Dimension of the input matrix:

mat = get_matrix(res_list)
dim(mat)
#> [1] 17541   500

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:mclust 2 1.000 0.961 0.977 **
MAD:mclust 2 0.980 0.948 0.969 **
ATC:NMF 2 0.939 0.951 0.979 *
ATC:skmeans 6 0.914 0.855 0.940 * 2,4,5
ATC:pam 5 0.906 0.889 0.957 * 2,3
ATC:kmeans 2 0.878 0.949 0.976
MAD:skmeans 3 0.861 0.885 0.952
SD:skmeans 3 0.856 0.899 0.957
MAD:NMF 2 0.797 0.881 0.951
CV:kmeans 3 0.797 0.845 0.932
CV:NMF 2 0.781 0.896 0.950
CV:skmeans 3 0.777 0.832 0.932
ATC:mclust 4 0.696 0.646 0.843
MAD:kmeans 3 0.680 0.824 0.896
SD:NMF 2 0.673 0.871 0.935
SD:kmeans 3 0.622 0.812 0.885
MAD:pam 2 0.456 0.784 0.894
CV:pam 3 0.454 0.749 0.848
SD:pam 2 0.406 0.695 0.869
CV:mclust 2 0.346 0.743 0.855
CV:hclust 3 0.226 0.537 0.792
ATC:hclust 2 0.190 0.676 0.825
MAD:hclust 2 0.074 0.628 0.787
SD:hclust 2 0.046 0.484 0.733

**: 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 0.6733           0.871       0.935          0.500 0.500   0.500
#> CV:NMF      2 0.7809           0.896       0.950          0.492 0.508   0.508
#> MAD:NMF     2 0.7975           0.881       0.951          0.498 0.502   0.502
#> ATC:NMF     2 0.9389           0.951       0.979          0.350 0.663   0.663
#> SD:skmeans  2 0.4833           0.590       0.814          0.498 0.507   0.507
#> CV:skmeans  2 0.7037           0.808       0.925          0.498 0.500   0.500
#> MAD:skmeans 2 0.8151           0.879       0.947          0.501 0.499   0.499
#> ATC:skmeans 2 0.9177           0.918       0.968          0.501 0.500   0.500
#> SD:mclust   2 1.0000           0.961       0.977          0.478 0.518   0.518
#> CV:mclust   2 0.3464           0.743       0.855          0.464 0.529   0.529
#> MAD:mclust  2 0.9797           0.948       0.969          0.480 0.521   0.521
#> ATC:mclust  2 0.8336           0.913       0.963          0.297 0.709   0.709
#> SD:kmeans   2 0.3966           0.641       0.845          0.493 0.499   0.499
#> CV:kmeans   2 0.3591           0.770       0.851          0.468 0.517   0.517
#> MAD:kmeans  2 0.4104           0.740       0.860          0.491 0.503   0.503
#> ATC:kmeans  2 0.8778           0.949       0.976          0.495 0.506   0.506
#> SD:pam      2 0.4057           0.695       0.869          0.481 0.506   0.506
#> CV:pam      2 0.2986           0.671       0.811          0.452 0.524   0.524
#> MAD:pam     2 0.4557           0.784       0.894          0.475 0.526   0.526
#> ATC:pam     2 0.9600           0.932       0.961          0.318 0.684   0.684
#> SD:hclust   2 0.0464           0.484       0.733          0.413 0.514   0.514
#> CV:hclust   2 0.3679           0.752       0.882          0.286 0.742   0.742
#> MAD:hclust  2 0.0736           0.628       0.787          0.407 0.596   0.596
#> ATC:hclust  2 0.1896           0.676       0.825          0.416 0.556   0.556
get_stats(res_list, k = 3)
#>             k  1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      3 0.7234           0.808       0.910          0.326 0.694   0.463
#> CV:NMF      3 0.8029           0.820       0.928          0.321 0.767   0.574
#> MAD:NMF     3 0.5285           0.716       0.852          0.329 0.711   0.485
#> ATC:NMF     3 0.6784           0.817       0.903          0.781 0.634   0.478
#> SD:skmeans  3 0.8557           0.899       0.957          0.341 0.701   0.474
#> CV:skmeans  3 0.7774           0.832       0.932          0.307 0.756   0.552
#> MAD:skmeans 3 0.8612           0.885       0.952          0.333 0.675   0.438
#> ATC:skmeans 3 0.7983           0.849       0.921          0.305 0.737   0.527
#> SD:mclust   3 0.5643           0.710       0.837          0.202 0.965   0.933
#> CV:mclust   3 0.5722           0.730       0.845          0.383 0.747   0.551
#> MAD:mclust  3 0.6169           0.666       0.841          0.245 0.902   0.813
#> ATC:mclust  3 0.4331           0.455       0.667          0.724 0.665   0.549
#> SD:kmeans   3 0.6216           0.812       0.885          0.332 0.661   0.424
#> CV:kmeans   3 0.7967           0.845       0.932          0.324 0.781   0.612
#> MAD:kmeans  3 0.6804           0.824       0.896          0.330 0.640   0.402
#> ATC:kmeans  3 0.7772           0.831       0.933          0.234 0.626   0.415
#> SD:pam      3 0.3550           0.453       0.716          0.337 0.707   0.494
#> CV:pam      3 0.4537           0.749       0.848          0.403 0.653   0.428
#> MAD:pam     3 0.4422           0.706       0.814          0.302 0.843   0.710
#> ATC:pam     3 0.9088           0.911       0.962          0.682 0.777   0.675
#> SD:hclust   3 0.0674           0.379       0.652          0.272 0.823   0.692
#> CV:hclust   3 0.2263           0.537       0.792          0.510 0.916   0.888
#> MAD:hclust  3 0.0856           0.478       0.714          0.294 0.898   0.835
#> ATC:hclust  3 0.2228           0.506       0.656          0.387 0.664   0.478
get_stats(res_list, k = 4)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      4 0.536           0.593       0.787         0.0796 0.742   0.406
#> CV:NMF      4 0.637           0.715       0.827         0.1302 0.821   0.551
#> MAD:NMF     4 0.511           0.506       0.705         0.1029 0.773   0.470
#> ATC:NMF     4 0.712           0.776       0.897         0.1375 0.751   0.452
#> SD:skmeans  4 0.709           0.629       0.811         0.1166 0.845   0.582
#> CV:skmeans  4 0.772           0.797       0.908         0.1178 0.887   0.690
#> MAD:skmeans 4 0.688           0.700       0.857         0.1197 0.838   0.567
#> ATC:skmeans 4 0.925           0.911       0.962         0.1370 0.850   0.602
#> SD:mclust   4 0.543           0.592       0.767         0.1596 0.788   0.581
#> CV:mclust   4 0.561           0.508       0.728         0.1318 0.884   0.689
#> MAD:mclust  4 0.486           0.532       0.741         0.1337 0.838   0.646
#> ATC:mclust  4 0.696           0.646       0.843         0.2761 0.753   0.498
#> SD:kmeans   4 0.593           0.693       0.818         0.0938 0.818   0.550
#> CV:kmeans   4 0.647           0.683       0.816         0.1151 0.910   0.777
#> MAD:kmeans  4 0.558           0.655       0.780         0.1066 0.807   0.526
#> ATC:kmeans  4 0.657           0.781       0.889         0.1602 0.755   0.473
#> SD:pam      4 0.537           0.565       0.781         0.1330 0.814   0.539
#> CV:pam      4 0.523           0.695       0.824         0.0980 0.948   0.850
#> MAD:pam     4 0.505           0.581       0.789         0.1539 0.759   0.474
#> ATC:pam     4 0.884           0.879       0.954         0.1621 0.795   0.608
#> SD:hclust   4 0.131           0.332       0.551         0.1901 0.683   0.448
#> CV:hclust   4 0.271           0.502       0.748         0.1699 0.874   0.812
#> MAD:hclust  4 0.150           0.336       0.592         0.2165 0.767   0.586
#> ATC:hclust  4 0.305           0.462       0.694         0.1383 0.778   0.541
get_stats(res_list, k = 5)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      5 0.587           0.559       0.774         0.0877 0.873   0.591
#> CV:NMF      5 0.622           0.580       0.755         0.0666 0.895   0.640
#> MAD:NMF     5 0.709           0.703       0.858         0.0681 0.842   0.533
#> ATC:NMF     5 0.694           0.703       0.854         0.0944 0.777   0.390
#> SD:skmeans  5 0.662           0.568       0.764         0.0630 0.874   0.568
#> CV:skmeans  5 0.696           0.644       0.814         0.0662 0.942   0.798
#> MAD:skmeans 5 0.652           0.323       0.655         0.0653 0.865   0.544
#> ATC:skmeans 5 0.930           0.879       0.946         0.0524 0.908   0.674
#> SD:mclust   5 0.559           0.599       0.742         0.1161 0.840   0.559
#> CV:mclust   5 0.527           0.367       0.676         0.0413 0.881   0.643
#> MAD:mclust  5 0.496           0.367       0.670         0.0830 0.884   0.681
#> ATC:mclust  5 0.734           0.822       0.905         0.0414 0.865   0.643
#> SD:kmeans   5 0.642           0.641       0.777         0.0677 0.901   0.686
#> CV:kmeans   5 0.608           0.620       0.774         0.0709 0.951   0.853
#> MAD:kmeans  5 0.623           0.576       0.757         0.0701 0.920   0.739
#> ATC:kmeans  5 0.875           0.851       0.939         0.0798 0.866   0.592
#> SD:pam      5 0.546           0.491       0.696         0.0626 0.833   0.492
#> CV:pam      5 0.558           0.601       0.778         0.0710 0.953   0.849
#> MAD:pam     5 0.634           0.582       0.791         0.0707 0.897   0.670
#> ATC:pam     5 0.906           0.889       0.957         0.1245 0.900   0.743
#> SD:hclust   5 0.214           0.341       0.564         0.1015 0.814   0.562
#> CV:hclust   5 0.283           0.456       0.733         0.1154 0.940   0.893
#> MAD:hclust  5 0.238           0.329       0.566         0.1060 0.840   0.606
#> ATC:hclust  5 0.394           0.495       0.683         0.0848 0.842   0.598
get_stats(res_list, k = 6)
#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      6 0.660           0.531       0.759         0.0384 0.885   0.565
#> CV:NMF      6 0.656           0.504       0.735         0.0398 0.850   0.469
#> MAD:NMF     6 0.734           0.667       0.809         0.0431 0.925   0.692
#> ATC:NMF     6 0.643           0.558       0.755         0.0545 0.895   0.587
#> SD:skmeans  6 0.740           0.629       0.815         0.0425 0.886   0.535
#> CV:skmeans  6 0.708           0.465       0.740         0.0505 0.898   0.619
#> MAD:skmeans 6 0.722           0.577       0.777         0.0418 0.850   0.426
#> ATC:skmeans 6 0.914           0.855       0.940         0.0423 0.938   0.730
#> SD:mclust   6 0.593           0.559       0.703         0.0569 0.941   0.790
#> CV:mclust   6 0.538           0.334       0.622         0.0487 0.883   0.603
#> MAD:mclust  6 0.559           0.347       0.681         0.0730 0.799   0.423
#> ATC:mclust  6 0.788           0.823       0.904         0.0940 0.862   0.610
#> SD:kmeans   6 0.682           0.624       0.745         0.0531 0.894   0.601
#> CV:kmeans   6 0.618           0.505       0.697         0.0569 0.909   0.713
#> MAD:kmeans  6 0.643           0.506       0.702         0.0478 0.853   0.501
#> ATC:kmeans  6 0.717           0.607       0.794         0.0549 0.943   0.773
#> SD:pam      6 0.615           0.562       0.734         0.0451 0.870   0.522
#> CV:pam      6 0.597           0.550       0.717         0.0657 0.865   0.554
#> MAD:pam     6 0.609           0.440       0.694         0.0429 0.855   0.532
#> ATC:pam     6 0.810           0.822       0.924         0.0939 0.910   0.710
#> SD:hclust   6 0.298           0.395       0.565         0.0769 0.877   0.619
#> CV:hclust   6 0.304           0.466       0.698         0.0866 0.919   0.845
#> MAD:hclust  6 0.318           0.362       0.583         0.0654 0.865   0.605
#> ATC:hclust  6 0.459           0.491       0.689         0.0454 0.920   0.743

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 17541 rows and 500 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 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-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 0.0464           0.484       0.733         0.4127 0.514   0.514
#> 3 3 0.0674           0.379       0.652         0.2722 0.823   0.692
#> 4 4 0.1312           0.332       0.551         0.1901 0.683   0.448
#> 5 5 0.2142           0.341       0.564         0.1015 0.814   0.562
#> 6 6 0.2977           0.395       0.565         0.0769 0.877   0.619

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.9129    0.40639 0.328 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2043    0.61573 0.968 0.032
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.4022    0.64291 0.080 0.920
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.9977    0.14408 0.528 0.472
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.9732    0.37911 0.596 0.404
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.6712    0.65516 0.176 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9996    0.02244 0.488 0.512
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.9993    0.06515 0.516 0.484
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.7883    0.61082 0.236 0.764
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.7950    0.57125 0.240 0.760
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.7674    0.60425 0.224 0.776
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.9963    0.16297 0.464 0.536
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.9286    0.45580 0.344 0.656
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.9993    0.12755 0.484 0.516
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.7299    0.65604 0.796 0.204
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.9522    0.45000 0.372 0.628
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.2043    0.61573 0.968 0.032
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.9170    0.48382 0.332 0.668
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.9686    0.40311 0.604 0.396
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.3431    0.63286 0.064 0.936
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.5946    0.50357 0.144 0.856
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.9815    0.28555 0.420 0.580
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2778    0.61955 0.952 0.048
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2043    0.61570 0.032 0.968
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.4298    0.64977 0.912 0.088
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.2423    0.62403 0.040 0.960
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.8207    0.62551 0.256 0.744
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.9922    0.21386 0.552 0.448
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.8813    0.58412 0.700 0.300
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.9833    0.29606 0.576 0.424
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.9732    0.36260 0.404 0.596
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.3431    0.63286 0.064 0.936
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.3114    0.62992 0.944 0.056
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.9944    0.19560 0.456 0.544
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.9491    0.49933 0.368 0.632
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.7376    0.65071 0.792 0.208
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.7376    0.65421 0.792 0.208
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.9129    0.52004 0.328 0.672
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3733    0.64234 0.928 0.072
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.2948    0.61823 0.948 0.052
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  1.0000    0.00936 0.504 0.496
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.9608    0.45670 0.616 0.384
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     1  0.9998    0.11357 0.508 0.492
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3114    0.60841 0.944 0.056
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.7299    0.65398 0.796 0.204
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.4161    0.65033 0.084 0.916
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.5946    0.50357 0.144 0.856
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.9998    0.05235 0.492 0.508
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  0.9795    0.39517 0.416 0.584
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.9988    0.03699 0.480 0.520
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.9944    0.19614 0.456 0.544
#> 4379559E-E467-49BD-9673-40A486146A3B     2  0.9983    0.09772 0.476 0.524
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.8207    0.54850 0.256 0.744
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.6531    0.65646 0.168 0.832
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.5842    0.66344 0.860 0.140
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.7602    0.65148 0.780 0.220
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.9580    0.37222 0.380 0.620
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.7674    0.64226 0.776 0.224
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.7745    0.63844 0.228 0.772
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.9909    0.15779 0.444 0.556
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.9170    0.54572 0.668 0.332
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1  0.9661    0.43688 0.608 0.392
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.5946    0.66590 0.856 0.144
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.9491    0.46949 0.632 0.368
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     2  0.9815    0.37422 0.420 0.580
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     2  0.4298    0.65172 0.088 0.912
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.9170    0.40810 0.332 0.668
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.9087    0.55872 0.676 0.324
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.9933    0.21871 0.548 0.452
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.5519    0.65859 0.872 0.128
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  1.0000    0.01040 0.496 0.504
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.9580    0.19030 0.620 0.380
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.9000    0.51706 0.316 0.684
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.6148    0.51750 0.152 0.848
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.3431    0.64227 0.064 0.936
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.2948    0.61823 0.948 0.052
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.4815    0.65094 0.104 0.896
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9754    0.37561 0.408 0.592
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.5842    0.65165 0.140 0.860
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.2236    0.62788 0.036 0.964
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.9491    0.49441 0.632 0.368
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.3879    0.63299 0.076 0.924
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.7883    0.64357 0.764 0.236
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.7745    0.63691 0.228 0.772
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.4815    0.65762 0.896 0.104
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.9732    0.32743 0.404 0.596
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.5519    0.66111 0.872 0.128
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.2043    0.62516 0.032 0.968
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.9944    0.19542 0.544 0.456
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.9393    0.45723 0.356 0.644
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     2  0.9933    0.21292 0.452 0.548
#> 4D361EA8-1F79-4B89-841B-87F83215D805     2  0.9522    0.44749 0.372 0.628
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.8608    0.60708 0.716 0.284
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.3879    0.63465 0.076 0.924
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.9996    0.04899 0.512 0.488
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.7376    0.59944 0.208 0.792
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1  0.9686    0.43474 0.604 0.396
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.4939    0.63640 0.108 0.892
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.2948    0.61823 0.948 0.052
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.8813    0.54146 0.300 0.700
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     2  0.9970    0.15143 0.468 0.532
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.9552    0.43777 0.624 0.376
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  1.0000    0.06487 0.504 0.496
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.1414    0.61833 0.020 0.980
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.9635    0.41589 0.612 0.388
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     2  0.9833    0.34495 0.424 0.576
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.7674    0.62152 0.224 0.776
#> AE903797-7FFB-44A1-B834-C644784B5DC2     2  0.9710    0.39220 0.400 0.600
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.9044    0.50550 0.320 0.680
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.3431    0.61001 0.936 0.064
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.9815    0.36347 0.580 0.420
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.8555    0.60257 0.720 0.280
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.9635    0.37143 0.388 0.612
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     2  0.9996    0.04797 0.488 0.512
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.9710    0.38744 0.600 0.400
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.9286    0.45845 0.344 0.656
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     2  0.9427    0.50884 0.360 0.640
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.9087    0.50146 0.324 0.676
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.7883    0.61082 0.236 0.764
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.6438    0.57122 0.836 0.164
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     2  0.9850    0.32705 0.428 0.572
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.5178    0.65987 0.884 0.116
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1  0.9129    0.54833 0.672 0.328
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     2  0.9460    0.40298 0.364 0.636
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.5059    0.60396 0.112 0.888
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.2043    0.61573 0.968 0.032
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.9323    0.52734 0.652 0.348
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.9815    0.33585 0.580 0.420
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.7453    0.65219 0.788 0.212
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.4690    0.61768 0.900 0.100
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     2  0.9977    0.12483 0.472 0.528
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.8608    0.54324 0.284 0.716
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.8016    0.60558 0.244 0.756
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     2  0.9580    0.43086 0.380 0.620
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.7219    0.65902 0.800 0.200
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.2236    0.60439 0.036 0.964
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.2043    0.61573 0.968 0.032
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.9087    0.50146 0.324 0.676
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.8327    0.62086 0.736 0.264
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.3431    0.63286 0.064 0.936
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.4298    0.64627 0.088 0.912
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.9710    0.37756 0.400 0.600
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.7745    0.62140 0.228 0.772
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.9833    0.22665 0.424 0.576
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     2  0.9922    0.23049 0.448 0.552
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.5737    0.65156 0.136 0.864
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.3274    0.63083 0.060 0.940
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1  0.6438    0.57122 0.836 0.164
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     2  0.4939    0.65602 0.108 0.892
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1  0.3879    0.64459 0.924 0.076
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.2043    0.62005 0.032 0.968
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     2  0.2236    0.62831 0.036 0.964
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     2  0.7815    0.62944 0.232 0.768
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     1  0.2423    0.60191 0.960 0.040
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     2  0.9996    0.04797 0.488 0.512
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     1  0.3431    0.61001 0.936 0.064
#> 23238B08-AA91-46A3-B147-91185A5FAE3F     1  0.9866    0.27783 0.568 0.432
#> DAB49A2E-BBFD-459B-B156-726D8D91D598     2  0.9732    0.36351 0.404 0.596
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F     2  0.9993    0.03993 0.484 0.516
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0     2  0.9732    0.32743 0.404 0.596
#> D149276E-A961-49D6-8BDA-004E8264A0A1     1  0.9635    0.43294 0.612 0.388
#> D17803A2-4BF2-4382-A544-76E28695214F     1  0.3733    0.64234 0.928 0.072
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#> E1876307-DFD9-4688-876F-D71B37466068     2  0.2043    0.62005 0.032 0.968
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04     2  0.9635    0.43205 0.388 0.612
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00     1  0.2948    0.61823 0.948 0.052
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79     2  0.3274    0.64001 0.060 0.940
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A     2  0.9209    0.52071 0.336 0.664
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18     1  0.9686    0.40338 0.604 0.396
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D     2  0.5737    0.65257 0.136 0.864
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854     2  0.2236    0.62766 0.036 0.964
#> B3CCA12D-4569-4AB8-AC41-457448268D90     1  0.5178    0.65921 0.884 0.116
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     1  0.9993    0.08102 0.516 0.484
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     2  0.7528    0.62734 0.216 0.784
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.9970    0.11216 0.468 0.532
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     1  0.9993    0.06930 0.516 0.484
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.2236    0.61848 0.036 0.964
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.4298    0.63959 0.088 0.912
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     2  0.6247    0.65921 0.156 0.844
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     2  0.8144    0.63292 0.252 0.748
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.5946    0.65214 0.144 0.856
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     1  0.9129    0.52743 0.672 0.328
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     2  0.7883    0.61082 0.236 0.764
#> 985FEEC2-9737-4018-80DF-21A07AB47900     2  0.6048    0.65859 0.148 0.852
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     2  0.9393    0.51314 0.356 0.644
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     2  0.9970    0.15626 0.468 0.532
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.3274    0.63083 0.060 0.940
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.1414    0.60662 0.020 0.980
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.9996    0.03903 0.512 0.488
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.8327    0.52904 0.264 0.736
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     2  0.6247    0.65813 0.156 0.844
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.5178    0.65994 0.884 0.116
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.9286    0.45845 0.344 0.656
#> 457090A2-AE7F-4E68-85EA-032DE8411110     2  0.9983    0.11957 0.476 0.524
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     2  0.5408    0.65477 0.124 0.876
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.8443    0.61398 0.728 0.272
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.4022    0.63320 0.080 0.920
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     2  0.9833    0.31200 0.424 0.576
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.6531    0.56882 0.832 0.168
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.6148    0.65731 0.152 0.848
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.7056    0.62445 0.808 0.192
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.7376    0.59944 0.208 0.792
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.8661    0.55516 0.288 0.712
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.7883    0.61082 0.236 0.764
#> A9195281-8CAE-45A8-8493-744E577907FA     1  0.9710    0.41926 0.600 0.400
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  1.0000   -0.09164 0.496 0.504
#> E789661A-C027-405D-9F76-E6D52CE3018B     1  0.9522    0.47740 0.628 0.372
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.7815    0.64484 0.768 0.232
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.5408    0.65629 0.124 0.876
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.5178    0.65921 0.884 0.116
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.3733    0.64234 0.928 0.072
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.9988    0.06655 0.520 0.480
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.7883    0.64700 0.764 0.236
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.2043    0.62629 0.032 0.968
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     1  0.9608    0.45532 0.616 0.384
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.9896    0.26469 0.440 0.560
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.3584    0.63769 0.068 0.932
#> 80936433-AA91-4219-98F1-706C36298060     2  0.4562    0.64421 0.096 0.904
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.2043    0.61573 0.968 0.032
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.9909    0.27188 0.444 0.556
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.9833    0.31519 0.576 0.424
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.2778    0.60449 0.952 0.048
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.6148    0.51750 0.152 0.848
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     2  0.9896    0.26501 0.440 0.560
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.5178    0.65921 0.884 0.116
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.7602    0.65043 0.780 0.220
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.8608    0.60708 0.716 0.284
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.9686    0.40418 0.604 0.396
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     2  0.6343    0.65051 0.160 0.840
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.7883    0.61082 0.236 0.764
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.2043    0.61573 0.968 0.032
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.6712    0.66422 0.824 0.176
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.2423    0.60123 0.960 0.040
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.9635    0.37143 0.388 0.612
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.7139    0.66106 0.804 0.196
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     2  0.8608    0.58285 0.284 0.716
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.7139    0.64639 0.196 0.804
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.5946    0.66590 0.856 0.144
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     2  0.8763    0.56356 0.296 0.704
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.9909    0.27188 0.444 0.556
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.6531    0.66428 0.832 0.168
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.9170    0.54228 0.668 0.332
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.8608    0.61021 0.716 0.284
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.5178    0.65432 0.116 0.884
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.8813    0.54146 0.300 0.700
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.8555    0.61025 0.720 0.280
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.9710    0.34241 0.400 0.600
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.7602    0.64161 0.220 0.780
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.7528    0.62734 0.216 0.784
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2423    0.60123 0.960 0.040
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.9710    0.31573 0.400 0.600
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.2043    0.61573 0.968 0.032
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.8081    0.63765 0.752 0.248
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.8386    0.60942 0.268 0.732
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.3114    0.62547 0.056 0.944
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.9815    0.36347 0.580 0.420
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.9732    0.36893 0.596 0.404
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     2  0.6247    0.65183 0.156 0.844
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     2  0.9909    0.24729 0.444 0.556
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.5946    0.66511 0.856 0.144
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.8386    0.57659 0.268 0.732
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.8443    0.56942 0.272 0.728
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.2043    0.61573 0.968 0.032
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.6438    0.65267 0.164 0.836
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  1.0000    0.03666 0.504 0.496
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.9427    0.50890 0.360 0.640
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.6247    0.65190 0.156 0.844
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.9608    0.45194 0.384 0.616
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.7453    0.64323 0.212 0.788
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.6247    0.65030 0.156 0.844
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     2  0.9661    0.40336 0.392 0.608
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.9833    0.31519 0.576 0.424
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.9963    0.14708 0.536 0.464
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.9209    0.53631 0.664 0.336
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.9983    0.12431 0.524 0.476
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.9686    0.39595 0.396 0.604
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.2603    0.63262 0.044 0.956
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.8763    0.58946 0.704 0.296
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.7219    0.60427 0.200 0.800
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.7883    0.61041 0.236 0.764
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.5178    0.65921 0.884 0.116
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.9393    0.48292 0.356 0.644
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.5178    0.65612 0.116 0.884
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.6343    0.66629 0.840 0.160
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     2  0.9754    0.37168 0.408 0.592
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.6712    0.63026 0.824 0.176
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.2948    0.63077 0.948 0.052
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.2948    0.63077 0.948 0.052
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.4939    0.65676 0.892 0.108
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9909    0.26784 0.556 0.444
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.6148    0.66323 0.848 0.152
#> C33059A9-A313-4806-B43B-0031365F3BE4     2  1.0000    0.05770 0.496 0.504
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.8443    0.59230 0.272 0.728
#> 1122039D-5785-4F70-9916-17C585453512     1  0.4690    0.61768 0.900 0.100
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6801    0.57765 0.820 0.180
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.9580    0.47608 0.380 0.620
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  1.0000    0.01040 0.496 0.504
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.9732    0.36175 0.404 0.596
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.9427    0.44926 0.360 0.640
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.9983    0.07366 0.524 0.476
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.4690    0.61768 0.900 0.100
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.9993    0.08274 0.516 0.484
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.9996    0.03371 0.512 0.488
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.3114    0.63807 0.056 0.944
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.9732    0.40015 0.596 0.404
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.9358    0.51482 0.648 0.352
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.5737    0.66347 0.864 0.136
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.9996    0.09344 0.512 0.488
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.4939    0.65501 0.108 0.892
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.9970    0.14228 0.532 0.468
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.9522    0.47840 0.372 0.628
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.6438    0.65703 0.164 0.836
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1  0.9881    0.30964 0.564 0.436
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     2  0.9996    0.06374 0.488 0.512
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     2  0.9933    0.21768 0.452 0.548
#> EB7883EB-0079-4548-9132-169E94A698BA     2  0.9944    0.19721 0.456 0.544
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.9209    0.53115 0.664 0.336
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.2043    0.61573 0.968 0.032
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.8661    0.59926 0.712 0.288
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.3431    0.63904 0.064 0.936
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.2236    0.60439 0.036 0.964
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.6343    0.62787 0.160 0.840
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.9833    0.31519 0.576 0.424
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.9954    0.19263 0.460 0.540
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     2  0.9833    0.31107 0.424 0.576
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.7815    0.64489 0.768 0.232

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3481    0.62224 0.044 0.904 0.052
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0747    0.58636 0.984 0.016 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3445    0.45974 0.016 0.088 0.896
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.7069    0.09961 0.508 0.020 0.472
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.9208    0.33958 0.532 0.204 0.264
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.5263    0.57742 0.116 0.060 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.9018    0.04120 0.456 0.132 0.412
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.6468    0.14282 0.444 0.004 0.552
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.4164    0.57196 0.144 0.008 0.848
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#> A0C429D9-0638-4873-BFB4-00056AB4719F     3  0.8777    0.07293 0.148 0.288 0.564
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.6680    0.12378 0.508 0.008 0.484
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.7868    0.22984 0.420 0.056 0.524
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5948    0.37232 0.360 0.000 0.640
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5291    0.56248 0.732 0.000 0.268

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4   0.606   0.703576 0.084 0.240 0.004 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1   0.355   0.631908 0.856 0.008 0.120 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2   0.615   0.202170 0.008 0.488 0.472 0.032
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3   0.764   0.114178 0.356 0.184 0.456 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1   0.868   0.282580 0.408 0.256 0.296 0.040
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3   0.607   0.211313 0.016 0.288 0.652 0.044
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3   0.831   0.035327 0.300 0.284 0.400 0.016
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3   0.380   0.496940 0.148 0.012 0.832 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.527   0.306509 0.024 0.268 0.700 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2   0.888   0.237275 0.068 0.440 0.272 0.220
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.831   0.299139 0.084 0.556 0.188 0.172
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3   0.432   0.537814 0.120 0.048 0.824 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.913   0.276580 0.200 0.400 0.312 0.088
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3   0.497   0.535613 0.136 0.080 0.780 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1   0.614   0.517895 0.584 0.060 0.356 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3   0.499   0.521414 0.072 0.148 0.776 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1   0.355   0.631908 0.856 0.008 0.120 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.901   0.338122 0.196 0.472 0.224 0.108
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1   0.869   0.299119 0.404 0.252 0.304 0.040
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.683   0.424306 0.012 0.640 0.184 0.164
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4   0.622   0.698110 0.072 0.212 0.024 0.692
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2   0.889   0.121852 0.244 0.352 0.352 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1   0.751   0.478942 0.596 0.032 0.208 0.164
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2   0.693   0.400556 0.008 0.620 0.180 0.192
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1   0.416   0.631366 0.772 0.004 0.220 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2   0.669   0.467115 0.004 0.632 0.212 0.152
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3   0.680   0.301075 0.068 0.292 0.612 0.028
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3   0.533   0.422721 0.236 0.044 0.716 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3   0.562   0.077619 0.372 0.012 0.604 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3   0.547   0.432867 0.236 0.028 0.716 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3   0.455   0.529761 0.100 0.096 0.804 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2   0.683   0.424306 0.012 0.640 0.184 0.164
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1   0.395   0.634859 0.832 0.012 0.140 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F     3   0.371   0.549571 0.100 0.040 0.856 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3   0.675   0.328437 0.064 0.188 0.680 0.068
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1   0.633   0.519421 0.592 0.080 0.328 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1   0.624   0.487040 0.568 0.064 0.368 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3   0.560   0.433428 0.076 0.200 0.720 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1   0.389   0.634276 0.796 0.000 0.196 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1   0.378   0.626892 0.852 0.012 0.112 0.024
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3   0.377   0.508095 0.136 0.016 0.840 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3   0.637   0.245489 0.308 0.068 0.616 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     3   0.861  -0.063653 0.296 0.280 0.392 0.032
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1   0.825   0.344177 0.516 0.044 0.240 0.200
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1   0.637   0.522299 0.584 0.080 0.336 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.628  -0.094175 0.004 0.428 0.520 0.048
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4   0.622   0.698110 0.072 0.212 0.024 0.692
#> 066B10C1-777F-4863-ACCA-6684310B913E     3   0.635   0.436079 0.244 0.116 0.640 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3   0.856   0.243213 0.180 0.200 0.528 0.092
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2   0.917   0.011155 0.308 0.328 0.296 0.068
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3   0.348   0.544909 0.116 0.028 0.856 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3   0.565   0.535869 0.168 0.100 0.728 0.004
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4   0.954   0.271560 0.204 0.288 0.136 0.372
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3   0.635   0.236911 0.016 0.256 0.656 0.072
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1   0.480   0.554034 0.656 0.000 0.340 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1   0.633   0.422149 0.536 0.028 0.416 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2   0.876   0.122603 0.220 0.380 0.352 0.048
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1   0.652   0.495829 0.576 0.092 0.332 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3   0.592   0.280133 0.024 0.272 0.672 0.032
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2   0.917   0.055146 0.288 0.324 0.320 0.068
#> A77DDA16-167D-4444-8C58-526C99F2B406     3   0.545   0.168927 0.332 0.012 0.644 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1   0.787   0.247294 0.440 0.204 0.348 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1   0.479   0.585788 0.680 0.008 0.312 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3   0.512   0.287651 0.276 0.016 0.700 0.008
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3   0.516   0.541073 0.100 0.116 0.776 0.008
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3   0.663  -0.100516 0.004 0.412 0.512 0.072
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4   0.643   0.699870 0.084 0.256 0.012 0.648
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3   0.609   0.113337 0.340 0.032 0.612 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3   0.556   0.429574 0.236 0.056 0.704 0.004
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1   0.453   0.602064 0.704 0.000 0.292 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     1   0.950  -0.012046 0.396 0.264 0.144 0.196
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4   0.986   0.224195 0.292 0.176 0.236 0.296
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2   0.822   0.248201 0.236 0.408 0.340 0.016
#> DCD81371-253F-4672-AA92-9F27A338F68E     4   0.679   0.702595 0.072 0.264 0.032 0.632
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3   0.750  -0.219509 0.004 0.372 0.464 0.160
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1   0.378   0.626892 0.852 0.012 0.112 0.024
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.579  -0.042777 0.004 0.416 0.556 0.024
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3   0.613   0.466228 0.104 0.184 0.700 0.012
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3   0.598   0.060587 0.024 0.392 0.572 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2   0.639   0.241241 0.000 0.488 0.448 0.064
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3   0.640   0.185686 0.328 0.064 0.600 0.008
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2   0.675   0.381438 0.016 0.656 0.164 0.164
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3   0.580  -0.202017 0.456 0.012 0.520 0.012
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3   0.598   0.279198 0.044 0.292 0.652 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1   0.452   0.619091 0.728 0.004 0.264 0.004
#> 46351E5C-2438-4B6A-8343-DDF329086771     3   0.829   0.016517 0.228 0.348 0.404 0.020
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1   0.441   0.591909 0.700 0.000 0.300 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2   0.627   0.227930 0.000 0.484 0.460 0.056
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3   0.537   0.398006 0.276 0.040 0.684 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3   0.806  -0.024867 0.196 0.368 0.420 0.016
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3   0.346   0.549759 0.108 0.032 0.860 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3   0.489   0.528935 0.088 0.120 0.788 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     3   0.636  -0.100368 0.400 0.048 0.544 0.008
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2   0.700   0.428531 0.020 0.636 0.184 0.160
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3   0.363   0.499598 0.144 0.008 0.840 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2   0.787   0.197896 0.068 0.592 0.144 0.196
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1   0.787   0.252706 0.440 0.204 0.348 0.008
#> 31322670-76A2-4308-A71F-D8E00049519D     2   0.734   0.365841 0.028 0.612 0.180 0.180
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1   0.378   0.626892 0.852 0.012 0.112 0.024
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2   0.814   0.261035 0.216 0.420 0.348 0.016
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3   0.386   0.531184 0.144 0.028 0.828 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     3   0.551   0.139955 0.376 0.024 0.600 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3   0.731   0.284393 0.236 0.204 0.556 0.004
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2   0.638   0.465476 0.012 0.624 0.300 0.064
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3   0.535   0.344666 0.280 0.024 0.688 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     2   0.976  -0.059625 0.152 0.324 0.256 0.268
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3   0.606   0.241496 0.040 0.300 0.644 0.016
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3   0.488   0.536696 0.092 0.096 0.800 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2   0.839   0.246620 0.196 0.412 0.360 0.032
#> C44C898C-EEF9-4E03-911A-9D951312C380     1   0.836   0.330830 0.504 0.048 0.248 0.200
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3   0.758  -0.018954 0.364 0.156 0.472 0.008
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1   0.730   0.410701 0.512 0.128 0.352 0.008
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     3   0.822   0.006349 0.212 0.356 0.412 0.020
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3   0.631   0.495693 0.156 0.084 0.716 0.044
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1   0.867   0.288433 0.412 0.252 0.296 0.040
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2   0.907   0.275021 0.196 0.404 0.316 0.084
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3   0.674   0.309019 0.060 0.188 0.680 0.072
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2   0.824   0.241065 0.240 0.404 0.340 0.016
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3   0.527   0.306509 0.024 0.268 0.700 0.008
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1   0.886   0.181189 0.388 0.060 0.348 0.204
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3   0.426   0.545688 0.112 0.068 0.820 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1   0.472   0.613722 0.716 0.004 0.272 0.008
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1   0.749   0.352669 0.468 0.160 0.368 0.004
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     2   0.926  -0.146249 0.100 0.384 0.200 0.316
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2   0.729   0.318915 0.028 0.616 0.156 0.200
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1   0.355   0.631908 0.856 0.008 0.120 0.016
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3   0.688  -0.009489 0.376 0.096 0.524 0.004
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3   0.555   0.384560 0.212 0.052 0.724 0.012
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1   0.508   0.450262 0.576 0.004 0.420 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1   0.485   0.580313 0.812 0.032 0.096 0.060
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3   0.427   0.535669 0.120 0.040 0.828 0.012
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2   0.845   0.285279 0.148 0.556 0.172 0.124
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3   0.559   0.327801 0.048 0.260 0.688 0.004
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3   0.556   0.518660 0.100 0.128 0.756 0.016
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1   0.569   0.347205 0.524 0.008 0.456 0.012
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2   0.809   0.379032 0.020 0.472 0.296 0.212
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1   0.355   0.631908 0.856 0.008 0.120 0.016
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2   0.824   0.241065 0.240 0.404 0.340 0.016
#> CBEFE77E-A0EB-457D-A145-763654236EBB     3   0.604  -0.160651 0.432 0.028 0.532 0.008
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2   0.683   0.424306 0.012 0.640 0.184 0.164
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3   0.566  -0.106652 0.000 0.440 0.536 0.024
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     3   0.447   0.530652 0.080 0.112 0.808 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2   0.777   0.292626 0.120 0.472 0.380 0.028
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     3   0.839  -0.000205 0.244 0.316 0.416 0.024
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     3   0.506   0.541024 0.164 0.076 0.760 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2   0.735   0.340693 0.064 0.496 0.400 0.040
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2   0.666   0.452158 0.012 0.656 0.188 0.144
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1   0.880   0.180358 0.388 0.056 0.352 0.204
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3   0.622  -0.066087 0.012 0.420 0.536 0.032
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1   0.416   0.630521 0.768 0.000 0.224 0.008
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#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3   0.551   0.545427 0.128 0.124 0.744 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1   0.840   0.496573 0.552 0.108 0.204 0.136
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1   0.371   0.635935 0.832 0.004 0.152 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1   0.371   0.635935 0.832 0.004 0.152 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1   0.451   0.603124 0.708 0.000 0.288 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1   0.912   0.207364 0.368 0.272 0.292 0.068
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1   0.460   0.566571 0.664 0.000 0.336 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     3   0.521   0.478998 0.224 0.052 0.724 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3   0.476   0.367359 0.020 0.216 0.756 0.008
#> 1122039D-5785-4F70-9916-17C585453512     1   0.485   0.580313 0.812 0.032 0.096 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1   0.879   0.203406 0.392 0.060 0.360 0.188
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3   0.647   0.340158 0.056 0.188 0.696 0.060
#> C56C7ED7-A684-40CC-B426-B108E2248467     1   0.950  -0.012046 0.396 0.264 0.144 0.196
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3   0.923  -0.252523 0.196 0.348 0.360 0.096
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3   0.808  -0.005544 0.200 0.360 0.424 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3   0.579   0.369686 0.284 0.060 0.656 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1   0.485   0.580313 0.812 0.032 0.096 0.060
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3   0.591   0.523990 0.192 0.092 0.708 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3   0.418   0.502585 0.160 0.020 0.812 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.644  -0.169465 0.000 0.436 0.496 0.068
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3   0.657   0.291092 0.300 0.084 0.608 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1   0.748   0.291163 0.456 0.156 0.384 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1   0.445   0.593336 0.692 0.000 0.308 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1   0.917   0.055644 0.332 0.308 0.292 0.068
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.591   0.003509 0.004 0.392 0.572 0.032
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3   0.425   0.464773 0.176 0.016 0.800 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3   0.624   0.380202 0.056 0.172 0.716 0.056
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3   0.643   0.209978 0.016 0.268 0.644 0.072
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1   0.860   0.214935 0.396 0.272 0.300 0.032
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3   0.354   0.522749 0.128 0.012 0.852 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3   0.420   0.555542 0.112 0.048 0.832 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     3   0.327   0.542231 0.108 0.024 0.868 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3   0.539   0.195388 0.320 0.012 0.656 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1   0.355   0.631908 0.856 0.008 0.120 0.016
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3   0.563   0.051287 0.376 0.012 0.600 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2   0.717   0.449913 0.040 0.564 0.332 0.064
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2   0.809   0.379032 0.020 0.472 0.296 0.212
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.781   0.494362 0.104 0.588 0.232 0.076
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3   0.465   0.405156 0.216 0.016 0.760 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3   0.617   0.500182 0.160 0.148 0.688 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3   0.502   0.536018 0.144 0.088 0.768 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3   0.581  -0.209613 0.460 0.012 0.516 0.012

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5   0.696   0.679605 0.000 0.380 0.092 0.064 0.464
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.475   0.604229 0.260 0.044 0.692 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1   0.838   0.115639 0.368 0.152 0.160 0.312 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2   0.734   0.143782 0.240 0.420 0.024 0.312 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1   0.541  -0.243300 0.496 0.016 0.460 0.000 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1   0.869  -0.199811 0.340 0.280 0.176 0.192 0.012
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1   0.242   0.551037 0.908 0.008 0.052 0.032 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1   0.475  -0.106852 0.556 0.012 0.428 0.004 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3   0.776   0.227007 0.124 0.204 0.548 0.040 0.084
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.541   0.348656 0.096 0.744 0.104 0.044 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1   0.315   0.539658 0.860 0.012 0.104 0.024 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.771   0.507675 0.216 0.520 0.100 0.152 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1   0.521   0.534941 0.748 0.076 0.100 0.076 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4   0.613   0.417418 0.384 0.104 0.008 0.504 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1   0.501   0.419163 0.708 0.044 0.224 0.024 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.711   0.416791 0.112 0.604 0.128 0.144 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2   0.754   0.126251 0.240 0.412 0.024 0.312 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.520   0.376286 0.048 0.696 0.232 0.004 0.020
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     5   0.370   0.706486 0.000 0.040 0.092 0.028 0.840
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2   0.829   0.432559 0.248 0.424 0.152 0.168 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4   0.805   0.450648 0.284 0.108 0.084 0.480 0.044
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2   0.686   0.285504 0.048 0.536 0.304 0.004 0.108
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4   0.389   0.629324 0.240 0.004 0.004 0.748 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2   0.631   0.313526 0.060 0.556 0.332 0.000 0.052
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1   0.620  -0.046917 0.504 0.024 0.416 0.036 0.020
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1   0.548   0.539890 0.712 0.052 0.072 0.164 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1   0.430   0.359925 0.736 0.008 0.024 0.232 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1   0.474   0.557642 0.772 0.020 0.084 0.120 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1   0.510   0.446862 0.708 0.016 0.208 0.068 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2   0.520   0.376286 0.048 0.696 0.232 0.004 0.020
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4   0.325   0.590374 0.084 0.040 0.008 0.864 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     1   0.432   0.526952 0.792 0.024 0.132 0.052 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1   0.676   0.243086 0.600 0.156 0.196 0.036 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4   0.649   0.413977 0.344 0.156 0.008 0.492 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     4   0.637   0.368866 0.408 0.116 0.012 0.464 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1   0.518   0.183162 0.600 0.004 0.352 0.044 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4   0.337   0.637232 0.212 0.000 0.000 0.784 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4   0.271   0.588114 0.076 0.004 0.008 0.892 0.020
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1   0.254   0.548647 0.904 0.016 0.056 0.024 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1   0.587   0.438786 0.668 0.056 0.072 0.204 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2   0.813   0.257317 0.344 0.352 0.100 0.200 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4   0.865   0.321780 0.300 0.140 0.104 0.404 0.052
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4   0.655   0.419460 0.356 0.148 0.012 0.484 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.500   0.567714 0.304 0.016 0.656 0.004 0.020
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     5   0.370   0.706486 0.000 0.040 0.092 0.028 0.840
#> 066B10C1-777F-4863-ACCA-6684310B913E     1   0.714   0.443528 0.548 0.072 0.172 0.208 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1   0.795   0.062806 0.464 0.088 0.292 0.136 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2   0.707   0.373537 0.224 0.524 0.020 0.220 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1   0.429   0.524440 0.788 0.012 0.132 0.068 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1   0.541   0.521723 0.684 0.012 0.200 0.104 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     5   0.890   0.247336 0.072 0.276 0.088 0.176 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1   0.559  -0.139799 0.512 0.016 0.432 0.000 0.040
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4   0.449   0.501700 0.404 0.000 0.004 0.588 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1   0.569  -0.191017 0.528 0.044 0.012 0.412 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2   0.841   0.407917 0.284 0.412 0.156 0.128 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     4   0.675   0.367188 0.336 0.184 0.012 0.468 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1   0.512  -0.107379 0.548 0.040 0.412 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2   0.776   0.389413 0.228 0.464 0.076 0.228 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     1   0.433   0.414941 0.756 0.012 0.032 0.200 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     4   0.846  -0.002801 0.272 0.236 0.112 0.368 0.012
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4   0.473   0.516641 0.396 0.008 0.004 0.588 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1   0.415   0.487004 0.804 0.016 0.044 0.132 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1   0.562   0.465484 0.680 0.044 0.212 0.064 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3   0.544   0.561036 0.312 0.020 0.628 0.004 0.036
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5   0.722   0.665209 0.004 0.392 0.104 0.064 0.436
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1   0.530   0.372549 0.720 0.048 0.044 0.184 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1   0.468   0.564589 0.756 0.008 0.104 0.132 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4   0.425   0.594238 0.296 0.000 0.016 0.688 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4   0.834  -0.118227 0.072 0.316 0.020 0.352 0.240
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2   0.983  -0.221323 0.216 0.260 0.192 0.212 0.120
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3   0.868  -0.168777 0.180 0.284 0.340 0.184 0.012
#> DCD81371-253F-4672-AA92-9F27A338F68E     5   0.458   0.698789 0.000 0.220 0.016 0.032 0.732
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3   0.651   0.530399 0.288 0.024 0.552 0.000 0.136
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4   0.271   0.588114 0.076 0.004 0.008 0.892 0.020
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.485   0.538363 0.360 0.024 0.612 0.000 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1   0.670   0.408532 0.620 0.148 0.168 0.056 0.008
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3   0.520   0.477449 0.408 0.028 0.556 0.004 0.004
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3   0.468   0.611427 0.232 0.020 0.720 0.000 0.028
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1   0.593   0.398303 0.656 0.060 0.064 0.220 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2   0.545   0.357821 0.044 0.684 0.236 0.008 0.028
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1   0.509   0.136159 0.648 0.012 0.028 0.308 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1   0.574  -0.167566 0.500 0.044 0.436 0.020 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4   0.414   0.603423 0.308 0.004 0.000 0.684 0.004
#> 46351E5C-2438-4B6A-8343-DDF329086771     1   0.873  -0.290375 0.320 0.312 0.216 0.132 0.020
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4   0.435   0.557403 0.356 0.000 0.004 0.636 0.004
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3   0.435   0.604814 0.236 0.012 0.732 0.000 0.020
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1   0.585   0.486713 0.620 0.008 0.128 0.244 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2   0.865   0.238802 0.292 0.304 0.272 0.116 0.016
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1   0.431   0.520086 0.788 0.016 0.136 0.060 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1   0.422   0.440192 0.756 0.020 0.212 0.008 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1   0.551   0.190985 0.636 0.072 0.012 0.280 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2   0.528   0.381549 0.048 0.700 0.224 0.012 0.016
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1   0.249   0.551271 0.904 0.008 0.056 0.032 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2   0.486   0.243533 0.048 0.784 0.112 0.032 0.024
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     4   0.847   0.000358 0.276 0.240 0.112 0.360 0.012
#> 31322670-76A2-4308-A71F-D8E00049519D     2   0.512   0.351117 0.056 0.736 0.176 0.012 0.020
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4   0.271   0.588114 0.076 0.004 0.008 0.892 0.020
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3   0.863  -0.161713 0.180 0.292 0.348 0.168 0.012
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1   0.479   0.533459 0.760 0.012 0.132 0.092 0.004
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1   0.628   0.289982 0.568 0.024 0.088 0.316 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1   0.734   0.346829 0.564 0.160 0.140 0.132 0.004
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3   0.629   0.335811 0.104 0.260 0.604 0.004 0.028
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1   0.465   0.489504 0.732 0.004 0.064 0.200 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3   0.923  -0.036558 0.192 0.144 0.408 0.108 0.148
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#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4   0.860   0.330735 0.288 0.136 0.104 0.420 0.052
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     5   0.458   0.698789 0.000 0.220 0.016 0.032 0.732
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1   0.352   0.525284 0.828 0.008 0.136 0.028 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     4   0.436   0.555405 0.360 0.000 0.004 0.632 0.004
#> 40467950-A95C-4731-AD93-0A128442C837     1   0.585   0.089816 0.612 0.036 0.036 0.308 0.008
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1   0.551   0.190985 0.636 0.072 0.012 0.280 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1   0.465   0.501240 0.740 0.012 0.052 0.196 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3   0.510   0.430343 0.428 0.016 0.544 0.008 0.004
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1   0.475  -0.106852 0.556 0.012 0.428 0.004 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4   0.636   0.517479 0.336 0.104 0.016 0.540 0.004
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4   0.845   0.340319 0.244 0.140 0.100 0.464 0.052
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2   0.869   0.290190 0.312 0.316 0.232 0.120 0.020
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4   0.504   0.390820 0.452 0.008 0.012 0.524 0.004
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1   0.481   0.223849 0.636 0.016 0.336 0.012 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1   0.479  -0.214885 0.520 0.012 0.464 0.000 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A     4   0.473   0.516641 0.396 0.008 0.004 0.588 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1   0.545   0.258944 0.624 0.028 0.312 0.036 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1   0.581   0.486313 0.700 0.160 0.084 0.048 0.008
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4   0.471   0.341388 0.484 0.000 0.008 0.504 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1   0.786  -0.227305 0.352 0.256 0.040 0.340 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1   0.646  -0.156011 0.464 0.068 0.044 0.424 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3   0.704   0.400534 0.192 0.216 0.552 0.020 0.020
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3   0.863  -0.161713 0.180 0.292 0.348 0.168 0.012
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1   0.457   0.295428 0.708 0.012 0.024 0.256 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2   0.873   0.284447 0.308 0.316 0.228 0.128 0.020
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1   0.486  -0.092765 0.548 0.024 0.428 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1   0.512  -0.253397 0.500 0.028 0.468 0.000 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4   0.845   0.340319 0.244 0.140 0.100 0.464 0.052
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2   0.827   0.410927 0.300 0.420 0.112 0.148 0.020
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1   0.481   0.139854 0.640 0.004 0.020 0.332 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1   0.595  -0.032593 0.528 0.052 0.392 0.028 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2   0.537   0.332212 0.028 0.668 0.256 0.000 0.048
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1   0.803  -0.013382 0.392 0.204 0.108 0.296 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1   0.473   0.517465 0.732 0.004 0.076 0.188 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3   0.520   0.449601 0.416 0.016 0.552 0.008 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1   0.492   0.510975 0.744 0.024 0.160 0.072 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4   0.456   0.543298 0.376 0.004 0.004 0.612 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2   0.848   0.232513 0.220 0.356 0.304 0.104 0.016
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2   0.825   0.456622 0.216 0.476 0.180 0.096 0.032
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3   0.521   0.414529 0.436 0.016 0.532 0.012 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1   0.573   0.534990 0.676 0.024 0.140 0.160 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1   0.699   0.227060 0.588 0.176 0.180 0.036 0.020
#> C075F09E-623C-46ED-B927-889B48F450B3     3   0.510   0.438101 0.424 0.016 0.548 0.008 0.004
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1   0.616   0.358496 0.660 0.152 0.148 0.032 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1   0.517  -0.255432 0.500 0.040 0.460 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3   0.494   0.495224 0.392 0.024 0.580 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1   0.500   0.433938 0.716 0.020 0.208 0.056 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1   0.362   0.552801 0.848 0.016 0.048 0.084 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1   0.251   0.555334 0.904 0.008 0.040 0.048 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1   0.789  -0.226144 0.352 0.260 0.036 0.336 0.016
#> 816CF68B-8476-4960-9F05-FB959A686323     1   0.841   0.112055 0.364 0.156 0.160 0.312 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1   0.485   0.453895 0.736 0.044 0.192 0.028 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3   0.509   0.596393 0.252 0.016 0.684 0.000 0.048
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1   0.453   0.359057 0.736 0.008 0.032 0.220 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2   0.501   0.283706 0.048 0.772 0.120 0.040 0.020
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     3   0.833  -0.031913 0.224 0.288 0.384 0.088 0.016
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4   0.436   0.555405 0.360 0.000 0.004 0.632 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1   0.405   0.395724 0.744 0.012 0.236 0.008 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.487   0.489419 0.384 0.012 0.592 0.000 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4   0.488   0.478222 0.416 0.004 0.012 0.564 0.004
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1   0.554   0.482045 0.684 0.032 0.208 0.076 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4   0.801   0.304293 0.212 0.228 0.072 0.468 0.020
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4   0.260   0.632555 0.148 0.000 0.000 0.852 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4   0.260   0.632555 0.148 0.000 0.000 0.852 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4   0.422   0.587438 0.324 0.000 0.004 0.668 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2   0.740   0.238025 0.224 0.464 0.016 0.276 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4   0.461   0.503220 0.408 0.000 0.008 0.580 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     1   0.605   0.503786 0.632 0.012 0.156 0.196 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1   0.496   0.100798 0.616 0.032 0.348 0.004 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4   0.372   0.534821 0.060 0.004 0.008 0.836 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1   0.877  -0.107572 0.404 0.148 0.128 0.272 0.048
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1   0.680   0.263503 0.596 0.164 0.192 0.036 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467     4   0.834  -0.118227 0.072 0.316 0.020 0.352 0.240
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2   0.745   0.426757 0.272 0.508 0.092 0.124 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2   0.867   0.240729 0.296 0.300 0.268 0.120 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1   0.664   0.459762 0.580 0.048 0.128 0.244 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4   0.372   0.534821 0.060 0.004 0.008 0.836 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1   0.559   0.487405 0.656 0.004 0.188 0.152 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1   0.408   0.558648 0.812 0.016 0.084 0.088 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.482   0.584305 0.284 0.012 0.676 0.000 0.028
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1   0.614   0.447259 0.656 0.072 0.084 0.188 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     4   0.767   0.109239 0.352 0.232 0.044 0.368 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4   0.450   0.560432 0.356 0.004 0.004 0.632 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2   0.717   0.332299 0.224 0.504 0.020 0.240 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.493   0.512827 0.372 0.012 0.600 0.000 0.016
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1   0.295   0.558657 0.884 0.016 0.044 0.056 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1   0.652   0.324749 0.632 0.152 0.168 0.036 0.012
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1   0.560  -0.185299 0.500 0.016 0.444 0.000 0.040
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2   0.782   0.194435 0.232 0.408 0.052 0.300 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1   0.296   0.551132 0.880 0.012 0.068 0.040 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1   0.489   0.520775 0.756 0.032 0.140 0.072 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1   0.417   0.524586 0.796 0.012 0.132 0.060 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1   0.404   0.428284 0.784 0.008 0.024 0.180 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4   0.218   0.599498 0.080 0.000 0.008 0.908 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1   0.425   0.340966 0.736 0.008 0.020 0.236 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.720   0.286278 0.156 0.268 0.528 0.020 0.028
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.651   0.446925 0.132 0.040 0.612 0.004 0.212
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.769   0.344325 0.112 0.484 0.300 0.088 0.016
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1   0.362   0.552801 0.848 0.016 0.048 0.084 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1   0.656   0.506858 0.652 0.112 0.128 0.100 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1   0.549   0.471266 0.684 0.016 0.192 0.108 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1   0.509   0.136286 0.648 0.012 0.028 0.308 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4   0.703   0.525825 0.000 0.176 0.040 0.396 0.364 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6   0.160   0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.466   0.616343 0.156 0.068 0.740 0.008 0.028 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1   0.854  -0.144997 0.320 0.224 0.132 0.012 0.056 0.256
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2   0.757   0.366758 0.160 0.372 0.000 0.004 0.264 0.200
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3   0.505   0.305870 0.432 0.024 0.516 0.024 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2   0.764   0.574417 0.272 0.440 0.128 0.000 0.048 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1   0.310   0.591563 0.864 0.024 0.076 0.000 0.016 0.020
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.463   0.267362 0.484 0.012 0.488 0.004 0.012 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3   0.750   0.169699 0.084 0.136 0.492 0.052 0.232 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5   0.405   0.526604 0.048 0.112 0.020 0.000 0.800 0.020
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1   0.350   0.574564 0.824 0.020 0.124 0.000 0.020 0.012
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5   0.703   0.048487 0.128 0.316 0.016 0.000 0.456 0.084
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1   0.563   0.558029 0.708 0.068 0.104 0.004 0.076 0.040
#> 5AB5396F-925B-469C-B240-FB37991004DD     6   0.637   0.069220 0.336 0.252 0.000 0.004 0.008 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1   0.499   0.419776 0.668 0.044 0.256 0.004 0.020 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6   0.160   0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5   0.684   0.396495 0.060 0.244 0.052 0.008 0.560 0.076
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2   0.748   0.366769 0.156 0.364 0.000 0.000 0.268 0.212
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5   0.409   0.589162 0.016 0.092 0.116 0.000 0.776 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4   0.271   0.684786 0.000 0.028 0.084 0.876 0.008 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2   0.777   0.443617 0.152 0.460 0.080 0.000 0.220 0.088
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6   0.767   0.418536 0.264 0.200 0.032 0.000 0.096 0.408
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5   0.665   0.475334 0.032 0.116 0.176 0.088 0.588 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6   0.393   0.588382 0.216 0.040 0.004 0.000 0.000 0.740
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5   0.587   0.510064 0.024 0.100 0.240 0.024 0.612 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1   0.585  -0.158223 0.456 0.048 0.452 0.016 0.012 0.016
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1   0.572   0.585304 0.692 0.076 0.084 0.004 0.024 0.120
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1   0.454   0.488979 0.744 0.068 0.012 0.008 0.004 0.164
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1   0.483   0.601294 0.748 0.048 0.100 0.000 0.012 0.092
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1   0.523   0.425003 0.664 0.020 0.240 0.004 0.012 0.060
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5   0.409   0.589162 0.016 0.092 0.116 0.000 0.776 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     6   0.281   0.522237 0.028 0.076 0.000 0.012 0.008 0.876
#> C06D8112-0FA0-4607-988D-589D8694743F     1   0.463   0.547757 0.764 0.028 0.140 0.008 0.032 0.028
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1   0.672   0.310435 0.548 0.092 0.188 0.004 0.164 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     6   0.643  -0.180252 0.280 0.344 0.000 0.004 0.008 0.364
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1   0.662  -0.253279 0.364 0.268 0.004 0.004 0.012 0.348
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1   0.522   0.089933 0.556 0.012 0.384 0.004 0.016 0.028
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6   0.352   0.594962 0.188 0.036 0.000 0.000 0.000 0.776
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     6   0.219   0.544218 0.028 0.024 0.000 0.028 0.004 0.916
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#> B23A1419-0406-48BF-813B-B6ED6FD98789     1   0.508   0.462951 0.700 0.096 0.024 0.004 0.004 0.172
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5   0.284   0.515832 0.016 0.076 0.020 0.000 0.876 0.012
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2   0.724   0.338360 0.124 0.424 0.340 0.000 0.084 0.028
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6   0.476   0.506301 0.352 0.052 0.004 0.000 0.000 0.592
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1   0.453   0.425047 0.688 0.024 0.264 0.004 0.008 0.012
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.444   0.550146 0.312 0.020 0.652 0.004 0.012 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6   0.502   0.404846 0.408 0.048 0.012 0.000 0.000 0.532
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1   0.550   0.478569 0.656 0.064 0.224 0.004 0.008 0.044
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2   0.775   0.115214 0.148 0.364 0.020 0.004 0.136 0.328
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6   0.265   0.584276 0.112 0.028 0.000 0.000 0.000 0.860
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6   0.265   0.584276 0.112 0.028 0.000 0.000 0.000 0.860
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6   0.461   0.555669 0.308 0.052 0.004 0.000 0.000 0.636
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2   0.751   0.286443 0.140 0.344 0.000 0.004 0.320 0.192
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6   0.492   0.431362 0.400 0.048 0.008 0.000 0.000 0.544
#> C33059A9-A313-4806-B43B-0031365F3BE4     1   0.585   0.527154 0.612 0.024 0.176 0.004 0.004 0.180
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1   0.482  -0.052320 0.548 0.008 0.404 0.000 0.040 0.000
#> 1122039D-5785-4F70-9916-17C585453512     6   0.324   0.492582 0.024 0.024 0.000 0.104 0.004 0.844
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1   0.849  -0.076880 0.356 0.220 0.096 0.004 0.112 0.212
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1   0.684   0.312227 0.536 0.104 0.168 0.004 0.184 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     6   0.827  -0.244047 0.028 0.196 0.004 0.256 0.216 0.300
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5   0.751   0.092226 0.228 0.176 0.048 0.000 0.468 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2   0.730   0.532161 0.216 0.480 0.204 0.000 0.048 0.052
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1   0.650   0.511349 0.588 0.068 0.124 0.004 0.016 0.200
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6   0.324   0.492582 0.024 0.024 0.000 0.104 0.004 0.844
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1   0.574   0.487451 0.632 0.024 0.204 0.004 0.008 0.128
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1   0.441   0.591319 0.792 0.024 0.092 0.008 0.024 0.060
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.414   0.618721 0.180 0.036 0.760 0.016 0.008 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1   0.639   0.470456 0.616 0.156 0.080 0.008 0.012 0.128
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2   0.756   0.491708 0.260 0.396 0.028 0.004 0.060 0.252
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6   0.471   0.509929 0.352 0.048 0.004 0.000 0.000 0.596
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5   0.750  -0.235501 0.144 0.332 0.000 0.008 0.356 0.160
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.449   0.565884 0.300 0.020 0.660 0.008 0.012 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1   0.396   0.597737 0.820 0.060 0.068 0.004 0.012 0.036
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1   0.660   0.372246 0.576 0.092 0.144 0.004 0.176 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3   0.548   0.213305 0.432 0.044 0.488 0.032 0.004 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2   0.761   0.377865 0.140 0.396 0.012 0.000 0.256 0.196
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1   0.359   0.587338 0.840 0.028 0.084 0.004 0.016 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1   0.529   0.535160 0.712 0.028 0.160 0.004 0.044 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA     1   0.443   0.542153 0.776 0.024 0.136 0.008 0.020 0.036
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1   0.445   0.519170 0.756 0.076 0.016 0.004 0.004 0.144
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6   0.160   0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1   0.476   0.465343 0.724 0.080 0.012 0.008 0.004 0.172
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.744   0.137922 0.080 0.220 0.488 0.024 0.176 0.012
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.550   0.394962 0.060 0.032 0.668 0.208 0.032 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5   0.733   0.467605 0.076 0.144 0.176 0.004 0.536 0.064
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1   0.432   0.597784 0.796 0.080 0.056 0.004 0.012 0.052
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1   0.674   0.523474 0.612 0.116 0.128 0.004 0.076 0.064
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1   0.532   0.469237 0.664 0.028 0.212 0.000 0.008 0.088
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1   0.561   0.279663 0.620 0.104 0.016 0.004 0.008 0.248

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 17541 rows and 500 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 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-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 0.397           0.641       0.845         0.4932 0.499   0.499
#> 3 3 0.622           0.812       0.885         0.3320 0.661   0.424
#> 4 4 0.593           0.693       0.818         0.0938 0.818   0.550
#> 5 5 0.642           0.641       0.777         0.0677 0.901   0.686
#> 6 6 0.682           0.624       0.745         0.0531 0.894   0.601

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.7476 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.8661     0.5659 0.712 0.288
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.8861     0.6115 0.304 0.696
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.8813     0.5500 0.700 0.300
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.9998    -0.1483 0.492 0.508
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.9732     0.5119 0.404 0.596
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.5294     0.6621 0.120 0.880
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.8303 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.9522     0.5508 0.372 0.628
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.9710     0.5175 0.400 0.600
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.7476 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5519     0.7012 0.872 0.128
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.3879     0.6917 0.076 0.924
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.8909     0.3449 0.692 0.308
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.8499     0.5802 0.724 0.276
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.9775     0.4991 0.412 0.588
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.8661     0.5659 0.712 0.288
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.7476 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.9710     0.1264 0.400 0.600
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.7476 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0672     0.7456 0.008 0.992
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.7476 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8303 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.7476 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.8303 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.7476 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.9754     0.5061 0.408 0.592
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000     0.8303 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.1633     0.8118 0.976 0.024
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.8303 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.7219     0.5891 0.800 0.200
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.7476 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.9170     0.5022 0.668 0.332
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.8303 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.9775     0.4991 0.412 0.588
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.8661     0.5659 0.712 0.288
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.8327     0.5946 0.736 0.264
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.8303 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.8303 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.9129     0.5092 0.672 0.328
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0376     0.8275 0.996 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.8303 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.7476 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.8303 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.8555     0.5755 0.720 0.280
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.9732     0.5119 0.404 0.596
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000     0.7476 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000     0.8303 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  0.9954     0.3981 0.460 0.540
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.3431     0.7024 0.064 0.936
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.8303 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.6247     0.6639 0.844 0.156
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.7476 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.9754     0.5058 0.408 0.592
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.8303 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2043     0.8096 0.968 0.032
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.7476 0.000 1.000
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#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.7476 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000     0.8303 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.8303 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.9775     0.4991 0.412 0.588
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000     0.8303 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.8303 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.9635     0.1121 0.612 0.388
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.8303 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.9754     0.3714 0.592 0.408
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.7950     0.6201 0.760 0.240
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.7476 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.7476 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0000     0.8303 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000     0.7476 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.9754     0.5058 0.408 0.592
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.9491     0.5563 0.368 0.632
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.8303 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.7476 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.8661     0.5659 0.712 0.288
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.8303 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.9000     0.3245 0.684 0.316
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.7476 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.9988    -0.1147 0.480 0.520
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.8303 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.9044     0.3297 0.680 0.320
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000     0.8303 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.8303 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.7476 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.7476 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.8713     0.5606 0.708 0.292
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.9775     0.4991 0.412 0.588
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.8303 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.9775     0.4991 0.412 0.588
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.9710     0.5175 0.400 0.600
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.8608     0.4241 0.716 0.284
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.9710     0.5175 0.400 0.600
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.9129     0.5925 0.328 0.672
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.8303 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.8303 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.8303 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.9775     0.3640 0.588 0.412
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.7528     0.5898 0.216 0.784
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.9795     0.4920 0.416 0.584
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.7815     0.6568 0.232 0.768
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.8303 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.7476 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.7476 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.8303 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.8713     0.4046 0.708 0.292
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.9754     0.5057 0.408 0.592
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.8303 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.8303 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.9775     0.3640 0.588 0.412
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.7745     0.6325 0.772 0.228
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.8144     0.6071 0.748 0.252
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.8303 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9775     0.3640 0.588 0.412
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.8303 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.8303 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.9775     0.4991 0.412 0.588
#> 1122039D-5785-4F70-9916-17C585453512     1  0.8713     0.5614 0.708 0.292
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4022     0.7579 0.920 0.080
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.9775     0.4991 0.412 0.588
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.9608     0.1682 0.384 0.616
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.9754     0.1034 0.408 0.592
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0376     0.7455 0.004 0.996
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.8303 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.8713     0.5614 0.708 0.292
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.8303 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8303 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.9427     0.5635 0.360 0.640
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0376     0.8276 0.996 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.6887     0.5691 0.184 0.816
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.8303 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.9988    -0.1147 0.480 0.520
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.9710     0.0644 0.600 0.400
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3274     0.7788 0.940 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.9795     0.4920 0.416 0.584
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.9732     0.5119 0.404 0.596
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.8909     0.3517 0.308 0.692
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.8303 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.8303 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.8303 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.8303 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.8763     0.5550 0.704 0.296
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.8303 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.7476 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.7950     0.6538 0.240 0.760
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.7476 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.8303 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0938     0.8231 0.988 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.8303 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.8303 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4397   0.865972 0.028 0.856 0.116
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3826   0.809596 0.868 0.124 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1964   0.870029 0.000 0.056 0.944
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.4068   0.818158 0.864 0.120 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4883   0.730644 0.208 0.788 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1753   0.875971 0.000 0.048 0.952
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.5677   0.755928 0.160 0.792 0.048
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.5254   0.695660 0.264 0.000 0.736
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.1950   0.878661 0.008 0.040 0.952
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1585   0.857627 0.028 0.008 0.964
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2773   0.894697 0.024 0.928 0.048
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.3500   0.841996 0.116 0.004 0.880
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0661   0.911387 0.008 0.988 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.8255   0.586005 0.252 0.128 0.620
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.1905   0.872783 0.956 0.028 0.016
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.1832   0.878774 0.008 0.036 0.956
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.4139   0.814486 0.860 0.124 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0661   0.911387 0.008 0.988 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2434   0.894083 0.024 0.940 0.036
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0592   0.913334 0.000 0.988 0.012
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.6087   0.777705 0.076 0.780 0.144
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0237   0.912217 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0592   0.872899 0.988 0.000 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0424   0.913367 0.000 0.992 0.008
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1289   0.879311 0.968 0.000 0.032
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0892   0.911810 0.000 0.980 0.020
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.1529   0.878154 0.000 0.040 0.960
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4842   0.718258 0.776 0.000 0.224
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.5285   0.714270 0.244 0.004 0.752
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.4047   0.820768 0.148 0.004 0.848
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2955   0.861804 0.080 0.008 0.912
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0592   0.913334 0.000 0.988 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.3965   0.805670 0.860 0.132 0.008
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.3816   0.821049 0.148 0.000 0.852
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.1289   0.878701 0.000 0.032 0.968
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.3120   0.847239 0.908 0.080 0.012
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5178   0.655671 0.744 0.256 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.5431   0.666027 0.284 0.000 0.716
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1411   0.879136 0.964 0.000 0.036
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.4139   0.814486 0.860 0.124 0.016
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.5138   0.712697 0.252 0.000 0.748
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.5754   0.644072 0.296 0.004 0.700
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0424   0.913367 0.000 0.992 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.1643   0.861731 0.956 0.000 0.044
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.3610   0.838027 0.888 0.096 0.016
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.1529   0.877154 0.000 0.040 0.960
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.5070   0.737425 0.004 0.772 0.224
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5560   0.579074 0.700 0.000 0.300
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.2280   0.860370 0.052 0.008 0.940
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.1832   0.899057 0.008 0.956 0.036
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.6286   0.067469 0.536 0.000 0.464
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.2301   0.866703 0.060 0.004 0.936
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0424   0.912743 0.008 0.992 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.1643   0.877394 0.000 0.044 0.956
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1411   0.879136 0.964 0.000 0.036
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.1015   0.870495 0.980 0.008 0.012
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0424   0.913367 0.000 0.992 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.6432   0.256885 0.428 0.568 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.1643   0.875881 0.000 0.044 0.956
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0592   0.910578 0.012 0.988 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.5722   0.650585 0.292 0.004 0.704
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0747   0.909384 0.016 0.984 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3192   0.845665 0.888 0.000 0.112
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.5733   0.542193 0.676 0.000 0.324
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.1647   0.866045 0.036 0.004 0.960
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.1289   0.878185 0.000 0.032 0.968
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.2903   0.893085 0.028 0.924 0.048
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.1860   0.861438 0.948 0.000 0.052
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.4293   0.811455 0.164 0.004 0.832
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.1411   0.879136 0.964 0.000 0.036
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0237   0.912217 0.004 0.996 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.5970   0.812904 0.060 0.780 0.160
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000   0.912957 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.1411   0.906437 0.000 0.964 0.036
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.2066   0.870113 0.000 0.060 0.940
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#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.5639   0.781004 0.080 0.112 0.808
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.5497   0.604453 0.708 0.000 0.292
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.1643   0.861731 0.956 0.000 0.044
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0892   0.911810 0.000 0.980 0.020
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.3918   0.826784 0.140 0.004 0.856
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.1411   0.879136 0.964 0.000 0.036
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.2356   0.869829 0.928 0.000 0.072
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.3551   0.833065 0.868 0.000 0.132
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.3482   0.837289 0.872 0.000 0.128
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1950   0.878661 0.008 0.040 0.952
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.1950   0.878661 0.008 0.040 0.952
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.4139   0.814486 0.860 0.124 0.016
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.1877   0.878486 0.956 0.012 0.032
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.1643   0.861731 0.956 0.000 0.044
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1753   0.898315 0.000 0.952 0.048
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1411   0.879136 0.964 0.000 0.036
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.4164   0.825276 0.144 0.008 0.848
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.1529   0.878154 0.000 0.040 0.960
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1529   0.878871 0.960 0.000 0.040
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.5831   0.661637 0.284 0.008 0.708
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.6322   0.776854 0.108 0.120 0.772
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.1411   0.879136 0.964 0.000 0.036
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.6148   0.454726 0.356 0.640 0.004
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.1636   0.876069 0.964 0.016 0.020
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.4121   0.805082 0.000 0.832 0.168
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0424   0.911157 0.008 0.992 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.3267   0.845427 0.884 0.000 0.116
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0592   0.912923 0.000 0.988 0.012
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.1832   0.878768 0.008 0.036 0.956
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1950   0.878661 0.008 0.040 0.952
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.1643   0.861731 0.956 0.000 0.044
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0424   0.913367 0.000 0.992 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.4068   0.818158 0.864 0.120 0.016
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.3412   0.838317 0.876 0.000 0.124
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.4982   0.830976 0.136 0.036 0.828
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0592   0.913334 0.000 0.988 0.012
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5760   0.524151 0.328 0.672 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.3619   0.827777 0.864 0.000 0.136
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1643   0.871176 0.044 0.000 0.956
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.5216   0.666983 0.260 0.000 0.740
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1411   0.879136 0.964 0.000 0.036
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000   0.912957 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0592   0.913334 0.000 0.988 0.012
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.4059   0.810240 0.860 0.128 0.012
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1832   0.878768 0.008 0.036 0.956
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.3412   0.837259 0.876 0.000 0.124
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.1267   0.861274 0.024 0.004 0.972
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1529   0.877154 0.000 0.040 0.960
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.2878   0.849076 0.096 0.000 0.904
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.1529   0.876984 0.000 0.040 0.960
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.1643   0.875881 0.000 0.044 0.956
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3349   0.848680 0.108 0.004 0.888
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.4233   0.812226 0.160 0.004 0.836
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.5497   0.653238 0.292 0.000 0.708
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4099   0.812992 0.140 0.852 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.9203   0.264871 0.156 0.368 0.476
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.1267   0.870029 0.024 0.004 0.972
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.2711   0.852383 0.000 0.088 0.912
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.3482   0.837289 0.872 0.000 0.128
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.2793   0.892808 0.028 0.928 0.044
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0424   0.913367 0.000 0.992 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1411   0.879136 0.964 0.000 0.036
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.3030   0.854267 0.092 0.004 0.904
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.1411   0.878111 0.000 0.036 0.964
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1411   0.879136 0.964 0.000 0.036
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.3983   0.823458 0.144 0.004 0.852
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.5470   0.785470 0.168 0.796 0.036
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.1620   0.877033 0.964 0.012 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.1636   0.876069 0.964 0.016 0.020
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1411   0.879136 0.964 0.000 0.036
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.3148   0.885638 0.048 0.916 0.036
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1411   0.879136 0.964 0.000 0.036
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1643   0.877742 0.956 0.000 0.044
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.1832   0.878768 0.008 0.036 0.956
#> 1122039D-5785-4F70-9916-17C585453512     1  0.3989   0.812140 0.864 0.124 0.012
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.4654   0.766453 0.208 0.000 0.792
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.0747   0.869855 0.016 0.000 0.984
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.1529   0.897208 0.040 0.960 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.2550   0.894322 0.024 0.936 0.040
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.2356   0.883940 0.000 0.928 0.072
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4346   0.771753 0.816 0.000 0.184
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.3755   0.813567 0.872 0.120 0.008
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1529   0.878580 0.960 0.000 0.040
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.6302  -0.004977 0.520 0.000 0.480
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1753   0.875971 0.000 0.048 0.952
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.6498   0.326474 0.596 0.008 0.396
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0747   0.909384 0.016 0.984 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1411   0.879136 0.964 0.000 0.036
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4413   0.836460 0.104 0.860 0.036
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1877   0.875135 0.032 0.012 0.956
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.4842   0.746702 0.224 0.000 0.776
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.2959   0.848644 0.100 0.000 0.900
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1753   0.875971 0.000 0.048 0.952
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0747   0.909628 0.016 0.984 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.6274   0.252916 0.456 0.000 0.544
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.4346   0.780779 0.184 0.000 0.816
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.6309  -0.087494 0.504 0.000 0.496
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3482   0.837289 0.872 0.000 0.128
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.4059   0.810240 0.860 0.128 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4178   0.788789 0.828 0.000 0.172
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.3879   0.822480 0.000 0.848 0.152
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2496   0.862403 0.004 0.068 0.928
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0424   0.913452 0.000 0.992 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.5497   0.652356 0.292 0.000 0.708
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6081   0.461100 0.652 0.004 0.344
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5497   0.652541 0.292 0.000 0.708
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1964   0.875610 0.944 0.000 0.056

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5249     0.7060 0.044 0.708 0.000 0.248
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0376     0.8770 0.000 0.004 0.992 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4746     0.5881 0.008 0.688 0.000 0.304
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0336     0.8804 0.008 0.000 0.992 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4656     0.7065 0.000 0.784 0.056 0.160
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3400     0.7449 0.820 0.000 0.180 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0469     0.8797 0.012 0.000 0.988 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3301     0.7968 0.048 0.000 0.876 0.076
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.4466     0.7603 0.036 0.784 0.000 0.180
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4761     0.5340 0.628 0.000 0.372 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.4103     0.7418 0.000 0.744 0.000 0.256
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7158     0.5903 0.632 0.176 0.164 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.5288     0.4760 0.472 0.008 0.000 0.520
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.2814     0.7867 0.132 0.000 0.868 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4222     0.7291 0.000 0.728 0.000 0.272
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5126     0.5083 0.004 0.552 0.000 0.444
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.8167    -0.1277 0.016 0.380 0.216 0.388
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2589     0.8047 0.000 0.884 0.000 0.116
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.1867     0.6889 0.928 0.000 0.000 0.072
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2281     0.8044 0.000 0.904 0.000 0.096
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3486     0.5502 0.812 0.000 0.000 0.188
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.2976     0.8000 0.000 0.872 0.008 0.120
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0895     0.8771 0.020 0.000 0.976 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2530     0.7613 0.896 0.000 0.100 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4679     0.5674 0.648 0.000 0.352 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.4164     0.6850 0.736 0.000 0.264 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2589     0.8027 0.116 0.000 0.884 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3837     0.7235 0.776 0.000 0.224 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.1940     0.8410 0.076 0.000 0.924 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.5607     0.4284 0.484 0.020 0.000 0.496
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5755     0.3703 0.624 0.332 0.000 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.5143     0.3264 0.540 0.000 0.456 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3801     0.4975 0.780 0.000 0.000 0.220
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3569     0.7383 0.804 0.000 0.196 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3569     0.7385 0.804 0.000 0.196 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0524     0.8092 0.000 0.988 0.004 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3569     0.6310 0.804 0.000 0.000 0.196
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.5688    -0.3470 0.512 0.024 0.000 0.464
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.7028     0.0177 0.000 0.380 0.496 0.124
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.2859     0.7616 0.880 0.000 0.112 0.008
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.6791     0.1598 0.392 0.000 0.508 0.100
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.2589     0.8018 0.000 0.884 0.000 0.116
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2831     0.7607 0.876 0.000 0.120 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4103     0.5895 0.256 0.000 0.744 0.000
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#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     3  0.6587     0.3823 0.324 0.000 0.576 0.100
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.1940     0.7591 0.924 0.000 0.076 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.2976     0.8000 0.000 0.872 0.008 0.120
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.3638     0.7958 0.000 0.848 0.032 0.120
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.2142     0.7508 0.928 0.000 0.056 0.016
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.4590     0.7523 0.036 0.772 0.000 0.192
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     3  0.0712     0.8787 0.008 0.004 0.984 0.004
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.2589     0.6517 0.884 0.000 0.000 0.116
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.2760     0.7592 0.872 0.000 0.128 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.0000     0.8800 0.000 0.000 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.1576     0.7160 0.948 0.000 0.004 0.048
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.4907     0.4224 0.580 0.000 0.420 0.000
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.6808     0.4685 0.572 0.000 0.300 0.128
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.0000     0.8800 0.000 0.000 1.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     4  0.4542     0.8592 0.228 0.020 0.000 0.752
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.5083     0.7125 0.036 0.716 0.000 0.248
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0707     0.8112 0.000 0.980 0.000 0.020
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.0469     0.8797 0.012 0.000 0.988 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4640     0.6324 0.188 0.776 0.004 0.032
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.4420     0.6693 0.012 0.748 0.000 0.240
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.4483     0.5940 0.004 0.712 0.000 0.284
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     4  0.6192     0.4855 0.436 0.052 0.000 0.512
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.1356     0.8055 0.000 0.960 0.032 0.008
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.4103     0.4214 0.744 0.000 0.000 0.256
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.3569     0.7376 0.804 0.000 0.196 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.1822     0.7194 0.944 0.008 0.004 0.044
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.0376     0.8770 0.000 0.004 0.992 0.004
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.4687     0.5859 0.004 0.704 0.004 0.288
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.4598     0.7299 0.044 0.792 0.004 0.160
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> 80936433-AA91-4219-98F1-706C36298060     2  0.2408     0.8036 0.000 0.896 0.000 0.104
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.4295     0.8603 0.240 0.008 0.000 0.752
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.7125     0.5207 0.576 0.076 0.316 0.032
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.2530     0.7610 0.888 0.000 0.112 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.3528     0.6328 0.808 0.000 0.000 0.192
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.5950     0.6697 0.000 0.696 0.156 0.148
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.4776     0.5306 0.624 0.000 0.376 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.1576     0.7508 0.948 0.000 0.048 0.004
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.2421     0.7515 0.924 0.020 0.048 0.008
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.1637     0.7557 0.940 0.000 0.060 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.1489     0.7119 0.952 0.004 0.000 0.044
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.3528     0.6328 0.808 0.000 0.000 0.192
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.2282     0.7930 0.000 0.924 0.052 0.024
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.4994     0.2428 0.520 0.000 0.480 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0336     0.8804 0.008 0.000 0.992 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1762     0.7175 0.944 0.004 0.004 0.048
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.4277     0.6727 0.720 0.000 0.280 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.6473     0.5853 0.612 0.108 0.280 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.5036     0.5763 0.024 0.696 0.000 0.280
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.5000     0.4144 0.496 0.000 0.000 0.504
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.5119     0.2543 0.000 0.556 0.440 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0895     0.8078 0.000 0.976 0.004 0.020
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.2010     0.7447 0.940 0.008 0.040 0.012
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.1004     0.8075 0.000 0.972 0.004 0.024
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.0592     0.8787 0.016 0.000 0.984 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8800 0.000 0.000 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.3688     0.6162 0.792 0.000 0.000 0.208
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1004     0.8075 0.000 0.972 0.004 0.024
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.1807     0.7519 0.940 0.000 0.052 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.4406     0.6482 0.700 0.000 0.300 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.2976     0.8000 0.000 0.872 0.008 0.120
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5231     0.5600 0.028 0.676 0.000 0.296
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2021     0.7520 0.932 0.000 0.056 0.012
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.5742     0.6470 0.664 0.000 0.276 0.060
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0336     0.8095 0.000 0.992 0.000 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2089     0.7453 0.932 0.000 0.048 0.020
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.5496     0.5803 0.232 0.000 0.704 0.064
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.6383     0.4925 0.568 0.000 0.356 0.076
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.0469     0.8797 0.012 0.000 0.988 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8800 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3873     0.6374 0.228 0.000 0.772 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4304     0.6702 0.716 0.000 0.284 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3356     0.7465 0.824 0.000 0.176 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4158     0.6677 0.008 0.768 0.000 0.224
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.8150     0.2868 0.056 0.248 0.540 0.156
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.5929     0.2799 0.356 0.000 0.596 0.048
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1151     0.8589 0.000 0.024 0.968 0.008
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1661     0.7524 0.944 0.000 0.052 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4508     0.7577 0.036 0.780 0.000 0.184
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1004     0.8075 0.000 0.972 0.004 0.024
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.2345     0.6699 0.900 0.000 0.000 0.100
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.4967     0.3584 0.548 0.000 0.452 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0188     0.8806 0.004 0.000 0.996 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1557     0.7100 0.944 0.000 0.000 0.056
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.4500     0.6261 0.684 0.000 0.316 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.5999     0.4115 0.044 0.552 0.000 0.404
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.4072     0.8461 0.252 0.000 0.000 0.748
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.4328     0.8562 0.244 0.008 0.000 0.748
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.5987     0.5229 0.040 0.520 0.000 0.440
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1637     0.7069 0.940 0.000 0.000 0.060
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1807     0.7175 0.940 0.000 0.008 0.052
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0817     0.8759 0.024 0.000 0.976 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.4353     0.8621 0.232 0.012 0.000 0.756
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6167     0.6320 0.668 0.000 0.208 0.124
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.3052     0.7824 0.136 0.000 0.860 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3688     0.4567 0.000 0.208 0.000 0.792
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.4643     0.6586 0.000 0.656 0.000 0.344
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4139     0.6882 0.000 0.800 0.176 0.024
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.2450     0.7565 0.912 0.000 0.072 0.016
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.4284     0.8575 0.224 0.012 0.000 0.764
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.2089     0.7273 0.932 0.000 0.020 0.048
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2647     0.7603 0.880 0.000 0.120 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0376     0.8770 0.000 0.004 0.992 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5397     0.7039 0.772 0.112 0.096 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3668     0.7079 0.000 0.808 0.004 0.188
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2589     0.6517 0.884 0.000 0.000 0.116
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4889     0.6237 0.004 0.636 0.000 0.360
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0336     0.8804 0.008 0.000 0.992 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4382     0.6545 0.704 0.000 0.296 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.6519     0.4757 0.584 0.000 0.320 0.096
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0524     0.8807 0.008 0.000 0.988 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.4250     0.6231 0.000 0.724 0.000 0.276
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3105     0.7572 0.856 0.000 0.140 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5284     0.6723 0.696 0.000 0.264 0.040
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.2647     0.7603 0.880 0.000 0.120 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1474     0.7535 0.948 0.000 0.052 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4387     0.8639 0.236 0.012 0.000 0.752
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1867     0.7587 0.928 0.000 0.072 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.6452     0.1621 0.000 0.472 0.460 0.068
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0779     0.8699 0.000 0.004 0.980 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2647     0.8008 0.000 0.880 0.000 0.120
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3539     0.7460 0.820 0.000 0.176 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4537     0.7334 0.824 0.088 0.072 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5360     0.3753 0.552 0.000 0.436 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1489     0.7490 0.952 0.000 0.044 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.4929    0.50910 0.016 0.260 0.000 0.036 0.688
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.1399    0.89483 0.028 0.020 0.000 0.952 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0451    0.83801 0.000 0.008 0.988 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1949    0.89068 0.040 0.012 0.000 0.932 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3319    0.63788 0.000 0.820 0.000 0.160 0.020
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.2017    0.83145 0.000 0.008 0.912 0.000 0.080
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.3161    0.66439 0.024 0.872 0.084 0.008 0.012
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4375    0.74835 0.728 0.000 0.032 0.004 0.236
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.1493    0.83284 0.024 0.000 0.948 0.000 0.028
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3292    0.76150 0.016 0.000 0.836 0.008 0.140
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#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.3548    0.77227 0.012 0.000 0.796 0.004 0.188
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0162    0.83938 0.004 0.000 0.996 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.4548    0.64529 0.232 0.000 0.716 0.000 0.052
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.5156    0.71153 0.688 0.000 0.092 0.004 0.216
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.4178    0.75662 0.748 0.000 0.028 0.004 0.220
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.2416    0.68142 0.012 0.888 0.000 0.100 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.6250    0.29082 0.088 0.352 0.540 0.008 0.012
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.6910    0.05526 0.312 0.000 0.392 0.004 0.292
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1372    0.83266 0.000 0.016 0.956 0.004 0.024
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1708    0.79488 0.944 0.004 0.016 0.004 0.032
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.4264    0.59122 0.000 0.376 0.000 0.004 0.620
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0324    0.70382 0.000 0.992 0.000 0.004 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1341    0.77420 0.944 0.000 0.000 0.056 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.5815    0.64225 0.624 0.000 0.152 0.004 0.220
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0510    0.84148 0.000 0.000 0.984 0.000 0.016
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1774    0.77637 0.932 0.000 0.000 0.052 0.016
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.4117    0.76556 0.788 0.000 0.116 0.000 0.096
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6270    0.42076 0.020 0.604 0.000 0.168 0.208
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.2574    0.82428 0.112 0.012 0.000 0.876 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.1444    0.88650 0.040 0.012 0.000 0.948 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1740    0.77520 0.932 0.000 0.000 0.056 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.6532   -0.00252 0.012 0.432 0.000 0.136 0.420
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1845    0.77523 0.928 0.000 0.000 0.056 0.016
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1124    0.78227 0.960 0.000 0.000 0.036 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3851    0.75983 0.016 0.000 0.768 0.004 0.212
#> 1122039D-5785-4F70-9916-17C585453512     4  0.2002    0.89297 0.028 0.020 0.000 0.932 0.020
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6364    0.50877 0.476 0.000 0.076 0.032 0.416
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.5535    0.63619 0.088 0.000 0.620 0.004 0.288
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3477    0.78781 0.000 0.056 0.000 0.832 0.112
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.5631    0.53699 0.000 0.424 0.000 0.076 0.500
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.2491    0.68029 0.024 0.904 0.064 0.004 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3003    0.79298 0.872 0.000 0.020 0.016 0.092
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.1710    0.89318 0.024 0.012 0.000 0.944 0.020
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1597    0.78989 0.948 0.000 0.020 0.024 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3124    0.78630 0.844 0.000 0.016 0.004 0.136
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0798    0.83848 0.000 0.008 0.976 0.000 0.016
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5414    0.09716 0.512 0.440 0.000 0.008 0.040
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1894    0.69175 0.000 0.920 0.000 0.072 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1764    0.77241 0.928 0.000 0.000 0.064 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5927   -0.41013 0.000 0.468 0.000 0.104 0.428
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1478    0.83405 0.000 0.000 0.936 0.000 0.064
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.5213    0.70868 0.680 0.000 0.092 0.004 0.224
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.6679   -0.48920 0.412 0.000 0.124 0.024 0.440
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2563    0.81827 0.000 0.008 0.872 0.000 0.120
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3327    0.64132 0.000 0.828 0.000 0.144 0.028
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3521    0.78335 0.824 0.000 0.024 0.008 0.144
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4844    0.75451 0.740 0.000 0.104 0.008 0.148
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3573    0.78584 0.832 0.000 0.032 0.012 0.124
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1278    0.79371 0.960 0.000 0.016 0.004 0.020
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.1399    0.89483 0.028 0.020 0.000 0.952 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1756    0.79535 0.940 0.000 0.016 0.008 0.036
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6095    0.31165 0.000 0.184 0.588 0.004 0.224
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1059    0.83561 0.000 0.008 0.968 0.004 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.4452    0.61002 0.000 0.496 0.000 0.004 0.500
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4240    0.75495 0.756 0.004 0.028 0.004 0.208
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5999    0.56001 0.608 0.264 0.016 0.000 0.112
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5288    0.58831 0.664 0.000 0.260 0.012 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1256    0.79179 0.964 0.004 0.012 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.4243    0.48571 0.272 0.032 0.000 0.008 0.688 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0951    0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0405    0.84420 0.008 0.000 0.988 0.000 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.2551    0.84235 0.028 0.008 0.000 0.896 0.016 0.052
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2490    0.81171 0.044 0.892 0.000 0.052 0.012 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3921    0.50321 0.308 0.000 0.676 0.004 0.012 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.2333    0.80656 0.024 0.912 0.020 0.000 0.016 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3756    0.50572 0.644 0.000 0.000 0.000 0.004 0.352
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.1983    0.82471 0.060 0.000 0.916 0.000 0.012 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2679    0.79565 0.096 0.000 0.864 0.000 0.040 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.2948    0.85787 0.008 0.188 0.000 0.000 0.804 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4633    0.56842 0.640 0.000 0.040 0.000 0.012 0.308
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.3479    0.85616 0.012 0.212 0.000 0.008 0.768 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5341    0.52426 0.632 0.004 0.008 0.000 0.140 0.216
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.5889    0.24157 0.020 0.236 0.000 0.184 0.000 0.560
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4663    0.58515 0.664 0.000 0.244 0.000 0.000 0.092
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0951    0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.3691    0.85028 0.012 0.204 0.000 0.020 0.764 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.6718    0.32039 0.036 0.348 0.000 0.256 0.360 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.2854    0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.6054    0.49751 0.044 0.004 0.108 0.556 0.288 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3684    0.15968 0.000 0.628 0.000 0.000 0.372 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.3649    0.54433 0.180 0.004 0.000 0.016 0.016 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.3481    0.83398 0.032 0.192 0.000 0.000 0.776 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0858    0.66961 0.000 0.004 0.000 0.028 0.000 0.968
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.2854    0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4521    0.55084 0.212 0.000 0.716 0.004 0.016 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.4382    0.24031 0.416 0.004 0.004 0.000 0.012 0.564
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     6  0.5365   -0.06426 0.380 0.008 0.032 0.008 0.020 0.552
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.4589    0.46045 0.580 0.008 0.000 0.004 0.020 0.388
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4737    0.53289 0.248 0.000 0.672 0.000 0.012 0.068
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.2854    0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0405    0.89405 0.000 0.008 0.000 0.988 0.004 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4343    0.44704 0.592 0.000 0.020 0.000 0.004 0.384
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3742    0.39661 0.648 0.000 0.348 0.004 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5827    0.43311 0.044 0.528 0.000 0.080 0.000 0.348
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3971    0.71830 0.060 0.772 0.000 0.000 0.012 0.156
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     6  0.6062    0.14270 0.204 0.000 0.268 0.000 0.016 0.512
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2003    0.62903 0.000 0.000 0.000 0.116 0.000 0.884
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0405    0.89405 0.000 0.008 0.000 0.988 0.004 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3864    0.51688 0.648 0.000 0.004 0.000 0.004 0.344
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     6  0.4637    0.28464 0.352 0.008 0.000 0.004 0.028 0.608
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0748    0.82969 0.004 0.976 0.004 0.000 0.016 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.5542    0.41383 0.232 0.004 0.000 0.016 0.132 0.616
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.5677    0.57751 0.052 0.624 0.000 0.060 0.012 0.252
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0405    0.84539 0.008 0.000 0.988 0.000 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.5510    0.50919 0.044 0.008 0.628 0.060 0.260 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.3295    0.60275 0.184 0.004 0.004 0.000 0.012 0.796
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.5404    0.48870 0.712 0.008 0.084 0.008 0.112 0.076
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.2883    0.86476 0.000 0.212 0.000 0.000 0.788 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.4109    0.36973 0.328 0.000 0.008 0.000 0.012 0.652
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.6762    0.43921 0.404 0.008 0.224 0.008 0.016 0.340
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.5242    0.38927 0.040 0.036 0.000 0.564 0.360 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5014    0.37782 0.584 0.004 0.364 0.008 0.016 0.024
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.0692    0.67409 0.020 0.000 0.000 0.000 0.004 0.976
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.3313    0.59805 0.152 0.016 0.000 0.012 0.004 0.816
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0508    0.83144 0.004 0.984 0.000 0.000 0.012 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.2291    0.81902 0.044 0.904 0.000 0.040 0.000 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.4070    0.21638 0.568 0.000 0.424 0.004 0.004 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.3934    0.84249 0.016 0.204 0.000 0.028 0.752 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     6  0.4689   -0.19503 0.460 0.008 0.000 0.004 0.020 0.508
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1718    0.82738 0.044 0.932 0.000 0.016 0.008 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.1194    0.67338 0.032 0.004 0.000 0.000 0.008 0.956
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.4689    0.31348 0.508 0.008 0.000 0.004 0.020 0.460
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.5791    0.50651 0.208 0.000 0.616 0.000 0.052 0.124
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0547    0.84635 0.020 0.000 0.980 0.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.4112    0.55476 0.224 0.048 0.000 0.004 0.724 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5156    0.03131 0.528 0.012 0.000 0.004 0.048 0.408
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     6  0.4015    0.55867 0.188 0.008 0.008 0.004 0.028 0.764
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.1297    0.66933 0.040 0.000 0.000 0.000 0.012 0.948
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.5458    0.30159 0.040 0.048 0.000 0.532 0.380 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.6887    0.33432 0.276 0.488 0.004 0.012 0.168 0.052
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0508    0.83211 0.004 0.984 0.000 0.000 0.012 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     5  0.6030    0.29575 0.040 0.040 0.352 0.036 0.532 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3269    0.73751 0.168 0.008 0.808 0.004 0.012 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0436    0.89461 0.000 0.004 0.000 0.988 0.004 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0405    0.84539 0.008 0.000 0.988 0.000 0.004 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.5941   -0.13604 0.152 0.488 0.004 0.000 0.348 0.008
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0363    0.84623 0.012 0.000 0.988 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0622    0.84256 0.012 0.000 0.980 0.000 0.008 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.5800    0.23602 0.108 0.512 0.000 0.004 0.016 0.360
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.2854    0.86692 0.000 0.208 0.000 0.000 0.792 0.000
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#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.3118    0.61304 0.124 0.012 0.000 0.004 0.020 0.840
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0951    0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     6  0.3676    0.56228 0.184 0.012 0.000 0.004 0.020 0.780
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4865    0.51185 0.024 0.056 0.664 0.000 0.256 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1564    0.82818 0.040 0.000 0.936 0.000 0.024 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.3320    0.85678 0.016 0.212 0.000 0.000 0.772 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4467    0.47915 0.592 0.004 0.000 0.004 0.020 0.380
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.6649   -0.04381 0.284 0.332 0.000 0.000 0.028 0.356
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.4936    0.44869 0.212 0.000 0.104 0.000 0.012 0.672
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.2558    0.64424 0.084 0.012 0.000 0.004 0.016 0.884

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 17541 rows and 500 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 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-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 0.483           0.590       0.814         0.4981 0.507   0.507
#> 3 3 0.856           0.899       0.957         0.3412 0.701   0.474
#> 4 4 0.709           0.629       0.811         0.1166 0.845   0.582
#> 5 5 0.662           0.568       0.764         0.0630 0.874   0.568
#> 6 6 0.740           0.629       0.815         0.0425 0.886   0.535

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.9988     0.7655 0.480 0.520
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.0000     0.3742 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.4815     0.1700 0.896 0.104
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.3742 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2423     0.4156 0.040 0.960
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.4101 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9866     0.7409 0.432 0.568
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.9988     0.7357 0.520 0.480
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0000     0.4101 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.4101 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.9988     0.7655 0.480 0.520
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.9635     0.7016 0.612 0.388
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.9881     0.7431 0.436 0.564
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7602     0.5735 0.780 0.220
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.0000     0.3742 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.4101 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0000     0.3742 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.9988     0.7655 0.480 0.520
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.9248     0.6853 0.340 0.660
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.9988     0.7655 0.480 0.520
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.9988     0.7655 0.480 0.520
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.9988     0.7655 0.480 0.520
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.9988     0.7357 0.520 0.480
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.9988     0.7655 0.480 0.520
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.9988     0.7357 0.520 0.480
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.9988     0.7655 0.480 0.520
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.4101 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.9988     0.7357 0.520 0.480
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.9988     0.7357 0.520 0.480
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.9988     0.7357 0.520 0.480
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.9970     0.7317 0.532 0.468
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.9988     0.7655 0.480 0.520
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0000     0.3742 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.9988     0.7357 0.520 0.480
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000     0.4101 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0000     0.3742 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.3742 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.9988     0.7357 0.520 0.480
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.9988     0.7357 0.520 0.480
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.0000     0.3742 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.9988     0.7357 0.520 0.480
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.9988     0.7357 0.520 0.480
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.9988     0.7655 0.480 0.520
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.9988     0.7357 0.520 0.480
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.0000     0.3742 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.4101 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.9988     0.7655 0.480 0.520
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.9988     0.7357 0.520 0.480
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.7299     0.5827 0.796 0.204
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.9988     0.7655 0.480 0.520
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.9988     0.7357 0.520 0.480
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.9635     0.7016 0.612 0.388
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.9988     0.7655 0.480 0.520
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000     0.4101 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.9988     0.7357 0.520 0.480
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.7745    -0.2545 0.228 0.772
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.9988     0.7655 0.480 0.520
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.3742 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.0000     0.4101 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.9580     0.7110 0.380 0.620
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.9988     0.7357 0.520 0.480
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.9635     0.7156 0.388 0.612
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.9988     0.7357 0.520 0.480
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.9988     0.7357 0.520 0.480
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.9248     0.6695 0.660 0.340
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0000     0.4101 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.9988     0.7655 0.480 0.520
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.9988     0.7357 0.520 0.480
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.9988     0.7357 0.520 0.480
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.9988     0.7357 0.520 0.480
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.9988     0.7655 0.480 0.520
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.9963     0.7571 0.464 0.536
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.9988     0.7655 0.480 0.520
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.9988     0.7655 0.480 0.520
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.0000     0.4101 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     2  0.0000     0.3742 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.0000     0.4101 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9988     0.7655 0.480 0.520
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.6048     0.5159 0.852 0.148
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.5519     0.0973 0.872 0.128
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.9988     0.7357 0.520 0.480
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.9988     0.7655 0.480 0.520
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.9988     0.7357 0.520 0.480
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.5629     0.0843 0.868 0.132
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.9988     0.7357 0.520 0.480
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.9988     0.7655 0.480 0.520
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.9988     0.7357 0.520 0.480
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     1  0.0000     0.4101 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.9988     0.7357 0.520 0.480
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.9988     0.7655 0.480 0.520
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.9988     0.7357 0.520 0.480
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.2778     0.4530 0.952 0.048
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.9988     0.7357 0.520 0.480
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.9988     0.7655 0.480 0.520
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.9988     0.7357 0.520 0.480
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.9988     0.7655 0.480 0.520
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.9580     0.7110 0.380 0.620
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.9988     0.7655 0.480 0.520
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     2  0.0000     0.3742 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.9988     0.7655 0.480 0.520
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.9988     0.7357 0.520 0.480
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.9988     0.7357 0.520 0.480
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.9993     0.7618 0.484 0.516
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.9988     0.7655 0.480 0.520
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#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.9608     0.6998 0.616 0.384
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0000     0.4101 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.9988     0.7357 0.520 0.480
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.9988     0.7357 0.520 0.480
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000     0.3742 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.4161     0.1867 0.084 0.916
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.2948     0.2664 0.052 0.948
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.9988     0.7357 0.520 0.480
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000     0.3742 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.9988     0.7357 0.520 0.480
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.9988     0.7357 0.520 0.480
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0000     0.4101 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     2  0.0000     0.3742 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.9988     0.7357 0.520 0.480
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000     0.4101 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.9460     0.7024 0.364 0.636
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.8555     0.6405 0.280 0.720
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.9988     0.7655 0.480 0.520
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.9988     0.7357 0.520 0.480
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.0000     0.3742 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.9988     0.7357 0.520 0.480
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.9988     0.7357 0.520 0.480
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0000     0.4101 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.9988     0.7357 0.520 0.480
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.9635     0.7156 0.388 0.612
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.9988     0.7357 0.520 0.480
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.6887     0.5581 0.184 0.816
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.9358     0.6838 0.648 0.352
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.9988     0.7357 0.520 0.480
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.6973     0.5710 0.812 0.188
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0000     0.4101 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.9580     0.7110 0.380 0.620
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.9988     0.7357 0.520 0.480
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.9988     0.7357 0.520 0.480
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.9988     0.7357 0.520 0.480
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.9988     0.7357 0.520 0.480
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0000     0.3742 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.9988     0.7357 0.520 0.480
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.9988     0.7655 0.480 0.520
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  1.0000     0.7499 0.496 0.504
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.9988     0.7655 0.480 0.520
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.9988     0.7357 0.520 0.480
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.8909    -0.4430 0.308 0.692
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.9988     0.7357 0.520 0.480
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.9988     0.7357 0.520 0.480

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9540 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0747     0.9456 0.984 0.016 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.9508 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.0000     0.9573 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9540 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000     0.9508 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0424     0.9482 0.008 0.992 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4796     0.7064 0.780 0.000 0.220
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0000     0.9508 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000     0.9508 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.9540 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.4346     0.7654 0.184 0.000 0.816
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9540 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.9717     0.0424 0.384 0.396 0.220
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000     0.9573 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0000     0.9508 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0424     0.9516 0.992 0.008 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9540 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000     0.9540 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9540 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.4702     0.7232 0.000 0.788 0.212
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9540 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9573 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9540 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9573 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9540 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.9508 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000     0.9573 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.5948     0.4344 0.640 0.000 0.360
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.4452     0.7589 0.192 0.000 0.808
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000     0.9508 0.000 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9540 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.1529     0.9255 0.960 0.040 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.3619     0.8259 0.136 0.000 0.864
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.0000     0.9508 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000     0.9573 1.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5058     0.6577 0.756 0.244 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.5810     0.5150 0.336 0.000 0.664
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9573 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.4346     0.7657 0.816 0.184 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.5621     0.5538 0.692 0.000 0.308
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9573 1.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9540 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9573 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0237     0.9545 0.996 0.004 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.9508 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.5254     0.6408 0.000 0.736 0.264
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000     0.9573 1.000 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.2261     0.8958 0.068 0.000 0.932
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9540 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9573 1.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.0000     0.9508 0.000 0.000 1.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.9540 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0000     0.9508 0.000 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9573 1.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000     0.9573 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9540 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.5058     0.6825 0.244 0.756 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0000     0.9508 0.000 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9540 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.4291     0.7619 0.820 0.000 0.180
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9540 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.9573 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0237     0.9544 0.996 0.000 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.3551     0.8308 0.132 0.000 0.868
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000     0.9508 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.9540 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.9573 1.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.5529     0.5907 0.296 0.000 0.704
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.9573 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9540 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.0000     0.9540 0.000 1.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9540 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.9540 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000     0.9508 0.000 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.0000     0.9573 1.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.9508 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0000     0.9540 0.000 1.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.9508 0.000 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.9508 0.000 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0000     0.9573 1.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.9540 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000     0.9573 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0000     0.9508 0.000 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0000     0.9573 1.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9540 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.9573 1.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.9508 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000     0.9573 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.9540 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000     0.9573 1.000 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0000     0.9508 0.000 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000     0.9573 1.000 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9540 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0747     0.9449 0.984 0.000 0.016
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.0000     0.9540 0.000 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9540 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9540 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0000     0.9573 1.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.9540 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0000     0.9573 1.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.9573 1.000 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0237     0.9511 0.000 0.996 0.004
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.9540 0.000 1.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0000     0.9573 1.000 0.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.0000     0.9508 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.4750     0.7047 0.784 0.000 0.216
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.0000     0.9508 0.000 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000     0.9540 0.000 1.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000     0.9573 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.6154     0.3393 0.408 0.592 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.4346     0.7682 0.184 0.816 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000     0.9540 0.000 1.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3  0.3116     0.8566 0.108 0.000 0.892
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0000     0.9540 0.000 1.000 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.9540 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3  0.0000     0.9508 0.000 0.000 1.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000     0.9540 0.000 1.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0000     0.9508 0.000 0.000 1.000
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#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9540 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9573 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0000     0.9508 0.000 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.9508 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9573 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.0747     0.9402 0.016 0.000 0.984
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000     0.9540 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9573 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.9573 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9573 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000     0.9540 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9573 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9573 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000     0.9508 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.3816     0.8124 0.852 0.148 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.6168     0.3068 0.412 0.000 0.588
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.0000     0.9508 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.9540 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9540 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9540 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.9573 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0592     0.9486 0.988 0.012 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.9573 1.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9573 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.9508 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5085     0.8157 0.836 0.092 0.072
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9540 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9573 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9540 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.9508 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.6180     0.2953 0.416 0.000 0.584
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.0000     0.9508 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000     0.9508 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9540 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9573 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.5810     0.5027 0.336 0.000 0.664
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9573 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9573 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0747     0.9456 0.984 0.016 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9573 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5178     0.6544 0.000 0.744 0.256
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.9508 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9540 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4235     0.7675 0.824 0.000 0.176
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0237     0.9545 0.996 0.004 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.6225     0.2679 0.432 0.000 0.568
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9573 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3569     0.6800 0.196 0.804 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.5161     0.5752 0.000 0.592 0.400 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4877     0.8590 0.408 0.000 0.592 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.5039     0.5773 0.000 0.592 0.404 0.004
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4996     0.7772 0.484 0.000 0.516 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3649     0.6731 0.796 0.000 0.000 0.204
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.4406     0.6720 0.000 0.700 0.300 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     4  0.7683    -0.3936 0.384 0.216 0.000 0.400
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.1389     0.4016 0.952 0.000 0.048 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.3610     0.7467 0.000 0.800 0.200 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5028     0.5797 0.000 0.596 0.400 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4998     0.0854 0.000 0.488 0.512 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.3764     0.3240 0.216 0.000 0.000 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.1557     0.6245 0.000 0.000 0.056 0.944
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4898     0.8517 0.416 0.000 0.584 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.6521     0.5063 0.512 0.000 0.076 0.412
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3649     0.6731 0.796 0.000 0.000 0.204
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.5339     0.8524 0.384 0.000 0.600 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1474     0.3927 0.948 0.000 0.052 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.7816    -0.3752 0.000 0.340 0.400 0.260
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.7619     0.4317 0.208 0.000 0.436 0.356
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     4  0.5172    -0.3145 0.404 0.000 0.008 0.588
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.4761    -0.1720 0.372 0.000 0.000 0.628
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4898     0.3005 0.000 0.416 0.584 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.4630     0.3910 0.196 0.000 0.036 0.768
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0336     0.4650 0.992 0.000 0.008 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     4  0.4898    -0.3196 0.416 0.000 0.000 0.584
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4830    -0.5640 0.608 0.000 0.392 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0336     0.8564 0.000 0.992 0.008 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4431    -0.3585 0.696 0.000 0.304 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.7648     0.4614 0.208 0.000 0.396 0.396
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.5582     0.5539 0.000 0.576 0.400 0.024
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.4866     0.8627 0.404 0.000 0.596 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.5016     0.5837 0.000 0.600 0.396 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.4817     0.5956 0.000 0.612 0.388 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4855    -0.5911 0.600 0.000 0.400 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0469     0.8531 0.012 0.988 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     4  0.7441    -0.2221 0.192 0.000 0.320 0.488
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.0336     0.6150 0.008 0.000 0.000 0.992
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.4916     0.2412 0.424 0.576 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.4585     0.4272 0.000 0.668 0.332 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0336     0.8554 0.008 0.992 0.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     4  0.4406     0.0513 0.300 0.000 0.000 0.700
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.4933     0.6308 0.568 0.000 0.000 0.432
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.0188     0.6172 0.004 0.000 0.000 0.996
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     4  0.4661    -0.1238 0.348 0.000 0.000 0.652
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.4977     0.8049 0.460 0.000 0.540 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.4866     0.6590 0.596 0.000 0.000 0.404
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.4898     0.6499 0.584 0.000 0.000 0.416
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.0817     0.8459 0.024 0.976 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.5016     0.5837 0.000 0.600 0.396 0.004
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.4985     0.7973 0.468 0.000 0.532 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.4222    -0.2658 0.728 0.000 0.272 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000     0.8593 0.000 1.000 0.000 0.000
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#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.5387     0.5653 0.000 0.584 0.400 0.016
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.4998    -0.0238 0.000 0.512 0.488 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.2345     0.8103 0.000 0.900 0.100 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     4  0.4643    -0.0977 0.344 0.000 0.000 0.656
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.3649     0.3466 0.204 0.000 0.000 0.796
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     4  0.4356     0.0767 0.292 0.000 0.000 0.708
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.7143     0.5748 0.232 0.000 0.560 0.208
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5387     0.5653 0.000 0.584 0.400 0.016
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     4  0.2921     0.4512 0.140 0.000 0.000 0.860
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     4  0.7883    -0.3277 0.292 0.000 0.328 0.380
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0188     0.4697 0.996 0.000 0.004 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.3649     0.6731 0.796 0.000 0.000 0.204
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.4866     0.8627 0.404 0.000 0.596 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.6854     0.6379 0.204 0.000 0.600 0.196
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4585     0.6764 0.668 0.000 0.000 0.332
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.4877     0.6569 0.592 0.000 0.000 0.408
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5161     0.5752 0.000 0.592 0.400 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0336     0.4050 0.000 0.000 0.992 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0188     0.4697 0.996 0.000 0.004 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4888     0.6536 0.588 0.000 0.000 0.412
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.0336     0.6150 0.008 0.000 0.000 0.992
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.3597     0.6420 0.836 0.000 0.016 0.148
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.6685     0.5208 0.132 0.000 0.600 0.268
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6256     0.5375 0.036 0.552 0.400 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.5692     0.5629 0.016 0.576 0.400 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.4866     0.8627 0.404 0.000 0.596 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3942     0.6785 0.764 0.000 0.000 0.236
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0188     0.4697 0.996 0.000 0.004 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.5279     0.5703 0.000 0.588 0.400 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.5268     0.5747 0.000 0.592 0.396 0.012
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3942     0.6101 0.000 0.764 0.236 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.2589     0.6229 0.000 0.000 0.116 0.884
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.0469     0.6127 0.012 0.000 0.000 0.988
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     4  0.6087     0.2814 0.140 0.024 0.112 0.724
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4843     0.5879 0.000 0.604 0.396 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0000     0.6193 0.000 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5016     0.5837 0.000 0.600 0.396 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4331     0.6805 0.712 0.000 0.000 0.288
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3610     0.6716 0.800 0.000 0.000 0.200
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4907     0.8479 0.420 0.000 0.580 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.5016     0.5837 0.000 0.600 0.396 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4356     0.6804 0.708 0.000 0.000 0.292
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.4331     0.0981 0.288 0.000 0.000 0.712
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4888     0.6536 0.588 0.000 0.000 0.412
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4855     0.6150 0.000 0.000 0.400 0.600
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4989     0.5729 0.528 0.000 0.000 0.472
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4898     0.3005 0.000 0.416 0.584 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4855     0.8652 0.400 0.000 0.600 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.8593 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4855     0.6622 0.600 0.000 0.000 0.400
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.4830     0.6153 0.000 0.000 0.392 0.608
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.5003     0.2335 0.016 0.000 0.308 0.676
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4977     0.5887 0.540 0.000 0.000 0.460

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.3143   6.01e-01 0.000 0.204 0.000 0.000 0.796
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000   8.39e-01 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.6660   1.58e-01 0.000 0.392 0.000 0.380 0.228
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1768   8.11e-01 0.072 0.000 0.924 0.000 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4078   6.93e-01 0.004 0.796 0.072 0.128 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0290   6.83e-01 0.992 0.000 0.000 0.000 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0000   8.39e-01 0.000 0.000 1.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3274   6.77e-01 0.000 0.000 0.780 0.000 0.220
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3143   6.01e-01 0.000 0.204 0.000 0.000 0.796
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0771   6.81e-01 0.976 0.000 0.020 0.000 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.5961   5.14e-01 0.000 0.260 0.000 0.160 0.580
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.6362  -5.91e-02 0.496 0.184 0.000 0.000 0.320
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4481   1.23e-01 0.576 0.000 0.416 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.6021   4.85e-01 0.000 0.232 0.000 0.188 0.580
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.6622   2.78e-01 0.000 0.220 0.000 0.364 0.416
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     5  0.8397   3.59e-01 0.000 0.192 0.252 0.196 0.360
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.4262   6.13e-01 0.000 0.440 0.000 0.000 0.560
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.6804  -5.00e-01 0.300 0.000 0.000 0.332 0.368
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.5700   5.54e-01 0.176 0.000 0.000 0.628 0.196
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.1831   8.04e-01 0.076 0.000 0.920 0.000 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4855   5.34e-01 0.720 0.000 0.000 0.112 0.168
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0898   6.82e-01 0.972 0.000 0.020 0.000 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0162   6.83e-01 0.996 0.000 0.000 0.000 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0566   8.33e-01 0.012 0.000 0.984 0.000 0.004
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1121   6.83e-01 0.956 0.000 0.000 0.000 0.044
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.4497   9.73e-02 0.568 0.000 0.424 0.000 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.1386   6.28e-01 0.032 0.016 0.000 0.952 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3611   6.83e-01 0.004 0.780 0.000 0.208 0.008
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.4063   6.81e-01 0.112 0.000 0.800 0.084 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.5930   5.37e-01 0.208 0.000 0.000 0.596 0.196
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0290   6.83e-01 0.992 0.000 0.000 0.000 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3003   6.17e-01 0.812 0.000 0.000 0.000 0.188
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000   7.48e-01 0.000 1.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     5  0.6500  -5.09e-01 0.400 0.000 0.000 0.188 0.412
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.1992   6.07e-01 0.032 0.044 0.000 0.924 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0162   8.39e-01 0.000 0.000 0.996 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.7156   1.23e-01 0.000 0.168 0.496 0.048 0.288
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.6599   3.49e-01 0.180 0.000 0.004 0.416 0.400
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.6155   4.59e-01 0.580 0.004 0.196 0.000 0.220
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.6417   4.55e-02 0.528 0.000 0.004 0.272 0.196
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4448   5.19e-02 0.480 0.000 0.516 0.000 0.004
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     5  0.6476   5.27e-01 0.000 0.244 0.000 0.260 0.496
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4443  -6.60e-02 0.524 0.000 0.472 0.000 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.6530   4.12e-01 0.380 0.000 0.000 0.424 0.196
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.6008   3.68e-01 0.200 0.000 0.000 0.584 0.216
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000   7.48e-01 0.000 1.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4030   5.63e-01 0.000 0.648 0.000 0.352 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.3398   7.12e-01 0.216 0.000 0.780 0.000 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.6438   3.85e-01 0.000 0.220 0.000 0.280 0.500
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0162   6.83e-01 0.996 0.000 0.000 0.000 0.004
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3274   6.79e-01 0.000 0.780 0.000 0.220 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4  0.6510   4.44e-01 0.360 0.000 0.000 0.444 0.196
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0162   6.83e-01 0.996 0.000 0.000 0.000 0.004
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#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0671   6.82e-01 0.980 0.000 0.016 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4276   5.99e-01 0.716 0.000 0.028 0.000 0.256
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3689   6.72e-01 0.256 0.000 0.740 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.6715   1.37e-01 0.000 0.392 0.000 0.360 0.248
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3242   6.18e-01 0.784 0.000 0.000 0.000 0.216
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5584   5.83e-01 0.592 0.000 0.096 0.000 0.312
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.6303   1.39e-02 0.524 0.000 0.000 0.280 0.196
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3003   6.17e-01 0.812 0.000 0.000 0.000 0.188
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000   6.27e-01 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3003   6.17e-01 0.812 0.000 0.000 0.000 0.188
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6161   2.52e-01 0.000 0.196 0.556 0.000 0.248
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0162   8.39e-01 0.000 0.000 0.996 0.000 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.4227   6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0162   6.83e-01 0.996 0.000 0.000 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.6580  -5.53e-02 0.176 0.408 0.000 0.412 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.8464  -2.41e-01 0.292 0.000 0.316 0.196 0.196
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.3196   6.11e-01 0.804 0.000 0.000 0.004 0.192

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.3659     0.4838 0.364 0.000 0.000 0.000 0.636 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.5091     0.1635 0.000 0.080 0.000 0.416 0.504 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4503     0.5300 0.232 0.000 0.684 0.000 0.000 0.084
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0146     0.8878 0.000 0.996 0.004 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3684     0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0146     0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3883     0.4567 0.332 0.000 0.656 0.000 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000     0.8353 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3684     0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0508     0.8387 0.000 0.012 0.000 0.004 0.984 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.4821     0.2086 0.416 0.016 0.000 0.000 0.540 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1700     0.7858 0.000 0.004 0.000 0.916 0.000 0.080
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5193     0.2988 0.552 0.000 0.344 0.000 0.000 0.104
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0622     0.8371 0.000 0.012 0.000 0.008 0.980 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.4095     0.1124 0.000 0.008 0.000 0.480 0.512 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.5515     0.1384 0.000 0.000 0.136 0.492 0.372 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.1663     0.7839 0.000 0.088 0.000 0.000 0.912 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.4105     0.4661 0.348 0.000 0.000 0.020 0.000 0.632
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.0458     0.8384 0.000 0.016 0.000 0.000 0.984 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.2996     0.6708 0.000 0.000 0.000 0.228 0.000 0.772
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4226     0.5924 0.152 0.000 0.736 0.000 0.000 0.112
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.3183     0.5889 0.128 0.004 0.000 0.040 0.000 0.828
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3998     0.3832 0.504 0.000 0.004 0.000 0.000 0.492
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3659     0.5377 0.636 0.000 0.000 0.000 0.000 0.364
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0551     0.8336 0.004 0.004 0.984 0.000 0.000 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3971     0.3801 0.548 0.004 0.000 0.000 0.000 0.448
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.4972     0.2792 0.568 0.000 0.352 0.000 0.000 0.080
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4527     0.5637 0.000 0.236 0.000 0.680 0.000 0.084
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3280     0.7494 0.004 0.808 0.000 0.160 0.000 0.028
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.3388     0.6505 0.000 0.000 0.792 0.036 0.000 0.172
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2969     0.6728 0.000 0.000 0.000 0.224 0.000 0.776
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3647     0.5311 0.640 0.000 0.000 0.000 0.000 0.360
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     6  0.1957     0.5990 0.112 0.000 0.000 0.000 0.000 0.888
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0260     0.8882 0.000 0.992 0.000 0.000 0.008 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.4486     0.4008 0.396 0.000 0.000 0.016 0.012 0.576
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.4765     0.5484 0.012 0.244 0.000 0.672 0.000 0.072
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.6082    -0.0513 0.000 0.000 0.368 0.272 0.360 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.4573     0.4785 0.324 0.004 0.004 0.028 0.004 0.636
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3463     0.5255 0.840 0.040 0.088 0.000 0.012 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.4017     0.6395 0.160 0.004 0.000 0.076 0.000 0.760
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.5746    -0.0597 0.376 0.000 0.452 0.000 0.000 0.172
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.4103     0.0741 0.004 0.004 0.000 0.544 0.448 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5412     0.1967 0.496 0.000 0.384 0.000 0.000 0.120
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.1814     0.7223 0.000 0.000 0.000 0.100 0.000 0.900
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.6178     0.2170 0.336 0.000 0.000 0.264 0.004 0.396
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.3717     0.3965 0.000 0.616 0.000 0.384 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.4263     0.3908 0.376 0.000 0.600 0.000 0.000 0.024
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.2980     0.6842 0.000 0.012 0.000 0.180 0.808 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.3867     0.3932 0.512 0.000 0.000 0.000 0.000 0.488
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.2823     0.7191 0.000 0.796 0.000 0.204 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.2003     0.7223 0.000 0.000 0.000 0.116 0.000 0.884
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.3843     0.4349 0.548 0.000 0.000 0.000 0.000 0.452
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.4127     0.3864 0.364 0.000 0.620 0.000 0.012 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.3390     0.5767 0.296 0.000 0.000 0.000 0.704 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.2805     0.4613 0.828 0.000 0.000 0.000 0.012 0.160
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     6  0.1970     0.6149 0.092 0.000 0.008 0.000 0.000 0.900
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.2191     0.7220 0.000 0.004 0.000 0.120 0.000 0.876
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     5  0.3866     0.1045 0.000 0.000 0.000 0.484 0.516 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.4293     0.3974 0.396 0.584 0.000 0.000 0.016 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     5  0.5064     0.4625 0.000 0.000 0.152 0.216 0.632 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3483     0.6693 0.212 0.024 0.764 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.2815     0.7367 0.032 0.120 0.000 0.000 0.848 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.5181     0.1232 0.088 0.484 0.000 0.000 0.000 0.428
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     6  0.2527     0.5370 0.168 0.000 0.000 0.000 0.000 0.832
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0146     0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     6  0.2762     0.6907 0.000 0.000 0.000 0.196 0.000 0.804
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     6  0.2048     0.7218 0.000 0.000 0.000 0.120 0.000 0.880
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     6  0.2101     0.7224 0.004 0.004 0.000 0.100 0.000 0.892
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     6  0.3670     0.6213 0.152 0.004 0.000 0.056 0.000 0.788
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.5659     0.0951 0.448 0.004 0.416 0.000 0.000 0.132
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     6  0.4506     0.4422 0.176 0.120 0.000 0.000 0.000 0.704
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.3819     0.5232 0.624 0.004 0.000 0.000 0.000 0.372
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0146     0.8338 0.004 0.000 0.000 0.000 0.996 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     5  0.5421     0.0514 0.000 0.116 0.000 0.432 0.452 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0713     0.8792 0.000 0.972 0.000 0.000 0.028 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     6  0.3838     0.6684 0.116 0.004 0.000 0.096 0.000 0.784
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     6  0.1958     0.7224 0.000 0.004 0.000 0.100 0.000 0.896
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     5  0.3975     0.3351 0.000 0.392 0.008 0.000 0.600 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     6  0.1958     0.7224 0.000 0.004 0.000 0.100 0.000 0.896
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.5349     0.3024 0.356 0.000 0.548 0.084 0.012 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.0632     0.8258 0.000 0.000 0.024 0.976 0.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.5516     0.2650 0.504 0.000 0.356 0.000 0.000 0.140
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.3620     0.4275 0.000 0.648 0.000 0.000 0.352 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     6  0.4555     0.4020 0.392 0.000 0.000 0.020 0.012 0.576
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     5  0.7279     0.1797 0.000 0.160 0.000 0.208 0.432 0.200
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.2378     0.7770 0.000 0.848 0.000 0.152 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.1082     0.5662 0.956 0.000 0.000 0.000 0.004 0.040
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     4  0.4855    -0.0318 0.000 0.056 0.000 0.484 0.460 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.1367     0.5481 0.944 0.000 0.044 0.000 0.012 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.1074     0.8774 0.000 0.960 0.000 0.028 0.012 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0146     0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.3898     0.1535 0.652 0.000 0.000 0.000 0.012 0.336
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3  0.4122     0.0714 0.000 0.004 0.520 0.004 0.000 0.472
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     6  0.2003     0.7223 0.000 0.000 0.000 0.116 0.000 0.884
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#> 17CA5D73-4384-4645-83F8-587847043DD2     6  0.1714     0.7212 0.000 0.000 0.000 0.092 0.000 0.908
#> 40467950-A95C-4731-AD93-0A128442C837     6  0.3023     0.4941 0.232 0.000 0.000 0.000 0.000 0.768
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     6  0.2333     0.6229 0.092 0.024 0.000 0.000 0.000 0.884
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     6  0.2263     0.7096 0.036 0.004 0.000 0.060 0.000 0.900
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0146     0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     6  0.4962     0.4741 0.320 0.000 0.000 0.060 0.012 0.608
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     6  0.4345     0.4249 0.372 0.000 0.000 0.012 0.012 0.604
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0146     0.8878 0.000 0.996 0.004 0.000 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     6  0.2135     0.7205 0.000 0.000 0.000 0.128 0.000 0.872
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     6  0.5587     0.0516 0.156 0.004 0.292 0.000 0.000 0.548
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3717     0.6693 0.148 0.000 0.780 0.000 0.000 0.072
#> A7ECBC06-1332-4278-8723-85DC8351188A     6  0.2219     0.7185 0.000 0.000 0.000 0.136 0.000 0.864
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     6  0.4110     0.3697 0.012 0.004 0.296 0.008 0.000 0.680
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.3995     0.0242 0.516 0.000 0.000 0.000 0.480 0.004
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     6  0.1814     0.7223 0.000 0.000 0.000 0.100 0.000 0.900
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0865     0.8746 0.000 0.964 0.000 0.036 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.1863     0.7632 0.000 0.000 0.000 0.896 0.000 0.104
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0547     0.8786 0.000 0.980 0.020 0.000 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0858     0.8792 0.000 0.968 0.000 0.028 0.004 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     6  0.2300     0.5672 0.144 0.000 0.000 0.000 0.000 0.856
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.2320     0.7581 0.132 0.000 0.864 0.000 0.000 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     6  0.4407     0.4305 0.364 0.000 0.000 0.016 0.012 0.608
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     6  0.1501     0.6337 0.076 0.000 0.000 0.000 0.000 0.924
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.5258     0.2740 0.092 0.004 0.540 0.000 0.000 0.364
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     5  0.5479     0.0475 0.000 0.124 0.000 0.428 0.448 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     6  0.1471     0.7132 0.000 0.004 0.000 0.064 0.000 0.932
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.5852    -0.1159 0.484 0.004 0.120 0.000 0.012 0.380
#> 887E7408-C7D7-420F-A763-0EE70A316D17     6  0.2135     0.7205 0.000 0.000 0.000 0.128 0.000 0.872
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0632     0.8813 0.000 0.976 0.000 0.000 0.024 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     6  0.2048     0.7222 0.000 0.000 0.000 0.120 0.000 0.880
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1151     0.5645 0.956 0.000 0.000 0.000 0.012 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1225     0.5639 0.952 0.000 0.000 0.000 0.012 0.036
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.3789     0.3501 0.416 0.000 0.584 0.000 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.2933     0.6498 0.000 0.004 0.796 0.000 0.000 0.200
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.3695     0.5293 0.624 0.000 0.000 0.000 0.000 0.376
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3774     0.4914 0.592 0.000 0.000 0.000 0.000 0.408
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0260     0.8872 0.000 0.992 0.000 0.008 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     4  0.4118     0.4621 0.000 0.028 0.312 0.660 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.1511     0.5480 0.940 0.004 0.044 0.000 0.012 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0692     0.8316 0.004 0.020 0.976 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     6  0.2730     0.4992 0.192 0.000 0.000 0.000 0.000 0.808
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.0000     0.8353 0.000 0.000 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.2092     0.7216 0.000 0.000 0.000 0.124 0.000 0.876
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.3672     0.5336 0.632 0.000 0.000 0.000 0.000 0.368
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.1814     0.7223 0.000 0.000 0.000 0.100 0.000 0.900
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     6  0.3807     0.3289 0.000 0.004 0.368 0.000 0.000 0.628
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.6270     0.2657 0.352 0.228 0.000 0.408 0.012 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.2178     0.7327 0.000 0.000 0.000 0.868 0.000 0.132
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.1075     0.8124 0.000 0.000 0.000 0.952 0.000 0.048
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.2048     0.7218 0.000 0.000 0.000 0.120 0.000 0.880
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.5841     0.1101 0.192 0.000 0.000 0.372 0.436 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.1910     0.7226 0.000 0.000 0.000 0.108 0.000 0.892
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.1910     0.7226 0.000 0.000 0.000 0.108 0.000 0.892
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3907     0.3612 0.408 0.004 0.588 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2121     0.5019 0.892 0.000 0.000 0.000 0.012 0.096
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2274     0.5429 0.892 0.000 0.088 0.000 0.012 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.1814     0.7367 0.000 0.000 0.000 0.900 0.100 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.2527     0.6964 0.000 0.000 0.000 0.168 0.832 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0146     0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.3329     0.6578 0.004 0.004 0.000 0.236 0.000 0.756
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.2843     0.7149 0.000 0.000 0.036 0.116 0.000 0.848
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.3383     0.4656 0.268 0.004 0.000 0.000 0.000 0.728
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.2309     0.8124 0.028 0.888 0.000 0.000 0.000 0.084
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2823     0.7191 0.000 0.796 0.000 0.204 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.2135     0.7205 0.000 0.000 0.000 0.128 0.000 0.872
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.3967     0.4019 0.000 0.012 0.000 0.356 0.632 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1334     0.8171 0.032 0.000 0.948 0.000 0.000 0.020
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3684     0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1349     0.5405 0.940 0.000 0.000 0.000 0.056 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.5136     0.1388 0.420 0.000 0.496 0.000 0.000 0.084
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     5  0.5414     0.0983 0.000 0.116 0.000 0.416 0.468 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     6  0.3805     0.3318 0.328 0.004 0.000 0.000 0.004 0.664
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5419     0.3171 0.636 0.004 0.184 0.000 0.012 0.164
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.4185     0.6358 0.168 0.004 0.000 0.084 0.000 0.744
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.2527     0.5350 0.168 0.000 0.000 0.000 0.000 0.832
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000     0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     6  0.2664     0.5099 0.184 0.000 0.000 0.000 0.000 0.816
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.3747     0.3592 0.000 0.000 0.604 0.000 0.396 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0146     0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.0363     0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3563     0.5500 0.664 0.000 0.000 0.000 0.000 0.336
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.5698     0.1094 0.016 0.500 0.000 0.108 0.000 0.376
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.4241     0.6123 0.004 0.004 0.164 0.080 0.000 0.748
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.2178     0.5824 0.132 0.000 0.000 0.000 0.000 0.868

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 17541 rows and 500 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 0.406           0.695       0.869         0.4811 0.506   0.506
#> 3 3 0.355           0.453       0.716         0.3368 0.707   0.494
#> 4 4 0.537           0.565       0.781         0.1330 0.814   0.539
#> 5 5 0.546           0.491       0.696         0.0626 0.833   0.492
#> 6 6 0.615           0.562       0.734         0.0451 0.870   0.522

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.7453    0.68209 0.212 0.788
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.8016    0.61032 0.756 0.244
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.7453    0.71511 0.212 0.788
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.8608    0.56037 0.284 0.716
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.8608    0.56037 0.284 0.716
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.8443    0.54847 0.728 0.272
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.8144    0.68912 0.252 0.748
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000    0.83597 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.7883    0.69749 0.236 0.764
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.8608    0.53111 0.716 0.284
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.8661    0.56026 0.288 0.712
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000    0.83597 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0376    0.82534 0.004 0.996
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2778    0.81360 0.952 0.048
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.1414    0.82970 0.980 0.020
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.8661    0.52173 0.712 0.288
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.8861    0.53230 0.696 0.304
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.6887    0.70498 0.184 0.816
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.8608    0.56037 0.284 0.716
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0376    0.82534 0.004 0.996
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.7376    0.68563 0.208 0.792
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0376    0.82534 0.004 0.996
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.83597 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0672    0.82734 0.008 0.992
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1414    0.82970 0.980 0.020
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0376    0.82534 0.004 0.996
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.8081    0.58749 0.752 0.248
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1843    0.82426 0.972 0.028
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0376    0.83541 0.996 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0376    0.83541 0.996 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.8861    0.49188 0.696 0.304
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0376    0.82534 0.004 0.996
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.9909    0.23731 0.556 0.444
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000    0.83597 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.4431    0.77176 0.908 0.092
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.7815    0.62420 0.768 0.232
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.6438    0.70022 0.836 0.164
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0376    0.83541 0.996 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1414    0.83178 0.980 0.020
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.9044    0.49459 0.320 0.680
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000    0.83597 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1184    0.83249 0.984 0.016
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0938    0.82888 0.012 0.988
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0938    0.83282 0.988 0.012
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.7674    0.62873 0.776 0.224
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.8499    0.54146 0.724 0.276
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000    0.82525 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.1633    0.82716 0.976 0.024
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.8713    0.52119 0.708 0.292
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.8386    0.58876 0.268 0.732
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0672    0.83299 0.992 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0376    0.83541 0.996 0.004
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.8608    0.56037 0.284 0.716
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.8499    0.54146 0.724 0.276
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0376    0.83541 0.996 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.3274    0.80449 0.940 0.060
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0938    0.82888 0.012 0.988
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.9775    0.24842 0.412 0.588
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.9963   -0.00203 0.536 0.464
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.8608    0.56037 0.284 0.716
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0376    0.83541 0.996 0.004
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0938    0.82888 0.012 0.988
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3733    0.79417 0.928 0.072
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000    0.83597 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.9460    0.35892 0.636 0.364
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.9393    0.37781 0.644 0.356
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0938    0.82888 0.012 0.988
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.1184    0.82910 0.984 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0376    0.83541 0.996 0.004
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0672    0.83299 0.992 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.8608    0.56037 0.284 0.716
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.9977    0.05106 0.472 0.528
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0938    0.82888 0.012 0.988
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0376    0.82534 0.004 0.996
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.7815    0.69618 0.232 0.768
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.9815    0.29987 0.580 0.420
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.9909    0.25467 0.444 0.556
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.7528    0.67713 0.216 0.784
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.9358    0.49232 0.352 0.648
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.9993   -0.06151 0.516 0.484
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.1843    0.82803 0.972 0.028
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0938    0.82888 0.012 0.988
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000    0.83597 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.1633    0.82559 0.024 0.976
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0672    0.83299 0.992 0.008
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0938    0.82888 0.012 0.988
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0672    0.83299 0.992 0.008
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.7883    0.69183 0.236 0.764
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000    0.83597 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0938    0.82832 0.012 0.988
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000    0.83597 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.8608    0.52874 0.716 0.284
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000    0.83597 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0376    0.82534 0.004 0.996
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000    0.83597 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.8608    0.56037 0.284 0.716
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0376    0.82534 0.004 0.996
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.1184    0.82842 0.016 0.984
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.7299    0.65770 0.796 0.204
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0376    0.82534 0.004 0.996
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0672    0.83299 0.992 0.008
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000    0.83597 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.2236    0.82505 0.036 0.964
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0938    0.82888 0.012 0.988
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0376    0.83541 0.996 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.9998   -0.07633 0.508 0.492
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.8499    0.64904 0.276 0.724
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0376    0.83541 0.996 0.004
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0938    0.82888 0.012 0.988
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0938    0.83282 0.988 0.012
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.9087    0.50697 0.324 0.676
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.9427    0.42245 0.360 0.640
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0672    0.82830 0.008 0.992
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.0376    0.83541 0.996 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.9896    0.24871 0.560 0.440
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0938    0.82888 0.012 0.988
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0000    0.83597 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0938    0.82888 0.012 0.988
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.8016    0.68279 0.244 0.756
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0376    0.83541 0.996 0.004
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.8327    0.56822 0.736 0.264
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0672    0.83299 0.992 0.008
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0938    0.82888 0.012 0.988
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.0938    0.83359 0.988 0.012
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.0938    0.82888 0.012 0.988
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.6801    0.68661 0.820 0.180
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.7745    0.62601 0.772 0.228
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.8861    0.50112 0.696 0.304
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0000    0.83597 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     2  0.1633    0.82402 0.024 0.976
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0000    0.83597 1.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0376    0.82534 0.004 0.996
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  1.0000   -0.10542 0.504 0.496
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.0376    0.83541 0.996 0.004
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0000    0.83597 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.7815    0.69618 0.232 0.768
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.9795    0.29930 0.584 0.416
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.0938    0.82888 0.012 0.988
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.0376    0.83541 0.996 0.004
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.0938    0.82888 0.012 0.988
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.8443    0.65426 0.272 0.728
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.9815    0.37681 0.420 0.580
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0672    0.82830 0.008 0.992
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.0672    0.82830 0.008 0.992
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     1  0.6247    0.71193 0.844 0.156
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.0672    0.82830 0.008 0.992
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.0672    0.82731 0.008 0.992
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1  0.0376    0.83541 0.996 0.004
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     1  0.8499    0.54146 0.724 0.276
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1  0.1184    0.83121 0.984 0.016
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.0938    0.82888 0.012 0.988
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     1  0.9209    0.42307 0.664 0.336
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     2  0.7950    0.69312 0.240 0.760
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     1  0.0672    0.83299 0.992 0.008
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     1  0.8081    0.58732 0.752 0.248
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     1  0.0376    0.83541 0.996 0.004
#> 23238B08-AA91-46A3-B147-91185A5FAE3F     1  0.0000    0.83597 1.000 0.000
#> DAB49A2E-BBFD-459B-B156-726D8D91D598     1  0.0000    0.83597 1.000 0.000
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F     2  0.8763    0.55105 0.296 0.704
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0     2  0.0672    0.82830 0.008 0.992
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#> 9EF7685F-CA09-4869-94EA-12A1129093B1     2  0.0672    0.82830 0.008 0.992
#> 18AB08E8-6C1A-49E4-9DF0-79D80D9BEC78     2  0.7745    0.69993 0.228 0.772
#> 97FB3176-395F-475B-8EAE-332C5BEE8155     1  0.0000    0.83597 1.000 0.000
#> E1876307-DFD9-4688-876F-D71B37466068     2  0.0938    0.82888 0.012 0.988
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04     2  0.1414    0.82596 0.020 0.980
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00     1  0.7602    0.63300 0.780 0.220
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79     2  0.8443    0.64439 0.272 0.728
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A     1  0.9977   -0.03484 0.528 0.472
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18     1  0.4690    0.76665 0.900 0.100
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D     2  0.7950    0.68744 0.240 0.760
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854     2  0.7815    0.69618 0.232 0.768
#> B3CCA12D-4569-4AB8-AC41-457448268D90     1  0.0672    0.83299 0.992 0.008
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     1  0.0376    0.83528 0.996 0.004
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     2  0.7950    0.68744 0.240 0.760
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.0938    0.82888 0.012 0.988
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     1  0.0000    0.83597 1.000 0.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.0376    0.82534 0.004 0.996
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.0672    0.82830 0.008 0.992
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     2  0.7528    0.71114 0.216 0.784
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     1  0.8661    0.52869 0.712 0.288
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.0672    0.82830 0.008 0.992
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     1  0.0000    0.83597 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     2  0.9460    0.50425 0.364 0.636
#> 985FEEC2-9737-4018-80DF-21A07AB47900     1  0.8813    0.50289 0.700 0.300
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  0.0938    0.83359 0.988 0.012
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.2423    0.81722 0.960 0.040
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.0672    0.82830 0.008 0.992
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.0672    0.82830 0.008 0.992
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.9044    0.48285 0.680 0.320
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.7745    0.65023 0.228 0.772
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     2  0.7815    0.69618 0.232 0.768
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0938    0.83261 0.988 0.012
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.0376    0.82534 0.004 0.996
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0000    0.83597 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     1  0.8499    0.54146 0.724 0.276
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.0376    0.83541 0.996 0.004
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.0376    0.82534 0.004 0.996
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.9815    0.16293 0.580 0.420
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.0376    0.83541 0.996 0.004
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.7674    0.70381 0.224 0.776
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.9909    0.23731 0.556 0.444
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.2948    0.81049 0.052 0.948
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0938    0.82888 0.012 0.988
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.8144    0.68091 0.252 0.748
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.8813    0.54849 0.300 0.700
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.8713    0.55999 0.292 0.708
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0376    0.82534 0.004 0.996
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.9522    0.41113 0.628 0.372
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0672    0.82830 0.008 0.992
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000    0.83597 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0672    0.83299 0.992 0.008
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.1633    0.82616 0.976 0.024
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0376    0.83541 0.996 0.004
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.7883    0.69222 0.236 0.764
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0938    0.82888 0.012 0.988
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0672    0.82830 0.008 0.992
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0938    0.82888 0.012 0.988
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0376    0.82534 0.004 0.996
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.2043    0.82623 0.968 0.032
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0672    0.83371 0.992 0.008
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000    0.83597 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0672    0.83299 0.992 0.008
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.2236    0.81804 0.036 0.964
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0000    0.83597 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000    0.83597 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0376    0.83541 0.996 0.004
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0000    0.83597 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000    0.83597 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.9983   -0.03519 0.524 0.476
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.8608    0.63973 0.284 0.716
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.9909    0.23731 0.556 0.444
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.0376    0.83541 0.996 0.004
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0672    0.83299 0.992 0.008
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0672    0.82830 0.008 0.992
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0938    0.83218 0.988 0.012
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.1414    0.83011 0.980 0.020
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.0376    0.83541 0.996 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0376    0.83526 0.996 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.9983   -0.04652 0.524 0.476
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.4431    0.78060 0.908 0.092
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0376    0.83541 0.996 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.3879    0.80208 0.076 0.924
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.7453    0.65027 0.788 0.212
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.1633    0.82559 0.024 0.976
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0376    0.82534 0.004 0.996
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0376    0.83541 0.996 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0672    0.82830 0.008 0.992
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.8499    0.54146 0.724 0.276
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.7815    0.69633 0.232 0.768
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0672    0.83299 0.992 0.008
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0938    0.82888 0.012 0.988
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.9866    0.26670 0.568 0.432
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0376    0.83541 0.996 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.9996    0.13812 0.488 0.512
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0938    0.82888 0.012 0.988
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.8608    0.56037 0.284 0.716
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0376    0.83541 0.996 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0376    0.83541 0.996 0.004
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0672    0.83299 0.992 0.008
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0672    0.83299 0.992 0.008
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0938    0.82888 0.012 0.988
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0938    0.82888 0.012 0.988
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.9909    0.23731 0.556 0.444
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.8661    0.52173 0.712 0.288
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.9993   -0.07083 0.516 0.484
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000    0.83597 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.9996    0.16660 0.488 0.512
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0672    0.83339 0.992 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.9988   -0.06273 0.520 0.480
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.7815    0.69601 0.232 0.768
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.8499    0.54146 0.724 0.276
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0376    0.83541 0.996 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000    0.83597 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5408    0.76816 0.124 0.876
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.1843    0.82749 0.028 0.972
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.1843    0.82216 0.972 0.028
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.7528    0.71114 0.216 0.784
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0376    0.83541 0.996 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0376    0.82534 0.004 0.996
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0938    0.82888 0.012 0.988
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0938    0.83282 0.988 0.012
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000    0.83597 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.8661    0.52173 0.712 0.288
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.83597 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.8661    0.52869 0.712 0.288
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.8608    0.56037 0.284 0.716
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.7528    0.64441 0.784 0.216
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.7815    0.62420 0.768 0.232
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0376    0.83541 0.996 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9522    0.40994 0.628 0.372
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0672    0.83299 0.992 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0376    0.83541 0.996 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.8813    0.49265 0.700 0.300
#> 1122039D-5785-4F70-9916-17C585453512     1  0.9661    0.36699 0.608 0.392
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0376    0.83541 0.996 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000    0.83597 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.8608    0.56037 0.284 0.716
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.8608    0.56037 0.284 0.716
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0672    0.82830 0.008 0.992
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0672    0.83443 0.992 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.5629    0.75755 0.868 0.132
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0376    0.83541 0.996 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000    0.83597 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.7950    0.68784 0.240 0.760
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.7745    0.70068 0.228 0.772
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.8386    0.60250 0.268 0.732
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0938    0.83261 0.988 0.012
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.9988    0.13250 0.520 0.480
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0376    0.83541 0.996 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0376    0.83541 0.996 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0672    0.83371 0.992 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.8499    0.54146 0.724 0.276
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0376    0.82534 0.004 0.996
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000    0.83597 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000    0.83597 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000    0.83597 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0376    0.83541 0.996 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.9909    0.23731 0.556 0.444
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0376    0.83541 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0938    0.82888 0.012 0.988
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.7815    0.69618 0.232 0.768
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0938    0.82888 0.012 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000    0.83597 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.9732    0.31305 0.596 0.404
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0376    0.83541 0.996 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000    0.83597 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5733     0.6123 0.000 0.676 0.324
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.5178     0.5152 0.744 0.256 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.6302    -0.2710 0.000 0.480 0.520
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.8608    -0.0650 0.412 0.488 0.100
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.6309     0.0411 0.504 0.496 0.000
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#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.5835     0.4091 0.660 0.340 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.6148     0.4755 0.356 0.004 0.640
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0237     0.7819 0.000 0.996 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.6215    -0.1581 0.000 0.428 0.572
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.7827 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.6521     0.3612 0.496 0.004 0.500
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.8260     0.3684 0.192 0.636 0.172
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.9623     0.3005 0.232 0.304 0.464
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.6521     0.3612 0.496 0.004 0.500

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.7485    0.55928 0.164 0.560 0.260 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.1174    0.80750 0.012 0.020 0.000 0.968
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.5656    0.01660 0.012 0.384 0.592 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1635    0.79822 0.044 0.008 0.000 0.948
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.3837    0.68907 0.000 0.224 0.000 0.776
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4972   -0.10214 0.456 0.000 0.544 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.7692    0.46120 0.048 0.248 0.580 0.124
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0188    0.64280 0.996 0.000 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.7009    0.59522 0.164 0.628 0.192 0.016
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.5320    0.34853 0.572 0.000 0.416 0.012
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.5986    0.57090 0.276 0.656 0.064 0.004
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4500    0.40844 0.684 0.000 0.316 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2921    0.74430 0.000 0.860 0.000 0.140
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2188    0.64188 0.936 0.020 0.032 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1022    0.80385 0.032 0.000 0.000 0.968
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4193    0.50455 0.732 0.000 0.268 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.1174    0.80750 0.012 0.020 0.000 0.968
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.7292    0.17489 0.152 0.460 0.000 0.388
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.4380    0.69368 0.164 0.032 0.004 0.800
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.1109    0.81138 0.000 0.968 0.028 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4389    0.54114 0.000 0.116 0.812 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3969    0.67088 0.000 0.804 0.016 0.180
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.5728    0.13902 0.600 0.000 0.036 0.364
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1109    0.81138 0.000 0.968 0.028 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.4790    0.43519 0.380 0.000 0.000 0.620
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.3390    0.77630 0.000 0.852 0.132 0.016
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3837    0.58365 0.224 0.000 0.776 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1297    0.63577 0.964 0.020 0.000 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.4605    0.46930 0.336 0.000 0.664 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0921    0.64062 0.972 0.000 0.028 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4831    0.59887 0.188 0.024 0.772 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1109    0.81138 0.000 0.968 0.028 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.1022    0.80533 0.000 0.032 0.000 0.968
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1452    0.64257 0.956 0.000 0.036 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.5068    0.43960 0.676 0.004 0.308 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.2973    0.78214 0.096 0.020 0.000 0.884
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.7462    0.51030 0.244 0.172 0.568 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.5352    0.51279 0.388 0.000 0.596 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.4790    0.43519 0.380 0.000 0.000 0.620
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.1022    0.80533 0.000 0.032 0.000 0.968
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2704    0.61383 0.876 0.000 0.124 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.5580    0.49727 0.408 0.016 0.572 0.004
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0188    0.81487 0.000 0.996 0.004 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.5713    0.14979 0.604 0.000 0.036 0.360
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.5073    0.70579 0.056 0.200 0.000 0.744
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.1637    0.60137 0.060 0.000 0.940 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.4661    0.70013 0.000 0.728 0.256 0.016
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5646    0.14389 0.592 0.384 0.008 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.5560    0.33510 0.392 0.024 0.584 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.8132   -0.16233 0.192 0.420 0.020 0.368
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1610    0.64176 0.952 0.000 0.032 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4331    0.55897 0.288 0.000 0.712 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.3444    0.72624 0.000 0.184 0.000 0.816
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4843    0.30876 0.604 0.000 0.396 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.5511    0.38545 0.484 0.000 0.500 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.5028    0.06303 0.596 0.000 0.004 0.400
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.3471    0.76665 0.072 0.868 0.000 0.060
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.5814    0.37865 0.620 0.024 0.344 0.012
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     4  0.5865    0.34738 0.036 0.412 0.000 0.552
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.3688    0.47156 0.792 0.000 0.208 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.5754    0.26041 0.428 0.548 0.008 0.016
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0336    0.64342 0.992 0.000 0.008 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.5934    0.34711 0.376 0.024 0.588 0.012
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.2255    0.59742 0.068 0.000 0.920 0.012
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.5302    0.67841 0.164 0.752 0.080 0.004
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.1118    0.63864 0.964 0.000 0.036 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.5310    0.49547 0.412 0.000 0.576 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.6031    0.44149 0.420 0.000 0.536 0.044
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.5361    0.52257 0.004 0.344 0.016 0.636
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.7006    0.32836 0.328 0.136 0.536 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0188    0.81523 0.000 0.996 0.004 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.3647    0.76651 0.000 0.832 0.152 0.016
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.7076   -0.10057 0.404 0.088 0.496 0.012
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0657    0.80588 0.004 0.000 0.012 0.984
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.2131    0.60022 0.032 0.036 0.932 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.4630    0.68234 0.196 0.768 0.036 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.5238    0.59175 0.204 0.040 0.744 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.1792    0.60143 0.068 0.000 0.932 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.5643    0.47620 0.428 0.024 0.548 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.1489    0.81226 0.000 0.952 0.044 0.004
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000    0.64210 1.000 0.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.4353    0.70273 0.000 0.756 0.232 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.4382    0.57264 0.296 0.000 0.000 0.704
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.4898    0.36636 0.416 0.000 0.000 0.584
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.2495    0.59489 0.028 0.036 0.924 0.012
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.5483    0.44709 0.448 0.000 0.536 0.016
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0657    0.81438 0.012 0.984 0.004 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.3790    0.49994 0.820 0.000 0.164 0.016
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.4936    0.30796 0.624 0.004 0.372 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0336    0.64091 0.992 0.000 0.000 0.008
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.3245    0.77251 0.000 0.872 0.028 0.100
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000    0.64210 1.000 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.5687    0.66763 0.164 0.732 0.096 0.008
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2469    0.76678 0.000 0.892 0.000 0.108
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.6335    0.66343 0.164 0.688 0.136 0.012
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0927    0.80828 0.016 0.008 0.000 0.976
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.4837    0.30779 0.648 0.000 0.004 0.348
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     3  0.5483    0.44709 0.448 0.000 0.536 0.016
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.1389    0.80617 0.048 0.952 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0921    0.81488 0.000 0.972 0.028 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.5417    0.49250 0.412 0.000 0.572 0.016
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.3810    0.42434 0.188 0.008 0.804 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.0657    0.80588 0.004 0.000 0.012 0.984
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.3726    0.58584 0.212 0.000 0.788 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.5873   -0.03574 0.548 0.000 0.036 0.416
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.4898    0.69473 0.156 0.772 0.000 0.072
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.2345    0.77643 0.100 0.900 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0188    0.81523 0.000 0.996 0.004 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.4248    0.55209 0.768 0.000 0.220 0.012
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     4  0.1792    0.79610 0.000 0.068 0.000 0.932
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.5300    0.35762 0.580 0.000 0.408 0.012
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.3450    0.59519 0.032 0.072 0.880 0.016
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.1305    0.63827 0.960 0.000 0.036 0.004
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3  0.6144    0.51404 0.380 0.028 0.576 0.016
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     4  0.4830    0.40808 0.392 0.000 0.000 0.608
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.5310    0.35369 0.576 0.000 0.412 0.012
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.7528    0.55326 0.164 0.552 0.268 0.016
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     4  0.0592    0.80728 0.016 0.000 0.000 0.984
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.4730    0.44245 0.364 0.636 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.7078    0.38570 0.612 0.200 0.176 0.012
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     3  0.5497    0.42901 0.460 0.000 0.524 0.016
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     4  0.1109    0.80184 0.000 0.004 0.028 0.968
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.2589    0.61159 0.884 0.000 0.116 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.4477    0.56623 0.000 0.688 0.000 0.312
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.7053    0.56469 0.212 0.620 0.152 0.016
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3  0.2704    0.60289 0.124 0.000 0.876 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.3790    0.49994 0.820 0.000 0.164 0.016
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3  0.2495    0.59489 0.028 0.036 0.924 0.012
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     4  0.0592    0.80728 0.016 0.000 0.000 0.984
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     3  0.5483    0.44709 0.448 0.000 0.536 0.016
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.3479    0.77050 0.000 0.840 0.148 0.012
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3  0.5465    0.38570 0.032 0.252 0.704 0.012
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.6542    0.60997 0.088 0.648 0.248 0.016
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0336    0.81542 0.000 0.992 0.008 0.000
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#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.4925    0.49277 0.428 0.000 0.572 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     4  0.7318    0.58952 0.164 0.184 0.032 0.620
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0188    0.81523 0.000 0.996 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     3  0.5483    0.44709 0.448 0.000 0.536 0.016
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.2704    0.60898 0.876 0.000 0.124 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.5366   -0.08537 0.440 0.000 0.548 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.3790    0.49994 0.820 0.000 0.164 0.016
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.6152    0.53693 0.336 0.036 0.612 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.8261    0.00540 0.164 0.440 0.036 0.360
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0592    0.80728 0.016 0.000 0.000 0.984
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0592    0.80728 0.016 0.000 0.000 0.984
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.5673    0.43954 0.448 0.000 0.528 0.024
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.6712    0.60161 0.164 0.200 0.004 0.632
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.4907   -0.00690 0.580 0.000 0.000 0.420
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.5417    0.49250 0.412 0.000 0.572 0.016
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.5189    0.37033 0.616 0.000 0.372 0.012
#> 1122039D-5785-4F70-9916-17C585453512     4  0.1174    0.80581 0.000 0.020 0.012 0.968
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4961   -0.18705 0.552 0.000 0.448 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.5110    0.39766 0.636 0.000 0.352 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3688    0.70070 0.000 0.208 0.000 0.792
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.7702    0.18855 0.196 0.452 0.004 0.348
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0804    0.81516 0.008 0.980 0.012 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.6703    0.29771 0.612 0.232 0.000 0.156
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0657    0.80588 0.004 0.000 0.012 0.984
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5408    0.49660 0.408 0.000 0.576 0.016
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0336    0.64130 0.992 0.000 0.000 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2495    0.59489 0.028 0.036 0.924 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.4980    0.52823 0.304 0.680 0.016 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1118    0.80326 0.036 0.964 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.4961    0.27987 0.448 0.000 0.000 0.552
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.5398    0.65766 0.200 0.064 0.004 0.732
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.5273   -0.10796 0.456 0.000 0.536 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2589    0.61159 0.884 0.000 0.116 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.5143    0.40739 0.628 0.000 0.360 0.012
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4998   -0.14268 0.488 0.000 0.512 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1557    0.79489 0.000 0.944 0.000 0.056
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0524    0.64194 0.988 0.000 0.004 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.1557    0.64176 0.944 0.000 0.056 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0592    0.63869 0.984 0.000 0.000 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3266    0.50370 0.832 0.000 0.168 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.1022    0.80533 0.000 0.032 0.000 0.968
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3528    0.48189 0.808 0.000 0.192 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2495    0.59489 0.028 0.036 0.924 0.012
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.81510 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0336    0.64342 0.992 0.000 0.008 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.6955    0.35840 0.296 0.560 0.144 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5313    0.51978 0.376 0.000 0.608 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0188    0.64176 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     3  0.6611   -0.43240 0.048 0.420 0.456 0.000 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.6587    0.39674 0.000 0.220 0.444 0.000 0.336
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.2605    0.72032 0.148 0.000 0.000 0.852 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.4626    0.44993 0.000 0.364 0.020 0.616 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     5  0.2020    0.45146 0.000 0.000 0.100 0.000 0.900
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.6799    0.08649 0.036 0.516 0.360 0.024 0.064
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     5  0.4304    0.19230 0.484 0.000 0.000 0.000 0.516
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.7998    0.16721 0.172 0.440 0.244 0.000 0.144
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.3276    0.39784 0.032 0.000 0.132 0.000 0.836
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.7850    0.43963 0.128 0.448 0.272 0.000 0.152
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     5  0.4141    0.57717 0.236 0.000 0.028 0.000 0.736
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1907    0.73181 0.000 0.928 0.028 0.044 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4912   -0.13647 0.500 0.012 0.008 0.000 0.480
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1270    0.81674 0.052 0.000 0.000 0.948 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     5  0.1701    0.49608 0.048 0.000 0.016 0.000 0.936
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     4  0.7909   -0.04931 0.108 0.392 0.056 0.400 0.044
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.3267    0.78246 0.024 0.044 0.000 0.868 0.064
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.3636    0.66383 0.000 0.728 0.272 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.5183    0.31602 0.000 0.024 0.708 0.204 0.064
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3531    0.64536 0.000 0.816 0.036 0.148 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2685    0.65031 0.880 0.000 0.092 0.000 0.028
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.3550    0.67800 0.004 0.760 0.236 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3109    0.61690 0.800 0.000 0.000 0.200 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.3983    0.62416 0.000 0.660 0.340 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     5  0.5793    0.01290 0.100 0.000 0.364 0.000 0.536
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1168    0.68238 0.960 0.008 0.000 0.000 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     5  0.6000    0.25205 0.160 0.000 0.268 0.000 0.572
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     5  0.4182    0.28098 0.400 0.000 0.000 0.000 0.600
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.6418    0.37466 0.316 0.004 0.508 0.000 0.172
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.3636    0.66383 0.000 0.728 0.272 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.4304    0.14155 0.484 0.000 0.000 0.000 0.516
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     5  0.2416    0.56298 0.100 0.000 0.012 0.000 0.888
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.4235    0.16036 0.576 0.000 0.000 0.424 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5617    0.43472 0.620 0.124 0.256 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4410    0.19190 0.556 0.000 0.440 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3074    0.61904 0.804 0.000 0.000 0.196 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     5  0.3999    0.47456 0.344 0.000 0.000 0.000 0.656
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5701    0.34100 0.580 0.004 0.328 0.000 0.088
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1043    0.74208 0.000 0.960 0.040 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3539    0.63775 0.848 0.000 0.092 0.032 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.6813   -0.11282 0.360 0.332 0.000 0.308 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4126    0.54250 0.000 0.000 0.620 0.000 0.380
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.5650   -0.42716 0.000 0.460 0.464 0.000 0.076
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.2554    0.66441 0.892 0.036 0.000 0.000 0.072
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.6306    0.18067 0.172 0.000 0.328 0.000 0.500
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.7637    0.23421 0.108 0.536 0.048 0.252 0.056
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2127    0.65931 0.892 0.000 0.000 0.000 0.108
#> 4379559E-E467-49BD-9673-40A486146A3B     5  0.6244    0.07039 0.156 0.000 0.348 0.000 0.496
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.3081    0.75015 0.000 0.156 0.012 0.832 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     5  0.2754    0.49102 0.040 0.000 0.080 0.000 0.880
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1357    0.68320 0.948 0.000 0.048 0.000 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.4543    0.61897 0.768 0.000 0.008 0.120 0.104
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0290    0.73924 0.000 0.992 0.008 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4413    0.57184 0.232 0.724 0.000 0.044 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     5  0.1522    0.51818 0.044 0.000 0.012 0.000 0.944
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.6459    0.12559 0.104 0.528 0.028 0.340 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     5  0.5022    0.40090 0.332 0.000 0.048 0.000 0.620
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0404    0.73970 0.000 0.988 0.012 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.1197    0.67717 0.952 0.048 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     5  0.4161    0.30619 0.392 0.000 0.000 0.000 0.608
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.7582    0.18798 0.300 0.040 0.352 0.000 0.308
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.4626    0.55554 0.020 0.000 0.616 0.000 0.364
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.6478    0.50592 0.044 0.516 0.364 0.000 0.076
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.4728    0.55968 0.700 0.000 0.060 0.000 0.240
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5518    0.24489 0.544 0.000 0.384 0.000 0.072
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.1331    0.68487 0.952 0.000 0.040 0.008 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.5748    0.22084 0.020 0.444 0.044 0.492 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.8450    0.10402 0.220 0.204 0.352 0.000 0.224
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0807    0.73892 0.012 0.976 0.012 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.4527    0.59016 0.012 0.596 0.392 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     5  0.3821    0.30292 0.000 0.020 0.216 0.000 0.764
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.4989    0.53248 0.000 0.032 0.552 0.000 0.416
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.4971    0.64761 0.112 0.752 0.028 0.000 0.108
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.6096    0.51816 0.060 0.032 0.536 0.000 0.372
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.4935    0.56391 0.040 0.000 0.616 0.000 0.344
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.5965    0.30898 0.544 0.000 0.328 0.000 0.128
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.3934    0.66044 0.000 0.716 0.276 0.000 0.008
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.3336    0.53465 0.772 0.000 0.000 0.000 0.228
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.6186    0.44402 0.016 0.596 0.248 0.000 0.140
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.3707    0.53712 0.716 0.000 0.000 0.284 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0404    0.73898 0.000 0.988 0.012 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.1197    0.68292 0.952 0.000 0.000 0.048 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4794    0.57117 0.000 0.032 0.624 0.000 0.344
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.1725    0.68195 0.936 0.000 0.044 0.000 0.020
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0912    0.73803 0.012 0.972 0.016 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1410    0.67752 0.940 0.000 0.000 0.000 0.060
#> 4D361EA8-1F79-4B89-841B-87F83215D805     5  0.4513    0.50534 0.128 0.004 0.104 0.000 0.764
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0880    0.68125 0.968 0.000 0.000 0.000 0.032
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.4924    0.62527 0.000 0.668 0.272 0.060 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     5  0.4304    0.17306 0.484 0.000 0.000 0.000 0.516
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.6965    0.48709 0.056 0.488 0.360 0.004 0.092
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.1668    0.73536 0.000 0.940 0.028 0.032 0.000
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.2329    0.63950 0.876 0.000 0.000 0.000 0.124
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.6800   -0.11026 0.000 0.364 0.292 0.000 0.344
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.2917    0.72269 0.052 0.884 0.012 0.052 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.6648    0.55499 0.056 0.596 0.212 0.000 0.136
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1557    0.73885 0.008 0.940 0.052 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0880    0.73932 0.000 0.968 0.032 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     5  0.4037    0.57091 0.176 0.012 0.028 0.000 0.784
#> D85CB054-7F54-4383-96C0-6C99761B84E7     5  0.4256    0.27464 0.436 0.000 0.000 0.000 0.564
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.3452    0.63879 0.852 0.000 0.092 0.032 0.024
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.4276    0.68670 0.032 0.724 0.244 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     5  0.4166    0.38345 0.348 0.000 0.004 0.000 0.648
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.1310    0.68258 0.956 0.000 0.020 0.000 0.024
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.4335    0.59232 0.760 0.000 0.072 0.000 0.168
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.1341    0.67491 0.944 0.000 0.000 0.000 0.056
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0880    0.68198 0.968 0.000 0.000 0.000 0.032
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.4963    0.56020 0.040 0.000 0.608 0.000 0.352
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.5944    0.55744 0.020 0.092 0.608 0.000 0.280
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.3339    0.65383 0.840 0.000 0.000 0.048 0.112
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.3932    0.63136 0.828 0.000 0.092 0.036 0.044
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1043    0.73629 0.000 0.960 0.040 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0510    0.68528 0.984 0.000 0.016 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.6512    0.25728 0.348 0.000 0.452 0.000 0.200
#> D957A2ED-97CD-4107-90A5-73C7691A5681     5  0.2230    0.44146 0.000 0.000 0.116 0.000 0.884
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0510    0.68386 0.984 0.016 0.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.7142    0.00456 0.428 0.400 0.072 0.000 0.100
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.5647   -0.04958 0.476 0.028 0.028 0.000 0.468
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.3949    0.42216 0.668 0.000 0.332 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.2989    0.70617 0.080 0.872 0.004 0.000 0.044
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.3586    0.59262 0.264 0.000 0.000 0.736 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.5956   -0.05876 0.000 0.476 0.416 0.000 0.108
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0807    0.74073 0.012 0.976 0.012 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.6458    0.21721 0.496 0.000 0.280 0.000 0.224
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.3628    0.57304 0.012 0.772 0.216 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     5  0.3086    0.32621 0.004 0.000 0.180 0.000 0.816
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.6917    0.13285 0.012 0.460 0.272 0.000 0.256
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.6062    0.52937 0.672 0.000 0.092 0.160 0.076
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000    0.73947 0.000 1.000 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.2520    0.67353 0.896 0.000 0.048 0.000 0.056
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.6934    0.06933 0.456 0.068 0.392 0.000 0.084
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4015    0.61897 0.000 0.652 0.348 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5375    0.55214 0.136 0.664 0.000 0.200 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.1251    0.68356 0.956 0.000 0.036 0.000 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.5272    0.51462 0.052 0.000 0.552 0.000 0.396
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6326   -0.05965 0.460 0.000 0.380 0.000 0.160
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2813    0.62625 0.832 0.000 0.000 0.168 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.73947 0.000 1.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1792    0.73260 0.000 0.916 0.084 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4866    0.56287 0.036 0.000 0.620 0.000 0.344
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.5596    0.34233 0.596 0.304 0.100 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     5  0.2351    0.44858 0.016 0.000 0.088 0.000 0.896
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4851    0.56483 0.036 0.000 0.624 0.000 0.340
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     5  0.3109    0.57885 0.200 0.000 0.000 0.000 0.800
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     5  0.3977    0.25390 0.032 0.000 0.204 0.000 0.764
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.4929    0.57139 0.004 0.032 0.624 0.000 0.340
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.6494    0.20651 0.380 0.004 0.452 0.000 0.164
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     5  0.4075    0.56335 0.160 0.000 0.060 0.000 0.780
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3336    0.56218 0.772 0.000 0.000 0.000 0.228
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5978    0.32866 0.024 0.624 0.012 0.280 0.060
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.3552    0.71261 0.052 0.860 0.044 0.040 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     5  0.2929    0.56484 0.180 0.000 0.000 0.000 0.820
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.6725   -0.01004 0.000 0.400 0.256 0.000 0.344
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.6692    0.05553 0.416 0.000 0.336 0.000 0.248
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     4  0.7504    0.52276 0.028 0.108 0.272 0.528 0.064
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0798    0.73874 0.008 0.976 0.016 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1205    0.68403 0.956 0.000 0.040 0.004 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     5  0.3612    0.56099 0.268 0.000 0.000 0.000 0.732
#> 5E03E52F-957D-455B-A007-19714FAA818A     5  0.3957    0.21643 0.008 0.000 0.280 0.000 0.712
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1121    0.67711 0.956 0.000 0.000 0.000 0.044
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.6451    0.26011 0.364 0.000 0.452 0.000 0.184
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7808    0.33062 0.084 0.552 0.076 0.212 0.076
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1205    0.68403 0.956 0.000 0.040 0.004 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.6076    0.67683 0.032 0.168 0.044 0.692 0.064
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0609    0.68549 0.980 0.000 0.000 0.020 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4135    0.41045 0.656 0.000 0.340 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     5  0.5013    0.29501 0.100 0.000 0.204 0.000 0.696
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6754    0.08891 0.396 0.000 0.332 0.000 0.272
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.3476    0.47868 0.076 0.000 0.088 0.000 0.836
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3999    0.49182 0.000 0.344 0.000 0.656 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     4  0.8287    0.03317 0.164 0.348 0.028 0.380 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0794    0.73769 0.000 0.972 0.028 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.1074    0.68442 0.968 0.004 0.000 0.012 0.016
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.5099    0.34639 0.612 0.000 0.336 0.000 0.052
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2377    0.63557 0.872 0.000 0.000 0.000 0.128
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4794    0.57117 0.000 0.032 0.624 0.000 0.344
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.5510    0.24997 0.380 0.548 0.000 0.000 0.072
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2625    0.69936 0.108 0.876 0.016 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1121    0.68334 0.956 0.000 0.000 0.044 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.6229    0.63584 0.172 0.056 0.028 0.680 0.064
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     5  0.3203    0.40102 0.012 0.000 0.168 0.000 0.820
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     5  0.3684    0.54945 0.280 0.000 0.000 0.000 0.720
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.4360    0.55238 0.184 0.000 0.064 0.000 0.752
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     5  0.3558    0.51255 0.064 0.000 0.108 0.000 0.828
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1493    0.73503 0.000 0.948 0.028 0.024 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.4300    0.15520 0.476 0.000 0.000 0.000 0.524
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.4637    0.21653 0.452 0.000 0.012 0.000 0.536
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0880    0.68175 0.968 0.000 0.000 0.000 0.032
#> E6446572-BFA9-4018-89B3-7E4519EBE072     5  0.4644    0.20967 0.460 0.000 0.012 0.000 0.528
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000    0.84781 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.5293   -0.14546 0.492 0.000 0.048 0.000 0.460
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2645    0.72734 0.044 0.888 0.068 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4794    0.57117 0.000 0.032 0.624 0.000 0.344
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1121    0.73930 0.000 0.956 0.044 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     5  0.4383    0.27978 0.424 0.000 0.004 0.000 0.572
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5283    0.26166 0.572 0.384 0.032 0.000 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.6036    0.16125 0.432 0.000 0.452 0.000 0.116
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2230    0.64812 0.884 0.000 0.000 0.000 0.116

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.3208    0.64200 0.084 0.044 0.000 0.000 0.848 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2294    0.70699 0.036 0.072 0.892 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.3221    0.53671 0.000 0.000 0.000 0.736 0.000 0.264
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4752    0.55868 0.000 0.676 0.000 0.140 0.184 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.3371    0.54513 0.708 0.000 0.292 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4260    0.67853 0.004 0.744 0.136 0.000 0.000 0.116
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3351    0.62821 0.712 0.000 0.000 0.000 0.000 0.288
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.5599    0.59877 0.168 0.096 0.656 0.000 0.000 0.080
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.3584    0.48552 0.688 0.000 0.308 0.000 0.004 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3062    0.84600 0.000 0.144 0.000 0.000 0.824 0.032
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3376    0.67619 0.764 0.000 0.016 0.000 0.000 0.220
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.3219    0.62275 0.000 0.792 0.004 0.012 0.192 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4959    0.53429 0.692 0.028 0.000 0.000 0.092 0.188
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1007    0.83621 0.000 0.000 0.000 0.956 0.000 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3532    0.66696 0.796 0.000 0.140 0.000 0.000 0.064
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.6262    0.39845 0.000 0.120 0.000 0.312 0.512 0.056
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.3876    0.62859 0.000 0.120 0.000 0.772 0.108 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.2597    0.86865 0.000 0.176 0.000 0.000 0.824 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.6092    0.03135 0.016 0.000 0.440 0.380 0.164 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2664    0.63256 0.000 0.816 0.000 0.000 0.184 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.4111    0.52989 0.084 0.000 0.000 0.000 0.176 0.740
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.4845    0.57542 0.000 0.328 0.004 0.000 0.604 0.064
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.3482    0.45930 0.000 0.000 0.000 0.316 0.000 0.684
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.2597    0.86865 0.000 0.176 0.000 0.000 0.824 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.4493    0.47160 0.596 0.000 0.364 0.000 0.000 0.040
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.2703    0.59444 0.172 0.000 0.004 0.000 0.000 0.824
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4785    0.61910 0.664 0.000 0.120 0.000 0.000 0.216
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#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1007    0.71228 0.044 0.000 0.956 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1806    0.67127 0.908 0.000 0.004 0.000 0.000 0.088
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.3915    0.05714 0.584 0.000 0.412 0.000 0.000 0.004
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.1075    0.71239 0.048 0.000 0.952 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     6  0.5633    0.11025 0.148 0.000 0.412 0.000 0.000 0.440
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.3865    0.68567 0.752 0.000 0.056 0.000 0.000 0.192
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     6  0.3774    0.18325 0.408 0.000 0.000 0.000 0.000 0.592
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.2595    0.67857 0.004 0.836 0.000 0.160 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.5326    0.59589 0.016 0.640 0.056 0.024 0.000 0.264
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.3159    0.66144 0.832 0.000 0.068 0.000 0.000 0.100
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.2706    0.69139 0.036 0.104 0.860 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.5261    0.26496 0.460 0.000 0.096 0.000 0.000 0.444
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.2945    0.86017 0.000 0.156 0.000 0.020 0.824 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1411    0.74001 0.000 0.936 0.004 0.000 0.000 0.060
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.0632    0.64178 0.000 0.000 0.024 0.000 0.000 0.976
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.3614    0.67766 0.752 0.000 0.028 0.000 0.000 0.220
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.3782    0.20269 0.412 0.000 0.588 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.0692    0.63714 0.020 0.000 0.004 0.000 0.000 0.976
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     6  0.5583    0.09177 0.140 0.000 0.412 0.000 0.000 0.448
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6544    0.62739 0.080 0.636 0.004 0.092 0.076 0.112
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.0632    0.64178 0.000 0.000 0.024 0.000 0.000 0.976
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.5729    0.30742 0.004 0.252 0.000 0.540 0.204 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.0632    0.64067 0.000 0.000 0.000 0.024 0.000 0.976
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.1908    0.62681 0.004 0.000 0.096 0.000 0.000 0.900
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.5029   -0.01460 0.524 0.000 0.400 0.000 0.000 0.076
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6  0.6782    0.13036 0.320 0.000 0.068 0.000 0.176 0.436
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.3073    0.64163 0.840 0.000 0.080 0.000 0.000 0.080
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3789    0.38893 0.000 0.584 0.000 0.416 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     4  0.7989    0.14804 0.136 0.168 0.004 0.392 0.036 0.264
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.1714    0.70962 0.000 0.908 0.092 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.2996    0.60017 0.144 0.016 0.000 0.008 0.000 0.832
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.2320    0.61976 0.004 0.000 0.132 0.000 0.000 0.864
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.3620    0.22129 0.352 0.000 0.000 0.000 0.000 0.648
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0865    0.71145 0.036 0.000 0.964 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     6  0.4625    0.15072 0.032 0.424 0.004 0.000 0.000 0.540
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3492    0.70320 0.000 0.788 0.004 0.000 0.032 0.176
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0632    0.64067 0.000 0.000 0.000 0.024 0.000 0.976
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.6023    0.43522 0.000 0.108 0.000 0.608 0.192 0.092
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.3351    0.55038 0.712 0.000 0.288 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3514    0.67386 0.752 0.000 0.020 0.000 0.000 0.228
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1908    0.65578 0.916 0.000 0.028 0.000 0.000 0.056
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.3244    0.56892 0.732 0.000 0.268 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3219    0.62275 0.000 0.792 0.004 0.012 0.192 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3684    0.53352 0.628 0.000 0.000 0.000 0.000 0.372
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3670    0.60762 0.736 0.000 0.024 0.000 0.000 0.240
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.2527    0.59705 0.168 0.000 0.000 0.000 0.000 0.832
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3838    0.37283 0.552 0.000 0.000 0.000 0.000 0.448
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000    0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     6  0.3961   -0.08717 0.440 0.000 0.004 0.000 0.000 0.556
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5360    0.66388 0.012 0.680 0.088 0.000 0.036 0.184
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0937    0.71170 0.040 0.000 0.960 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.3979   -0.04608 0.000 0.540 0.004 0.000 0.456 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3446    0.60684 0.692 0.000 0.000 0.000 0.000 0.308
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.4802    0.49283 0.020 0.584 0.028 0.000 0.000 0.368
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.5633    0.08124 0.148 0.000 0.412 0.000 0.000 0.440
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.1663    0.61709 0.088 0.000 0.000 0.000 0.000 0.912

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 17541 rows and 500 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           0.961       0.977         0.4779 0.518   0.518
#> 3 3 0.564           0.710       0.837         0.2020 0.965   0.933
#> 4 4 0.543           0.592       0.767         0.1596 0.788   0.581
#> 5 5 0.559           0.599       0.742         0.1161 0.840   0.559
#> 6 6 0.593           0.559       0.703         0.0569 0.941   0.790

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.1184     0.9714 0.016 0.984
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.1414     0.9699 0.020 0.980
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.0938     0.9829 0.988 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.1184     0.9685 0.016 0.984
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1184     0.9714 0.016 0.984
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.1184     0.9851 0.984 0.016
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9988     0.0799 0.480 0.520
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0376     0.9875 0.996 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0000     0.9878 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.1184     0.9840 0.984 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.1184     0.9714 0.016 0.984
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0672     0.9868 0.992 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1184     0.9714 0.016 0.984
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0376     0.9875 0.996 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.2043     0.9522 0.032 0.968
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0376     0.9875 0.996 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.1414     0.9699 0.020 0.980
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0376     0.9655 0.004 0.996
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1184     0.9714 0.016 0.984
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.1184     0.9714 0.016 0.984
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0672     0.9642 0.008 0.992
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0938     0.9702 0.012 0.988
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9878 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1184     0.9714 0.016 0.984
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9878 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.1184     0.9714 0.016 0.984
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.1184     0.9851 0.984 0.016
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0376     0.9875 0.996 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0672     0.9868 0.992 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0672     0.9868 0.992 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0938     0.9829 0.988 0.012
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1184     0.9714 0.016 0.984
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0672     0.9642 0.008 0.992
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9878 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0376     0.9875 0.996 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.1184     0.9714 0.016 0.984
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.7883     0.7179 0.236 0.764
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0938     0.9829 0.988 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9878 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.0672     0.9642 0.008 0.992
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0672     0.9868 0.992 0.008
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.0938     0.9829 0.988 0.012
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.1414     0.9699 0.020 0.980
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0938     0.9702 0.012 0.988
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1184     0.9714 0.016 0.984
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0376     0.9655 0.004 0.996
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     2  0.0672     0.9642 0.008 0.992
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0376     0.9875 0.996 0.004
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0672     0.9868 0.992 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000     0.9878 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.1184     0.9714 0.016 0.984
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0376     0.9875 0.996 0.004
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0376     0.9872 0.996 0.004
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0672     0.9868 0.992 0.008
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0672     0.9868 0.992 0.008
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0376     0.9875 0.996 0.004
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.0938     0.9829 0.988 0.012
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.0938     0.9829 0.988 0.012
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.1414     0.9699 0.020 0.980
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.7602     0.7131 0.780 0.220
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.9878 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9648 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000     0.9878 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.9878 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.0672     0.9850 0.992 0.008
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0376     0.9875 0.996 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.9878 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0376     0.9875 0.996 0.004
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0376     0.9867 0.996 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0938     0.9702 0.012 0.988
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.1414     0.9699 0.020 0.980
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9648 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.1184     0.9714 0.016 0.984
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0672     0.9868 0.992 0.008
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0938     0.9702 0.012 0.988
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.0376     0.9875 0.996 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1  0.0938     0.9829 0.988 0.012
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9878 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0938     0.9702 0.012 0.988
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.1184     0.9685 0.016 0.984
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0376     0.9872 0.996 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0376     0.9875 0.996 0.004
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.1184     0.9714 0.016 0.984
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.1184     0.9714 0.016 0.984
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9878 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0938     0.9829 0.988 0.012
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0938     0.9829 0.988 0.012
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9878 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1184     0.9714 0.016 0.984
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1184     0.9714 0.016 0.984
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.1414     0.9699 0.020 0.980
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0938     0.9829 0.988 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9878 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0376     0.9875 0.996 0.004
#> C075F09E-623C-46ED-B927-889B48F450B3     1  0.0938     0.9829 0.988 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0376     0.9875 0.996 0.004
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0376     0.9875 0.996 0.004
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     1  0.0938     0.9829 0.988 0.012
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0938     0.9829 0.988 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0672     0.9868 0.992 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0376     0.9875 0.996 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0938     0.9702 0.012 0.988
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.8144     0.6985 0.252 0.748
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0376     0.9875 0.996 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.1184     0.9851 0.984 0.016
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0672     0.9868 0.992 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1184     0.9714 0.016 0.984
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0938     0.9702 0.012 0.988
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9878 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0672     0.9868 0.992 0.008
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0938     0.9829 0.988 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9878 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9878 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1184     0.9714 0.016 0.984
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.2423     0.9573 0.040 0.960
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.1414     0.9699 0.020 0.980
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9878 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0938     0.9702 0.012 0.988
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9878 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9878 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0000     0.9878 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     2  0.0672     0.9642 0.008 0.992
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0376     0.9875 0.996 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0376     0.9875 0.996 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.1184     0.9714 0.016 0.984
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.1184     0.9714 0.016 0.984
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3733     0.9215 0.072 0.928
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.9878 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.0672     0.9642 0.008 0.992
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0938     0.9829 0.988 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0376     0.9875 0.996 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0938     0.9846 0.988 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0672     0.9868 0.992 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1184     0.9714 0.016 0.984
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9878 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.1184     0.9714 0.016 0.984
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0938     0.9829 0.988 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0672     0.9868 0.992 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0376     0.9875 0.996 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.1184     0.9851 0.984 0.016
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1184     0.9714 0.016 0.984
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0376     0.9875 0.996 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0672     0.9850 0.992 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9878 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0672     0.9868 0.992 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.1414     0.9699 0.020 0.980
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0376     0.9872 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.1184     0.9685 0.016 0.984
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.1184     0.9817 0.984 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1184     0.9714 0.016 0.984
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0672     0.9868 0.992 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0376     0.9875 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0938     0.9829 0.988 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0672     0.9868 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3941    0.56206 0.156 0.844 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.6252   -0.66356 0.444 0.556 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.5706    0.76664 0.320 0.000 0.680
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.6252   -0.71133 0.444 0.556 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1289    0.72676 0.032 0.968 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4235    0.83435 0.176 0.000 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9658   -0.13911 0.212 0.420 0.368
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.0237    0.87372 0.004 0.000 0.996
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.4504    0.84095 0.196 0.000 0.804
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4842    0.81619 0.224 0.000 0.776
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2959    0.65224 0.100 0.900 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0237    0.87372 0.004 0.000 0.996
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0424    0.74119 0.008 0.992 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.3550    0.86176 0.080 0.024 0.896
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.9813   -0.28284 0.304 0.428 0.268
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0892    0.87453 0.020 0.000 0.980
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.6252   -0.66356 0.444 0.556 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.3551    0.56555 0.132 0.868 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1753    0.71238 0.048 0.952 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0237    0.74147 0.004 0.996 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.3752    0.54292 0.144 0.856 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0237    0.74147 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     3  0.2796    0.86468 0.092 0.000 0.908
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0237    0.74147 0.004 0.996 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.6295    0.73382 0.236 0.036 0.728
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0237    0.74147 0.004 0.996 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4654    0.84382 0.208 0.000 0.792
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.4848    0.83071 0.128 0.036 0.836
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.0424    0.87380 0.008 0.000 0.992
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.0237    0.87372 0.004 0.000 0.996
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4702    0.81868 0.212 0.000 0.788
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0237    0.74147 0.004 0.996 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.6244    0.97866 0.560 0.440 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.0892    0.87479 0.020 0.000 0.980
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.1031    0.87496 0.024 0.000 0.976
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.3879    0.52891 0.152 0.848 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.9059   -0.10011 0.136 0.456 0.408
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.4452    0.84811 0.192 0.000 0.808
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.4504    0.80770 0.196 0.000 0.804
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.6235    0.98260 0.564 0.436 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0237    0.87372 0.004 0.000 0.996
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.2537    0.86516 0.080 0.000 0.920
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0424    0.74075 0.008 0.992 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     3  0.4452    0.81309 0.192 0.000 0.808
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.7980   -0.01756 0.172 0.660 0.168
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.5397    0.76785 0.280 0.000 0.720
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.3619    0.55696 0.136 0.864 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     3  0.2537    0.86445 0.080 0.000 0.920
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.2261    0.86785 0.068 0.000 0.932
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.1529    0.71827 0.040 0.960 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3  0.1031    0.87575 0.024 0.000 0.976
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.1289    0.87596 0.032 0.000 0.968
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0237    0.74012 0.004 0.996 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0892    0.87606 0.020 0.000 0.980
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.2711    0.85384 0.088 0.000 0.912
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#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4745    0.54669 0.080 0.852 0.068
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.1753    0.70335 0.048 0.952 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.1163    0.72665 0.028 0.972 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.4682    0.42756 0.192 0.804 0.004
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.1267    0.73160 0.024 0.972 0.004
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     3  0.3551    0.84791 0.132 0.000 0.868
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     3  0.4605    0.80207 0.204 0.000 0.796
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     3  0.1753    0.87106 0.048 0.000 0.952
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     3  0.2959    0.86028 0.100 0.000 0.900
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.5254    0.77971 0.264 0.000 0.736
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0592    0.73691 0.012 0.988 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.3941    0.56594 0.156 0.844 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0237    0.74147 0.004 0.996 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.3619    0.55696 0.136 0.864 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.6442    0.97747 0.564 0.432 0.004
#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.2261    0.86789 0.068 0.000 0.932
#> D85CB054-7F54-4383-96C0-6C99761B84E7     3  0.0592    0.87368 0.012 0.000 0.988
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     3  0.4291    0.81901 0.180 0.000 0.820
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0424    0.74133 0.008 0.992 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.0592    0.87400 0.012 0.000 0.988
#> 17CA5D73-4384-4645-83F8-587847043DD2     3  0.3267    0.85010 0.116 0.000 0.884
#> 40467950-A95C-4731-AD93-0A128442C837     3  0.2066    0.87033 0.060 0.000 0.940
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     3  0.3038    0.85855 0.104 0.000 0.896
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     3  0.2711    0.86358 0.088 0.000 0.912
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.5397    0.76785 0.280 0.000 0.720
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.5363    0.77472 0.276 0.000 0.724
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.6286   -0.72424 0.464 0.536 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     3  0.8435    0.44924 0.132 0.268 0.600
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     3  0.4121    0.82819 0.168 0.000 0.832
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.3267    0.59817 0.116 0.884 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     3  0.4062    0.83138 0.164 0.000 0.836
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.2448    0.86907 0.076 0.000 0.924
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3267    0.85884 0.116 0.000 0.884
#> A7ECBC06-1332-4278-8723-85DC8351188A     3  0.4235    0.82609 0.176 0.000 0.824
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.2796    0.87604 0.092 0.000 0.908
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.3637    0.85940 0.084 0.024 0.892
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.1643    0.87704 0.044 0.000 0.956
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.1753    0.71571 0.048 0.952 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.9431   -0.17715 0.212 0.496 0.292
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.3983    0.55048 0.144 0.852 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000    0.74121 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.3116    0.85733 0.108 0.000 0.892
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.2496    0.68241 0.068 0.928 0.004
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.2356    0.87257 0.072 0.000 0.928
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.5621    0.76787 0.308 0.000 0.692
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     3  0.4750    0.79928 0.216 0.000 0.784
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0424    0.74075 0.008 0.992 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.6291    0.91314 0.532 0.468 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.0424    0.87416 0.008 0.000 0.992
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.2356    0.86620 0.072 0.000 0.928
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0237    0.74147 0.004 0.996 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.1163    0.72665 0.028 0.972 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.0424    0.87440 0.008 0.000 0.992
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.5327    0.77474 0.272 0.000 0.728
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.4121    0.83764 0.168 0.000 0.832
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3  0.5355    0.80613 0.168 0.032 0.800
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0237    0.74147 0.004 0.996 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0237    0.74147 0.004 0.996 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.6252   -0.66356 0.444 0.556 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.5397    0.76785 0.280 0.000 0.720
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.3340    0.85275 0.120 0.000 0.880
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.1031    0.87537 0.024 0.000 0.976
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.5397    0.76785 0.280 0.000 0.720
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.1031    0.87483 0.024 0.000 0.976
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.3340    0.85926 0.120 0.000 0.880
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.6777    0.73307 0.364 0.020 0.616
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3686    0.85204 0.140 0.000 0.860
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.0237    0.87372 0.004 0.000 0.996
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0237    0.87372 0.004 0.000 0.996
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1753    0.71571 0.048 0.952 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.8665   -0.05712 0.124 0.552 0.324
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.0892    0.87515 0.020 0.000 0.980
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.6341    0.78019 0.312 0.016 0.672
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.1964    0.87136 0.056 0.000 0.944
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1411    0.71958 0.036 0.964 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0424    0.74015 0.008 0.992 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     3  0.4002    0.82962 0.160 0.000 0.840
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0237    0.87372 0.004 0.000 0.996
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.5254    0.78048 0.264 0.000 0.736
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     3  0.2711    0.86109 0.088 0.000 0.912
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.0592    0.87476 0.012 0.000 0.988
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.3551    0.61676 0.132 0.868 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.7841   -0.72434 0.472 0.476 0.052
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.6633   -0.67979 0.444 0.548 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.2959    0.85842 0.100 0.000 0.900
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.3482    0.61026 0.128 0.872 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     3  0.3267    0.85421 0.116 0.000 0.884
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.0424    0.87493 0.008 0.000 0.992
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3412    0.85577 0.124 0.000 0.876
#> 1122039D-5785-4F70-9916-17C585453512     1  0.6442    0.97747 0.564 0.432 0.004
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.2625    0.86735 0.084 0.000 0.916
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.1529    0.87543 0.040 0.000 0.960
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.2165    0.69088 0.064 0.936 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0892    0.73437 0.020 0.980 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5998    0.38663 0.128 0.788 0.084
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.3826    0.84844 0.124 0.008 0.868
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.6442    0.97747 0.564 0.432 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3619    0.84718 0.136 0.000 0.864
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3  0.0592    0.87400 0.012 0.000 0.988
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.5178    0.78529 0.256 0.000 0.744
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.3340    0.85292 0.120 0.000 0.880
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0424    0.73856 0.008 0.992 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.4555    0.80546 0.200 0.000 0.800
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.1529    0.71754 0.040 0.960 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.5254    0.78015 0.264 0.000 0.736
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.0237    0.87372 0.004 0.000 0.996
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.1643    0.87640 0.044 0.000 0.956
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2537    0.86989 0.080 0.000 0.920
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0592    0.73691 0.012 0.988 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.0424    0.87403 0.008 0.000 0.992
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.1643    0.87540 0.044 0.000 0.956
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.1031    0.87514 0.024 0.000 0.976
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.0592    0.87427 0.012 0.000 0.988
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.6252   -0.66356 0.444 0.556 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0424    0.87416 0.008 0.000 0.992
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0592    0.73691 0.012 0.988 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.6667    0.72885 0.368 0.016 0.616
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0424    0.73856 0.008 0.992 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.0747    0.87363 0.016 0.000 0.984
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.5696    0.80488 0.136 0.064 0.800
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4121    0.84055 0.168 0.000 0.832
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.2537    0.86536 0.080 0.000 0.920

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5338    0.69105 0.140 0.768 0.016 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4804    0.75089 0.016 0.276 0.000 0.708
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2216    0.61337 0.092 0.000 0.908 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4364    0.79994 0.016 0.220 0.000 0.764
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1452    0.87014 0.008 0.956 0.000 0.036
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4836    0.35982 0.320 0.000 0.672 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.9177   -0.06676 0.240 0.340 0.344 0.076
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.5085    0.59119 0.616 0.000 0.376 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3569    0.56770 0.196 0.000 0.804 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2647    0.60421 0.120 0.000 0.880 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2662    0.84278 0.000 0.900 0.016 0.084
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5150    0.56423 0.596 0.000 0.396 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1118    0.87152 0.000 0.964 0.000 0.036
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5228    0.54171 0.664 0.000 0.312 0.024
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.8023    0.49814 0.284 0.272 0.008 0.436
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.5290   -0.25086 0.476 0.000 0.516 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.5426    0.79765 0.060 0.232 0.000 0.708
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4053    0.68121 0.000 0.768 0.004 0.228
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2665    0.84616 0.008 0.900 0.004 0.088
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.1109    0.87237 0.000 0.968 0.004 0.028
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.4303    0.69236 0.008 0.768 0.004 0.220
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0592    0.87502 0.000 0.984 0.000 0.016
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.4019    0.64283 0.792 0.000 0.196 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0592    0.87369 0.000 0.984 0.000 0.016
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.4352    0.56122 0.816 0.000 0.080 0.104
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0592    0.87369 0.000 0.984 0.000 0.016
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4564    0.40915 0.328 0.000 0.672 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4685    0.60355 0.784 0.000 0.156 0.060
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.5085    0.59135 0.616 0.000 0.376 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.5150    0.56350 0.596 0.000 0.396 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2281    0.63020 0.096 0.000 0.904 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1109    0.87237 0.000 0.968 0.004 0.028
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.2928    0.88246 0.052 0.052 0.000 0.896
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.5112    0.51501 0.560 0.000 0.436 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.5229   -0.02991 0.428 0.000 0.564 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.6529    0.29393 0.088 0.600 0.004 0.308
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.6702    0.12840 0.572 0.344 0.012 0.072
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#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.1356    0.87231 0.008 0.960 0.000 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2675    0.59905 0.100 0.000 0.892 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0707    0.87361 0.000 0.980 0.000 0.020
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4917    0.61912 0.656 0.000 0.336 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4475    0.63849 0.748 0.004 0.240 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4406    0.42756 0.300 0.000 0.700 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4262    0.65061 0.756 0.000 0.236 0.008

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4631    0.73163 0.000 0.728 0.224 0.024 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.2806    0.83338 0.000 0.152 0.000 0.844 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4840    0.79360 0.320 0.000 0.640 0.000 0.040
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.2358    0.85686 0.000 0.104 0.000 0.888 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2962    0.84621 0.000 0.868 0.084 0.048 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.3242    0.39524 0.816 0.000 0.172 0.000 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     5  0.8448    0.04185 0.076 0.328 0.240 0.024 0.332
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2583    0.63664 0.864 0.000 0.004 0.000 0.132
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.5645    0.74128 0.376 0.000 0.540 0.000 0.084
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.5234    0.64041 0.460 0.000 0.496 0.000 0.044
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2727    0.83964 0.000 0.868 0.116 0.016 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2124    0.64470 0.900 0.000 0.004 0.000 0.096
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2362    0.84910 0.000 0.900 0.076 0.024 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5583    0.31303 0.572 0.000 0.072 0.004 0.352
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.6248    0.20190 0.000 0.084 0.020 0.456 0.440
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0609    0.58195 0.980 0.000 0.020 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.2806    0.83338 0.000 0.152 0.000 0.844 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4712    0.72849 0.000 0.736 0.080 0.180 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.3848    0.82016 0.000 0.816 0.076 0.104 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2069    0.84904 0.000 0.912 0.076 0.012 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.3895    0.72275 0.000 0.796 0.032 0.164 0.008
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2233    0.84890 0.000 0.904 0.080 0.016 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.3409    0.67655 0.160 0.000 0.024 0.000 0.816
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.85284 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     5  0.4041    0.70652 0.064 0.000 0.020 0.100 0.816
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0162    0.85282 0.000 0.996 0.000 0.000 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.5240    0.19218 0.656 0.000 0.252 0.000 0.092
#> EE97212E-8D5D-4548-8DD2-317049601FDB     5  0.3755    0.68889 0.140 0.000 0.032 0.012 0.816
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3427    0.61261 0.796 0.000 0.012 0.000 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2488    0.64578 0.872 0.000 0.004 0.000 0.124
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4713    0.71034 0.440 0.000 0.544 0.000 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2069    0.84904 0.000 0.912 0.076 0.012 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2824    0.64825 0.864 0.000 0.020 0.000 0.116
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1753    0.58220 0.936 0.000 0.032 0.000 0.032
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5693    0.41836 0.000 0.572 0.028 0.360 0.040
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     5  0.6169    0.36923 0.016 0.236 0.036 0.068 0.644
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6778   -0.05095 0.380 0.000 0.340 0.000 0.280
#> A84EA172-9823-40E9-BC22-C882725DD1C8     5  0.4288    0.71146 0.088 0.000 0.020 0.092 0.800
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2843    0.63142 0.848 0.000 0.008 0.000 0.144
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4953    0.20491 0.532 0.000 0.028 0.000 0.440
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1372    0.85123 0.000 0.956 0.024 0.016 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293     5  0.4781    0.63568 0.112 0.000 0.160 0.000 0.728
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.7607   -0.02865 0.000 0.392 0.048 0.300 0.260
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4278    0.72064 0.452 0.000 0.548 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.3693    0.72839 0.000 0.808 0.032 0.156 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E     5  0.3994    0.64709 0.188 0.000 0.040 0.000 0.772
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4010    0.58030 0.760 0.000 0.032 0.000 0.208
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.2597    0.84884 0.000 0.884 0.092 0.024 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.5454    0.29984 0.532 0.000 0.064 0.000 0.404
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3184    0.61897 0.852 0.000 0.048 0.000 0.100
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.2362    0.84994 0.000 0.900 0.076 0.024 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.1956    0.53704 0.916 0.000 0.076 0.000 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     5  0.5415    0.04323 0.464 0.000 0.016 0.028 0.492
#> 311D089C-33F1-4722-9118-F56427C5C128     5  0.3731    0.70714 0.096 0.004 0.020 0.040 0.840
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2206    0.85678 0.000 0.912 0.068 0.016 0.004
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.3689    0.83116 0.000 0.828 0.076 0.092 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.2179    0.50792 0.896 0.000 0.100 0.000 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.3180    0.83973 0.000 0.856 0.076 0.068 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.3171    0.61512 0.816 0.000 0.008 0.000 0.176
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0404    0.85227 0.000 0.988 0.000 0.012 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     5  0.3320    0.70555 0.124 0.000 0.016 0.016 0.844
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.4016    0.51622 0.716 0.000 0.012 0.000 0.272
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6510    0.25217 0.488 0.000 0.260 0.000 0.252
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.4546    0.70517 0.460 0.000 0.532 0.000 0.008
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.3416    0.82820 0.000 0.840 0.124 0.020 0.016
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     5  0.6190    0.47972 0.236 0.000 0.172 0.008 0.584
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5233    0.48149 0.684 0.000 0.168 0.000 0.148
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     5  0.4990    0.62899 0.232 0.000 0.012 0.056 0.700
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.2362    0.84994 0.000 0.900 0.076 0.024 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.8055    0.17079 0.040 0.392 0.228 0.028 0.312
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0404    0.85308 0.000 0.988 0.000 0.012 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0324    0.85285 0.000 0.992 0.000 0.004 0.004
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.4036    0.46143 0.788 0.000 0.144 0.000 0.068
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.4307   -0.64541 0.500 0.000 0.500 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.5858    0.63817 0.044 0.696 0.040 0.032 0.188
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.4538    0.71157 0.452 0.000 0.540 0.000 0.008
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.5452    0.75934 0.292 0.000 0.616 0.000 0.092
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     5  0.4770    0.47878 0.320 0.000 0.036 0.000 0.644
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0162    0.85282 0.000 0.996 0.000 0.000 0.004
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     5  0.4275    0.65848 0.228 0.000 0.008 0.024 0.740
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.6557    0.53771 0.340 0.000 0.448 0.000 0.212
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     5  0.3622    0.70734 0.056 0.000 0.000 0.124 0.820
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.1461    0.85076 0.000 0.952 0.028 0.016 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     5  0.4377    0.71181 0.088 0.000 0.024 0.092 0.796
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4264    0.78789 0.376 0.000 0.620 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.4760    0.29711 0.564 0.000 0.020 0.000 0.416
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.2269    0.84871 0.000 0.920 0.028 0.032 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.4329    0.49856 0.672 0.000 0.016 0.000 0.312
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.1981    0.55335 0.920 0.000 0.064 0.000 0.016
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     5  0.4466    0.63535 0.232 0.000 0.032 0.008 0.728
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.2006    0.85027 0.000 0.916 0.072 0.012 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.2848    0.63204 0.840 0.000 0.004 0.000 0.156
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.3416    0.82820 0.000 0.840 0.124 0.020 0.016
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2446    0.85358 0.000 0.900 0.044 0.056 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.2351    0.84761 0.000 0.896 0.088 0.016 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0865    0.85647 0.000 0.972 0.024 0.004 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     5  0.5188    0.15249 0.416 0.000 0.044 0.000 0.540
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.4627    0.22746 0.544 0.000 0.012 0.000 0.444
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.6196   -0.00715 0.468 0.000 0.096 0.012 0.424
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0451    0.85237 0.000 0.988 0.000 0.008 0.004
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.6263    0.38728 0.540 0.000 0.216 0.000 0.244
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.5854    0.65196 0.252 0.000 0.596 0.000 0.152
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.7236    0.27066 0.084 0.000 0.472 0.104 0.340
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.1403    0.59621 0.952 0.000 0.024 0.000 0.024
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.2069    0.84904 0.000 0.912 0.076 0.012 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     5  0.4759    0.62542 0.080 0.004 0.168 0.004 0.744
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.5661    0.56580 0.008 0.656 0.020 0.060 0.256
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.2806    0.85385 0.000 0.888 0.052 0.052 0.008
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.3170    0.84804 0.000 0.856 0.104 0.036 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.3304    0.61907 0.816 0.000 0.016 0.000 0.168
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.3536    0.83111 0.000 0.832 0.084 0.084 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000    0.85284 0.000 1.000 0.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.2074    0.57401 0.920 0.000 0.036 0.000 0.044
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0404    0.85227 0.000 0.988 0.000 0.012 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.4392    0.78685 0.380 0.000 0.612 0.000 0.008
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     5  0.6043    0.47025 0.252 0.000 0.176 0.000 0.572
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.6131    0.04752 0.536 0.000 0.308 0.000 0.156
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     5  0.5130    0.68712 0.168 0.000 0.020 0.088 0.724
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.3170    0.84728 0.000 0.856 0.104 0.036 0.004
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     3  0.6374    0.08242 0.300 0.000 0.504 0.000 0.196
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.1943    0.85394 0.000 0.924 0.056 0.020 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     4  0.2100    0.89402 0.000 0.048 0.012 0.924 0.016
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     5  0.6789    0.06911 0.020 0.368 0.036 0.068 0.508
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.4295    0.54654 0.740 0.000 0.044 0.000 0.216
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     5  0.4902    0.07493 0.460 0.000 0.012 0.008 0.520
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     2  0.5036    0.08530 0.000 0.516 0.032 0.452 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.1831    0.63825 0.920 0.000 0.004 0.000 0.076
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.2172    0.84874 0.000 0.908 0.076 0.016 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  0.6596   -0.21176 0.456 0.000 0.308 0.000 0.236
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.1818    0.60315 0.932 0.000 0.024 0.000 0.044
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.4182    0.36221 0.600 0.000 0.000 0.000 0.400
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3  0.4679    0.79405 0.316 0.000 0.652 0.000 0.032
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.1673    0.84723 0.000 0.944 0.008 0.016 0.032
#> CBEFE77E-A0EB-457D-A145-763654236EBB     5  0.3924    0.71561 0.120 0.000 0.004 0.068 0.808
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#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0404    0.85498 0.000 0.988 0.012 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.2325    0.85163 0.000 0.904 0.028 0.068 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4416    0.42781 0.632 0.000 0.012 0.000 0.356
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.5048    0.57162 0.476 0.000 0.492 0.000 0.032
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6175    0.05919 0.508 0.000 0.344 0.000 0.148
#> 887E7408-C7D7-420F-A763-0EE70A316D17     5  0.3464    0.71724 0.096 0.000 0.000 0.068 0.836
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0162    0.85370 0.000 0.996 0.004 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1270    0.85539 0.000 0.948 0.052 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.2583    0.85024 0.000 0.132 0.000 0.864 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4436    0.77112 0.396 0.000 0.596 0.000 0.008
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     5  0.3276    0.69497 0.132 0.000 0.032 0.000 0.836
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.2067    0.59163 0.920 0.000 0.032 0.000 0.048
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4457    0.79267 0.368 0.000 0.620 0.000 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.2873    0.63623 0.856 0.000 0.016 0.000 0.128
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.3152    0.48297 0.840 0.000 0.136 0.000 0.024
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.5434    0.73695 0.232 0.000 0.648 0.000 0.120
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4840    0.24428 0.688 0.000 0.248 0.000 0.064
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.2233    0.64518 0.892 0.000 0.004 0.000 0.104
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.2719    0.63008 0.852 0.000 0.004 0.000 0.144
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.3090    0.84827 0.000 0.860 0.104 0.032 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.8372    0.06924 0.088 0.404 0.196 0.024 0.288
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.1956    0.62686 0.916 0.000 0.008 0.000 0.076
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.5911   -0.40888 0.488 0.000 0.408 0.000 0.104
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4066    0.43960 0.672 0.000 0.004 0.000 0.324
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.2172    0.84874 0.000 0.908 0.076 0.016 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1653    0.85021 0.000 0.944 0.028 0.024 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     5  0.4683    0.70370 0.124 0.000 0.020 0.088 0.768
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1205    0.62368 0.956 0.000 0.004 0.000 0.040
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.4450   -0.58957 0.508 0.000 0.488 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     5  0.5640    0.58533 0.260 0.000 0.020 0.076 0.644
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.3409    0.62781 0.816 0.000 0.024 0.000 0.160
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.3482    0.84222 0.000 0.844 0.096 0.052 0.008
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.4104    0.71613 0.008 0.020 0.012 0.788 0.172
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.3197    0.83116 0.000 0.152 0.012 0.832 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     5  0.5322    0.67293 0.180 0.000 0.024 0.088 0.708
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.3375    0.84266 0.000 0.852 0.096 0.040 0.012
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     5  0.4737    0.70338 0.136 0.000 0.024 0.076 0.764
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4201    0.30145 0.592 0.000 0.000 0.000 0.408
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2674    0.49447 0.868 0.000 0.120 0.000 0.012
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0771    0.90301 0.000 0.020 0.000 0.976 0.004
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4841    0.52741 0.708 0.000 0.084 0.000 0.208
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2193    0.55838 0.912 0.000 0.060 0.000 0.028
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.5119    0.61177 0.000 0.656 0.060 0.280 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.2300    0.85645 0.000 0.908 0.052 0.040 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.6135    0.61558 0.016 0.660 0.096 0.028 0.200
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     5  0.3058    0.69598 0.096 0.000 0.044 0.000 0.860
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0671    0.90284 0.000 0.016 0.000 0.980 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.6436    0.29474 0.504 0.000 0.264 0.000 0.232
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4181    0.54446 0.712 0.000 0.020 0.000 0.268
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.4446   -0.59782 0.520 0.000 0.476 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     5  0.4949    0.51331 0.296 0.000 0.044 0.004 0.656
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2325    0.85599 0.000 0.904 0.068 0.028 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     5  0.4342    0.71187 0.092 0.000 0.020 0.092 0.796
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2813    0.84616 0.000 0.876 0.084 0.040 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4101   -0.08482 0.664 0.000 0.332 0.000 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2612    0.64269 0.868 0.000 0.008 0.000 0.124
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3527    0.61729 0.828 0.000 0.056 0.000 0.116
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.1768    0.53231 0.924 0.000 0.072 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2813    0.84741 0.000 0.876 0.084 0.040 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4206    0.54346 0.708 0.000 0.020 0.000 0.272
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5766    0.51770 0.616 0.000 0.164 0.000 0.220
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.5415    0.33361 0.552 0.000 0.064 0.000 0.384
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3398    0.58041 0.780 0.000 0.004 0.000 0.216
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.2763    0.83715 0.000 0.148 0.000 0.848 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3966    0.44773 0.664 0.000 0.000 0.000 0.336
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0854    0.85410 0.000 0.976 0.004 0.012 0.008
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.5312    0.75456 0.248 0.000 0.652 0.000 0.100
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0290    0.85229 0.000 0.992 0.000 0.008 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3355    0.60324 0.804 0.000 0.012 0.000 0.184
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     5  0.3722    0.68341 0.144 0.000 0.040 0.004 0.812
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.6300    0.38150 0.420 0.000 0.428 0.000 0.152
#> 2785594A-571A-46B4-A901-CB9C62DC6174     5  0.4341    0.47302 0.364 0.000 0.000 0.008 0.628

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4 p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3819    0.67702 0.000 0.652 0.000 0.008 NA 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.2954    0.83104 0.000 0.048 0.000 0.852 NA 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2444    0.71221 0.068 0.000 0.892 0.000 NA 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.3090    0.81071 0.000 0.088 0.000 0.848 NA 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4464    0.71866 0.000 0.676 0.000 0.056 NA 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.4658    0.15332 0.580 0.000 0.376 0.000 NA 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.8389    0.17565 0.032 0.380 0.104 0.036 NA 0.224
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0820    0.63595 0.972 0.000 0.016 0.000 NA 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3460    0.70224 0.084 0.000 0.828 0.000 NA 0.072
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4063    0.62307 0.252 0.000 0.712 0.000 NA 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3653    0.70115 0.000 0.692 0.000 0.008 NA 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1155    0.63057 0.956 0.000 0.036 0.000 NA 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.3586    0.74200 0.000 0.756 0.000 0.028 NA 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5953    0.28168 0.592 0.004 0.072 0.000 NA 0.256
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.6075    0.21216 0.000 0.068 0.000 0.312 NA 0.536
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.1970    0.60645 0.900 0.000 0.092 0.000 NA 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.2954    0.83104 0.000 0.048 0.000 0.852 NA 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.5065    0.61806 0.000 0.636 0.000 0.172 NA 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5195    0.58791 0.000 0.540 0.000 0.084 NA 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2805    0.75453 0.000 0.812 0.000 0.004 NA 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.4468    0.59311 0.000 0.732 0.004 0.148 NA 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3595    0.73379 0.000 0.704 0.000 0.008 NA 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.3755    0.65266 0.172 0.000 0.032 0.000 NA 0.780
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0547    0.76549 0.000 0.980 0.000 0.000 NA 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.2890    0.70914 0.096 0.000 0.000 0.032 NA 0.860
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.1204    0.75660 0.000 0.944 0.000 0.000 NA 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.5869    0.37038 0.568 0.000 0.292 0.000 NA 0.080
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.4540    0.64888 0.216 0.000 0.004 0.000 NA 0.696
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2602    0.63769 0.884 0.000 0.024 0.000 NA 0.072
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1285    0.62751 0.944 0.000 0.052 0.000 NA 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4329    0.66703 0.232 0.000 0.712 0.000 NA 0.040
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2871    0.75069 0.000 0.804 0.000 0.004 NA 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0405    0.84833 0.000 0.008 0.000 0.988 NA 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2544    0.60834 0.864 0.000 0.120 0.000 NA 0.012
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3269    0.50870 0.792 0.000 0.184 0.000 NA 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.7129    0.03678 0.000 0.336 0.000 0.356 NA 0.084
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     6  0.5927    0.31585 0.004 0.260 0.000 0.008 NA 0.536
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.6463    0.13035 0.336 0.000 0.436 0.000 NA 0.196
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2933    0.70805 0.108 0.000 0.000 0.032 NA 0.852
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0260    0.84842 0.000 0.008 0.000 0.992 NA 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.1546    0.63956 0.944 0.000 0.020 0.000 NA 0.020
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4566    0.18907 0.596 0.000 0.004 0.000 NA 0.364
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1714    0.76498 0.000 0.908 0.000 0.000 NA 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.4945    0.57954 0.092 0.000 0.068 0.000 NA 0.724
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     6  0.7677   -0.16873 0.000 0.276 0.000 0.216 NA 0.296
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3298    0.68571 0.236 0.000 0.756 0.000 NA 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.4568    0.57738 0.000 0.724 0.012 0.152 NA 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.4476    0.60180 0.268 0.000 0.008 0.000 NA 0.676
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3023    0.60295 0.864 0.000 0.052 0.000 NA 0.028
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.3867    0.70757 0.000 0.660 0.000 0.012 NA 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.6325    0.24461 0.512 0.000 0.152 0.000 NA 0.288
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3645    0.55638 0.784 0.000 0.176 0.000 NA 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.2915    0.75539 0.000 0.808 0.000 0.008 NA 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.3509    0.43460 0.744 0.000 0.240 0.000 NA 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.5025    0.34974 0.408 0.000 0.000 0.012 NA 0.532
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.3631    0.63761 0.036 0.004 0.012 0.008 NA 0.820
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2793    0.76686 0.000 0.800 0.000 0.000 NA 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.5714    0.61332 0.000 0.560 0.000 0.160 NA 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.3979    0.38640 0.708 0.000 0.256 0.000 NA 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.4546    0.71102 0.000 0.692 0.000 0.104 NA 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0993    0.63840 0.964 0.000 0.012 0.000 NA 0.024
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0865    0.76321 0.000 0.964 0.000 0.000 NA 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.3456    0.68550 0.172 0.000 0.000 0.000 NA 0.788
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.2152    0.61802 0.904 0.000 0.004 0.000 NA 0.068
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6650    0.20628 0.448 0.000 0.320 0.000 NA 0.176
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.3489    0.64057 0.288 0.000 0.708 0.000 NA 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.3874    0.68772 0.000 0.636 0.000 0.008 NA 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     6  0.6966    0.29601 0.292 0.004 0.068 0.000 NA 0.436
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5700    0.33732 0.588 0.000 0.276 0.000 NA 0.096
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.5515    0.55702 0.280 0.000 0.036 0.020 NA 0.620
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.3230    0.74367 0.000 0.776 0.000 0.012 NA 0.000
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#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3001    0.70245 0.060 0.000 0.868 0.004 NA 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0713    0.76351 0.000 0.972 0.000 0.000 NA 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0909    0.63749 0.968 0.000 0.012 0.000 NA 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.4681    0.63326 0.232 0.000 0.000 0.000 NA 0.668
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5858    0.41387 0.320 0.000 0.544 0.000 NA 0.096
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.3868    0.25051 0.496 0.000 0.000 0.000 NA 0.504

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)

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 17541 rows and 500 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 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-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 0.673           0.871       0.935         0.5000 0.500   0.500
#> 3 3 0.723           0.808       0.910         0.3263 0.694   0.463
#> 4 4 0.536           0.593       0.787         0.0796 0.742   0.406
#> 5 5 0.587           0.559       0.774         0.0877 0.873   0.591
#> 6 6 0.660           0.531       0.759         0.0384 0.885   0.565

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9282 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.1843     0.9190 0.972 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.1843     0.9246 0.028 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.9970     0.2025 0.468 0.532
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.9970     0.0458 0.532 0.468
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.5629     0.8367 0.132 0.868
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.1633     0.9257 0.024 0.976
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1414     0.9255 0.980 0.020
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.6343     0.8272 0.160 0.840
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.1843     0.9246 0.028 0.972
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0376     0.9279 0.004 0.996
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5178     0.8612 0.884 0.116
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.6148     0.8277 0.152 0.848
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0376     0.9307 0.996 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0938     0.9268 0.988 0.012
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.7453     0.7624 0.788 0.212
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.1843     0.9190 0.972 0.028
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0672     0.9273 0.008 0.992
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.6531     0.8112 0.168 0.832
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9282 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000     0.9282 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1184     0.9249 0.016 0.984
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9311 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0376     0.9279 0.004 0.996
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9311 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9282 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.2236     0.9211 0.036 0.964
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1633     0.9212 0.976 0.024
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.5178     0.8612 0.884 0.116
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1414     0.9255 0.980 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.3274     0.9041 0.940 0.060
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9282 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.9850     0.3275 0.428 0.572
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1184     0.9271 0.984 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.9732     0.3964 0.596 0.404
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.1843     0.9190 0.972 0.028
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.1414     0.9234 0.980 0.020
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0938     0.9281 0.988 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9311 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.6048     0.8316 0.148 0.852
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.1414     0.9255 0.980 0.020
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9311 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9282 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9311 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.1843     0.9190 0.972 0.028
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.1843     0.9246 0.028 0.972
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000     0.9282 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.1184     0.9250 0.984 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.9248     0.5499 0.660 0.340
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.5842     0.8394 0.140 0.860
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0376     0.9304 0.996 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.6148     0.8285 0.848 0.152
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0938     0.9262 0.012 0.988
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.9896     0.2916 0.560 0.440
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9311 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.1414     0.9231 0.980 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9282 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.1843     0.9190 0.972 0.028
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.2043     0.9229 0.032 0.968
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.6531     0.8112 0.168 0.832
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.1184     0.9268 0.984 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.5946     0.8357 0.144 0.856
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.9311 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0376     0.9304 0.996 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6438     0.8214 0.836 0.164
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     2  0.1843     0.9246 0.028 0.972
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.9282 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.9311 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0938     0.9281 0.988 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.9311 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.1184     0.9249 0.016 0.984
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.1184     0.9273 0.016 0.984
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0672     0.9273 0.008 0.992
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.9282 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.1843     0.9246 0.028 0.972
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.7602     0.7054 0.780 0.220
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.2603     0.9163 0.044 0.956
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0000     0.9282 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.6343     0.8224 0.840 0.160
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.1633     0.9257 0.024 0.976
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0000     0.9311 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.9282 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000     0.9311 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.1414     0.9267 0.020 0.980
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0000     0.9311 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9282 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.9311 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.1843     0.9246 0.028 0.972
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000     0.9311 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.4815     0.8722 0.104 0.896
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000     0.9311 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.6247     0.8250 0.844 0.156
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000     0.9311 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.2603     0.9122 0.044 0.956
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.9311 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.0376     0.9279 0.004 0.996
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.6712     0.8028 0.176 0.824
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9282 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.2423     0.9132 0.960 0.040
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.1633     0.9220 0.024 0.976
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0000     0.9311 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.9311 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.3274     0.9104 0.060 0.940
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.9282 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0376     0.9304 0.996 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     2  0.1843     0.9246 0.028 0.972
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.2603     0.9081 0.956 0.044
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.6623     0.8088 0.828 0.172
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0376     0.9279 0.004 0.996
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000     0.9311 1.000 0.000
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#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.7056     0.7590 0.192 0.808
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9311 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1184     0.9271 0.984 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.8713     0.6396 0.292 0.708
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.1414     0.9231 0.980 0.020
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.1843     0.9190 0.972 0.028
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9311 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.6973     0.7892 0.188 0.812
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9311 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9311 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.6801     0.8010 0.820 0.180
#> 1122039D-5785-4F70-9916-17C585453512     2  0.4431     0.8800 0.092 0.908
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2948     0.9092 0.948 0.052
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.7883     0.7301 0.764 0.236
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.5629     0.8466 0.132 0.868
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.9087     0.5801 0.324 0.676
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4022     0.8901 0.080 0.920
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.1633     0.9212 0.976 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.7056     0.7993 0.192 0.808
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0376     0.9304 0.996 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9311 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.1843     0.9246 0.028 0.972
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.9311 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.6438     0.8157 0.164 0.836
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9311 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.9754     0.3857 0.408 0.592
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.8386     0.6815 0.732 0.268
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2778     0.9115 0.952 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.6531     0.8130 0.832 0.168
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.2423     0.9186 0.040 0.960
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.6048     0.8315 0.148 0.852
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9311 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2603     0.9140 0.956 0.044
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9311 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9311 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.1843     0.9190 0.972 0.028
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0376     0.9304 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9282 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.1633     0.9257 0.024 0.976
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0938     0.9262 0.012 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0938     0.9285 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1633     0.9212 0.976 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0376     0.9304 0.996 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9311 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     3  0.5178    0.63807 0.000 0.256 0.744
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.2448    0.85606 0.076 0.924 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000    0.87071 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0237    0.89758 0.004 0.996 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0237    0.89758 0.004 0.996 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0592    0.87011 0.012 0.000 0.988
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.7960    0.56419 0.120 0.648 0.232
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1753    0.91082 0.952 0.000 0.048
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3686    0.78278 0.140 0.000 0.860
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000    0.87071 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0747    0.89628 0.000 0.984 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3816    0.82447 0.852 0.000 0.148
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.89844 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2066    0.90379 0.940 0.000 0.060
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6192    0.22483 0.580 0.420 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.4504    0.72368 0.196 0.000 0.804
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.4002    0.78151 0.160 0.840 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0424    0.89801 0.000 0.992 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000    0.89844 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2625    0.85632 0.000 0.916 0.084
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.2959    0.80477 0.000 0.100 0.900
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0237    0.89848 0.000 0.996 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.92532 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1163    0.89168 0.000 0.972 0.028
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0592    0.91928 0.988 0.012 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.6299    0.09451 0.000 0.524 0.476
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0237    0.87088 0.004 0.000 0.996
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0592    0.92081 0.988 0.012 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3192    0.86290 0.888 0.000 0.112
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2066    0.90375 0.940 0.000 0.060
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5678    0.58267 0.684 0.000 0.316
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1411    0.88806 0.000 0.964 0.036
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0592    0.89518 0.012 0.988 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2261    0.89801 0.932 0.000 0.068
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.1529    0.86215 0.040 0.000 0.960
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5327    0.65061 0.272 0.728 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.5882    0.51302 0.348 0.652 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.1753    0.91067 0.952 0.000 0.048
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.92532 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.0237    0.89758 0.004 0.996 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.1411    0.91670 0.964 0.000 0.036
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0592    0.92573 0.988 0.000 0.012
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.2448    0.86428 0.000 0.924 0.076
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.92532 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.6274    0.19782 0.456 0.544 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0237    0.87088 0.004 0.000 0.996
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.2261    0.83065 0.000 0.068 0.932
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0475    0.92559 0.992 0.004 0.004
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.5497    0.58130 0.292 0.000 0.708
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000    0.89844 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0747    0.92513 0.984 0.000 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.6299    0.14013 0.524 0.000 0.476
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0237    0.89848 0.000 0.996 0.004
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.1289    0.86534 0.032 0.000 0.968
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000    0.92532 1.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.1289    0.90495 0.968 0.032 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0892    0.89511 0.000 0.980 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0747    0.89398 0.016 0.984 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0237    0.87088 0.004 0.000 0.996
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.89844 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.1163    0.92052 0.972 0.000 0.028
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.89844 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000    0.92532 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0592    0.92573 0.988 0.000 0.012
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.6280    0.14101 0.460 0.000 0.540
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000    0.87071 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.3551    0.81454 0.000 0.868 0.132
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0237    0.92610 0.996 0.000 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.1163    0.92052 0.972 0.000 0.028
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000    0.92532 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0237    0.89848 0.000 0.996 0.004
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.5138    0.64434 0.000 0.252 0.748
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0892    0.89491 0.000 0.980 0.020
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.5733    0.48581 0.000 0.324 0.676
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000    0.87071 0.000 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     2  0.1289    0.88637 0.032 0.968 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0592    0.87000 0.012 0.000 0.988
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3  0.6169    0.44896 0.004 0.360 0.636
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.5678    0.51371 0.316 0.000 0.684
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0237    0.86948 0.000 0.004 0.996
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0237    0.92610 0.996 0.000 0.004
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.5706    0.52258 0.000 0.680 0.320
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000    0.92532 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0237    0.86948 0.000 0.004 0.996
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0892    0.91380 0.980 0.020 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.2711    0.85511 0.000 0.912 0.088
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0237    0.92375 0.996 0.004 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000    0.87071 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0424    0.92611 0.992 0.000 0.008
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0661    0.89822 0.004 0.988 0.008
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0747    0.92501 0.984 0.000 0.016
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.6235    0.26938 0.564 0.000 0.436
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000    0.92532 1.000 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0237    0.89848 0.000 0.996 0.004
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0747    0.92501 0.984 0.000 0.016
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.1163    0.89168 0.000 0.972 0.028
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000    0.89844 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.5216    0.64131 0.000 0.740 0.260
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     2  0.4452    0.73998 0.192 0.808 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0237    0.89848 0.000 0.996 0.004
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0237    0.92610 0.996 0.000 0.004
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0237    0.92610 0.996 0.000 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3  0.9454    0.18378 0.180 0.388 0.432
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.5810    0.47725 0.000 0.336 0.664
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0424    0.92611 0.992 0.000 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.0237    0.86948 0.000 0.004 0.996
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.7248    0.17375 0.536 0.028 0.436
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.5621    0.53960 0.308 0.000 0.692
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.1163    0.89168 0.000 0.972 0.028
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0237    0.92375 0.996 0.004 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.5327    0.64711 0.272 0.728 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0892    0.89284 0.020 0.980 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0237    0.89848 0.000 0.996 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3  0.5835    0.47772 0.340 0.000 0.660
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0424    0.89644 0.008 0.992 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0424    0.89801 0.000 0.992 0.008
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3  0.0892    0.86852 0.020 0.000 0.980
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0237    0.89848 0.000 0.996 0.004
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.2711    0.83291 0.088 0.000 0.912
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.1482    0.91788 0.968 0.020 0.012
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.2448    0.89402 0.924 0.000 0.076
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000    0.92532 1.000 0.000 0.000
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#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0892    0.92379 0.980 0.000 0.020
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000    0.89844 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.4555    0.72675 0.000 0.800 0.200
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5733    0.55283 0.676 0.000 0.324
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0237    0.86948 0.000 0.004 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0237    0.92610 0.996 0.000 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0424    0.89801 0.000 0.992 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0237    0.89848 0.000 0.996 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000    0.92532 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.5497    0.61262 0.708 0.000 0.292
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0892    0.86850 0.020 0.000 0.980
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.92532 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.2066    0.90370 0.940 0.000 0.060
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000    0.89844 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.2878    0.84779 0.904 0.096 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.5926    0.41260 0.644 0.356 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000    0.92532 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000    0.89844 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000    0.92532 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0237    0.92610 0.996 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3192    0.81335 0.112 0.000 0.888
#> 1122039D-5785-4F70-9916-17C585453512     2  0.4521    0.74651 0.004 0.816 0.180
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3619    0.83883 0.864 0.000 0.136
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.1964    0.85501 0.056 0.000 0.944
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000    0.89844 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000    0.89844 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3038    0.84231 0.000 0.896 0.104
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0237    0.92375 0.996 0.004 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.5850    0.71370 0.040 0.772 0.188
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0424    0.92611 0.992 0.000 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0592    0.92573 0.988 0.000 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000    0.87071 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0237    0.92610 0.996 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000    0.89844 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0237    0.92375 0.996 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000    0.89844 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1860    0.85705 0.052 0.000 0.948
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2066    0.90379 0.940 0.000 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.4887    0.68499 0.228 0.000 0.772
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0237    0.87088 0.004 0.000 0.996
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.89844 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0747    0.92501 0.984 0.000 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2448    0.89230 0.924 0.000 0.076
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0747    0.92501 0.984 0.000 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0237    0.92610 0.996 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.1289    0.88564 0.032 0.968 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0237    0.92610 0.996 0.000 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6111    0.30834 0.000 0.396 0.604
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0237    0.86948 0.000 0.004 0.996
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1031    0.89332 0.000 0.976 0.024
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1031    0.92227 0.976 0.000 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0829    0.92265 0.984 0.012 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0892    0.92379 0.980 0.000 0.020
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0237    0.92610 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4631   0.660504 0.260 0.728 0.004 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4360   0.467561 0.000 0.248 0.008 0.744
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4193   0.697088 0.268 0.000 0.732 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5093   0.280206 0.000 0.348 0.012 0.640
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1940   0.825142 0.000 0.924 0.000 0.076
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.2704   0.653163 0.876 0.000 0.124 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.7427   0.291099 0.044 0.488 0.404 0.064
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2814   0.731241 0.868 0.000 0.000 0.132
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.4933  -0.297154 0.568 0.000 0.432 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2868   0.696680 0.136 0.000 0.864 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2799   0.806345 0.108 0.884 0.000 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2149   0.733110 0.912 0.000 0.000 0.088
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1637   0.829053 0.000 0.940 0.000 0.060
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.3612   0.649051 0.856 0.100 0.000 0.044
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1867   0.607751 0.000 0.072 0.000 0.928
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0804   0.714076 0.980 0.008 0.000 0.012
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4164   0.448468 0.000 0.264 0.000 0.736
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.1389   0.833176 0.000 0.952 0.000 0.048
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1389   0.835317 0.000 0.952 0.000 0.048
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2480   0.815870 0.088 0.904 0.000 0.008
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000   0.695056 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1022   0.837316 0.000 0.968 0.000 0.032
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.4817   0.194325 0.388 0.000 0.000 0.612
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0895   0.840035 0.004 0.976 0.000 0.020
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.1637   0.634257 0.060 0.000 0.000 0.940
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.5473   0.664317 0.084 0.724 0.192 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4999  -0.178949 0.492 0.000 0.508 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.6561   0.409877 0.564 0.092 0.000 0.344
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3808   0.718792 0.812 0.000 0.012 0.176
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2408   0.733483 0.896 0.000 0.000 0.104
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5267   0.701628 0.740 0.000 0.076 0.184
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2048   0.826572 0.064 0.928 0.000 0.008
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4868   0.371824 0.000 0.304 0.012 0.684
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1867   0.732007 0.928 0.000 0.000 0.072
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0992   0.705495 0.976 0.008 0.012 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.3486   0.545980 0.000 0.188 0.000 0.812
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4907   0.323454 0.000 0.580 0.000 0.420
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.6337   0.130625 0.380 0.000 0.068 0.552
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.1716   0.633222 0.064 0.000 0.000 0.936
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.6980   0.215663 0.000 0.132 0.332 0.536
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2216   0.734889 0.908 0.000 0.000 0.092
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3219   0.726058 0.836 0.000 0.000 0.164
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1209   0.839750 0.032 0.964 0.000 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.4999  -0.160153 0.492 0.000 0.000 0.508
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.2589   0.590540 0.000 0.116 0.000 0.884
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2011   0.713151 0.080 0.000 0.920 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000   0.695056 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.4643   0.310645 0.344 0.000 0.000 0.656
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3540   0.656811 0.876 0.064 0.048 0.012
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0336   0.840010 0.000 0.992 0.000 0.008
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4746   0.541946 0.632 0.000 0.000 0.368
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3833   0.726156 0.848 0.000 0.080 0.072
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.5594   0.649908 0.000 0.716 0.092 0.192
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.2345   0.677702 0.900 0.000 0.100 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.4985  -0.118748 0.468 0.000 0.000 0.532
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.5830   0.292242 0.332 0.048 0.000 0.620
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0524   0.840589 0.004 0.988 0.000 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.2647   0.801503 0.000 0.880 0.000 0.120
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.1743   0.675401 0.940 0.004 0.056 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.2081   0.818783 0.000 0.916 0.000 0.084
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.4193   0.657691 0.732 0.000 0.000 0.268
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.2345   0.810409 0.000 0.900 0.000 0.100
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4  0.4996  -0.173743 0.484 0.000 0.000 0.516
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.3486   0.713668 0.812 0.000 0.000 0.188
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6797   0.558622 0.608 0.012 0.100 0.280
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0592   0.700419 0.016 0.000 0.984 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.2737   0.809446 0.104 0.888 0.000 0.008
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5848   0.661421 0.684 0.088 0.000 0.228
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4713   0.558129 0.640 0.000 0.000 0.360
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.3074   0.586703 0.152 0.000 0.000 0.848
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.2469   0.806047 0.000 0.892 0.000 0.108
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.6359   0.374012 0.372 0.568 0.052 0.008
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1118   0.836551 0.000 0.964 0.000 0.036
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.5869   0.351066 0.044 0.360 0.596 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.4585   0.198678 0.668 0.000 0.332 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.5277   0.479968 0.000 0.116 0.132 0.752
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.4889   0.615162 0.360 0.000 0.636 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.5130   0.530910 0.344 0.644 0.004 0.008
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.1256   0.690111 0.008 0.000 0.964 0.028
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0336   0.697989 0.008 0.000 0.992 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.4454   0.623483 0.692 0.000 0.000 0.308
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.4888   0.741813 0.096 0.780 0.124 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.4866   0.458744 0.596 0.000 0.000 0.404
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.6452  -0.471253 0.472 0.068 0.460 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.1867   0.630654 0.072 0.000 0.000 0.928
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.2124   0.825129 0.068 0.924 0.000 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.2589   0.611023 0.116 0.000 0.000 0.884
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.3726   0.715522 0.212 0.000 0.788 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.4992   0.320248 0.524 0.000 0.000 0.476
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.2706   0.821082 0.080 0.900 0.000 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.4585   0.599245 0.668 0.000 0.000 0.332
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.2489   0.730393 0.912 0.000 0.020 0.068
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.5882   0.551679 0.608 0.048 0.000 0.344
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0895   0.840062 0.004 0.976 0.000 0.020
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.3610   0.710507 0.800 0.000 0.000 0.200
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.2922   0.806624 0.104 0.884 0.004 0.008
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2408   0.808159 0.000 0.896 0.000 0.104
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.3534   0.778416 0.148 0.840 0.004 0.008
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.5440   0.458678 0.000 0.104 0.160 0.736
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.1302   0.834387 0.000 0.956 0.000 0.044
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     4  0.5000  -0.248007 0.500 0.000 0.000 0.500
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#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1389   0.689104 0.048 0.000 0.952 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.5028   0.584212 0.400 0.000 0.596 0.004
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.4957   0.340720 0.000 0.320 0.012 0.668
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4  0.6724   0.405337 0.192 0.192 0.000 0.616
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4  0.4916   0.092859 0.424 0.000 0.000 0.576
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.5008   0.642399 0.016 0.716 0.260 0.008
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4  0.3444   0.557995 0.184 0.000 0.000 0.816
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.3074   0.728939 0.848 0.000 0.000 0.152
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.2799   0.680113 0.884 0.000 0.108 0.008
#> A7ECBC06-1332-4278-8723-85DC8351188A     4  0.4855   0.276057 0.352 0.004 0.000 0.644
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.3311   0.724805 0.828 0.000 0.000 0.172
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.4063   0.511129 0.808 0.172 0.004 0.016
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4  0.4564   0.331911 0.328 0.000 0.000 0.672
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.1474   0.835354 0.000 0.948 0.000 0.052
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.2011   0.605530 0.000 0.080 0.000 0.920
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.1411   0.697440 0.020 0.020 0.960 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.2408   0.808360 0.000 0.896 0.000 0.104
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4972   0.346634 0.544 0.000 0.000 0.456
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.4785   0.774369 0.108 0.812 0.052 0.028
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.1743   0.688719 0.940 0.000 0.056 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.3679   0.701168 0.084 0.000 0.856 0.060
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.2921   0.606890 0.140 0.000 0.000 0.860
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0672   0.840088 0.008 0.984 0.000 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.4019   0.520498 0.000 0.196 0.012 0.792
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.4817   0.506351 0.612 0.000 0.000 0.388
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.2216   0.733276 0.908 0.000 0.000 0.092
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.3727   0.764163 0.164 0.824 0.004 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.3074   0.778117 0.000 0.848 0.000 0.152
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4925   0.424220 0.572 0.000 0.000 0.428
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.2675   0.673819 0.100 0.000 0.892 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.5403   0.547512 0.628 0.000 0.024 0.348
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.3123   0.583551 0.156 0.000 0.000 0.844
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1022   0.837316 0.000 0.968 0.000 0.032
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1722   0.832894 0.048 0.944 0.000 0.008
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.5018   0.316536 0.000 0.332 0.012 0.656
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0921   0.702533 0.028 0.000 0.972 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     4  0.3444   0.557683 0.184 0.000 0.000 0.816
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1994   0.667249 0.936 0.052 0.004 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000   0.695056 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1816   0.705144 0.948 0.024 0.004 0.024
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.4193   0.301102 0.732 0.000 0.268 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000   0.695056 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4546   0.676830 0.732 0.000 0.012 0.256
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.3172   0.725715 0.840 0.000 0.000 0.160
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3726   0.702997 0.788 0.000 0.000 0.212
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1022   0.839733 0.000 0.968 0.000 0.032
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.7741   0.183635 0.004 0.448 0.204 0.344
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.2282   0.718086 0.924 0.024 0.000 0.052
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.4193   0.699056 0.268 0.000 0.732 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4624   0.573462 0.660 0.000 0.000 0.340
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1807   0.829913 0.052 0.940 0.000 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1489   0.836004 0.004 0.952 0.000 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.3801   0.516567 0.220 0.000 0.000 0.780
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1867   0.732012 0.928 0.000 0.000 0.072
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.4483   0.443169 0.712 0.000 0.284 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.4999  -0.202737 0.492 0.000 0.000 0.508
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.2921   0.730427 0.860 0.000 0.000 0.140
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1059   0.838836 0.016 0.972 0.000 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0895   0.628692 0.004 0.020 0.000 0.976
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.2334   0.598695 0.000 0.088 0.004 0.908
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.4072   0.472271 0.252 0.000 0.000 0.748
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.1059   0.839736 0.012 0.972 0.000 0.016
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.4431   0.381740 0.304 0.000 0.000 0.696
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.4998  -0.200731 0.488 0.000 0.000 0.512
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.1807   0.700174 0.940 0.000 0.052 0.008
#> 1122039D-5785-4F70-9916-17C585453512     3  0.6396   0.142807 0.000 0.072 0.548 0.380
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3117   0.727812 0.880 0.028 0.000 0.092
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1486   0.691156 0.960 0.024 0.008 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3907   0.688027 0.000 0.768 0.000 0.232
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.1305   0.839539 0.004 0.960 0.000 0.036
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.6568   0.657484 0.056 0.692 0.184 0.068
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.2469   0.616141 0.108 0.000 0.000 0.892
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.6257   0.045344 0.000 0.056 0.508 0.436
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.4868   0.524968 0.212 0.000 0.040 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4331   0.642883 0.712 0.000 0.000 0.288
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4830   0.593728 0.392 0.000 0.608 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4761   0.531806 0.628 0.000 0.000 0.372
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1389   0.833275 0.000 0.952 0.000 0.048
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.2216   0.622876 0.092 0.000 0.000 0.908
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0376   0.839884 0.004 0.992 0.000 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4624   0.521654 0.660 0.000 0.340 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2530   0.733346 0.888 0.000 0.000 0.112
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2156   0.659248 0.928 0.060 0.004 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.3356   0.582523 0.824 0.000 0.176 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1716   0.827366 0.000 0.936 0.000 0.064
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4356   0.633502 0.708 0.000 0.000 0.292
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4372   0.656596 0.728 0.000 0.004 0.268
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4585   0.590594 0.668 0.000 0.000 0.332
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4585   0.587511 0.668 0.000 0.000 0.332
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4522   0.351733 0.000 0.320 0.000 0.680
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4830   0.496020 0.608 0.000 0.000 0.392
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6197   0.153811 0.052 0.440 0.508 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0188   0.696549 0.004 0.000 0.996 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0657   0.840620 0.004 0.984 0.000 0.012
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3448   0.723384 0.828 0.004 0.000 0.168
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4638   0.703501 0.776 0.044 0.000 0.180
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.4817   0.134368 0.388 0.000 0.000 0.612
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4761   0.521523 0.628 0.000 0.000 0.372

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.4503   0.508387 0.036 0.268 0.000 0.000 0.696
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.3586   0.493385 0.000 0.264 0.000 0.736 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2563   0.660706 0.120 0.000 0.872 0.000 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.3906   0.460545 0.000 0.292 0.004 0.704 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1205   0.788404 0.000 0.956 0.000 0.040 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.1787   0.698429 0.936 0.004 0.044 0.000 0.016
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6306  -0.026433 0.500 0.328 0.172 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4489   0.664169 0.740 0.000 0.000 0.068 0.192
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     5  0.5987   0.233417 0.132 0.000 0.324 0.000 0.544
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.2970   0.587135 0.004 0.000 0.168 0.000 0.828
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.1270   0.663838 0.000 0.052 0.000 0.000 0.948
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2921   0.705049 0.856 0.000 0.000 0.020 0.124
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2491   0.762937 0.000 0.896 0.000 0.036 0.068
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.0963   0.670121 0.036 0.000 0.000 0.000 0.964
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0963   0.688492 0.000 0.036 0.000 0.964 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.1341   0.718865 0.944 0.000 0.000 0.000 0.056
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.3661   0.480597 0.000 0.276 0.000 0.724 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4664   0.158838 0.000 0.552 0.004 0.008 0.436
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1357   0.785206 0.000 0.948 0.000 0.048 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.3177   0.669482 0.000 0.792 0.000 0.000 0.208
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000   0.670430 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0404   0.794070 0.000 0.988 0.000 0.012 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.3958   0.618560 0.176 0.000 0.000 0.780 0.044
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000   0.794494 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0703   0.710318 0.024 0.000 0.000 0.976 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.6261   0.286633 0.000 0.356 0.156 0.000 0.488
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.4225   0.451437 0.632 0.004 0.364 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.7117   0.118584 0.452 0.116 0.000 0.372 0.060
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0566   0.716294 0.984 0.000 0.000 0.004 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1399   0.726388 0.952 0.000 0.000 0.028 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6615   0.411333 0.484 0.000 0.004 0.216 0.296
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2377   0.746678 0.000 0.872 0.000 0.000 0.128
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.3999   0.369904 0.000 0.344 0.000 0.656 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.1043   0.671711 0.040 0.000 0.000 0.000 0.960
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3707   0.583983 0.716 0.000 0.000 0.000 0.284
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.3395   0.550422 0.000 0.236 0.000 0.764 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4547   0.624989 0.072 0.736 0.000 0.192 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.2570   0.703175 0.084 0.000 0.028 0.888 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.0794   0.710943 0.028 0.000 0.000 0.972 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.6193   0.242975 0.000 0.192 0.260 0.548 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4780   0.580291 0.672 0.000 0.000 0.048 0.280
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1043   0.724171 0.960 0.000 0.000 0.040 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.2377   0.764229 0.128 0.872 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.5862   0.488365 0.176 0.000 0.000 0.604 0.220
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.3630   0.683921 0.016 0.780 0.000 0.204 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0162   0.671309 0.004 0.000 0.996 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000   0.670430 0.000 0.000 1.000 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.1740   0.711568 0.056 0.000 0.000 0.932 0.012
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.1753   0.684155 0.936 0.032 0.000 0.000 0.032
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0451   0.793949 0.000 0.988 0.000 0.008 0.004
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#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.6817   0.138216 0.356 0.000 0.000 0.332 0.312
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4818   0.399448 0.460 0.000 0.520 0.000 0.020
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1741   0.696886 0.936 0.040 0.000 0.024 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0609   0.792849 0.000 0.980 0.000 0.020 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0880   0.711328 0.032 0.000 0.000 0.968 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.1195   0.790415 0.000 0.960 0.000 0.028 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.5324   0.412978 0.568 0.000 0.380 0.004 0.048
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3110   0.724606 0.860 0.000 0.000 0.060 0.080
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.0162   0.670091 0.004 0.000 0.000 0.000 0.996
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.2054   0.673761 0.916 0.004 0.072 0.000 0.008
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0955   0.790888 0.000 0.968 0.000 0.028 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.6816   0.156574 0.360 0.000 0.000 0.320 0.320
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.4573   0.528569 0.092 0.000 0.000 0.164 0.744
#> EB7883EB-0079-4548-9132-169E94A698BA     5  0.3278   0.606816 0.020 0.000 0.000 0.156 0.824
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3508   0.640482 0.748 0.000 0.000 0.252 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.3949   0.394642 0.000 0.332 0.000 0.668 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3730   0.601855 0.712 0.000 0.000 0.288 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4829  -0.076603 0.000 0.500 0.480 0.000 0.020
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000   0.670430 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0162   0.794424 0.000 0.996 0.000 0.000 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1750   0.729063 0.936 0.000 0.000 0.036 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4204   0.667747 0.756 0.048 0.000 0.196 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.2727   0.684494 0.116 0.000 0.000 0.868 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.3586   0.629544 0.736 0.000 0.000 0.264 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     3  0.5039   -0.00445 0.004 0.172 0.668 0.000 0.152 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.2805    0.65083 0.000 0.184 0.004 0.000 0.000 0.812
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4817    0.13952 0.012 0.000 0.564 0.388 0.036 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     6  0.2714    0.68642 0.000 0.136 0.004 0.000 0.012 0.848
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0862    0.80471 0.000 0.972 0.004 0.000 0.016 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.1075    0.69852 0.952 0.000 0.048 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.7329   -0.10556 0.292 0.360 0.236 0.112 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0881    0.71252 0.972 0.000 0.008 0.000 0.012 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.5335    0.00554 0.008 0.000 0.476 0.080 0.436 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.5721    0.20133 0.008 0.000 0.344 0.508 0.140 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.4734    0.57608 0.000 0.168 0.152 0.000 0.680 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0520    0.71192 0.984 0.000 0.008 0.000 0.008 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1672    0.79417 0.000 0.932 0.004 0.000 0.048 0.016
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3514    0.55280 0.208 0.004 0.020 0.000 0.768 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.0436    0.77307 0.004 0.004 0.004 0.000 0.000 0.988
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0935    0.71181 0.964 0.000 0.032 0.000 0.004 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.3329    0.59504 0.000 0.236 0.004 0.000 0.004 0.756
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.4226    0.08659 0.000 0.484 0.004 0.000 0.504 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1173    0.80323 0.000 0.960 0.008 0.000 0.016 0.016
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2996    0.67108 0.000 0.772 0.000 0.000 0.228 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.0146    0.72669 0.000 0.000 0.000 0.996 0.000 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0603    0.80629 0.000 0.980 0.000 0.000 0.016 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.5230    0.42073 0.548 0.000 0.344 0.000 0.000 0.108
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1275    0.80631 0.000 0.956 0.016 0.000 0.016 0.012
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0363    0.77390 0.012 0.000 0.000 0.000 0.000 0.988
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.2747    0.63566 0.000 0.108 0.028 0.000 0.860 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.3965    0.32827 0.604 0.000 0.008 0.388 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.5716    0.46946 0.636 0.124 0.016 0.000 0.024 0.200
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0508    0.71273 0.984 0.000 0.012 0.000 0.000 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0405    0.71255 0.988 0.000 0.008 0.000 0.000 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     5  0.5774    0.24141 0.340 0.000 0.036 0.000 0.536 0.088
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2092    0.76526 0.000 0.876 0.000 0.000 0.124 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     6  0.3650    0.54780 0.000 0.272 0.004 0.000 0.008 0.716
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.2783    0.60776 0.148 0.000 0.016 0.000 0.836 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1649    0.70358 0.932 0.000 0.036 0.000 0.032 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.3942    0.33757 0.004 0.624 0.004 0.000 0.000 0.368
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3409    0.76372 0.076 0.832 0.076 0.000 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     6  0.1826    0.76713 0.052 0.000 0.000 0.020 0.004 0.924
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.0458    0.77416 0.016 0.000 0.000 0.000 0.000 0.984
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.5201    0.35923 0.000 0.088 0.004 0.592 0.004 0.312
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.1364    0.71217 0.952 0.000 0.016 0.000 0.020 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2810    0.60679 0.832 0.004 0.156 0.000 0.000 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1958    0.79258 0.004 0.896 0.100 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     3  0.6306   -0.15084 0.324 0.000 0.380 0.000 0.008 0.288
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.2188    0.80318 0.032 0.912 0.020 0.000 0.000 0.036
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     4  0.0000    0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.0146    0.72669 0.000 0.000 0.000 0.996 0.000 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.1562    0.76333 0.004 0.032 0.024 0.000 0.000 0.940
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.3766    0.05573 0.304 0.012 0.684 0.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0717    0.80702 0.000 0.976 0.008 0.000 0.016 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     5  0.6187    0.13589 0.128 0.000 0.036 0.000 0.456 0.380
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.1387    0.68672 0.932 0.000 0.068 0.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.4890    0.11167 0.000 0.464 0.004 0.492 0.008 0.032
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.1663    0.67541 0.912 0.000 0.088 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.3563    0.45642 0.664 0.000 0.000 0.000 0.000 0.336
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.6371    0.31274 0.444 0.028 0.340 0.000 0.000 0.188
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.1531    0.80478 0.004 0.928 0.068 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0748    0.81015 0.004 0.976 0.016 0.000 0.004 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.2398    0.65759 0.876 0.000 0.104 0.000 0.020 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.1321    0.80015 0.000 0.952 0.004 0.000 0.020 0.024
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0508    0.71273 0.984 0.000 0.012 0.000 0.000 0.004
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1194    0.80361 0.000 0.956 0.004 0.000 0.008 0.032
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.2562    0.69607 0.172 0.000 0.000 0.000 0.000 0.828
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.1285    0.70704 0.944 0.000 0.052 0.000 0.000 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.6227   -0.11112 0.240 0.000 0.396 0.008 0.000 0.356
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.0000    0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.5659    0.21018 0.000 0.488 0.348 0.000 0.164 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.4159    0.43363 0.588 0.016 0.396 0.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.2912    0.64617 0.844 0.000 0.040 0.000 0.000 0.116
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.0865    0.77266 0.036 0.000 0.000 0.000 0.000 0.964
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.1321    0.80166 0.000 0.952 0.004 0.000 0.020 0.024
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.4493    0.19266 0.160 0.132 0.708 0.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1411    0.80955 0.000 0.936 0.060 0.000 0.000 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.7217    0.23088 0.000 0.284 0.188 0.428 0.092 0.008
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.4317    0.31964 0.408 0.004 0.572 0.016 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     6  0.1138    0.76298 0.000 0.012 0.004 0.024 0.000 0.960
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     4  0.4948    0.08034 0.040 0.000 0.436 0.512 0.012 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.1151    0.65881 0.000 0.012 0.032 0.000 0.956 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     4  0.2171    0.68016 0.032 0.000 0.040 0.912 0.000 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     4  0.0777    0.71794 0.000 0.000 0.024 0.972 0.000 0.004
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.3345    0.52033 0.776 0.020 0.204 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.1245    0.65595 0.000 0.032 0.016 0.000 0.952 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1232    0.70750 0.956 0.016 0.024 0.000 0.000 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.5585    0.06052 0.012 0.000 0.484 0.100 0.404 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     6  0.0713    0.77374 0.028 0.000 0.000 0.000 0.000 0.972
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.3364    0.71581 0.024 0.780 0.196 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     6  0.0937    0.77219 0.040 0.000 0.000 0.000 0.000 0.960
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     4  0.3974    0.41461 0.000 0.000 0.296 0.680 0.024 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     6  0.3468    0.55418 0.284 0.000 0.000 0.000 0.004 0.712
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.4246    0.44006 0.020 0.580 0.400 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.5684    0.33549 0.528 0.000 0.000 0.000 0.244 0.228
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.3489    0.40540 0.708 0.004 0.288 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.3819    0.46702 0.624 0.004 0.372 0.000 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.2377    0.75055 0.000 0.868 0.004 0.000 0.124 0.004
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0976    0.71259 0.968 0.000 0.008 0.000 0.016 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.4793    0.52878 0.000 0.084 0.288 0.000 0.628 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.1552    0.79617 0.000 0.940 0.004 0.000 0.020 0.036
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.4094    0.41172 0.000 0.324 0.024 0.000 0.652 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     6  0.2547    0.72204 0.000 0.036 0.004 0.080 0.000 0.880
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0665    0.80986 0.000 0.980 0.008 0.000 0.008 0.004
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     6  0.2629    0.73715 0.040 0.000 0.000 0.000 0.092 0.868
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     6  0.1814    0.75087 0.100 0.000 0.000 0.000 0.000 0.900
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.5772    0.20222 0.184 0.468 0.348 0.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.5148    0.18743 0.000 0.472 0.468 0.012 0.044 0.004
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     6  0.2854    0.66655 0.208 0.000 0.000 0.000 0.000 0.792
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.0146    0.72630 0.000 0.000 0.004 0.996 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     6  0.0779    0.76931 0.000 0.008 0.000 0.008 0.008 0.976
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0858    0.70409 0.968 0.000 0.028 0.000 0.004 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.1615    0.80765 0.004 0.928 0.064 0.000 0.004 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     3  0.6374   -0.14945 0.212 0.000 0.392 0.000 0.020 0.376
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.4274    0.28299 0.008 0.560 0.000 0.000 0.008 0.424
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.1124    0.81022 0.008 0.956 0.036 0.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.3457    0.69389 0.016 0.752 0.232 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.3547    0.51143 0.668 0.000 0.332 0.000 0.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.1148    0.80272 0.000 0.960 0.004 0.000 0.016 0.020
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#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1448    0.80260 0.000 0.948 0.016 0.000 0.024 0.012
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#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     6  0.0405    0.77015 0.000 0.008 0.004 0.000 0.000 0.988
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#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0520    0.71255 0.984 0.000 0.008 0.000 0.000 0.008
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#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     4  0.5703    0.26585 0.000 0.400 0.072 0.500 0.016 0.012
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#> A17B743B-080B-4D00-9124-5CAECE38ABA5     4  0.2070    0.62947 0.100 0.000 0.000 0.892 0.008 0.000
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#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0891    0.70514 0.968 0.008 0.024 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.2537    0.64683 0.000 0.096 0.032 0.000 0.872 0.000
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#> D9C02B51-F92B-4F5F-89AC-BD526832C915     5  0.3247    0.56065 0.156 0.000 0.036 0.000 0.808 0.000
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#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.3053    0.59026 0.168 0.000 0.020 0.000 0.812 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.1951    0.78707 0.000 0.916 0.004 0.000 0.020 0.060
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.4731    0.51230 0.000 0.288 0.032 0.000 0.652 0.028
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.5339    0.23873 0.116 0.312 0.568 0.004 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.3844    0.66555 0.060 0.128 0.004 0.000 0.012 0.796
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#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.4748    0.01339 0.048 0.000 0.000 0.504 0.000 0.448
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4488    0.58794 0.720 0.000 0.204 0.000 0.052 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.6075    0.35659 0.348 0.000 0.468 0.168 0.016 0.000
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#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0767    0.80952 0.000 0.976 0.008 0.000 0.004 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0632    0.77408 0.024 0.000 0.000 0.000 0.000 0.976
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0976    0.80478 0.000 0.968 0.008 0.000 0.016 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.2257    0.67159 0.876 0.000 0.000 0.116 0.008 0.000
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#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.6113   -0.22696 0.296 0.000 0.356 0.000 0.348 0.000
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#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.6192    0.17624 0.416 0.000 0.344 0.000 0.232 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     5  0.2444    0.65102 0.036 0.000 0.016 0.000 0.896 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0458    0.71229 0.984 0.000 0.000 0.000 0.000 0.016
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.3476    0.56795 0.000 0.260 0.004 0.000 0.004 0.732
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#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     4  0.0000    0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0717    0.80588 0.000 0.976 0.000 0.000 0.016 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1556    0.69698 0.920 0.000 0.080 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6327    0.12470 0.480 0.060 0.112 0.000 0.000 0.348
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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-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 17541 rows and 500 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.
#>   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 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 0.368           0.752       0.882         0.2860 0.742   0.742
#> 3 3 0.226           0.537       0.792         0.5095 0.916   0.888
#> 4 4 0.271           0.502       0.748         0.1699 0.874   0.812
#> 5 5 0.283           0.456       0.733         0.1154 0.940   0.893
#> 6 6 0.304           0.466       0.698         0.0866 0.919   0.845

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.3733    0.85340 0.928 0.072
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000    0.87216 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.9393    0.65047 0.356 0.644
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.9815    0.52319 0.420 0.580
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.0672    0.87322 0.992 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.8763    0.43550 0.704 0.296
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6247    0.75319 0.844 0.156
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000    0.87216 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.8713    0.52974 0.708 0.292
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.5519    0.73678 0.128 0.872
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.6438    0.76386 0.836 0.164
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0376    0.87243 0.996 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     1  0.6438    0.76239 0.836 0.164
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.1184    0.87221 0.984 0.016
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.4939    0.78195 0.892 0.108
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.2778    0.86428 0.952 0.048
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000    0.87216 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.9850    0.52451 0.428 0.572
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.0672    0.87322 0.992 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     1  0.7139    0.71901 0.804 0.196
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000    0.68050 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     1  0.4298    0.84361 0.912 0.088
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.87216 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.9922    0.45372 0.448 0.552
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000    0.87216 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     1  0.9286    0.38282 0.656 0.344
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.9933    0.47544 0.452 0.548
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2236    0.86844 0.964 0.036
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2603    0.85029 0.956 0.044
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000    0.87216 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6801    0.75427 0.820 0.180
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     1  0.7139    0.71901 0.804 0.196
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.9087    0.67612 0.324 0.676
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1184    0.87221 0.984 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1414    0.87262 0.980 0.020
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000    0.87216 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.0000    0.87216 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.8909    0.44928 0.692 0.308
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.87216 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.1633    0.69733 0.024 0.976
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000    0.87216 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000    0.87216 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     1  0.2043    0.87001 0.968 0.032
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.87216 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0000    0.87216 1.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.6973    0.74125 0.188 0.812
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000    0.68050 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3274    0.85945 0.940 0.060
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.1633    0.87025 0.976 0.024
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.1414    0.87242 0.980 0.020
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1843    0.87159 0.972 0.028
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4022    0.82807 0.920 0.080
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.9795    0.53120 0.416 0.584
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4298    0.83952 0.912 0.088
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1184    0.86788 0.984 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000    0.87216 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     1  0.4690    0.83131 0.900 0.100
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.0000    0.87216 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.6343    0.77087 0.840 0.160
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.0672    0.87322 0.992 0.008
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.2043    0.85863 0.968 0.032
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1  0.5629    0.80524 0.868 0.132
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000    0.87216 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000    0.87216 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.5294    0.76558 0.880 0.120
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     2  0.5519    0.73678 0.128 0.872
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.4298    0.84189 0.912 0.088
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0672    0.87319 0.992 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.6623    0.72832 0.828 0.172
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000    0.87216 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.9866    0.50243 0.432 0.568
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0672    0.87307 0.992 0.008
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     1  0.7056    0.73150 0.808 0.192
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.9795    0.53120 0.416 0.584
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.7219    0.71656 0.800 0.200
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.8955    0.30461 0.688 0.312
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.9866    0.50532 0.432 0.568
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.1184    0.87221 0.984 0.016
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.7815    0.73248 0.232 0.768
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.8955    0.70095 0.312 0.688
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0000    0.87216 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     1  0.8813    0.51182 0.700 0.300
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000    0.87216 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.8713    0.52961 0.708 0.292
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0000    0.87216 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.3274    0.85529 0.940 0.060
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000    0.87216 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.6973    0.74125 0.188 0.812
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0376    0.87252 0.996 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.4690    0.83038 0.900 0.100
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1184    0.87221 0.984 0.016
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0376    0.87243 0.996 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000    0.87216 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     1  0.6801    0.74293 0.820 0.180
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0376    0.87243 0.996 0.004
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.6623    0.75231 0.828 0.172
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1  0.5629    0.80524 0.868 0.132
#> 31322670-76A2-4308-A71F-D8E00049519D     1  0.6801    0.74294 0.820 0.180
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.9427    0.12915 0.640 0.360
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     1  0.5946    0.79215 0.856 0.144
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.1184    0.87221 0.984 0.016
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0376    0.87241 0.996 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.1184    0.87213 0.984 0.016
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     1  0.9983   -0.20339 0.524 0.476
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.4815    0.78607 0.896 0.104
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     2  0.4431    0.72759 0.092 0.908
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.9775    0.55336 0.412 0.588
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.1633    0.87115 0.976 0.024
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     1  0.5737    0.79887 0.864 0.136
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000    0.87216 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.0938    0.87338 0.988 0.012
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.1843    0.87101 0.972 0.028
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     1  0.3431    0.85672 0.936 0.064
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.0938    0.87287 0.988 0.012
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.0672    0.87322 0.992 0.008
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     1  0.6531    0.75754 0.832 0.168
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0376    0.87243 0.996 0.004
#> 9980293D-AF0A-4215-9688-C576B1F8B519     1  0.7376    0.70709 0.792 0.208
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     1  1.0000   -0.30765 0.500 0.500
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0000    0.87216 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.2236    0.86672 0.964 0.036
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000    0.87216 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1  0.2423    0.86475 0.960 0.040
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     2  0.5519    0.73678 0.128 0.872
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     1  0.8955    0.47207 0.688 0.312
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.4690    0.79270 0.900 0.100
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.0672    0.87299 0.992 0.008
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.0376    0.87243 0.996 0.004
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0000    0.87216 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     2  0.1633    0.69733 0.024 0.976
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0376    0.87243 0.996 0.004
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     1  0.6531    0.75754 0.832 0.168
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  0.8443    0.57677 0.728 0.272
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.2236    0.86306 0.964 0.036
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0000    0.87216 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.3733    0.72028 0.072 0.928
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.8955    0.30461 0.688 0.312
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     1  0.7376    0.70709 0.792 0.208
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.0000    0.87216 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     1  0.6623    0.75333 0.828 0.172
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.9393    0.64401 0.356 0.644
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     1  0.1843    0.87158 0.972 0.028
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     1  0.5059    0.82456 0.888 0.112
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     1  0.8207    0.60923 0.744 0.256
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     1  0.3431    0.85575 0.936 0.064
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     1  0.8608    0.55090 0.716 0.284
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     1  0.6712    0.74843 0.824 0.176
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1  0.0000    0.87216 1.000 0.000
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#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000    0.87216 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0376    0.87243 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5946    0.78880 0.856 0.144
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000    0.87216 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.5247   0.642339 0.768 0.224 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.1267   0.766584 0.972 0.024 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.8924   0.353469 0.268 0.172 0.560
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.8939  -0.147528 0.124 0.440 0.436
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.4178   0.678189 0.828 0.172 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.7918   0.315578 0.640 0.104 0.256
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.7411   0.480654 0.668 0.256 0.076
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0475   0.765221 0.992 0.004 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.7446   0.349179 0.664 0.076 0.260
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4137   0.587625 0.096 0.032 0.872
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.7962   0.145646 0.576 0.352 0.072
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0592   0.765329 0.988 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     1  0.7458   0.445756 0.672 0.244 0.084
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2680   0.759329 0.924 0.068 0.008
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.4966   0.668587 0.840 0.100 0.060
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3889   0.739414 0.884 0.084 0.032
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.1267   0.766584 0.972 0.024 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     3  0.9489   0.026358 0.252 0.252 0.496
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.4002   0.690619 0.840 0.160 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     1  0.8414  -0.080754 0.528 0.380 0.092
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.1964   0.520921 0.000 0.056 0.944
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     1  0.6319   0.579648 0.732 0.228 0.040
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000   0.763936 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.9118   0.024829 0.144 0.468 0.388
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0424   0.765912 0.992 0.008 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.9827   0.522898 0.372 0.384 0.244
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.7508   0.260637 0.416 0.040 0.544
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.3769   0.737438 0.880 0.104 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2550   0.747484 0.936 0.040 0.024
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0424   0.765002 0.992 0.008 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5757   0.628542 0.792 0.056 0.152
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     1  0.8414  -0.080754 0.528 0.380 0.092
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.8676   0.322485 0.112 0.368 0.520
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1620   0.766485 0.964 0.024 0.012
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2383   0.762854 0.940 0.044 0.016
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.4121   0.687365 0.832 0.168 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.4399   0.670479 0.812 0.188 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.8013   0.329325 0.636 0.112 0.252
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000   0.763936 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.2636   0.545402 0.020 0.048 0.932
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0475   0.765221 0.992 0.004 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2448   0.751247 0.924 0.076 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     1  0.5254   0.572812 0.736 0.264 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0237   0.764339 0.996 0.004 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.3116   0.733836 0.892 0.108 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.6254   0.572105 0.116 0.108 0.776
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.1964   0.520921 0.000 0.056 0.944
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.4179   0.737886 0.876 0.072 0.052
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3112   0.753557 0.916 0.056 0.028
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.4796   0.634154 0.780 0.220 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2176   0.763044 0.948 0.032 0.020
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3896   0.719162 0.888 0.052 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.8844   0.135657 0.116 0.440 0.444
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5760   0.673810 0.796 0.140 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1170   0.760280 0.976 0.016 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0424   0.765739 0.992 0.008 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     1  0.6985   0.210176 0.592 0.384 0.024
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.4654   0.645276 0.792 0.208 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.6004   0.613325 0.780 0.064 0.156
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.4178   0.677774 0.828 0.172 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.2050   0.754150 0.952 0.028 0.020
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1  0.7233   0.463551 0.672 0.264 0.064
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0237   0.765562 0.996 0.004 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0237   0.764719 0.996 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4569   0.665718 0.860 0.072 0.068
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.4137   0.587625 0.096 0.032 0.872
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.6388   0.513374 0.692 0.284 0.024
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.1950   0.766389 0.952 0.040 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5744   0.614573 0.800 0.072 0.128
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000   0.763936 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.9068  -0.112461 0.136 0.444 0.420
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.2682   0.756819 0.920 0.076 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     1  0.8363  -0.185309 0.504 0.412 0.084
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.8844   0.135657 0.116 0.440 0.444
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.7726   0.454569 0.676 0.192 0.132
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.6967   0.319393 0.668 0.044 0.288
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.9601   0.179732 0.328 0.216 0.456
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.1999   0.766310 0.952 0.036 0.012
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.7447   0.546224 0.160 0.140 0.700
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.8503   0.441967 0.120 0.304 0.576
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.3038   0.735847 0.896 0.104 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     1  0.9292  -0.140228 0.516 0.284 0.200
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0237   0.764761 0.996 0.004 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.7951   0.292755 0.636 0.104 0.260
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.1031   0.765749 0.976 0.024 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.5763   0.535648 0.716 0.276 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000   0.763936 1.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.6254   0.571858 0.116 0.108 0.776
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0592   0.764684 0.988 0.000 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.6651   0.404607 0.656 0.320 0.024
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1482   0.766265 0.968 0.020 0.012
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.1950   0.765412 0.952 0.040 0.008
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.3879   0.703120 0.848 0.152 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     1  0.8169  -0.039111 0.536 0.388 0.076
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0475   0.764775 0.992 0.004 0.004
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.7810   0.367257 0.640 0.268 0.092
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1  0.7233   0.463551 0.672 0.264 0.064
#> 31322670-76A2-4308-A71F-D8E00049519D     1  0.8227  -0.036929 0.536 0.384 0.080
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.6934   0.216053 0.624 0.028 0.348
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     1  0.7919   0.058116 0.556 0.380 0.064
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.1482   0.766265 0.968 0.020 0.012
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.1015   0.767822 0.980 0.012 0.008
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.2261   0.755809 0.932 0.068 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.9724   0.244624 0.224 0.412 0.364
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.4087   0.684208 0.880 0.068 0.052
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.3356   0.577459 0.056 0.036 0.908
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.8955   0.221666 0.332 0.144 0.524
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.1999   0.763733 0.952 0.036 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     1  0.7736   0.012069 0.548 0.400 0.052
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000   0.763936 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.4784   0.650545 0.796 0.200 0.004
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.5138   0.588215 0.748 0.252 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     1  0.6200   0.463884 0.676 0.312 0.012
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.1877   0.767179 0.956 0.032 0.012
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.3941   0.695585 0.844 0.156 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     1  0.7831   0.343637 0.632 0.280 0.088
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.1129   0.766175 0.976 0.020 0.004
#> 9980293D-AF0A-4215-9688-C576B1F8B519     1  0.8608  -0.255538 0.488 0.412 0.100
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.8686  -0.078069 0.432 0.104 0.464
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0237   0.765003 0.996 0.004 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.2116   0.760290 0.948 0.012 0.040
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000   0.763936 1.000 0.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1  0.5285   0.592216 0.752 0.244 0.004
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     3  0.4137   0.587625 0.096 0.032 0.872
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.7622   0.660099 0.272 0.648 0.080
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.4194   0.691788 0.876 0.060 0.064
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.1860   0.761903 0.948 0.052 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.2959   0.745218 0.900 0.100 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0237   0.764178 0.996 0.000 0.004
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.2636   0.545402 0.020 0.048 0.932
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0592   0.765329 0.988 0.012 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     1  0.7770   0.367589 0.640 0.272 0.088
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  0.7139   0.409445 0.688 0.068 0.244
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.2434   0.758550 0.940 0.036 0.024
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0237   0.764719 0.996 0.004 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3  0.2926   0.568352 0.040 0.036 0.924
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.6967   0.319393 0.668 0.044 0.288
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     1  0.8608  -0.255538 0.488 0.412 0.100
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.1529   0.762128 0.960 0.040 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     1  0.8022   0.002882 0.544 0.388 0.068
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3  0.8623   0.395176 0.272 0.144 0.584
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     1  0.2152   0.764235 0.948 0.036 0.016
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     1  0.7013   0.369944 0.640 0.324 0.036
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.6473   0.659113 0.332 0.652 0.016
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     1  0.2947   0.747551 0.920 0.020 0.060
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.8929   0.500487 0.416 0.460 0.124
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     1  0.8108  -0.041064 0.536 0.392 0.072
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1  0.0237   0.764719 0.996 0.004 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3  0.7328   0.347894 0.364 0.040 0.596
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1  0.0000   0.763936 1.000 0.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.7622   0.660099 0.272 0.648 0.080
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     3  0.5067   0.584213 0.116 0.052 0.832
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     1  0.6306   0.541873 0.748 0.052 0.200
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     1  0.0000   0.763936 1.000 0.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     1  0.3193   0.746514 0.896 0.100 0.004
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     1  0.0592   0.765142 0.988 0.012 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F     1  0.0237   0.764317 0.996 0.004 0.000
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#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1031   0.767696 0.976 0.024 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.4504   0.661015 0.804 0.196 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000   0.763936 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.4399   0.665120 0.812 0.188 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.7328   0.347894 0.364 0.040 0.596
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0237   0.764317 0.996 0.004 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1267   0.766427 0.972 0.024 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.7129   0.547990 0.716 0.180 0.104
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1  0.5858   0.589413 0.740 0.240 0.020
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0475   0.764939 0.992 0.004 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2550   0.755896 0.936 0.040 0.024
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1482   0.766265 0.968 0.020 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0237   0.764719 0.996 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.1267   0.766584 0.972 0.024 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1337   0.758897 0.972 0.012 0.016
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.8887  -0.111509 0.120 0.456 0.424
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2926   0.568352 0.040 0.036 0.924
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.7590   0.657263 0.268 0.652 0.080
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0237   0.764317 0.996 0.004 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0592   0.766235 0.988 0.012 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4551   0.673380 0.840 0.020 0.140
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0237   0.764761 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.5897    0.49995 0.704 0.224 0.024 0.048
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2019    0.74501 0.940 0.032 0.004 0.024
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.8862    0.34590 0.216 0.164 0.500 0.120
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.7013    0.81983 0.024 0.104 0.256 0.616
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.4220    0.51839 0.748 0.248 0.000 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.7051    0.27891 0.612 0.088 0.268 0.032
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6724    0.21986 0.588 0.332 0.052 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0376    0.75081 0.992 0.004 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6748    0.29076 0.644 0.064 0.252 0.040
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2593    0.39494 0.080 0.000 0.904 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.7804   -0.41913 0.468 0.396 0.048 0.088
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0524    0.75097 0.988 0.008 0.004 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     1  0.7342    0.05800 0.584 0.292 0.068 0.056
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.3283    0.71097 0.872 0.104 0.020 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.5122    0.63238 0.796 0.112 0.048 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3827    0.70486 0.860 0.080 0.048 0.012
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.2019    0.74501 0.940 0.032 0.004 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     3  0.9482   -0.02893 0.188 0.220 0.420 0.172
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.4123    0.56877 0.772 0.220 0.000 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.8491    0.58751 0.396 0.404 0.060 0.140
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.3972    0.04260 0.000 0.008 0.788 0.204
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     1  0.5736    0.28556 0.640 0.324 0.016 0.020
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     4  0.8117    0.75002 0.048 0.196 0.212 0.544
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0336    0.75157 0.992 0.008 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.9665    0.45604 0.248 0.376 0.168 0.208
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5970    0.32694 0.388 0.024 0.576 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4475    0.66674 0.824 0.096 0.012 0.068
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2418    0.73268 0.928 0.032 0.024 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0376    0.75043 0.992 0.004 0.004 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5044    0.59844 0.780 0.044 0.156 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.8491    0.58751 0.396 0.404 0.060 0.140
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.7581    0.69764 0.064 0.060 0.352 0.524
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1707    0.74874 0.952 0.024 0.020 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2456    0.74221 0.924 0.040 0.028 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.4635    0.49052 0.720 0.268 0.000 0.012
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.4908    0.43681 0.692 0.292 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.7214    0.28558 0.604 0.088 0.268 0.040
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.3997    0.15762 0.012 0.008 0.816 0.164
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0376    0.75081 0.992 0.004 0.004 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2921    0.68715 0.860 0.140 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     1  0.5835    0.13644 0.588 0.372 0.000 0.040
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0188    0.75049 0.996 0.004 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.3725    0.63592 0.812 0.180 0.000 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.5015    0.37849 0.088 0.076 0.804 0.032
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.3972    0.04260 0.000 0.008 0.788 0.204
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.4573    0.68543 0.832 0.072 0.048 0.048
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.2936    0.72834 0.900 0.056 0.040 0.004
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.4744    0.43634 0.704 0.284 0.000 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2165    0.74698 0.936 0.032 0.024 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3587    0.70047 0.876 0.052 0.056 0.016
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.6788    0.81647 0.016 0.104 0.252 0.628
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5576    0.59735 0.756 0.140 0.084 0.020
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1139    0.74689 0.972 0.012 0.008 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0469    0.75124 0.988 0.012 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.5770    0.48904 0.432 0.544 0.012 0.012
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.5173    0.35654 0.660 0.320 0.000 0.020
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.5797    0.53841 0.740 0.056 0.168 0.036
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.4313    0.49733 0.736 0.260 0.000 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.1975    0.73940 0.944 0.028 0.016 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1  0.7375   -0.00923 0.556 0.324 0.040 0.080
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0188    0.75096 0.996 0.004 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0188    0.75018 0.996 0.000 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4277    0.65229 0.844 0.076 0.052 0.028
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.2593    0.39494 0.080 0.000 0.904 0.016
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.6384    0.18298 0.612 0.320 0.016 0.052
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.2099    0.74648 0.936 0.044 0.012 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5202    0.59626 0.788 0.060 0.120 0.032
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.7197    0.81560 0.036 0.104 0.244 0.616
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.3043    0.71198 0.876 0.112 0.008 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.7129    0.65578 0.336 0.564 0.056 0.044
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.6788    0.81647 0.016 0.104 0.252 0.628
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.7527    0.27005 0.620 0.196 0.124 0.060
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.6462    0.31384 0.644 0.044 0.276 0.036
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.9050    0.33472 0.288 0.204 0.424 0.084
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.2297    0.74367 0.928 0.044 0.024 0.004
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.6789    0.40396 0.128 0.120 0.692 0.060
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.8425   -0.12441 0.076 0.128 0.496 0.300
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.3494    0.64768 0.824 0.172 0.000 0.004
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     1  0.9036   -0.50433 0.424 0.320 0.144 0.112
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0188    0.75023 0.996 0.004 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.7587    0.17040 0.596 0.084 0.248 0.072
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.1302    0.74379 0.956 0.044 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.5178    0.11657 0.600 0.392 0.004 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.5015    0.37703 0.088 0.076 0.804 0.032
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0469    0.75106 0.988 0.000 0.012 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.5803   -0.29457 0.504 0.472 0.016 0.008
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1598    0.74900 0.956 0.020 0.020 0.004
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.1936    0.74825 0.940 0.032 0.028 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.4319    0.56298 0.760 0.228 0.000 0.012
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.8315    0.58622 0.396 0.416 0.048 0.140
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0376    0.75095 0.992 0.004 0.004 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.7600   -0.11598 0.544 0.324 0.076 0.056
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1  0.7342    0.02600 0.564 0.316 0.040 0.080
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.8371    0.58552 0.396 0.416 0.056 0.132
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.6283    0.21668 0.604 0.024 0.340 0.032
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.6951    0.57556 0.400 0.520 0.036 0.044
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.1598    0.74900 0.956 0.020 0.020 0.004
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.1114    0.75414 0.972 0.016 0.008 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.2149    0.72331 0.912 0.088 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     4  0.9305    0.43040 0.100 0.284 0.224 0.392
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.3697    0.67291 0.872 0.068 0.032 0.028
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.2262    0.33710 0.040 0.016 0.932 0.012
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.8797    0.31723 0.308 0.120 0.460 0.112
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.1958    0.74711 0.944 0.020 0.028 0.008
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.6680    0.60657 0.384 0.548 0.028 0.040
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.4621    0.44076 0.708 0.284 0.000 0.008
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.5666    0.22315 0.616 0.348 0.000 0.036
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     1  0.5155   -0.17771 0.528 0.468 0.004 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.1943    0.74999 0.944 0.032 0.016 0.008
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.3945    0.57552 0.780 0.216 0.000 0.004
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     1  0.7698   -0.17433 0.532 0.332 0.072 0.064
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.1297    0.75116 0.964 0.020 0.016 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.7338    0.64848 0.320 0.564 0.064 0.052
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.8263    0.04477 0.408 0.088 0.424 0.080
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0188    0.75030 0.996 0.004 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.2076    0.74056 0.932 0.004 0.056 0.008
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1  0.4730    0.24914 0.636 0.364 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     3  0.2593    0.39494 0.080 0.000 0.904 0.016
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.7090    0.15430 0.116 0.604 0.020 0.260
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.4186    0.67252 0.852 0.056 0.052 0.040
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.1867    0.73318 0.928 0.072 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.3236    0.69185 0.856 0.136 0.004 0.004
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0188    0.75009 0.996 0.000 0.004 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.3997    0.15762 0.012 0.008 0.816 0.164
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0524    0.75097 0.988 0.008 0.004 0.000
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#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0336    0.75137 0.992 0.000 0.008 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1739    0.75048 0.952 0.024 0.016 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.2707    0.38325 0.068 0.008 0.908 0.016
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1114    0.75046 0.972 0.008 0.016 0.004
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.5721    0.54489 0.744 0.052 0.168 0.036
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.7974    0.37916 0.168 0.124 0.600 0.108
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.1484    0.74758 0.960 0.020 0.016 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0336    0.75119 0.992 0.008 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0188    0.75018 0.996 0.000 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.4855    0.11797 0.600 0.400 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.7509    0.26910 0.624 0.200 0.104 0.072
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.2528    0.73700 0.908 0.080 0.004 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.9186   -0.03920 0.180 0.428 0.280 0.112
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.7600   -0.11598 0.544 0.324 0.076 0.056
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.6488    0.61988 0.372 0.568 0.032 0.028
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1486    0.74395 0.960 0.024 0.008 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0376    0.75081 0.992 0.004 0.004 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.7263    0.30182 0.404 0.068 0.496 0.032
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1191    0.75267 0.968 0.024 0.004 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.5404    0.31951 0.644 0.328 0.000 0.028
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0967    0.74897 0.976 0.016 0.004 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.3852    0.60723 0.800 0.192 0.000 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0469    0.75120 0.988 0.000 0.012 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4380    0.61688 0.800 0.032 0.164 0.004
#> 1122039D-5785-4F70-9916-17C585453512     3  0.3997    0.15762 0.012 0.008 0.816 0.164
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0188    0.75018 0.996 0.000 0.004 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1811    0.74703 0.948 0.028 0.020 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.7197    0.81560 0.036 0.104 0.244 0.616
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.3739    0.70632 0.868 0.076 0.024 0.032
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.6103    0.36160 0.480 0.484 0.024 0.012
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3299    0.72332 0.888 0.056 0.012 0.044
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.4241    0.16506 0.012 0.016 0.808 0.164
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.7093    0.25526 0.428 0.060 0.484 0.028
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0524    0.75109 0.988 0.004 0.008 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.9016    0.18979 0.344 0.196 0.384 0.076
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0921    0.75046 0.972 0.028 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.5157    0.42080 0.688 0.284 0.000 0.028
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000    0.74964 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.4516    0.49930 0.736 0.252 0.000 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.5857    0.40586 0.340 0.032 0.620 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0188    0.74964 0.996 0.004 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1369    0.75046 0.964 0.016 0.016 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.6871    0.45222 0.672 0.172 0.112 0.044
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1  0.6057    0.33368 0.648 0.288 0.008 0.056
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0336    0.75046 0.992 0.000 0.008 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2521    0.74036 0.924 0.032 0.028 0.016
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1707    0.74776 0.952 0.024 0.020 0.004
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0188    0.75018 0.996 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.2019    0.74501 0.940 0.032 0.004 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1229    0.74533 0.968 0.020 0.008 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.7373    0.75442 0.020 0.144 0.256 0.580
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1707    0.30305 0.024 0.004 0.952 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.7090    0.14168 0.112 0.600 0.020 0.268
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0188    0.74964 0.996 0.004 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0657    0.75226 0.984 0.012 0.004 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3983    0.64285 0.828 0.020 0.144 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0188    0.75023 0.996 0.004 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.6163    0.33682 0.624 0.236 0.024 0.004 0.112
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2596    0.71815 0.908 0.032 0.004 0.036 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.8525    0.40994 0.164 0.116 0.488 0.064 0.168
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.2387    0.80694 0.004 0.040 0.048 0.908 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.5191    0.25349 0.624 0.324 0.000 0.008 0.044
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.6657    0.22164 0.552 0.032 0.272 0.000 0.144
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6927   -0.10204 0.484 0.348 0.044 0.000 0.124
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0451    0.73114 0.988 0.000 0.008 0.000 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6503    0.29144 0.620 0.076 0.244 0.032 0.028
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1809    0.49711 0.060 0.000 0.928 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.7737    0.47147 0.360 0.428 0.032 0.040 0.140
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0486    0.73079 0.988 0.004 0.004 0.000 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     1  0.7308   -0.28949 0.468 0.372 0.056 0.024 0.080
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4127    0.63517 0.792 0.156 0.024 0.000 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.5158    0.59588 0.756 0.068 0.036 0.012 0.128
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4291    0.65172 0.808 0.092 0.056 0.000 0.044
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.2596    0.71815 0.908 0.032 0.004 0.036 0.020
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     3  0.9328   -0.10271 0.140 0.240 0.372 0.108 0.140
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.5250    0.34529 0.656 0.280 0.000 0.016 0.048
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.8219    0.43799 0.280 0.436 0.040 0.056 0.188
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.5051    0.09402 0.000 0.000 0.664 0.264 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     1  0.5886   -0.13089 0.520 0.412 0.004 0.036 0.028
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0162    0.72915 0.996 0.000 0.000 0.000 0.004
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     4  0.5510    0.71566 0.024 0.132 0.056 0.740 0.048
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0693    0.73266 0.980 0.008 0.000 0.000 0.012
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.9212    0.13511 0.180 0.416 0.128 0.128 0.148
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5406    0.36691 0.348 0.008 0.592 0.000 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.5010    0.59705 0.764 0.116 0.008 0.080 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2131    0.71647 0.920 0.008 0.016 0.000 0.056
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0613    0.73194 0.984 0.004 0.004 0.000 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.4887    0.58258 0.756 0.024 0.160 0.008 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.8219    0.43799 0.280 0.436 0.040 0.056 0.188
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4866    0.73152 0.048 0.016 0.144 0.768 0.024
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2418    0.72059 0.912 0.044 0.024 0.000 0.020
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2617    0.71976 0.904 0.036 0.032 0.000 0.028
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.5733    0.28031 0.616 0.276 0.000 0.008 0.100
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5993    0.17594 0.576 0.312 0.000 0.012 0.100
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6729    0.25288 0.556 0.028 0.264 0.004 0.148
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0404    0.73046 0.988 0.000 0.000 0.000 0.012
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4712    0.21819 0.004 0.000 0.720 0.216 0.060
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0451    0.73114 0.988 0.000 0.008 0.000 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3936    0.61435 0.800 0.144 0.000 0.004 0.052
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     1  0.6528   -0.23765 0.444 0.408 0.000 0.012 0.136
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0290    0.73042 0.992 0.000 0.000 0.000 0.008
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.4555    0.52894 0.740 0.196 0.000 0.004 0.060
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4506    0.49271 0.056 0.068 0.812 0.016 0.048
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.5051    0.09402 0.000 0.000 0.664 0.264 0.072
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5018    0.63409 0.780 0.088 0.048 0.064 0.020
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3569    0.68762 0.852 0.072 0.040 0.000 0.036
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.5552    0.13466 0.588 0.340 0.000 0.008 0.064
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2772    0.72075 0.896 0.044 0.028 0.000 0.032
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3538    0.67548 0.848 0.016 0.056 0.000 0.080
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.1981    0.80799 0.000 0.028 0.048 0.924 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5926    0.51281 0.700 0.120 0.092 0.004 0.084
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0992    0.72957 0.968 0.000 0.008 0.000 0.024
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0771    0.73211 0.976 0.020 0.000 0.000 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.4910    0.48053 0.328 0.640 0.004 0.008 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.6279    0.00252 0.520 0.352 0.000 0.012 0.116
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.5705    0.51176 0.712 0.052 0.172 0.036 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.5334    0.21477 0.612 0.328 0.000 0.008 0.052
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.1757    0.72173 0.936 0.004 0.012 0.000 0.048
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1  0.7955   -0.28724 0.444 0.328 0.024 0.112 0.092
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0613    0.73259 0.984 0.008 0.004 0.000 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0162    0.72974 0.996 0.000 0.004 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4054    0.63759 0.812 0.028 0.040 0.000 0.120
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.1809    0.49711 0.060 0.000 0.928 0.012 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.6577   -0.14407 0.520 0.344 0.012 0.012 0.112
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.2568    0.71850 0.904 0.048 0.016 0.000 0.032
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4519    0.59124 0.764 0.004 0.120 0.000 0.112
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.2443    0.80218 0.008 0.036 0.040 0.912 0.004
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.3489    0.65834 0.824 0.148 0.012 0.000 0.016
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.5933    0.39460 0.244 0.656 0.032 0.048 0.020
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.1981    0.80799 0.000 0.028 0.048 0.924 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.7532    0.14868 0.556 0.188 0.140 0.016 0.100
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.5965    0.32298 0.624 0.004 0.264 0.020 0.088
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.8505    0.32160 0.236 0.128 0.416 0.020 0.200
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.2784    0.70979 0.888 0.072 0.028 0.000 0.012
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.6014    0.50171 0.084 0.048 0.692 0.016 0.160
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.8059    0.13605 0.048 0.112 0.496 0.260 0.084
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.4515    0.54020 0.748 0.184 0.000 0.004 0.064
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.8707    0.44694 0.344 0.368 0.112 0.064 0.112
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0451    0.73072 0.988 0.008 0.000 0.000 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.7413    0.15491 0.560 0.100 0.240 0.064 0.036
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.1914    0.71810 0.924 0.060 0.000 0.000 0.016
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.4450   -0.23848 0.508 0.488 0.000 0.000 0.004
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#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     4  0.4866    0.73152 0.048 0.016 0.144 0.768 0.024
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     1  0.7553   -0.39701 0.424 0.396 0.064 0.024 0.092
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.5139    0.47480 0.316 0.640 0.008 0.008 0.028
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     1  0.5414    0.46206 0.696 0.060 0.216 0.012 0.016
#> A9195281-8CAE-45A8-8493-744E577907FA     1  0.4138    0.20058 0.616 0.384 0.000 0.000 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     1  0.5302    0.23633 0.620 0.320 0.000 0.008 0.052
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.5614    0.49434 0.396 0.552 0.012 0.024 0.016
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.3766    0.47720 0.728 0.268 0.000 0.000 0.004
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     1  0.7007   -0.16252 0.516 0.348 0.056 0.040 0.040
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0404    0.73046 0.988 0.000 0.000 0.000 0.012
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.2972    0.68490 0.872 0.084 0.000 0.004 0.040
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.3845    0.62541 0.812 0.124 0.000 0.004 0.060
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.5244    0.48663 0.060 0.072 0.764 0.016 0.088
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     1  0.7461   -0.29721 0.440 0.384 0.020 0.060 0.096
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     1  0.5758    0.22932 0.612 0.304 0.016 0.004 0.064
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     4  0.8732    0.18659 0.076 0.264 0.140 0.428 0.092
#> 80936433-AA91-4219-98F1-706C36298060     3  0.5821    0.11908 0.000 0.024 0.652 0.220 0.104
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.4566    0.61687 0.796 0.012 0.084 0.020 0.088
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.3609    0.66072 0.832 0.128 0.012 0.004 0.024
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0290    0.73120 0.992 0.000 0.000 0.000 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0404    0.73120 0.988 0.000 0.000 0.000 0.012
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     4  0.1981    0.80799 0.000 0.028 0.048 0.924 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0579    0.73237 0.984 0.000 0.008 0.000 0.008
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0579    0.73090 0.984 0.008 0.000 0.000 0.008
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.5283    0.40364 0.672 0.240 0.000 0.008 0.080
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.1243    0.73389 0.960 0.028 0.004 0.000 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1597    0.48839 0.048 0.000 0.940 0.012 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.5749    0.44025 0.680 0.060 0.216 0.012 0.032
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.2596    0.71815 0.908 0.032 0.004 0.036 0.020
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.1216    0.73402 0.960 0.020 0.000 0.000 0.020
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0404    0.73046 0.988 0.000 0.000 0.000 0.012
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.5014    0.44679 0.432 0.540 0.004 0.000 0.024
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1443    0.72993 0.948 0.044 0.004 0.000 0.004
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.3214    0.67532 0.856 0.020 0.112 0.004 0.008
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.5113    0.58122 0.748 0.044 0.088 0.000 0.120
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1443    0.72993 0.948 0.044 0.004 0.000 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.1777    0.73051 0.944 0.020 0.020 0.004 0.012
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.2186    0.72536 0.924 0.044 0.012 0.004 0.016
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.2919    0.67418 0.868 0.004 0.024 0.000 0.104
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.4305   -0.21608 0.512 0.488 0.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.2473    0.72224 0.912 0.040 0.004 0.032 0.012
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.8142    0.18541 0.232 0.488 0.168 0.048 0.064
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.6052    0.47829 0.316 0.596 0.012 0.040 0.036
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4439    0.61174 0.784 0.036 0.040 0.000 0.140
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.4273   -0.06132 0.552 0.448 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.4923    0.59994 0.764 0.044 0.088 0.000 0.104
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.8225    0.44192 0.180 0.068 0.500 0.060 0.192
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0404    0.73046 0.988 0.000 0.000 0.000 0.012
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     1  0.4273   -0.06132 0.552 0.448 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.3375    0.68520 0.864 0.012 0.024 0.016 0.084
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0451    0.73203 0.988 0.000 0.004 0.000 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.4756    0.65105 0.800 0.068 0.060 0.048 0.024
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     1  0.7917   -0.46261 0.400 0.392 0.076 0.036 0.096
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.5536    0.10787 0.580 0.352 0.000 0.008 0.060
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2332    0.70526 0.904 0.004 0.016 0.000 0.076
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1809    0.49711 0.060 0.000 0.928 0.012 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6803    0.26393 0.568 0.032 0.248 0.008 0.144
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0162    0.72915 0.996 0.000 0.000 0.000 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.6499    0.18784 0.196 0.644 0.024 0.040 0.096
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.6340    0.48478 0.296 0.596 0.052 0.020 0.036
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.2596    0.71815 0.908 0.032 0.004 0.036 0.020
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.5159    0.42233 0.300 0.004 0.640 0.000 0.056
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0740    0.73212 0.980 0.004 0.008 0.000 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1891    0.73086 0.936 0.016 0.016 0.000 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1757    0.48922 0.048 0.004 0.936 0.012 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1503    0.73010 0.952 0.020 0.020 0.000 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.5639    0.51846 0.716 0.048 0.172 0.036 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.7575    0.48215 0.124 0.072 0.588 0.060 0.156
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.1748    0.73059 0.944 0.008 0.016 0.004 0.028
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0290    0.73120 0.992 0.000 0.000 0.000 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0162    0.72974 0.996 0.000 0.004 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.4307   -0.24451 0.504 0.496 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.7387    0.10698 0.560 0.240 0.080 0.092 0.028
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.3406    0.69777 0.856 0.084 0.020 0.000 0.040
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     5  0.8854    0.02942 0.100 0.288 0.276 0.036 0.300
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0162    0.72915 0.996 0.000 0.000 0.000 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.7551   -0.38920 0.428 0.392 0.064 0.024 0.092
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.5623    0.44370 0.284 0.644 0.020 0.016 0.036
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1591    0.72508 0.940 0.004 0.004 0.000 0.052
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0451    0.73114 0.988 0.000 0.008 0.000 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.6387    0.35610 0.352 0.008 0.500 0.000 0.140
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1364    0.73142 0.952 0.036 0.012 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.6360   -0.03570 0.508 0.356 0.000 0.012 0.124
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0566    0.73087 0.984 0.004 0.000 0.000 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0566    0.73087 0.984 0.004 0.000 0.000 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1124    0.72995 0.960 0.000 0.004 0.000 0.036
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.4865    0.38737 0.672 0.280 0.000 0.004 0.044
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0854    0.73221 0.976 0.004 0.012 0.000 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4100    0.60246 0.784 0.028 0.172 0.000 0.016
#> 1122039D-5785-4F70-9916-17C585453512     3  0.4712    0.21819 0.004 0.000 0.720 0.216 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0451    0.73167 0.988 0.008 0.004 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2492    0.71800 0.908 0.048 0.024 0.000 0.020
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.2443    0.80218 0.008 0.036 0.040 0.912 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.4138    0.65530 0.824 0.100 0.020 0.020 0.036
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5514    0.49210 0.396 0.556 0.024 0.008 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3835    0.68922 0.848 0.064 0.016 0.048 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.4946    0.22470 0.004 0.000 0.704 0.216 0.076
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.6002    0.29734 0.392 0.000 0.492 0.000 0.116
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0451    0.73104 0.988 0.000 0.008 0.000 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.8550    0.25756 0.288 0.128 0.384 0.020 0.180
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1205    0.73032 0.956 0.040 0.000 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.6208    0.13953 0.568 0.312 0.000 0.024 0.096
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0290    0.72962 0.992 0.000 0.000 0.000 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.5287    0.22004 0.612 0.332 0.000 0.008 0.048
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.5295    0.42002 0.304 0.004 0.628 0.000 0.064
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0162    0.72945 0.996 0.000 0.000 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2072    0.72548 0.928 0.036 0.020 0.000 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.6956    0.34442 0.604 0.120 0.112 0.004 0.160
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1  0.7148    0.01435 0.536 0.276 0.004 0.088 0.096
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0290    0.73042 0.992 0.000 0.008 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2745    0.72000 0.896 0.024 0.028 0.000 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.2291    0.71964 0.916 0.048 0.024 0.000 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0324    0.73070 0.992 0.000 0.004 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.2596    0.71815 0.908 0.032 0.004 0.036 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1412    0.72615 0.952 0.004 0.008 0.000 0.036
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.5128    0.70596 0.004 0.084 0.148 0.740 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1200    0.43397 0.012 0.000 0.964 0.016 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.7024   -0.52486 0.068 0.436 0.012 0.060 0.424
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0162    0.72945 0.996 0.000 0.000 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0932    0.73309 0.972 0.020 0.004 0.000 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3763    0.62881 0.812 0.024 0.152 0.004 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0451    0.73072 0.988 0.008 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.6865    0.14969 0.544 0.124 0.024 0.000 0.216 0.092
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3138    0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.7755    0.40260 0.124 0.296 0.440 0.020 0.040 0.080
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1036    0.78893 0.000 0.024 0.000 0.964 0.008 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.5489   -0.18661 0.496 0.100 0.000 0.000 0.396 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.6636    0.15701 0.512 0.148 0.280 0.000 0.020 0.040
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.7014   -0.21036 0.432 0.340 0.044 0.000 0.156 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0603    0.73378 0.980 0.000 0.004 0.000 0.016 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6583    0.27814 0.584 0.104 0.220 0.008 0.060 0.024
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1616    0.49382 0.048 0.000 0.932 0.000 0.000 0.020
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3964    0.56830 0.228 0.012 0.004 0.004 0.740 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0653    0.73361 0.980 0.004 0.004 0.000 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.5072    0.47218 0.340 0.040 0.016 0.000 0.596 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4015    0.55340 0.724 0.012 0.016 0.000 0.244 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.5119    0.60717 0.740 0.132 0.032 0.012 0.052 0.032
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4540    0.63627 0.772 0.112 0.040 0.000 0.056 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.3138    0.70294 0.864 0.012 0.000 0.040 0.064 0.020
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#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.5152    0.64522 0.760 0.060 0.048 0.048 0.064 0.020
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.5277    0.55828 0.264 0.044 0.028 0.004 0.648 0.012
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     5  0.5486    0.26671 0.444 0.096 0.000 0.000 0.452 0.008
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2338    0.71727 0.900 0.068 0.012 0.000 0.004 0.016
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1616    0.49382 0.048 0.000 0.932 0.000 0.000 0.020
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6830    0.26759 0.544 0.156 0.220 0.004 0.032 0.044
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0508    0.73371 0.984 0.004 0.000 0.000 0.012 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.7539    0.30721 0.148 0.484 0.008 0.036 0.232 0.092
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.7104    0.35772 0.236 0.376 0.016 0.012 0.340 0.020
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.3138    0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4785    0.43431 0.284 0.048 0.652 0.000 0.004 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0810    0.73578 0.976 0.008 0.008 0.000 0.004 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.2302    0.73350 0.912 0.036 0.012 0.000 0.024 0.016
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1666    0.48840 0.036 0.008 0.936 0.000 0.000 0.020
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1624    0.73075 0.936 0.008 0.012 0.000 0.044 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.5772    0.50455 0.676 0.072 0.164 0.028 0.056 0.004
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.7198    0.46361 0.096 0.228 0.544 0.020 0.040 0.072
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.1553    0.73710 0.944 0.032 0.012 0.004 0.000 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0508    0.73417 0.984 0.004 0.000 0.000 0.012 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0405    0.73269 0.988 0.000 0.004 0.000 0.008 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.5940   -0.37344 0.440 0.332 0.000 0.000 0.228 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.7752    0.05143 0.512 0.188 0.056 0.088 0.132 0.024
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.3621    0.69808 0.828 0.092 0.012 0.000 0.052 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.7646   -0.25732 0.036 0.452 0.212 0.004 0.088 0.208
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0146    0.73252 0.996 0.000 0.000 0.000 0.004 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.4942    0.54062 0.292 0.028 0.024 0.000 0.644 0.012
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.6899    0.49563 0.224 0.476 0.008 0.012 0.248 0.032
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1697    0.73187 0.936 0.036 0.004 0.000 0.004 0.020
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0603    0.73378 0.980 0.000 0.004 0.000 0.016 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.6264    0.34179 0.328 0.120 0.508 0.000 0.008 0.036
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0551    0.73350 0.984 0.004 0.000 0.000 0.008 0.004
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1860    0.73507 0.928 0.036 0.004 0.000 0.028 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.7355   -0.20116 0.396 0.232 0.000 0.000 0.236 0.136
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0767    0.73416 0.976 0.004 0.000 0.000 0.012 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0767    0.73416 0.976 0.004 0.000 0.000 0.012 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1198    0.73578 0.960 0.020 0.004 0.000 0.004 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.5510    0.18378 0.584 0.104 0.000 0.000 0.292 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0837    0.73596 0.972 0.004 0.000 0.000 0.020 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0912    0.73615 0.972 0.008 0.012 0.000 0.004 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4406    0.60643 0.760 0.032 0.152 0.000 0.048 0.008
#> 1122039D-5785-4F70-9916-17C585453512     3  0.5279    0.22319 0.000 0.040 0.676 0.204 0.008 0.072
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0692    0.73538 0.976 0.000 0.004 0.000 0.020 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2458    0.71570 0.888 0.008 0.016 0.000 0.084 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.1053    0.78683 0.004 0.020 0.000 0.964 0.012 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.4001    0.61907 0.776 0.032 0.004 0.004 0.168 0.016
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.7003    0.41704 0.340 0.376 0.024 0.004 0.240 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4124    0.68119 0.820 0.044 0.012 0.052 0.052 0.020
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.5608    0.22443 0.000 0.056 0.656 0.204 0.012 0.072
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.6018    0.28379 0.376 0.088 0.496 0.000 0.008 0.032
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0653    0.73413 0.980 0.000 0.004 0.000 0.012 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.7707    0.21271 0.244 0.316 0.336 0.000 0.044 0.060
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1334    0.73463 0.948 0.032 0.000 0.000 0.020 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.7300   -0.06954 0.460 0.208 0.000 0.016 0.220 0.096
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0551    0.73350 0.984 0.004 0.000 0.000 0.008 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.5517   -0.22096 0.488 0.092 0.000 0.000 0.408 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4993    0.42962 0.288 0.048 0.640 0.000 0.008 0.016
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0363    0.73246 0.988 0.000 0.000 0.000 0.012 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2144    0.72401 0.908 0.008 0.012 0.000 0.068 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.6959    0.27518 0.544 0.228 0.104 0.000 0.072 0.052
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     1  0.7863   -0.20329 0.436 0.184 0.000 0.092 0.220 0.068
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0748    0.73654 0.976 0.000 0.004 0.000 0.016 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3249    0.71758 0.864 0.040 0.028 0.000 0.044 0.024
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.2370    0.71888 0.896 0.008 0.012 0.000 0.076 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0665    0.73464 0.980 0.008 0.004 0.000 0.008 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.3138    0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1382    0.73161 0.948 0.036 0.008 0.000 0.000 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.4923    0.67587 0.000 0.120 0.072 0.744 0.040 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1198    0.44347 0.000 0.012 0.960 0.004 0.004 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F     6  0.6430    0.53942 0.016 0.180 0.004 0.004 0.388 0.408
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0363    0.73246 0.988 0.000 0.000 0.000 0.012 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1293    0.73753 0.956 0.016 0.004 0.000 0.020 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3984    0.63351 0.796 0.028 0.136 0.004 0.028 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0405    0.73439 0.988 0.004 0.000 0.000 0.008 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-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 17541 rows and 500 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 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 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 0.359           0.770       0.851         0.4681 0.517   0.517
#> 3 3 0.797           0.845       0.932         0.3239 0.781   0.612
#> 4 4 0.647           0.683       0.816         0.1151 0.910   0.777
#> 5 5 0.608           0.620       0.774         0.0709 0.951   0.853
#> 6 6 0.618           0.505       0.697         0.0569 0.909   0.713

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5737     0.8711 0.136 0.864
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.6623     0.7168 0.828 0.172
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.6343     0.7382 0.160 0.840
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.5408     0.8688 0.124 0.876
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.9044     0.6139 0.320 0.680
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.5737     0.7700 0.864 0.136
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.5842     0.7686 0.860 0.140
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.8863 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.9710     0.5669 0.400 0.600
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.9954     0.1438 0.460 0.540
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.5737     0.8711 0.136 0.864
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.8863 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.5737     0.8711 0.136 0.864
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0000     0.8863 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.4815     0.8030 0.896 0.104
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.8863 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.8327     0.5809 0.736 0.264
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.8028 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5737     0.8711 0.136 0.864
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.5737     0.8711 0.136 0.864
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.2043     0.8029 0.032 0.968
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.5737     0.8711 0.136 0.864
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8863 1.000 0.000
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#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.6973     0.7114 0.188 0.812
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.0000     0.8028 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.5737     0.8711 0.136 0.864
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.5737     0.8711 0.136 0.864
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     1  0.9710     0.0518 0.600 0.400
#> A9195281-8CAE-45A8-8493-744E577907FA     1  0.8327     0.5809 0.736 0.264
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.5737     0.8711 0.136 0.864
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.6887     0.8257 0.184 0.816
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.8327     0.5809 0.736 0.264
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.5737     0.8711 0.136 0.864
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000     0.8863 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0000     0.8863 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.0000     0.8863 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0000     0.8863 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.7139     0.7028 0.196 0.804
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.5737     0.8711 0.136 0.864
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.5737     0.8711 0.136 0.864
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.5519     0.8702 0.128 0.872
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000     0.8028 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.5842     0.7686 0.860 0.140
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0000     0.8863 1.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000     0.8863 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000     0.8863 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.4815     0.8604 0.104 0.896
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0000     0.8863 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000     0.8863 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0000     0.8863 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0000     0.8863 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000     0.8863 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     2  0.9209     0.4870 0.336 0.664
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.9491     0.1771 0.632 0.368
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.8499     0.5608 0.724 0.276
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.0000     0.8863 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.8863 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0672     0.8036 0.008 0.992
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000     0.8863 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.8863 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.4939     0.7967 0.892 0.108
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000     0.8863 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.8863 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0000     0.8863 1.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.8863 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.9833     0.2064 0.576 0.424
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.4562     0.8016 0.904 0.096
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0672     0.8037 0.008 0.992
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.5737     0.8711 0.136 0.864
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4939     0.7967 0.892 0.108
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.9954     0.0790 0.540 0.460
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.0000     0.8863 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.8267     0.6221 0.260 0.740
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.8863 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     1  0.9944     0.0942 0.544 0.456
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.4298     0.8127 0.912 0.088
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.8863 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.1184     0.8746 0.984 0.016
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.5737     0.8711 0.136 0.864
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5737     0.8711 0.136 0.864
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.8863 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.5842     0.7686 0.860 0.140
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4939     0.7967 0.892 0.108
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.8863 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.5519     0.8702 0.128 0.872
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.5737     0.8711 0.136 0.864
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.9044     0.4763 0.680 0.320
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.5842     0.7686 0.860 0.140
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.8863 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.8863 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.8267     0.6221 0.260 0.740
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.8863 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.9710     0.0518 0.600 0.400
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.7139     0.7028 0.196 0.804
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.8863 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.8863 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.8863 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.9866     0.1799 0.568 0.432
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.5737     0.8711 0.136 0.864
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000     0.8863 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.4562     0.7830 0.096 0.904
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.8863 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.6343     0.8583 0.160 0.840
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.5737     0.8711 0.136 0.864
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.8863 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.8863 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.5737     0.7700 0.864 0.136
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.8863 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.8863 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.9963     0.0634 0.536 0.464
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.8863 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.8863 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.8863 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9775     0.2441 0.588 0.412
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.8863 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.8863 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0000     0.8863 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     2  0.5294     0.7692 0.120 0.880
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.8863 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000     0.8863 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.5519     0.8702 0.128 0.872
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.9323     0.4145 0.652 0.348
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5737     0.8711 0.136 0.864
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4562     0.8016 0.904 0.096
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.6623     0.7273 0.172 0.828
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.5737     0.7700 0.864 0.136
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8863 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.9358     0.4532 0.352 0.648
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.8863 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.5737     0.8711 0.136 0.864
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.8863 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.9963     0.0634 0.536 0.464
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.5842     0.7686 0.860 0.140
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.8863 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.8863 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5737     0.7700 0.864 0.136
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.5737     0.8711 0.136 0.864
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.8863 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4690     0.8038 0.900 0.100
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.8863 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.8863 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.9286     0.4237 0.656 0.344
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.8863 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5178     0.8656 0.116 0.884
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.6623     0.7273 0.172 0.828
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.5519     0.8702 0.128 0.872
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.8863 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.8863 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.8863 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.8863 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0237     0.9470 0.000 0.996 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.5012     0.7046 0.788 0.204 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1491     0.9087 0.016 0.016 0.968
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0592     0.9467 0.000 0.988 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0424     0.9472 0.000 0.992 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.6045     0.3811 0.620 0.000 0.380
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6026     0.3913 0.624 0.000 0.376
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9166 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.9491    -0.1706 0.420 0.184 0.396
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1525     0.9110 0.032 0.004 0.964
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0424     0.9472 0.000 0.992 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.9166 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0424     0.9472 0.000 0.992 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0237     0.9139 0.996 0.000 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.4733     0.7260 0.800 0.004 0.196
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9166 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.6661     0.3299 0.588 0.400 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0892     0.9418 0.000 0.980 0.020
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0592     0.9460 0.000 0.988 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0424     0.9472 0.000 0.992 0.008
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.1031     0.8965 0.000 0.024 0.976
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0424     0.9472 0.000 0.992 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9166 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0424     0.9469 0.000 0.992 0.008
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9166 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0592     0.9462 0.000 0.988 0.012
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3340     0.8420 0.120 0.000 0.880
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.6686     0.3952 0.612 0.372 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.9166 1.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9166 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5560     0.5331 0.700 0.000 0.300
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0424     0.9472 0.000 0.992 0.008
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0892     0.9441 0.000 0.980 0.020
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9166 1.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000     0.9166 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.7063     0.1074 0.516 0.464 0.020
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.1031     0.9421 0.000 0.976 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4346     0.7382 0.816 0.000 0.184
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9166 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.1182     0.9064 0.012 0.012 0.976
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.9166 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0747     0.9062 0.984 0.000 0.016
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1031     0.9421 0.000 0.976 0.024
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9166 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.1170     0.9010 0.976 0.008 0.016
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#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.0000     0.9166 1.000 0.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.0000     0.9166 1.000 0.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.1482     0.9104 0.020 0.012 0.968
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.6079     0.3514 0.000 0.612 0.388
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.0424     0.9472 0.000 0.992 0.008
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0424     0.9469 0.000 0.992 0.008
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     1  0.6330     0.2893 0.600 0.004 0.396
#> A9195281-8CAE-45A8-8493-744E577907FA     1  0.6745     0.2466 0.560 0.428 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.0424     0.9472 0.000 0.992 0.008
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0424     0.9469 0.000 0.992 0.008
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.6498     0.3471 0.596 0.396 0.008
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0424     0.9469 0.000 0.992 0.008
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000     0.9166 1.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0000     0.9166 1.000 0.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.0747     0.9062 0.984 0.000 0.016
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0747     0.9062 0.984 0.000 0.016
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.1482     0.9103 0.020 0.012 0.968
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0892     0.9430 0.000 0.980 0.020
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0424     0.9469 0.000 0.992 0.008
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0424     0.9472 0.000 0.992 0.008
#> 80936433-AA91-4219-98F1-706C36298060     3  0.3192     0.8284 0.000 0.112 0.888
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.6026     0.3957 0.624 0.000 0.376
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0000     0.9166 1.000 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000     0.9166 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000     0.9166 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0592     0.9467 0.000 0.988 0.012
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0000     0.9166 1.000 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000     0.9166 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0000     0.9166 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0747     0.9062 0.984 0.000 0.016
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000     0.9166 1.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1525     0.9110 0.032 0.004 0.964
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.6521    -0.0655 0.500 0.004 0.496
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.6661     0.3299 0.588 0.400 0.012
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.0000     0.9166 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.9166 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     3  0.5835     0.4743 0.000 0.340 0.660
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000     0.9166 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.9166 1.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.3752     0.7795 0.856 0.000 0.144
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000     0.9166 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.9166 1.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0000     0.9166 1.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.9166 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.1453     0.9308 0.024 0.968 0.008
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.4555     0.7162 0.800 0.200 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.1163     0.8963 0.000 0.028 0.972
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0424     0.9469 0.000 0.992 0.008
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4346     0.7382 0.816 0.000 0.184
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.5896     0.5609 0.292 0.700 0.008
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.4452     0.7168 0.808 0.000 0.192
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1399     0.9119 0.028 0.004 0.968
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9166 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1315     0.9346 0.020 0.972 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.4963     0.7089 0.792 0.200 0.008
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.9166 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0000     0.9166 1.000 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0424     0.9472 0.000 0.992 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0424     0.9472 0.000 0.992 0.008
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9166 1.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1411     0.9092 0.036 0.000 0.964
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.3752     0.7797 0.856 0.000 0.144
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9166 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0424     0.9469 0.000 0.992 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0424     0.9469 0.000 0.992 0.008
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.6713     0.2842 0.572 0.416 0.012
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1411     0.9092 0.036 0.000 0.964
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9166 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9166 1.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1399     0.9119 0.028 0.004 0.968
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9166 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.6169     0.3878 0.636 0.004 0.360
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.1337     0.9089 0.016 0.012 0.972
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.9166 1.000 0.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9166 1.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.9166 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1170     0.9382 0.016 0.976 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0892     0.9400 0.000 0.980 0.020
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000     0.9166 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0848     0.9030 0.008 0.008 0.984
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9166 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.2774     0.8734 0.072 0.920 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0424     0.9469 0.000 0.992 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9166 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.9166 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.1411     0.9092 0.036 0.000 0.964
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9166 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9166 1.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1129     0.9415 0.004 0.976 0.020
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9166 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.9166 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9166 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.1267     0.9407 0.004 0.972 0.024
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9166 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9166 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2959     0.8287 0.900 0.000 0.100
#> 1122039D-5785-4F70-9916-17C585453512     3  0.1170     0.9090 0.016 0.008 0.976
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9166 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000     0.9166 1.000 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0592     0.9467 0.000 0.988 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0424     0.9472 0.000 0.992 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0892     0.9422 0.000 0.980 0.020
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4346     0.7359 0.816 0.184 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.1170     0.9090 0.016 0.008 0.976
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.6204     0.2631 0.424 0.000 0.576
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9166 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1525     0.9110 0.032 0.004 0.964
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.9166 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0892     0.9430 0.000 0.980 0.020
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9166 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0661     0.9459 0.004 0.988 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1411     0.9092 0.036 0.000 0.964
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9166 1.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.9166 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2356     0.8850 0.072 0.000 0.928
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1031     0.9435 0.000 0.976 0.024
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9166 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.9166 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9166 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9166 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.6617     0.3444 0.388 0.600 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9166 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.3551     0.8285 0.000 0.868 0.132
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1337     0.9089 0.016 0.012 0.972
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0424     0.9472 0.000 0.992 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9166 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9166 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.9166 1.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9166 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4072    0.43178 0.000 0.748 0.000 0.252
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.7180    0.27129 0.504 0.148 0.000 0.348
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0817    0.85124 0.000 0.000 0.976 0.024
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5511    0.42311 0.000 0.352 0.028 0.620
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.4855    0.67400 0.000 0.400 0.000 0.600
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.6201    0.33339 0.564 0.000 0.376 0.060
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.8397   -0.01309 0.416 0.116 0.400 0.068
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0188    0.86761 0.996 0.000 0.000 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.8887   -0.01449 0.400 0.132 0.368 0.100
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0376    0.85378 0.004 0.000 0.992 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4  0.4382    0.76647 0.000 0.296 0.000 0.704
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0707    0.86460 0.980 0.000 0.000 0.020
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     4  0.4406    0.76535 0.000 0.300 0.000 0.700
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.1474    0.85864 0.948 0.000 0.000 0.052
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6980    0.62056 0.672 0.064 0.168 0.096
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.1635    0.85744 0.948 0.008 0.000 0.044
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.7812    0.05525 0.348 0.256 0.000 0.396
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     4  0.4776    0.75736 0.000 0.272 0.016 0.712
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.4955    0.47496 0.000 0.444 0.000 0.556
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     4  0.4535    0.76739 0.000 0.292 0.004 0.704
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.2469    0.82097 0.000 0.000 0.892 0.108
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.4996   -0.42850 0.000 0.516 0.000 0.484
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.1716    0.86299 0.936 0.000 0.000 0.064
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.5167   -0.38959 0.000 0.508 0.004 0.488
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1716    0.86299 0.936 0.000 0.000 0.064
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     4  0.4647    0.76539 0.000 0.288 0.008 0.704
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.1978    0.82435 0.068 0.000 0.928 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.6819    0.47990 0.604 0.208 0.000 0.188
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2101    0.86366 0.928 0.000 0.012 0.060
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0707    0.86460 0.980 0.000 0.000 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6124    0.53832 0.640 0.000 0.276 0.084
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     4  0.4535    0.76739 0.000 0.292 0.004 0.704
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#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.1854    0.85677 0.940 0.000 0.012 0.048
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1557    0.86603 0.944 0.000 0.000 0.056
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0921    0.86691 0.972 0.000 0.000 0.028
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.7785    0.06376 0.284 0.288 0.000 0.428
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0921    0.86691 0.972 0.000 0.000 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.6637    0.44304 0.000 0.240 0.144 0.616
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0592    0.85126 0.000 0.000 0.984 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F     4  0.4632    0.75372 0.000 0.308 0.004 0.688
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0921    0.86691 0.972 0.000 0.000 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0188    0.86697 0.996 0.000 0.000 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.1792    0.86453 0.932 0.000 0.000 0.068
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0921    0.86691 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4197     0.6065 0.000 0.728 0.000 0.028 0.244
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.5131     0.6053 0.148 0.044 0.000 0.740 0.068
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1356     0.6986 0.000 0.012 0.956 0.028 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.6141     0.5097 0.000 0.156 0.032 0.640 0.172
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.3579     0.7842 0.000 0.072 0.000 0.100 0.828
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.6728     0.0301 0.412 0.016 0.436 0.132 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.7260     0.0447 0.440 0.072 0.372 0.116 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.7955 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.8473     0.0588 0.340 0.120 0.356 0.164 0.020
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1041     0.7026 0.000 0.000 0.964 0.032 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.1410     0.8772 0.000 0.060 0.000 0.000 0.940
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1502     0.7889 0.940 0.000 0.000 0.056 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.1544     0.8766 0.000 0.068 0.000 0.000 0.932
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4149     0.7181 0.792 0.004 0.000 0.080 0.124
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.6956     0.1704 0.412 0.056 0.100 0.432 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.2932     0.7625 0.864 0.020 0.000 0.112 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.5358     0.6095 0.128 0.060 0.000 0.732 0.080
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.1591     0.8706 0.000 0.052 0.004 0.004 0.940
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.6539     0.0548 0.000 0.200 0.000 0.368 0.432
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.1638     0.8788 0.000 0.064 0.000 0.004 0.932
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4622     0.4961 0.000 0.000 0.684 0.276 0.040
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.5977     0.2745 0.000 0.332 0.000 0.128 0.540
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2843     0.7650 0.848 0.000 0.000 0.144 0.008
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.5954     0.4328 0.000 0.592 0.000 0.192 0.216
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.1571     0.8766 0.000 0.060 0.004 0.000 0.936
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3732     0.5996 0.120 0.000 0.820 0.056 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     4  0.6470     0.3552 0.392 0.088 0.000 0.488 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.1864     0.7918 0.924 0.004 0.004 0.068 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1341     0.7904 0.944 0.000 0.000 0.056 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.7117     0.3467 0.480 0.008 0.304 0.188 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.1638     0.8788 0.000 0.064 0.000 0.004 0.932
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.5889     0.5295 0.000 0.108 0.096 0.696 0.100
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2116     0.7858 0.912 0.004 0.000 0.076 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2747     0.7704 0.880 0.004 0.008 0.100 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.6105     0.2616 0.060 0.532 0.000 0.376 0.032
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3809     0.5602 0.000 0.736 0.000 0.256 0.008
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6285     0.4885 0.588 0.012 0.256 0.140 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4576     0.4995 0.000 0.000 0.692 0.268 0.040
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0486     0.7963 0.988 0.004 0.000 0.004 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3506     0.7346 0.832 0.064 0.000 0.104 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.4087     0.5794 0.000 0.756 0.000 0.208 0.036
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.2843     0.7650 0.848 0.000 0.000 0.144 0.008
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.6056     0.2386 0.556 0.156 0.000 0.288 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0162     0.7041 0.000 0.000 0.996 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4622     0.4962 0.000 0.000 0.684 0.276 0.040
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.6080     0.3555 0.328 0.080 0.000 0.568 0.024
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.2669     0.7690 0.876 0.020 0.000 0.104 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.2388     0.8547 0.000 0.072 0.000 0.028 0.900
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.3213     0.7851 0.836 0.004 0.000 0.144 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.2575     0.7792 0.884 0.012 0.004 0.100 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.6187     0.4741 0.000 0.204 0.016 0.608 0.172
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.2681     0.7681 0.876 0.012 0.000 0.108 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.2439     0.7753 0.876 0.000 0.000 0.120 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2233     0.7795 0.892 0.000 0.000 0.104 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2304     0.7185 0.000 0.892 0.000 0.008 0.100
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4040     0.5473 0.000 0.724 0.000 0.260 0.016
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.6465     0.3766 0.560 0.016 0.300 0.116 0.008
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.2927     0.8287 0.000 0.068 0.000 0.060 0.872
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.1043     0.7939 0.960 0.000 0.000 0.040 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.5133     0.3541 0.000 0.568 0.000 0.388 0.044
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.2753     0.7697 0.856 0.000 0.000 0.136 0.008
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0290     0.7953 0.992 0.000 0.000 0.008 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.8675     0.1074 0.364 0.188 0.244 0.192 0.012
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0865     0.7003 0.000 0.000 0.972 0.024 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.1544     0.8769 0.000 0.068 0.000 0.000 0.932
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0703     0.7940 0.976 0.000 0.000 0.024 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3066     0.7884 0.860 0.004 0.012 0.116 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.5638     0.4733 0.000 0.192 0.000 0.636 0.172
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.4908     0.5415 0.156 0.748 0.000 0.068 0.028
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.2361     0.7191 0.000 0.892 0.000 0.012 0.096
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.7673     0.4386 0.000 0.176 0.128 0.500 0.196
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.8241     0.0153 0.404 0.156 0.296 0.136 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.5068     0.3120 0.000 0.000 0.572 0.388 0.040
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.2452     0.6784 0.000 0.016 0.896 0.084 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.3150     0.7735 0.864 0.024 0.000 0.096 0.016
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0324     0.7038 0.000 0.004 0.992 0.004 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.1300     0.6970 0.000 0.000 0.956 0.028 0.016
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.6287     0.1473 0.276 0.528 0.000 0.196 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.1341     0.8739 0.000 0.056 0.000 0.000 0.944
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1082     0.7944 0.964 0.008 0.000 0.028 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.8694     0.0830 0.060 0.408 0.296 0.120 0.116
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.2020     0.7806 0.900 0.000 0.000 0.100 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.1965     0.7204 0.000 0.904 0.000 0.000 0.096
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0324     0.7032 0.000 0.000 0.992 0.004 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.3111     0.7845 0.840 0.004 0.000 0.144 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.2249     0.7194 0.000 0.896 0.000 0.008 0.096
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.3299     0.7854 0.828 0.004 0.000 0.152 0.016
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.2570     0.7694 0.880 0.008 0.000 0.108 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.5050     0.4874 0.024 0.660 0.000 0.292 0.024
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     5  0.1638     0.8788 0.000 0.064 0.000 0.004 0.932
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0613     0.7965 0.984 0.004 0.000 0.008 0.004
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.1410     0.8772 0.000 0.060 0.000 0.000 0.940
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.6700     0.0388 0.000 0.400 0.000 0.356 0.244
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.1638     0.8788 0.000 0.064 0.000 0.004 0.932
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.5588     0.2930 0.020 0.000 0.560 0.380 0.040
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.2522     0.7159 0.000 0.880 0.000 0.012 0.108
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.2886     0.7804 0.864 0.004 0.000 0.116 0.016
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.2843     0.7662 0.848 0.000 0.000 0.144 0.008
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.4735     0.5002 0.172 0.748 0.000 0.064 0.016
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.7870     0.1950 0.000 0.468 0.224 0.152 0.156
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.5431     0.6257 0.696 0.004 0.136 0.156 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.0865     0.7003 0.000 0.000 0.972 0.024 0.004
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.5861     0.4540 0.148 0.012 0.680 0.144 0.016
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.2170     0.7802 0.904 0.004 0.000 0.088 0.004
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.2707     0.7035 0.000 0.860 0.000 0.008 0.132
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.1908     0.7829 0.908 0.000 0.000 0.092 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     5  0.6879     0.0105 0.028 0.384 0.000 0.144 0.444
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.4382     0.5131 0.000 0.688 0.000 0.288 0.024
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.2124     0.7202 0.000 0.900 0.000 0.004 0.096
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.2011     0.7801 0.908 0.000 0.000 0.088 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.7516     0.1213 0.048 0.428 0.000 0.244 0.280
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     5  0.1478     0.8786 0.000 0.064 0.000 0.000 0.936
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.2408     0.7747 0.892 0.004 0.000 0.096 0.008
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.5166     0.5583 0.000 0.692 0.004 0.204 0.100
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     1  0.7045     0.1571 0.424 0.012 0.388 0.164 0.012
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0794     0.7936 0.972 0.000 0.000 0.028 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.4035     0.7770 0.780 0.004 0.012 0.188 0.016
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.2505     0.7202 0.000 0.888 0.000 0.020 0.092
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     3  0.3223     0.6524 0.072 0.004 0.868 0.048 0.008
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     5  0.2233     0.8464 0.000 0.104 0.000 0.004 0.892
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.3835     0.6865 0.744 0.000 0.000 0.244 0.012
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.5507     0.3644 0.596 0.316 0.000 0.088 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.5315     0.5956 0.688 0.148 0.000 0.160 0.004
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.2843     0.7662 0.848 0.000 0.000 0.144 0.008
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.4352     0.5243 0.000 0.000 0.720 0.244 0.036
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.1502     0.7889 0.940 0.000 0.000 0.056 0.004
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     5  0.1478     0.8786 0.000 0.064 0.000 0.000 0.936
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  0.6387     0.4349 0.576 0.012 0.276 0.128 0.008
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.2179     0.7790 0.896 0.000 0.000 0.100 0.004
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#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1116     0.7002 0.000 0.004 0.964 0.028 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.2664     0.7207 0.004 0.884 0.000 0.020 0.092
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.5158     0.6023 0.152 0.040 0.000 0.736 0.072
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.2017     0.7885 0.912 0.000 0.000 0.080 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.5566     0.5574 0.656 0.200 0.000 0.140 0.004
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.1410     0.8772 0.000 0.060 0.000 0.000 0.940
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     5  0.5884     0.2464 0.000 0.352 0.000 0.112 0.536
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.3013     0.7633 0.832 0.000 0.000 0.160 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1651     0.7004 0.008 0.000 0.944 0.036 0.012
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.7084     0.4483 0.488 0.008 0.272 0.216 0.016
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2389     0.7768 0.880 0.000 0.000 0.116 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.2660     0.7062 0.000 0.864 0.000 0.008 0.128
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.4219     0.1936 0.000 0.584 0.000 0.000 0.416
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.5338     0.6106 0.132 0.056 0.000 0.732 0.080
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1041     0.7026 0.000 0.000 0.964 0.032 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2753     0.7697 0.856 0.000 0.000 0.136 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.2237     0.7806 0.904 0.004 0.000 0.084 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0992     0.6995 0.000 0.000 0.968 0.024 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.2054     0.7832 0.916 0.004 0.000 0.072 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.6404     0.3721 0.556 0.008 0.308 0.116 0.012
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0290     0.7032 0.000 0.000 0.992 0.008 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.3631     0.7799 0.804 0.000 0.012 0.172 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0290     0.7953 0.992 0.000 0.000 0.008 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0162     0.7954 0.996 0.000 0.000 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.2700     0.7197 0.004 0.884 0.000 0.024 0.088
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.6733     0.4303 0.000 0.584 0.096 0.240 0.080
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5971     0.4180 0.588 0.292 0.004 0.112 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.5607     0.4388 0.000 0.312 0.604 0.076 0.008
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0963     0.7927 0.964 0.000 0.000 0.036 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.1965     0.8459 0.024 0.052 0.000 0.000 0.924
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.2305     0.7199 0.000 0.896 0.000 0.012 0.092
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.2843     0.7650 0.848 0.000 0.000 0.144 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1502     0.7889 0.940 0.000 0.000 0.056 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2727     0.6693 0.016 0.004 0.884 0.092 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.3123     0.7863 0.828 0.000 0.000 0.160 0.012
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.4731     0.4555 0.000 0.640 0.000 0.328 0.032
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.3013     0.7617 0.832 0.000 0.000 0.160 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.6696     0.2033 0.004 0.468 0.000 0.236 0.292
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.2753     0.7695 0.856 0.000 0.000 0.136 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.2753     0.7689 0.856 0.000 0.000 0.136 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.5335     0.6201 0.704 0.004 0.184 0.096 0.012
#> 1122039D-5785-4F70-9916-17C585453512     3  0.4404     0.5180 0.000 0.000 0.712 0.252 0.036
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.1341     0.7898 0.944 0.000 0.000 0.056 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2804     0.7757 0.880 0.004 0.012 0.096 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.5513     0.4762 0.000 0.180 0.000 0.652 0.168
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.5939     0.5127 0.036 0.084 0.000 0.240 0.640
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.2352     0.7160 0.000 0.896 0.004 0.008 0.092
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.6081     0.2218 0.428 0.036 0.000 0.488 0.048
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.4477     0.5148 0.000 0.000 0.708 0.252 0.040
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5172     0.2396 0.324 0.000 0.616 0.060 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0833     0.7972 0.976 0.004 0.000 0.016 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4609     0.5993 0.072 0.016 0.776 0.132 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.6372     0.4547 0.552 0.260 0.000 0.180 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4874     0.4031 0.000 0.600 0.000 0.368 0.032
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2886     0.7641 0.844 0.000 0.000 0.148 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.2853     0.8345 0.000 0.072 0.000 0.052 0.876
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1757     0.6970 0.012 0.000 0.936 0.048 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.7955 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2295     0.7817 0.900 0.004 0.000 0.088 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.7133     0.3204 0.292 0.052 0.516 0.136 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.5672     0.3343 0.000 0.544 0.000 0.368 0.088
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1202     0.7978 0.960 0.004 0.000 0.032 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2983     0.7795 0.872 0.008 0.012 0.100 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3381     0.7860 0.820 0.004 0.000 0.160 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1121     0.7925 0.956 0.000 0.000 0.044 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.5376     0.6080 0.124 0.064 0.000 0.732 0.080
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1270     0.7926 0.948 0.000 0.000 0.052 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.8196     0.3901 0.000 0.176 0.200 0.416 0.208
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1403     0.6955 0.000 0.000 0.952 0.024 0.024
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.2305     0.8546 0.000 0.092 0.000 0.012 0.896
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0609     0.7943 0.980 0.000 0.000 0.020 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0566     0.7969 0.984 0.000 0.000 0.012 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3648     0.7817 0.792 0.004 0.000 0.188 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1205     0.7941 0.956 0.000 0.000 0.040 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5798    0.46624 0.012 0.620 0.032 0.016 0.264 0.056
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.5590    0.27792 0.072 0.028 0.000 0.220 0.028 0.652
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2668    0.36148 0.000 0.000 0.828 0.168 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.6459    0.25834 0.000 0.088 0.004 0.508 0.088 0.312
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.2963    0.74653 0.000 0.016 0.000 0.004 0.828 0.152
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3957    0.41265 0.284 0.008 0.696 0.004 0.000 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.6237    0.20797 0.356 0.096 0.492 0.004 0.000 0.052
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1075    0.73003 0.952 0.000 0.000 0.000 0.000 0.048
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6414    0.29951 0.296 0.072 0.532 0.004 0.004 0.092
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4531    0.22551 0.036 0.000 0.608 0.352 0.000 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0291    0.87564 0.000 0.004 0.000 0.000 0.992 0.004
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0632    0.71778 0.976 0.000 0.024 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0291    0.87564 0.000 0.004 0.000 0.000 0.992 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4088    0.61737 0.780 0.000 0.100 0.000 0.100 0.020
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.6354    0.36629 0.164 0.044 0.120 0.052 0.000 0.620
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3328    0.60433 0.788 0.012 0.192 0.000 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.5630    0.25605 0.048 0.032 0.000 0.236 0.040 0.644
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0436    0.87312 0.000 0.004 0.000 0.004 0.988 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.6453    0.12886 0.000 0.104 0.000 0.076 0.460 0.360
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0508    0.87592 0.000 0.004 0.000 0.012 0.984 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.3782    0.50378 0.000 0.000 0.224 0.740 0.000 0.036
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.5561    0.42834 0.000 0.200 0.000 0.016 0.608 0.176
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.3390    0.67491 0.704 0.000 0.000 0.000 0.000 0.296
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.6515    0.31411 0.000 0.516 0.000 0.276 0.108 0.100
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3482    0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.0405    0.87611 0.000 0.004 0.000 0.008 0.988 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5083    0.21858 0.100 0.000 0.580 0.320 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.6483    0.43157 0.220 0.084 0.000 0.124 0.008 0.564
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3658    0.70144 0.792 0.000 0.104 0.000 0.000 0.104
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1408    0.72715 0.944 0.000 0.020 0.000 0.000 0.036
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.5712    0.15471 0.340 0.000 0.512 0.000 0.008 0.140
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0508    0.87592 0.000 0.004 0.000 0.012 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.5746    0.25443 0.000 0.044 0.020 0.492 0.028 0.416
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2163    0.68313 0.892 0.000 0.092 0.000 0.000 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3277    0.60634 0.792 0.000 0.188 0.000 0.004 0.016
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     6  0.5235    0.25392 0.004 0.420 0.000 0.060 0.008 0.508
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4955   -0.04182 0.000 0.520 0.000 0.056 0.004 0.420
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.4374    0.08485 0.448 0.000 0.532 0.004 0.000 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3482    0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.4680    0.49483 0.000 0.000 0.264 0.652 0.000 0.084
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0865    0.73016 0.964 0.000 0.000 0.000 0.000 0.036
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.6066    0.13241 0.504 0.064 0.020 0.036 0.000 0.376
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.5028   -0.00288 0.000 0.536 0.000 0.056 0.008 0.400
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3409    0.67277 0.700 0.000 0.000 0.000 0.000 0.300
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     6  0.6091    0.43185 0.216 0.180 0.000 0.040 0.000 0.564
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3619    0.26808 0.000 0.000 0.680 0.316 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.3852    0.48700 0.000 0.004 0.224 0.740 0.000 0.032
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.7236    0.38008 0.176 0.076 0.064 0.132 0.004 0.548
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3385    0.65102 0.808 0.016 0.156 0.000 0.000 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.1493    0.84576 0.000 0.004 0.000 0.004 0.936 0.056
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.3642    0.70495 0.760 0.000 0.036 0.000 0.000 0.204
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3660    0.67462 0.780 0.000 0.160 0.000 0.000 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.6587    0.27315 0.000 0.140 0.000 0.508 0.084 0.268
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.3198    0.61121 0.796 0.008 0.188 0.000 0.000 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.3221    0.68910 0.736 0.000 0.000 0.000 0.000 0.264
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2996    0.70198 0.772 0.000 0.000 0.000 0.000 0.228
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2263    0.71087 0.000 0.896 0.000 0.048 0.056 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.5074   -0.10191 0.000 0.496 0.000 0.056 0.008 0.440
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.4462    0.09342 0.540 0.008 0.436 0.000 0.000 0.016
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.1901    0.82920 0.000 0.004 0.000 0.008 0.912 0.076
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.2979    0.71825 0.840 0.000 0.044 0.000 0.000 0.116
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     6  0.5508    0.27037 0.000 0.400 0.000 0.092 0.012 0.496
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3753    0.67311 0.696 0.004 0.000 0.008 0.000 0.292
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.1858    0.72737 0.904 0.000 0.004 0.000 0.000 0.092
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#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.6916    0.10324 0.400 0.028 0.020 0.108 0.024 0.420
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.4673    0.48862 0.000 0.000 0.272 0.648 0.000 0.080
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.7209    0.00554 0.216 0.000 0.404 0.272 0.000 0.108
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1387    0.73355 0.932 0.000 0.000 0.000 0.000 0.068
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2320    0.44510 0.080 0.000 0.892 0.024 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.7341    0.28747 0.444 0.232 0.128 0.008 0.000 0.188
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     6  0.5308    0.25345 0.000 0.424 0.000 0.088 0.004 0.484
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.3482    0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.1588    0.83368 0.000 0.004 0.000 0.000 0.924 0.072
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4518    0.22388 0.044 0.000 0.604 0.352 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.1075    0.73003 0.952 0.000 0.000 0.000 0.000 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2712    0.66885 0.864 0.000 0.108 0.000 0.012 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3620    0.44394 0.228 0.012 0.752 0.004 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     6  0.5925    0.27080 0.000 0.396 0.000 0.100 0.032 0.472
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1700    0.73513 0.916 0.000 0.004 0.000 0.000 0.080
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3345    0.62690 0.776 0.000 0.204 0.000 0.000 0.020
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4703    0.68226 0.692 0.000 0.096 0.000 0.008 0.204
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2378    0.71919 0.848 0.000 0.000 0.000 0.000 0.152
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.5728    0.25303 0.048 0.032 0.000 0.232 0.048 0.640
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3083    0.71604 0.828 0.000 0.040 0.000 0.000 0.132
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.7387    0.34885 0.000 0.136 0.068 0.524 0.096 0.176
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3817    0.11351 0.000 0.000 0.568 0.432 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.2744    0.79150 0.000 0.072 0.000 0.064 0.864 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2053    0.72441 0.888 0.000 0.004 0.000 0.000 0.108
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0820    0.72491 0.972 0.000 0.012 0.000 0.000 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5268    0.62282 0.620 0.000 0.164 0.000 0.004 0.212
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2416    0.72107 0.844 0.000 0.000 0.000 0.000 0.156

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 17541 rows and 500 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 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 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 0.704           0.808       0.925         0.4982 0.500   0.500
#> 3 3 0.777           0.832       0.932         0.3070 0.756   0.552
#> 4 4 0.772           0.797       0.908         0.1178 0.887   0.690
#> 5 5 0.696           0.644       0.814         0.0662 0.942   0.798
#> 6 6 0.708           0.465       0.740         0.0505 0.898   0.619

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000    0.88900 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.9710    0.31264 0.600 0.400
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.1633    0.87357 0.024 0.976
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000    0.88900 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000    0.88900 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000    0.93329 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.8443    0.58691 0.728 0.272
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000    0.93329 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.8763    0.58698 0.296 0.704
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.9710    0.23892 0.600 0.400
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000    0.88900 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000    0.93329 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.88900 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0000    0.93329 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.9248    0.45148 0.660 0.340
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000    0.93329 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.9710    0.31264 0.600 0.400
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000    0.88900 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000    0.88900 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.88900 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000    0.88900 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.88900 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.93329 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.88900 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000    0.93329 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.88900 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000    0.93329 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.9710    0.31264 0.600 0.400
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000    0.93329 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000    0.93329 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0000    0.93329 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.88900 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0000    0.88900 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000    0.93329 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000    0.93329 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.9710    0.31264 0.600 0.400
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000    0.88900 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000    0.93329 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.93329 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.0000    0.88900 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000    0.93329 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000    0.93329 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.88900 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.93329 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.6973    0.71686 0.812 0.188
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.9710    0.39622 0.400 0.600
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000    0.88900 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.9896    0.20070 0.560 0.440
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000    0.93329 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000    0.88900 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000    0.93329 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000    0.93329 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000    0.88900 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000    0.93329 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000    0.93329 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000    0.93329 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.88900 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.9710    0.32086 0.400 0.600
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.9710    0.23892 0.600 0.400
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.88900 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000    0.93329 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.88900 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000    0.93329 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000    0.93329 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.9460    0.34015 0.636 0.364
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     2  0.9661    0.41318 0.392 0.608
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000    0.88900 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000    0.93329 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0000    0.93329 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000    0.93329 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000    0.88900 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.9850    0.24515 0.428 0.572
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000    0.88900 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000    0.88900 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.9977    0.20026 0.472 0.528
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     2  0.0000    0.88900 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.9881    0.30549 0.436 0.564
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.9248    0.41298 0.660 0.340
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.9710    0.39622 0.400 0.600
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000    0.88900 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.2948    0.88335 0.948 0.052
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000    0.88900 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000    0.93329 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.0000    0.88900 0.000 1.000
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#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000    0.93329 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.9491    0.46155 0.368 0.632
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000    0.93329 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.9710    0.23892 0.600 0.400
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0938    0.88150 0.012 0.988
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000    0.93329 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000    0.93329 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000    0.93329 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.9710    0.32086 0.400 0.600
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0000    0.88900 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.3584    0.86397 0.932 0.068
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000    0.88900 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000    0.93329 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000    0.88900 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.88900 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000    0.93329 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000    0.93329 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0000    0.93329 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.93329 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000    0.93329 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0376    0.88637 0.004 0.996
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000    0.93329 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000    0.93329 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000    0.93329 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.9710    0.32086 0.400 0.600
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000    0.93329 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000    0.93329 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0000    0.93329 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     2  0.0000    0.88900 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000    0.93329 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000    0.93329 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000    0.88900 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000    0.88900 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000    0.88900 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.8144    0.61828 0.748 0.252
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.0000    0.88900 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000    0.93329 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000    0.93329 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.9710    0.39622 0.400 0.600
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000    0.93329 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000    0.88900 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000    0.93329 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3879    0.83014 0.076 0.924
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000    0.93329 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000    0.93329 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000    0.93329 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.2778    0.88613 0.952 0.048
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.88900 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000    0.93329 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000    0.93329 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000    0.93329 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000    0.93329 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.9963    0.13352 0.464 0.536
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000    0.93329 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000    0.88900 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.1184    0.87889 0.016 0.984
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.88900 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000    0.93329 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000    0.93329 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000    0.93329 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000    0.93329 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9334 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.6095     0.3145 0.608 0.392 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8825 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.9334 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9334 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000     0.8825 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.4842     0.6576 0.224 0.000 0.776
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9315 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.8631     0.5600 0.220 0.180 0.600
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000     0.8825 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.9334 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.9315 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9334 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.3038     0.8257 0.896 0.104 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6126     0.3364 0.600 0.000 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9315 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.6126     0.3656 0.400 0.600 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.2537     0.8556 0.000 0.920 0.080
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000     0.9334 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9334 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000     0.8825 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9334 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9315 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9334 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9315 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9334 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.8825 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.6274     0.2039 0.456 0.544 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4555     0.7140 0.800 0.000 0.200
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9315 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.6095     0.4082 0.392 0.000 0.608
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9334 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0747     0.9195 0.000 0.984 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9315 1.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.4504     0.7119 0.804 0.000 0.196
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5926     0.4678 0.356 0.644 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9334 0.000 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000     0.8825 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9315 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.0000     0.8825 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.9315 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9315 1.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9334 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9315 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.4399     0.7218 0.812 0.188 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.8825 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000     0.8825 0.000 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.6912     0.2147 0.444 0.540 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000     0.9315 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9334 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9315 1.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4555     0.7140 0.800 0.000 0.200
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.9334 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.1753     0.8898 0.952 0.000 0.048
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9315 1.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000     0.9315 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9334 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9334 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.6126     0.3918 0.400 0.000 0.600
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9334 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000     0.9315 1.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9334 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.9315 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000     0.9315 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.0000     0.8825 0.000 0.000 1.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000     0.8825 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.9334 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.9315 1.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5621     0.5350 0.692 0.000 0.308
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.9315 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9334 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.6111     0.3757 0.396 0.604 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9334 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.9334 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000     0.8825 0.000 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.0000     0.8825 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.8825 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6168     0.3064 0.412 0.588 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.8825 0.000 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.8825 0.000 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.1643     0.8907 0.956 0.044 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.1031     0.9127 0.000 0.976 0.024
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000     0.9315 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.5497     0.5537 0.000 0.708 0.292
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0000     0.9315 1.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9334 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.9315 1.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.8825 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000     0.9315 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.9334 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000     0.9315 1.000 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0000     0.9315 1.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.2959     0.8342 0.100 0.900 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9334 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.9315 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.0000     0.9334 0.000 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9334 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9334 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.4121     0.7311 0.168 0.000 0.832
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.9334 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0000     0.9315 1.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.9315 1.000 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.4291     0.7320 0.180 0.820 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.9334 0.000 1.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.6045     0.3836 0.620 0.000 0.380
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#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9315 1.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8825 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9315 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.6126     0.3918 0.400 0.000 0.600
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8825 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4504     0.7119 0.804 0.000 0.196
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9315 1.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.9315 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000     0.9334 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0000     0.9334 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.4483     0.7830 0.848 0.024 0.128
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0000     0.8825 0.000 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9315 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9334 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9334 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9315 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.9315 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.8825 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9315 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9315 1.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000     0.9334 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9315 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.9315 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9315 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000     0.9334 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9315 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9315 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.6111     0.2695 0.604 0.000 0.396
#> 1122039D-5785-4F70-9916-17C585453512     3  0.0000     0.8825 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9315 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4555     0.7058 0.800 0.000 0.200
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.9334 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9334 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9334 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4931     0.6629 0.768 0.232 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0000     0.8825 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.4842     0.6576 0.224 0.000 0.776
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9315 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.8825 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.9315 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9334 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9315 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9334 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.8825 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9315 1.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.9315 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000     0.8825 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9334 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9315 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4555     0.7140 0.800 0.000 0.200
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9315 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9315 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.4605     0.7148 0.204 0.796 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9315 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9334 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8825 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9334 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9315 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9315 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4555     0.7058 0.800 0.000 0.200
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9315 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0817     0.8814 0.000 0.976 0.000 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.6592     0.1103 0.524 0.392 0.000 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.2081     0.8636 0.000 0.916 0.000 0.084
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0336     0.8849 0.000 0.992 0.000 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.4855     0.2612 0.000 0.000 0.600 0.400
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.7130     0.4662 0.200 0.008 0.596 0.196
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.4877     0.2955 0.408 0.592 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.5816     0.2839 0.572 0.000 0.392 0.036
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4331     0.5670 0.712 0.000 0.000 0.288
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.5938     0.6311 0.232 0.676 0.000 0.092
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0188     0.8857 0.000 0.996 0.004 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1118     0.8768 0.000 0.964 0.000 0.036
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0188     0.8864 0.000 0.996 0.000 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1792     0.8633 0.000 0.932 0.000 0.068
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.6446     0.4937 0.328 0.584 0.000 0.088
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3610     0.7087 0.800 0.000 0.200 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4855     0.3726 0.400 0.000 0.600 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.2466     0.8577 0.000 0.900 0.004 0.096
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2760     0.8076 0.872 0.000 0.128 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.0336     0.8820 0.000 0.008 0.000 0.992
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     4  0.0000     0.8832 0.000 0.000 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.0376     0.8460 0.000 0.004 0.992 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1022     0.9107 0.968 0.000 0.000 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     4  0.1118     0.8844 0.000 0.036 0.000 0.964
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.1474     0.8569 0.052 0.000 0.000 0.948
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.6429     0.6235 0.232 0.660 0.012 0.096
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3873     0.6743 0.772 0.000 0.000 0.228
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3610     0.7087 0.800 0.000 0.200 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.2011     0.8633 0.000 0.920 0.000 0.080
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.2845     0.8454 0.896 0.000 0.076 0.028
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0592     0.9206 0.984 0.000 0.000 0.016
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     4  0.1211     0.8855 0.000 0.040 0.000 0.960
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     4  0.0000     0.8832 0.000 0.000 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.4855     0.3726 0.400 0.000 0.600 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0592     0.8825 0.000 0.984 0.000 0.016
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3688     0.7655 0.000 0.792 0.000 0.208
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.4356     0.4964 0.000 0.000 0.708 0.292
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0469     0.8831 0.000 0.988 0.000 0.012
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4356     0.5591 0.708 0.000 0.292 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.2149     0.8618 0.000 0.912 0.000 0.088
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.0895     0.8878 0.004 0.020 0.000 0.976
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     4  0.4134     0.6244 0.000 0.260 0.000 0.740
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.1978     0.8666 0.000 0.928 0.004 0.068
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3726     0.6432 0.000 0.000 0.788 0.212
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.1510     0.8257 0.000 0.016 0.956 0.028
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.7726     0.1736 0.260 0.444 0.000 0.296
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     4  0.0000     0.8832 0.000 0.000 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1302     0.8969 0.956 0.000 0.000 0.044
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.5279     0.6787 0.000 0.736 0.192 0.072
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     4  0.1022     0.8876 0.000 0.032 0.000 0.968
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     4  0.1022     0.8876 0.000 0.032 0.000 0.968
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     4  0.0188     0.8828 0.000 0.004 0.000 0.996
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.9315 1.000 0.000 0.000 0.000
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#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     4  0.4163     0.7330 0.000 0.020 0.188 0.792
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4  0.3764     0.7080 0.216 0.000 0.000 0.784
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     4  0.4134     0.6578 0.260 0.000 0.000 0.740
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     4  0.0817     0.8878 0.000 0.024 0.000 0.976
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.6454     0.2648 0.572 0.344 0.000 0.084
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.3907     0.7218 0.000 0.768 0.000 0.232
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4843     0.3350 0.604 0.000 0.396 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     4  0.0921     0.8879 0.000 0.028 0.000 0.972
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.4888     0.3434 0.412 0.000 0.588 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     4  0.0921     0.8879 0.000 0.028 0.000 0.972
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.5489     0.6346 0.240 0.700 0.000 0.060
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     4  0.4327     0.6916 0.216 0.016 0.000 0.768
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     4  0.4605     0.4680 0.000 0.336 0.000 0.664
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.4925     0.2876 0.000 0.572 0.000 0.428
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.5128     0.7326 0.148 0.760 0.000 0.092
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.4855     0.3726 0.400 0.000 0.600 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.2973     0.7880 0.856 0.000 0.144 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     4  0.0817     0.8878 0.000 0.024 0.000 0.976
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.2334     0.8578 0.000 0.908 0.004 0.088
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     4  0.4008     0.6807 0.244 0.000 0.000 0.756
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.2149     0.7840 0.000 0.000 0.912 0.088
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     4  0.1022     0.8876 0.000 0.032 0.000 0.968
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0336     0.8820 0.000 0.008 0.000 0.992
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0188     0.9289 0.996 0.000 0.000 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0592     0.9207 0.984 0.000 0.000 0.016
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.3219     0.7857 0.000 0.836 0.000 0.164
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4643     0.4232 0.656 0.000 0.344 0.000
#> 1122039D-5785-4F70-9916-17C585453512     3  0.0188     0.8479 0.000 0.000 0.996 0.004
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.2704     0.8125 0.876 0.000 0.124 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.2345     0.8569 0.000 0.900 0.000 0.100
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0817     0.8794 0.000 0.976 0.000 0.024
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     4  0.1022     0.8876 0.000 0.032 0.000 0.968
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.6396     0.3772 0.380 0.548 0.000 0.072
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0188     0.8479 0.000 0.000 0.996 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.4431     0.5240 0.304 0.000 0.696 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     4  0.2345     0.8263 0.100 0.000 0.000 0.900
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     4  0.3444     0.6980 0.000 0.184 0.000 0.816
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0336     0.8849 0.000 0.992 0.000 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0188     0.9289 0.996 0.004 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2345     0.8567 0.000 0.900 0.000 0.100
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3610     0.7087 0.800 0.000 0.200 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.4426     0.7888 0.096 0.812 0.000 0.092
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.1978     0.8666 0.000 0.928 0.004 0.068
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8498 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.8871 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9315 1.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.2149     0.8529 0.912 0.000 0.088 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9315 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.1043     0.8339 0.000 0.040 0.000 0.000 0.960
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4191     0.6762 0.012 0.044 0.000 0.784 0.160
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4885     0.6136 0.000 0.056 0.000 0.668 0.276
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1197     0.7157 0.048 0.000 0.952 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.4557     0.2229 0.000 0.404 0.584 0.012 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.7903 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.7014     0.4024 0.052 0.224 0.560 0.160 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.7903 1.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3519     0.5667 0.216 0.000 0.000 0.008 0.776
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.4690     0.5003 0.048 0.004 0.240 0.708 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.1830     0.7466 0.924 0.068 0.000 0.008 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4510     0.6789 0.008 0.056 0.000 0.752 0.184
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0162     0.8616 0.000 0.000 0.004 0.000 0.996
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.3835     0.5179 0.000 0.008 0.000 0.260 0.732
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4161     0.2268 0.000 0.000 0.608 0.392 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.3636     0.7660 0.728 0.000 0.000 0.272 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.5409     0.4033 0.000 0.304 0.000 0.084 0.612
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3774     0.7575 0.704 0.000 0.000 0.296 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     4  0.7332     0.4094 0.292 0.056 0.000 0.476 0.176
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2358     0.7386 0.888 0.000 0.104 0.008 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0162     0.7909 0.996 0.000 0.000 0.004 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.5787     0.4007 0.152 0.000 0.608 0.240 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4769     0.6328 0.000 0.056 0.000 0.688 0.256
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0290     0.7884 0.992 0.000 0.000 0.008 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3427     0.6018 0.796 0.000 0.192 0.012 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.3838     0.6288 0.000 0.716 0.000 0.280 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3395     0.6683 0.000 0.764 0.000 0.236 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3774     0.7575 0.704 0.000 0.000 0.296 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4235     0.1543 0.000 0.000 0.576 0.424 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.7903 1.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3366     0.7250 0.784 0.004 0.000 0.212 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.3612     0.6717 0.000 0.764 0.000 0.228 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3636     0.7660 0.728 0.000 0.000 0.272 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.4465     0.5878 0.024 0.672 0.000 0.304 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4101     0.2709 0.000 0.000 0.628 0.372 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.3359     0.6634 0.000 0.052 0.000 0.840 0.108
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.1502     0.7616 0.940 0.056 0.000 0.004 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.0000     0.8656 0.000 0.000 0.000 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.3730     0.7608 0.712 0.000 0.000 0.288 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.2077     0.7475 0.908 0.000 0.084 0.008 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.4983     0.6155 0.000 0.064 0.000 0.664 0.272
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.2068     0.7269 0.904 0.004 0.092 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.2966     0.7864 0.816 0.000 0.000 0.184 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.3684     0.7634 0.720 0.000 0.000 0.280 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0290     0.7830 0.000 0.992 0.000 0.000 0.008
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#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4233     0.6717 0.000 0.044 0.000 0.748 0.208
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0510     0.7921 0.984 0.000 0.000 0.016 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     5  0.5830     0.1096 0.000 0.072 0.012 0.364 0.552
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.7383 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.0404     0.8573 0.000 0.012 0.000 0.000 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0162     0.7909 0.996 0.000 0.000 0.004 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1197     0.7922 0.952 0.000 0.000 0.048 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.6692     0.4213 0.432 0.000 0.272 0.296 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2648     0.7892 0.848 0.000 0.000 0.152 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0806    0.91527 0.000 0.008 0.000 0.020 0.972 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.1138    0.63068 0.000 0.004 0.000 0.960 0.024 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0291    0.75863 0.004 0.000 0.992 0.004 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1219    0.62919 0.000 0.004 0.000 0.948 0.048 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1753    0.72364 0.084 0.000 0.912 0.000 0.000 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.5554    0.22201 0.012 0.392 0.520 0.016 0.000 0.060
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     6  0.3860    0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6396    0.38109 0.052 0.220 0.528 0.000 0.000 0.200
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1700    0.71842 0.080 0.000 0.916 0.004 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     6  0.3860    0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3351    0.58308 0.288 0.000 0.000 0.000 0.712 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.7028    0.42230 0.208 0.000 0.196 0.472 0.000 0.124
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4663    0.00477 0.492 0.032 0.004 0.000 0.000 0.472
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.1116    0.63144 0.000 0.004 0.000 0.960 0.028 0.008
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.3797    0.25236 0.000 0.000 0.000 0.420 0.580 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.3797    0.19613 0.000 0.000 0.580 0.420 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.0458    0.53055 0.016 0.000 0.000 0.000 0.000 0.984
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.5887    0.23035 0.000 0.464 0.000 0.224 0.312 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0291    0.53193 0.004 0.000 0.000 0.004 0.000 0.992
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0508    0.75557 0.012 0.000 0.984 0.004 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     4  0.5542    0.43738 0.280 0.000 0.000 0.560 0.004 0.156
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     6  0.5399    0.08409 0.344 0.000 0.128 0.000 0.000 0.528
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> 97C34F1F-2002-4771-8D99-511EA08591CD     6  0.6086   -0.09334 0.280 0.000 0.336 0.000 0.000 0.384
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0858    0.63091 0.000 0.004 0.000 0.968 0.028 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3390    0.46900 0.704 0.000 0.000 0.000 0.000 0.296
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3892    0.51804 0.752 0.000 0.060 0.000 0.000 0.188
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.5989    0.11043 0.244 0.328 0.000 0.428 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.6016    0.03960 0.244 0.404 0.000 0.352 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0436    0.75828 0.004 0.000 0.988 0.004 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.3862    0.04481 0.000 0.000 0.476 0.524 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3860    0.04632 0.528 0.000 0.000 0.000 0.000 0.472
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5189   -0.07252 0.468 0.000 0.000 0.088 0.000 0.444
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.6138    0.04159 0.244 0.404 0.000 0.348 0.004 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.0458    0.53055 0.016 0.000 0.000 0.000 0.000 0.984
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.7490    0.19914 0.260 0.204 0.000 0.368 0.000 0.168
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0146    0.75877 0.000 0.000 0.996 0.004 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.3742    0.34807 0.000 0.004 0.648 0.348 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.3602    0.53695 0.208 0.000 0.000 0.760 0.000 0.032
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4468   -0.03335 0.488 0.020 0.004 0.000 0.000 0.488
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.3288    0.27884 0.276 0.000 0.000 0.000 0.000 0.724
#> 4379559E-E467-49BD-9673-40A486146A3B     6  0.5265    0.03766 0.400 0.000 0.100 0.000 0.000 0.500
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.1333    0.62821 0.000 0.008 0.000 0.944 0.048 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5027    0.07855 0.488 0.004 0.060 0.000 0.000 0.448
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.1957    0.48465 0.112 0.000 0.000 0.000 0.000 0.888
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.0937    0.52468 0.040 0.000 0.000 0.000 0.000 0.960
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.6004    0.06556 0.244 0.416 0.000 0.340 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.4828    0.16643 0.500 0.000 0.452 0.004 0.000 0.044
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     6  0.3975    0.12753 0.452 0.000 0.004 0.000 0.000 0.544
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     4  0.7010    0.32551 0.224 0.096 0.000 0.452 0.228 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.0291    0.53016 0.004 0.000 0.000 0.004 0.000 0.992
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.3691    0.55090 0.204 0.020 0.764 0.012 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0291    0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     6  0.3854    0.11589 0.464 0.000 0.000 0.000 0.000 0.536
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     6  0.3670    0.33385 0.024 0.000 0.240 0.000 0.000 0.736
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.2389    0.60009 0.000 0.008 0.000 0.864 0.128 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.0363    0.74300 0.012 0.988 0.000 0.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.2178    0.65871 0.000 0.868 0.000 0.000 0.132 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.3852    0.48456 0.000 0.016 0.012 0.732 0.240 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.5515    0.11222 0.372 0.136 0.492 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.3782    0.17908 0.000 0.000 0.412 0.588 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0363    0.75710 0.012 0.000 0.988 0.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6111    0.07932 0.324 0.372 0.000 0.000 0.304 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0146    0.75877 0.000 0.000 0.996 0.004 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0508    0.75645 0.000 0.004 0.984 0.012 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.6249    0.13429 0.248 0.444 0.000 0.296 0.000 0.012
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     6  0.3857    0.11324 0.468 0.000 0.000 0.000 0.000 0.532
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.6986    0.18537 0.016 0.404 0.268 0.032 0.280 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     6  0.3101    0.36996 0.244 0.000 0.000 0.000 0.000 0.756
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000    0.75894 0.000 0.000 1.000 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     6  0.3221    0.28844 0.264 0.000 0.000 0.000 0.000 0.736
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     6  0.3288    0.27884 0.276 0.000 0.000 0.000 0.000 0.724
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.4663    0.01376 0.492 0.004 0.032 0.000 0.000 0.472
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.6023    0.01477 0.244 0.392 0.000 0.364 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     6  0.3862    0.07862 0.476 0.000 0.000 0.000 0.000 0.524
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     4  0.5716    0.14026 0.164 0.000 0.000 0.444 0.392 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.3843    0.09698 0.000 0.000 0.452 0.548 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.2823    0.59838 0.000 0.796 0.000 0.000 0.204 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     6  0.3244    0.28552 0.268 0.000 0.000 0.000 0.000 0.732
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0146    0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.5529    0.42053 0.000 0.600 0.036 0.084 0.280 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     6  0.3189    0.34605 0.000 0.000 0.236 0.004 0.000 0.760
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.0405    0.75834 0.004 0.000 0.988 0.008 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.3448    0.47783 0.004 0.000 0.716 0.280 0.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     6  0.3868    0.05044 0.492 0.000 0.000 0.000 0.000 0.508
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.3076    0.56215 0.000 0.760 0.000 0.000 0.240 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     6  0.3531    0.27495 0.328 0.000 0.000 0.000 0.000 0.672
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.6023    0.01477 0.244 0.392 0.000 0.364 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     6  0.3864    0.08816 0.480 0.000 0.000 0.000 0.000 0.520
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     5  0.7235    0.01712 0.216 0.144 0.000 0.204 0.436 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.3221    0.48218 0.736 0.000 0.000 0.000 0.000 0.264
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.5601    0.34874 0.000 0.544 0.000 0.208 0.248 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.4941    0.35106 0.072 0.000 0.552 0.000 0.000 0.376
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     6  0.3851    0.12210 0.460 0.000 0.000 0.000 0.000 0.540
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     6  0.5046    0.14745 0.280 0.000 0.112 0.000 0.000 0.608
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0146    0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     3  0.2520    0.65875 0.152 0.000 0.844 0.004 0.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     5  0.0458    0.92435 0.000 0.016 0.000 0.000 0.984 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     4  0.5624    0.24566 0.000 0.000 0.148 0.456 0.000 0.396
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.1649    0.71955 0.036 0.932 0.000 0.000 0.000 0.032
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.5447    0.23970 0.664 0.180 0.000 0.092 0.000 0.064
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.3860    0.06590 0.000 0.000 0.528 0.472 0.000 0.000
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#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0935    0.72692 0.000 0.964 0.032 0.004 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     6  0.5446    0.00778 0.144 0.316 0.000 0.000 0.000 0.540
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     6  0.3421    0.30106 0.256 0.000 0.008 0.000 0.000 0.736
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3163    0.57560 0.232 0.000 0.764 0.000 0.000 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A     6  0.5464    0.13991 0.204 0.224 0.000 0.000 0.000 0.572
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     6  0.3531    0.24917 0.328 0.000 0.000 0.000 0.000 0.672
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.3515    0.41300 0.676 0.000 0.000 0.000 0.000 0.324
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0146    0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.2806    0.58311 0.000 0.004 0.000 0.844 0.016 0.136
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.3966    0.21916 0.000 0.444 0.552 0.004 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.3637    0.60540 0.000 0.780 0.000 0.056 0.164 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     6  0.5408    0.11163 0.104 0.000 0.384 0.004 0.000 0.508
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.4700    0.13912 0.500 0.000 0.456 0.000 0.000 0.044
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0291    0.75880 0.004 0.000 0.992 0.004 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0146    0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.1321    0.62928 0.000 0.004 0.000 0.952 0.024 0.020
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     6  0.2260    0.47315 0.140 0.000 0.000 0.000 0.000 0.860
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.6341    0.34110 0.092 0.544 0.004 0.084 0.000 0.276
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     6  0.0000    0.53184 0.000 0.000 0.000 0.000 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1753    0.71555 0.084 0.000 0.912 0.004 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.5165    0.45130 0.268 0.000 0.612 0.004 0.000 0.116
#> 887E7408-C7D7-420F-A763-0EE70A316D17     6  0.0291    0.53172 0.004 0.000 0.000 0.004 0.000 0.992
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.2597    0.62253 0.000 0.824 0.000 0.000 0.176 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.3765    0.26854 0.000 0.596 0.000 0.000 0.404 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.1116    0.63144 0.000 0.004 0.000 0.960 0.028 0.008
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0291    0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.3266    0.47486 0.728 0.000 0.000 0.000 0.000 0.272
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0405    0.75834 0.004 0.000 0.988 0.008 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.3464    0.42642 0.688 0.000 0.000 0.000 0.000 0.312
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.4389    0.42040 0.660 0.000 0.288 0.000 0.000 0.052
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0405    0.75834 0.004 0.000 0.988 0.008 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     6  0.3776    0.30111 0.048 0.000 0.196 0.000 0.000 0.756
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0146    0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     4  0.4798    0.50493 0.000 0.148 0.032 0.720 0.100 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.4384    0.07174 0.520 0.460 0.004 0.000 0.000 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1951    0.72082 0.016 0.076 0.908 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     6  0.3847    0.12783 0.456 0.000 0.000 0.000 0.000 0.544
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.0405    0.53170 0.008 0.000 0.000 0.004 0.000 0.988
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     6  0.3860    0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0291    0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.0000    0.53184 0.000 0.000 0.000 0.000 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     6  0.0260    0.52977 0.008 0.000 0.000 0.000 0.000 0.992
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.5969    0.13412 0.244 0.316 0.000 0.440 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.0458    0.52610 0.000 0.000 0.000 0.016 0.000 0.984
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.2092    0.44663 0.000 0.000 0.000 0.124 0.000 0.876
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.0146    0.53187 0.004 0.000 0.000 0.000 0.000 0.996
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.7463   -0.09481 0.212 0.196 0.000 0.200 0.392 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.0000    0.53184 0.000 0.000 0.000 0.000 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4462    0.50316 0.712 0.000 0.136 0.000 0.000 0.152
#> 1122039D-5785-4F70-9916-17C585453512     4  0.3867    0.01519 0.000 0.000 0.488 0.512 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4203    0.51279 0.716 0.000 0.068 0.000 0.000 0.216
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.1152    0.62982 0.000 0.004 0.000 0.952 0.044 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.1387    0.87083 0.000 0.000 0.000 0.068 0.932 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000    0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.1636    0.62643 0.000 0.004 0.000 0.936 0.024 0.036
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.3867    0.01519 0.000 0.000 0.488 0.512 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3874    0.33442 0.000 0.000 0.636 0.008 0.000 0.356
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3634    0.39095 0.644 0.000 0.000 0.000 0.000 0.356
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0458    0.75600 0.016 0.000 0.984 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.6259    0.21855 0.208 0.436 0.000 0.016 0.000 0.340
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     4  0.5911    0.14509 0.228 0.316 0.000 0.456 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0146    0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.0000    0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0291    0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     6  0.3860    0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3911    0.49197 0.712 0.000 0.000 0.000 0.032 0.256
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1531    0.73714 0.068 0.004 0.928 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     4  0.6964    0.22355 0.228 0.252 0.000 0.440 0.080 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3828    0.25619 0.560 0.000 0.000 0.000 0.000 0.440
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5731    0.31435 0.508 0.000 0.204 0.000 0.000 0.288
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.3309    0.27460 0.280 0.000 0.000 0.000 0.000 0.720
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.3847    0.12783 0.456 0.000 0.000 0.000 0.000 0.544
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.1116    0.63144 0.000 0.004 0.000 0.960 0.028 0.008
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     6  0.3955    0.14605 0.436 0.000 0.004 0.000 0.000 0.560
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.4582    0.43104 0.000 0.024 0.032 0.672 0.272 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0260    0.75827 0.000 0.000 0.992 0.008 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.0363    0.92712 0.000 0.012 0.000 0.000 0.988 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     6  0.3857    0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.3672    0.19962 0.368 0.000 0.000 0.000 0.000 0.632
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.4953    0.16454 0.268 0.000 0.108 0.000 0.000 0.624
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.3266    0.33819 0.272 0.000 0.000 0.000 0.000 0.728

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 17541 rows and 500 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 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 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 0.299           0.671       0.811         0.4520 0.524   0.524
#> 3 3 0.454           0.749       0.848         0.4033 0.653   0.428
#> 4 4 0.523           0.695       0.824         0.0980 0.948   0.850
#> 5 5 0.558           0.601       0.778         0.0710 0.953   0.849
#> 6 6 0.597           0.550       0.717         0.0657 0.865   0.554

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.9358     0.7203 0.352 0.648
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.2043     0.7110 0.032 0.968
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.0000     0.7857 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.2043     0.6979 0.032 0.968
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.7001 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.7857 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.1633     0.7824 0.976 0.024
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.8608     0.7554 0.284 0.716
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.9460     0.7096 0.364 0.636
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.5946     0.6606 0.856 0.144
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3431     0.7145 0.064 0.936
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.8608     0.7554 0.284 0.716
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1414     0.6999 0.020 0.980
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.8861     0.7487 0.304 0.696
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.9323     0.5675 0.652 0.348
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.9427     0.7131 0.360 0.640
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0000     0.7001 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.8661     0.3647 0.288 0.712
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000     0.7001 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.3733     0.6806 0.072 0.928
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.7674     0.6170 0.776 0.224
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.7001 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     2  0.8608     0.7554 0.284 0.716
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.4022     0.6772 0.080 0.920
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     2  0.2778     0.7152 0.048 0.952
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.4022     0.6772 0.080 0.920
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.7857 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.8499     0.7577 0.276 0.724
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3879     0.7634 0.924 0.076
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     2  0.8608     0.7554 0.284 0.716
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0672     0.7856 0.992 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.4022     0.6772 0.080 0.920
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.9491     0.5550 0.632 0.368
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.8861     0.7487 0.304 0.696
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.8861     0.7487 0.304 0.696
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.2603     0.7131 0.044 0.956
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.9209     0.3425 0.664 0.336
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.2778     0.7728 0.952 0.048
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.9963     0.1279 0.536 0.464
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.7950     0.6006 0.760 0.240
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.8608     0.7554 0.284 0.716
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.9993    -0.2131 0.516 0.484
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.9044     0.7118 0.320 0.680
#> 60EE5A75-84EC-419D-9540-0864A98EA293     2  0.8608     0.7554 0.284 0.716
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.8555     0.7566 0.280 0.720
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.7857 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.8608     0.5649 0.716 0.284
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.2948     0.7171 0.052 0.948
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  0.9044     0.7382 0.320 0.680
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.7001 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.8861     0.7487 0.304 0.696
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3879     0.7634 0.924 0.076
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.6148     0.5947 0.152 0.848
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.7883     0.5990 0.764 0.236
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.8499     0.5534 0.724 0.276
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.8443     0.7587 0.272 0.728
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.9323     0.6813 0.348 0.652
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0672     0.7057 0.008 0.992
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.9460     0.7096 0.364 0.636
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.7001 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.4298     0.7567 0.912 0.088
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.4022     0.6772 0.080 0.920
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.8608     0.7554 0.284 0.716
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.8608     0.7554 0.284 0.716
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.8713     0.3150 0.708 0.292
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0000     0.7857 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.4298     0.6948 0.088 0.912
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.8608     0.7554 0.284 0.716
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3584     0.7644 0.932 0.068
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     2  0.9170     0.6990 0.332 0.668
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.7001 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.9970    -0.3449 0.532 0.468
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.4022     0.6772 0.080 0.920
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.4022     0.6772 0.080 0.920
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.0672     0.7856 0.992 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.8909     0.5951 0.692 0.308
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.0000     0.7857 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9358     0.7203 0.352 0.648
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.0000     0.7857 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.0376     0.7853 0.996 0.004
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.9522     0.2878 0.628 0.372
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.4022     0.6772 0.080 0.920
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.8608     0.7554 0.284 0.716
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.8909     0.7220 0.308 0.692
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     2  0.8555     0.7567 0.280 0.720
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.8909     0.7216 0.308 0.692
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     2  0.7299     0.5287 0.204 0.796
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     1  0.0000     0.7857 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.9635     0.2337 0.612 0.388
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.7815     0.6200 0.768 0.232
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     2  0.8608     0.7554 0.284 0.716
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.7528     0.6031 0.784 0.216
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.8608     0.7554 0.284 0.716
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.3114     0.6882 0.056 0.944
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     2  0.8608     0.7554 0.284 0.716
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.2948     0.7134 0.052 0.948
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0672     0.7006 0.008 0.992
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.5178     0.7062 0.116 0.884
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.8909     0.5951 0.692 0.308
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.4022     0.6772 0.080 0.920
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     2  0.8608     0.7554 0.284 0.716
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     2  0.8608     0.7554 0.284 0.716
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.9460     0.7096 0.364 0.636
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.4022     0.6772 0.080 0.920
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.3584     0.7644 0.932 0.068
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.0376     0.7853 0.996 0.004
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.8081     0.6010 0.752 0.248
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.7674     0.6190 0.776 0.224
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.4022     0.6772 0.080 0.920
#> C44C898C-EEF9-4E03-911A-9D951312C380     2  0.8608     0.7554 0.284 0.716
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.0672     0.7037 0.008 0.992
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.7376     0.7592 0.208 0.792
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     1  0.9710     0.2505 0.600 0.400
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     2  0.8608     0.7554 0.284 0.716
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0672     0.7037 0.008 0.992
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.4022     0.6772 0.080 0.920
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     2  0.9209     0.7320 0.336 0.664
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.4022     0.6772 0.080 0.920
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     1  0.7139     0.6184 0.804 0.196
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     2  0.8608     0.7554 0.284 0.716
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.8207     0.5626 0.744 0.256
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     2  0.9661     0.5889 0.392 0.608
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.7950     0.7538 0.240 0.760
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.8861     0.2715 0.696 0.304
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.8608     0.7208 0.284 0.716
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.9896     0.4544 0.560 0.440
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.8608     0.7554 0.284 0.716
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     2  0.8608     0.7554 0.284 0.716
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     2  0.8713     0.7489 0.292 0.708
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.7950     0.6006 0.760 0.240
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     2  0.8608     0.7554 0.284 0.716
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.3879     0.6868 0.076 0.924
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.9460     0.7096 0.364 0.636
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.6438     0.6975 0.836 0.164
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     2  0.8763     0.7452 0.296 0.704
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     1  0.0376     0.7853 0.996 0.004
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.8909     0.5951 0.692 0.308
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.4022     0.6772 0.080 0.920
#> CBEFE77E-A0EB-457D-A145-763654236EBB     2  0.8608     0.7554 0.284 0.716
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.4161     0.6794 0.084 0.916
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     1  0.0000     0.7857 1.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.8909     0.7468 0.308 0.692
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     1  0.2603     0.7662 0.956 0.044
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.9608     0.6273 0.384 0.616
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     2  0.8499     0.3936 0.276 0.724
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     1  0.5059     0.7525 0.888 0.112
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.4022     0.6772 0.080 0.920
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     2  0.8608     0.7554 0.284 0.716
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     1  0.0000     0.7857 1.000 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     2  0.8327     0.7592 0.264 0.736
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.9087     0.7067 0.324 0.676
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     1  0.0000     0.7857 1.000 0.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     2  0.9460     0.7096 0.364 0.636
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     2  0.8608     0.7554 0.284 0.716
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     2  0.9087     0.7378 0.324 0.676
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     2  0.8608     0.7554 0.284 0.716
#> 23238B08-AA91-46A3-B147-91185A5FAE3F     2  0.8608     0.7554 0.284 0.716
#> DAB49A2E-BBFD-459B-B156-726D8D91D598     2  0.8861     0.7487 0.304 0.696
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F     1  0.3733     0.7652 0.928 0.072
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0     2  0.8955     0.7183 0.312 0.688
#> D149276E-A961-49D6-8BDA-004E8264A0A1     1  0.8443     0.5564 0.728 0.272
#> D17803A2-4BF2-4382-A544-76E28695214F     2  0.8555     0.7565 0.280 0.720
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6     1  0.4298     0.7567 0.912 0.088
#> 16F5BF94-5103-4973-9432-34FDCC82B6A2     2  0.8608     0.7554 0.284 0.716
#> 293FB23D-72CB-4211-B4ED-9C57412CE9F0     2  0.9522     0.6646 0.372 0.628
#> C99F0CD0-B9EB-45F3-885F-6D0519BF1BF7     2  0.9580     0.0540 0.380 0.620
#> 5B8D1101-572C-4445-81C4-83A6D6115451     2  0.9850    -0.1350 0.428 0.572
#> CA86A053-8669-43F5-947A-9D6D368E7087     1  0.6887     0.6746 0.816 0.184
#> FDDECB98-0151-4207-BC4E-040E121703DB     2  0.8608     0.7554 0.284 0.716
#> 862D2F88-77A9-4363-A744-7738F49980E8     2  0.9522     0.6307 0.372 0.628
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#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     2  0.8608     0.7554 0.284 0.716
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     1  0.0938     0.7836 0.988 0.012
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.0376     0.7030 0.004 0.996
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     1  0.4022     0.7653 0.920 0.080
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.4022     0.6772 0.080 0.920
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     1  0.2778     0.7649 0.952 0.048
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     2  0.9460     0.7096 0.364 0.636
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     1  0.7950     0.5733 0.760 0.240
#> 4326E7CF-426E-4352-9903-27BF06E76626     1  0.2948     0.7680 0.948 0.052
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     2  0.8608     0.7554 0.284 0.716
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     2  0.9460     0.7068 0.364 0.636
#> 985FEEC2-9737-4018-80DF-21A07AB47900     1  0.0672     0.7856 0.992 0.008
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  1.0000    -0.3647 0.504 0.496
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     2  0.8608     0.7554 0.284 0.716
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.4815     0.6847 0.104 0.896
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     1  0.6438     0.6617 0.836 0.164
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.9686     0.1832 0.604 0.396
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.1843     0.7042 0.028 0.972
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     1  0.7376     0.5988 0.792 0.208
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     2  0.8608     0.7554 0.284 0.716
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.4022     0.6772 0.080 0.920
#> 457090A2-AE7F-4E68-85EA-032DE8411110     2  0.8608     0.7554 0.284 0.716
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     1  0.0000     0.7857 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.4298     0.7567 0.912 0.088
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.1414     0.6999 0.020 0.980
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     2  0.8861     0.7487 0.304 0.696
#> 34ED910C-7470-4552-8561-D01D59190521     2  0.8608     0.7554 0.284 0.716
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     1  0.3431     0.7533 0.936 0.064
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.7299     0.4336 0.204 0.796
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.3584     0.6819 0.068 0.932
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.4022     0.6863 0.080 0.920
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.9460     0.7096 0.364 0.636
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.7950     0.7538 0.240 0.760
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.0672     0.7037 0.008 0.992
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0000     0.7001 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.0938     0.7052 0.012 0.988
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     1  0.9661     0.2255 0.608 0.392
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     2  0.8608     0.7554 0.284 0.716
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     2  0.2603     0.7131 0.044 0.956
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     2  0.8608     0.7554 0.284 0.716
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     2  0.8608     0.7554 0.284 0.716
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.0000     0.7857 1.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0938     0.6993 0.012 0.988
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.8813     0.7270 0.300 0.700
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.4022     0.6772 0.080 0.920
#> 80936433-AA91-4219-98F1-706C36298060     1  0.8608     0.5649 0.716 0.284
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.8955     0.5930 0.688 0.312
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.8608     0.7554 0.284 0.716
#> D85CB054-7F54-4383-96C0-6C99761B84E7     2  0.8608     0.7554 0.284 0.716
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     2  0.8608     0.7554 0.284 0.716
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.4022     0.6772 0.080 0.920
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     2  0.8608     0.7554 0.284 0.716
#> 17CA5D73-4384-4645-83F8-587847043DD2     2  0.8813     0.7411 0.300 0.700
#> 40467950-A95C-4731-AD93-0A128442C837     2  0.8608     0.7554 0.284 0.716
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.8608     0.7554 0.284 0.716
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     2  0.8608     0.7554 0.284 0.716
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.0000     0.7857 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.0672     0.7856 0.992 0.008
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.0000     0.7001 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.8608     0.7554 0.284 0.716
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     2  0.8499     0.7575 0.276 0.724
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     1  0.2778     0.7649 0.952 0.048
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.8608     0.7554 0.284 0.716
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.8081     0.5776 0.752 0.248
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.0376     0.7858 0.996 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.8608     0.7554 0.284 0.716
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     2  0.9833     0.5256 0.424 0.576
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.8608     0.7554 0.284 0.716
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.3879     0.7634 0.924 0.076
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.7602     0.7569 0.220 0.780
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.2603     0.7131 0.044 0.956
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     1  0.2778     0.7649 0.952 0.048
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.3733     0.6806 0.072 0.928
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.3733     0.7626 0.928 0.072
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.8144     0.6143 0.748 0.252
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.9833    -0.1504 0.576 0.424
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1  0.1633     0.7793 0.976 0.024
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     2  0.3879     0.7267 0.076 0.924
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.7950     0.7538 0.240 0.760
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.2603     0.7131 0.044 0.956
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.5408     0.7398 0.876 0.124
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.8763     0.7496 0.296 0.704
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4022     0.6772 0.080 0.920
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0376     0.7020 0.004 0.996
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4298     0.7567 0.912 0.088
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0000     0.7857 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.9954     0.0457 0.540 0.460
#> 887E7408-C7D7-420F-A763-0EE70A316D17     2  0.6623     0.7518 0.172 0.828
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.4431     0.6690 0.092 0.908
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.7453     0.7201 0.212 0.788
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.0000     0.7001 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0000     0.7857 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.9170     0.4084 0.668 0.332
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.8861     0.7487 0.304 0.696
#> C075F09E-623C-46ED-B927-889B48F450B3     1  0.0000     0.7857 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.8608     0.7554 0.284 0.716
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.9460     0.7096 0.364 0.636
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     1  0.7950     0.6006 0.760 0.240
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.3114     0.7720 0.944 0.056
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     2  0.9977     0.3681 0.472 0.528
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.8608     0.7554 0.284 0.716
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.3431     0.7314 0.064 0.936
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.9580     0.0293 0.380 0.620
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.8861     0.7487 0.304 0.696
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.0000     0.7857 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.8713     0.5204 0.708 0.292
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4939     0.6989 0.108 0.892
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.5946     0.6166 0.144 0.856
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.4431     0.7556 0.908 0.092
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.8608     0.7554 0.284 0.716
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0000     0.7857 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     2  0.8608     0.7554 0.284 0.716
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.8267     0.5555 0.740 0.260
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000     0.7001 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.2603     0.7131 0.044 0.956
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.2603     0.7131 0.044 0.956
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.8207     0.5924 0.744 0.256
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.2236     0.7119 0.036 0.964
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     2  0.8207     0.7602 0.256 0.744
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.8207     0.5841 0.744 0.256
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.9460     0.7096 0.364 0.636
#> 1122039D-5785-4F70-9916-17C585453512     1  0.8499     0.5996 0.724 0.276
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     2  0.8713     0.7519 0.292 0.708
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.9248     0.7294 0.340 0.660
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.7001 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.2423     0.7126 0.040 0.960
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.9286     0.5399 0.656 0.344
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.2778     0.7152 0.048 0.952
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.8327     0.5997 0.736 0.264
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.3584     0.7644 0.932 0.068
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     2  0.8608     0.7554 0.284 0.716
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0000     0.7857 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.8909     0.4739 0.692 0.308
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.7001 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     2  0.8608     0.7554 0.284 0.716
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2603     0.7131 0.044 0.956
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.7857 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.8713     0.7490 0.292 0.708
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.8861     0.7487 0.304 0.696
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0000     0.7857 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.7001 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     2  0.8608     0.7554 0.284 0.716
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     2  1.0000     0.3843 0.496 0.504
#> EB7883EB-0079-4548-9132-169E94A698BA     2  0.8608     0.7554 0.284 0.716
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.8763     0.5116 0.704 0.296
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0000     0.7001 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.7745     0.6340 0.772 0.228
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4022     0.6772 0.080 0.920
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.0376     0.7853 0.996 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.4161     0.6796 0.084 0.916
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.8608     0.7554 0.284 0.716
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.8608     0.7554 0.284 0.716
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3274     0.7715 0.940 0.060
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.8608     0.7554 0.284 0.716

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.6482     0.5063 0.680 0.296 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.5236     0.7509 0.804 0.168 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1163     0.7885 0.028 0.000 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.2031     0.8496 0.016 0.952 0.032
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4413     0.8145 0.124 0.852 0.024
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.2959     0.8177 0.100 0.000 0.900
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.3850     0.8169 0.088 0.028 0.884
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.8673 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6665     0.6937 0.276 0.036 0.688
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3295     0.8169 0.096 0.008 0.896
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.6597     0.5513 0.664 0.312 0.024
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1399     0.8615 0.968 0.004 0.028
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1620     0.8469 0.012 0.964 0.024
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2297     0.8573 0.944 0.036 0.020
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.8719     0.3903 0.548 0.128 0.324
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.7169     0.5487 0.404 0.028 0.568
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.6985     0.3943 0.592 0.384 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.3918     0.8000 0.004 0.856 0.140
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1453     0.8459 0.008 0.968 0.024
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#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D     3  0.2711     0.8161 0.088 0.000 0.912
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854     3  0.3983     0.8114 0.144 0.004 0.852
#> B3CCA12D-4569-4AB8-AC41-457448268D90     1  0.1315     0.8613 0.972 0.020 0.008
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     1  0.1919     0.8606 0.956 0.024 0.020
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     3  0.1163     0.7885 0.028 0.000 0.972
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.1399     0.8556 0.028 0.968 0.004
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     3  0.5785     0.7248 0.300 0.004 0.696
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.5346     0.8423 0.088 0.824 0.088
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.6192     0.5121 0.000 0.580 0.420
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     3  0.9457     0.4015 0.264 0.236 0.500
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     3  0.6917     0.6189 0.368 0.024 0.608
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.6007     0.7741 0.044 0.764 0.192
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     1  0.2050     0.8591 0.952 0.028 0.020
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     3  0.7032     0.7093 0.272 0.052 0.676
#> 985FEEC2-9737-4018-80DF-21A07AB47900     3  0.5327     0.7518 0.272 0.000 0.728
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  0.3573     0.7765 0.876 0.004 0.120
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.2297     0.8552 0.944 0.036 0.020
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     3  0.8255     0.6104 0.168 0.196 0.636
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     3  0.7069    -0.0370 0.024 0.408 0.568
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     3  0.7186     0.6688 0.336 0.040 0.624
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.4551     0.8077 0.132 0.844 0.024
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     3  0.6906     0.6721 0.324 0.032 0.644
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0237     0.8675 0.996 0.004 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.2773     0.8461 0.048 0.928 0.024
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0000     0.8673 1.000 0.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.3043     0.8140 0.084 0.008 0.908
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.5216     0.5297 0.740 0.000 0.260
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.4121     0.8239 0.108 0.868 0.024
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.1411     0.8599 0.964 0.036 0.000
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.1129     0.8640 0.976 0.004 0.020
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.1399     0.7880 0.028 0.004 0.968
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.2280     0.8417 0.008 0.940 0.052
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.4934     0.7863 0.156 0.820 0.024
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.1491     0.8550 0.016 0.968 0.016
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.6698     0.6921 0.280 0.036 0.684
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4634     0.8067 0.164 0.824 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.6287     0.6296 0.272 0.704 0.024
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.1163     0.8540 0.028 0.972 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.6512     0.5585 0.676 0.300 0.024
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.4217     0.8415 0.032 0.868 0.100
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000     0.8673 1.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.3765     0.8057 0.888 0.084 0.028
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.0000     0.8673 1.000 0.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0000     0.8673 1.000 0.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.1163     0.7885 0.028 0.000 0.972
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.1337     0.8533 0.016 0.972 0.012
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.6769     0.5953 0.320 0.652 0.028
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1950     0.8506 0.008 0.952 0.040
#> 80936433-AA91-4219-98F1-706C36298060     2  0.5733     0.6590 0.000 0.676 0.324
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     3  0.8300     0.4893 0.244 0.136 0.620
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.1129     0.8640 0.976 0.004 0.020
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000     0.8673 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0424     0.8642 0.992 0.000 0.008
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.2804     0.8501 0.016 0.924 0.060
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.1163     0.8611 0.972 0.000 0.028
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000     0.8673 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.1031     0.8626 0.976 0.000 0.024
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0829     0.8677 0.984 0.012 0.004
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.1267     0.8636 0.972 0.004 0.024
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.3043     0.8140 0.084 0.008 0.908
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.4233     0.8063 0.160 0.004 0.836
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.6818     0.4696 0.628 0.348 0.024
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.1163     0.8611 0.972 0.000 0.028
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.8673 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     3  0.4974     0.4883 0.000 0.236 0.764
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1289     0.8611 0.968 0.032 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.6045     0.6479 0.380 0.000 0.620
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.4555     0.7974 0.200 0.000 0.800
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1289     0.8611 0.968 0.032 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.7353     0.5500 0.396 0.036 0.568
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.2176     0.8571 0.948 0.032 0.020
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.5397     0.7581 0.280 0.000 0.720
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.4209     0.8247 0.120 0.860 0.020
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.5167     0.7482 0.804 0.172 0.024
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.1031     0.7654 0.000 0.024 0.976
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0747     0.8525 0.016 0.984 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.5529     0.6537 0.296 0.000 0.704
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.5497     0.7859 0.148 0.804 0.048
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.5948     0.6567 0.360 0.000 0.640
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1399     0.7876 0.028 0.004 0.968
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2998     0.8237 0.916 0.068 0.016
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.4485     0.8127 0.136 0.844 0.020
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.7256     0.6815 0.712 0.164 0.124
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.2448     0.8097 0.924 0.000 0.076
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.7013     0.6700 0.324 0.036 0.640
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4634     0.7878 0.164 0.824 0.012
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.6143     0.6505 0.256 0.720 0.024
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.3038     0.7796 0.896 0.000 0.104
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.3213     0.8155 0.092 0.008 0.900
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.5554     0.8066 0.112 0.076 0.812
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1620     0.8552 0.964 0.024 0.012
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.2998     0.8480 0.016 0.916 0.068
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.3683     0.8504 0.060 0.896 0.044
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.6541     0.5509 0.672 0.304 0.024
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.3295     0.8169 0.096 0.008 0.896
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.7366    -0.2064 0.524 0.032 0.444
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1399     0.8615 0.968 0.004 0.028
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1453     0.7844 0.024 0.008 0.968
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1315     0.8640 0.972 0.008 0.020
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.7287     0.5370 0.408 0.032 0.560
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.2796     0.7476 0.000 0.092 0.908
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.4974     0.7861 0.236 0.000 0.764
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.1163     0.8611 0.972 0.000 0.028
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.8673 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.3043     0.8512 0.084 0.908 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.1636     0.8531 0.016 0.964 0.020
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.2050     0.8589 0.952 0.028 0.020
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1163     0.7885 0.028 0.000 0.972
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0237     0.8668 0.996 0.000 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.6677     0.5398 0.324 0.652 0.024
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.3325     0.8486 0.020 0.904 0.076
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.2878     0.7882 0.904 0.000 0.096
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0892     0.8640 0.980 0.000 0.020
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2878     0.8171 0.096 0.000 0.904
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.8673 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.6339     0.6680 0.360 0.008 0.632
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1905     0.8518 0.028 0.956 0.016
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.4677     0.7756 0.840 0.132 0.028
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.5119     0.7569 0.812 0.160 0.028
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1643     0.8416 0.956 0.000 0.044
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.4811     0.7770 0.828 0.148 0.024
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0475     0.8675 0.992 0.004 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.6180    -0.0913 0.584 0.000 0.416
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.6451     0.5258 0.436 0.004 0.560
#> 1122039D-5785-4F70-9916-17C585453512     3  0.2878     0.7465 0.000 0.096 0.904
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6104     0.2335 0.648 0.004 0.348
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1129     0.8640 0.976 0.004 0.020
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.1031     0.8537 0.024 0.976 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.6252     0.6207 0.708 0.268 0.024
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.6908     0.5875 0.036 0.656 0.308
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.5167     0.7482 0.804 0.172 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.2878     0.7465 0.000 0.096 0.904
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3295     0.8169 0.096 0.008 0.896
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8673 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1989     0.8011 0.048 0.004 0.948
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.7319    -0.1292 0.548 0.032 0.420
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1031     0.8537 0.024 0.976 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0237     0.8675 0.996 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.5486     0.7288 0.780 0.196 0.024
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3295     0.8169 0.096 0.008 0.896
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0424     0.8669 0.992 0.000 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1129     0.8640 0.976 0.004 0.020
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3551     0.8188 0.132 0.000 0.868
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0592     0.8514 0.012 0.988 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0747     0.8653 0.984 0.000 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3644     0.7731 0.872 0.004 0.124
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0237     0.8677 0.996 0.004 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.8673 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.7091     0.3185 0.560 0.416 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.2066     0.8399 0.940 0.000 0.060
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2703     0.8508 0.016 0.928 0.056
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1453     0.7844 0.024 0.008 0.968
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2680     0.8451 0.008 0.924 0.068
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0747     0.8653 0.984 0.000 0.016
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.2297     0.8552 0.944 0.036 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5378     0.7873 0.236 0.008 0.756
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0237     0.8677 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.8612     0.3042 0.336 0.116 0.092 0.456
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3855     0.7375 0.820 0.012 0.004 0.164
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2861     0.7376 0.000 0.096 0.888 0.016
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.3105     0.7804 0.004 0.856 0.000 0.140
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#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.3123     0.7563 0.844 0.000 0.000 0.156
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1118     0.8205 0.964 0.000 0.036 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.5252     0.5420 0.692 0.020 0.008 0.280
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0336     0.8316 0.992 0.000 0.000 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4933    -0.0940 0.568 0.000 0.432 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.5906     0.5641 0.320 0.016 0.636 0.028
#> 1122039D-5785-4F70-9916-17C585453512     3  0.3668     0.7012 0.000 0.004 0.808 0.188
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.5993     0.0895 0.528 0.016 0.440 0.016
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4058     0.7945 0.840 0.016 0.116 0.028
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.2831     0.7906 0.004 0.876 0.000 0.120
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     4  0.6457     0.1491 0.428 0.044 0.012 0.516
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4074     0.5732 0.008 0.792 0.196 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3360     0.7744 0.860 0.008 0.008 0.124
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.3668     0.7012 0.000 0.004 0.808 0.188
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.2197     0.7589 0.000 0.004 0.916 0.080
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1271     0.8354 0.968 0.012 0.008 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2246     0.7671 0.016 0.052 0.928 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.5604     0.2551 0.476 0.000 0.504 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2831     0.7906 0.004 0.876 0.000 0.120
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0188     0.8315 0.996 0.000 0.000 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.4923     0.5566 0.304 0.004 0.008 0.684
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.2197     0.7589 0.000 0.004 0.916 0.080
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2983     0.8200 0.896 0.016 0.076 0.012
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.6614     0.5952 0.660 0.016 0.116 0.208
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1824     0.7793 0.060 0.000 0.936 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2831     0.7906 0.004 0.876 0.000 0.120
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1661     0.8325 0.944 0.000 0.052 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4086     0.7348 0.776 0.000 0.216 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0707     0.8309 0.980 0.000 0.000 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0524     0.8325 0.988 0.000 0.004 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.7086     0.2787 0.548 0.292 0.000 0.160
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3584     0.7895 0.836 0.004 0.152 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2053     0.8036 0.004 0.924 0.000 0.072
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4488     0.7140 0.000 0.096 0.808 0.096
#> A0C429D9-0638-4873-BFB4-00056AB4719F     4  0.4164     0.6182 0.000 0.264 0.000 0.736
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2911     0.8227 0.900 0.016 0.072 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4097     0.7980 0.840 0.016 0.112 0.032
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.3945     0.7504 0.216 0.000 0.780 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1297     0.8337 0.964 0.016 0.000 0.020

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.7075    0.32610 0.252 0.008 0.112 0.068 0.560
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.5009    0.70144 0.772 0.088 0.008 0.048 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4161    0.20126 0.000 0.000 0.608 0.392 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.2726    0.77517 0.000 0.884 0.000 0.052 0.064
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.4668    0.40379 0.000 0.352 0.000 0.024 0.624
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.2648    0.50963 0.000 0.000 0.848 0.152 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.2536    0.48903 0.000 0.004 0.900 0.044 0.052
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3791    0.76360 0.812 0.000 0.076 0.112 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.7337    0.35343 0.192 0.000 0.496 0.252 0.060
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4182    0.25156 0.000 0.000 0.600 0.400 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0510    0.83895 0.000 0.000 0.016 0.000 0.984
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5212    0.70248 0.692 0.000 0.192 0.112 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.1965    0.79381 0.000 0.096 0.000 0.000 0.904
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.7003    0.36791 0.224 0.000 0.100 0.108 0.568
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6938    0.48317 0.600 0.044 0.240 0.056 0.060
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.5947    0.44270 0.232 0.000 0.632 0.116 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.6423    0.42824 0.572 0.296 0.000 0.048 0.084
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0000    0.84360 0.000 0.000 0.000 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2962    0.76619 0.000 0.868 0.000 0.048 0.084
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0162    0.84366 0.000 0.004 0.000 0.000 0.996
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.4074    0.68363 0.000 0.000 0.364 0.636 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3183    0.74630 0.000 0.828 0.000 0.016 0.156
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.78692 1.000 0.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.6285    0.49461 0.000 0.548 0.004 0.176 0.272
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0960    0.78449 0.972 0.000 0.008 0.004 0.016
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.6562    0.14518 0.000 0.308 0.000 0.228 0.464
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3452    0.32749 0.000 0.000 0.756 0.244 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4803    0.74771 0.800 0.036 0.064 0.044 0.056
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.5059    0.45461 0.192 0.000 0.696 0.112 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.5080    0.70965 0.708 0.000 0.176 0.112 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.3888    0.53261 0.120 0.000 0.804 0.076 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0404    0.84067 0.000 0.012 0.000 0.000 0.988
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.2747    0.77674 0.000 0.888 0.004 0.048 0.060
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4501    0.73851 0.756 0.000 0.128 0.116 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.5393    0.70371 0.692 0.000 0.176 0.120 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.4004    0.73674 0.832 0.036 0.004 0.052 0.076
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.4371    0.50605 0.052 0.056 0.824 0.040 0.028
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.2187    0.54658 0.056 0.004 0.920 0.008 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0451    0.78573 0.988 0.000 0.008 0.004 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.5986    0.69955 0.000 0.072 0.356 0.552 0.020
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3849    0.76247 0.808 0.000 0.080 0.112 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4776    0.42286 0.612 0.000 0.364 0.004 0.020
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.2576    0.79720 0.008 0.900 0.072 0.012 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.78692 1.000 0.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.2681    0.78529 0.876 0.004 0.108 0.012 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2377    0.45075 0.000 0.000 0.872 0.128 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.3264    0.61603 0.000 0.016 0.164 0.820 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5243    0.70897 0.772 0.048 0.040 0.056 0.084
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.5736    0.44549 0.268 0.000 0.632 0.080 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.2690    0.75288 0.000 0.156 0.000 0.000 0.844
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4487    0.73640 0.756 0.000 0.140 0.104 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.1270    0.55683 0.052 0.000 0.948 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.2719    0.77468 0.000 0.884 0.000 0.048 0.068
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.5268    0.46235 0.220 0.000 0.668 0.112 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0963    0.78098 0.964 0.000 0.036 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.1942    0.79220 0.920 0.000 0.068 0.000 0.012
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2006    0.81208 0.000 0.916 0.000 0.072 0.012
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.1741    0.81470 0.040 0.936 0.000 0.024 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.6060    0.43582 0.244 0.000 0.616 0.120 0.020
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.4307    0.05906 0.000 0.504 0.000 0.000 0.496
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.5673    0.61326 0.596 0.000 0.292 0.112 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1124    0.81151 0.000 0.960 0.000 0.036 0.004
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.1059    0.78464 0.968 0.000 0.008 0.004 0.020
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.4317    0.75255 0.772 0.000 0.116 0.112 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.1278    0.54546 0.020 0.000 0.960 0.016 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.4256    0.61127 0.000 0.000 0.436 0.564 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.2329    0.77918 0.000 0.124 0.000 0.000 0.876
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.3617    0.77206 0.824 0.000 0.128 0.044 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.2890    0.51268 0.160 0.000 0.836 0.004 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0162    0.78600 0.996 0.000 0.000 0.004 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0955    0.81350 0.000 0.968 0.000 0.028 0.004
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.3453    0.54994 0.136 0.000 0.832 0.012 0.020
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1608    0.81379 0.000 0.928 0.000 0.072 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.3662    0.71163 0.000 0.744 0.000 0.252 0.004
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3840    0.52950 0.076 0.000 0.808 0.116 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.5839    0.16763 0.000 0.072 0.676 0.192 0.060
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.3561    0.35302 0.000 0.000 0.740 0.260 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.8971   -0.00407 0.296 0.124 0.184 0.048 0.348
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.2852    0.41206 0.000 0.000 0.828 0.172 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.3177    0.37495 0.000 0.000 0.792 0.208 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.6288   -0.02263 0.440 0.000 0.448 0.096 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.3823    0.76377 0.028 0.064 0.000 0.072 0.836
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.4893    0.74111 0.740 0.004 0.140 0.112 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     4  0.9474    0.09664 0.116 0.264 0.232 0.292 0.096
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.1357    0.79222 0.948 0.000 0.048 0.004 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.1894    0.79558 0.008 0.920 0.072 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000    0.78692 1.000 0.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4273    0.08790 0.000 0.000 0.552 0.448 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0613    0.78657 0.984 0.000 0.004 0.008 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.2179    0.81301 0.008 0.912 0.008 0.072 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1341    0.78958 0.944 0.000 0.000 0.056 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.4619    0.50133 0.216 0.000 0.720 0.064 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.3744    0.77915 0.832 0.008 0.120 0.020 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     5  0.0000    0.84360 0.000 0.000 0.000 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.2880    0.78122 0.864 0.004 0.120 0.004 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0000    0.84360 0.000 0.000 0.000 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.1124    0.81151 0.000 0.960 0.000 0.036 0.004
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.0794    0.83183 0.000 0.000 0.028 0.000 0.972
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.6288    0.69242 0.004 0.072 0.356 0.540 0.028
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0404    0.81828 0.000 0.988 0.000 0.012 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0579    0.78602 0.984 0.000 0.008 0.008 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0994    0.78488 0.972 0.004 0.004 0.004 0.016
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.7040    0.31198 0.180 0.536 0.248 0.016 0.020
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.3074    0.74271 0.000 0.804 0.000 0.196 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.3460    0.48334 0.128 0.000 0.828 0.044 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.4256    0.61142 0.000 0.000 0.436 0.564 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.5470    0.41003 0.048 0.076 0.760 0.056 0.060
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.5264    0.45653 0.256 0.000 0.652 0.092 0.000
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#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0324    0.78619 0.992 0.000 0.004 0.004 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.2953    0.77889 0.844 0.000 0.144 0.012 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.2730    0.79174 0.896 0.000 0.044 0.044 0.016
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.3616    0.76634 0.804 0.000 0.164 0.032 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.3966    0.22079 0.000 0.000 0.664 0.336 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.3657    0.54101 0.116 0.000 0.820 0.064 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.6404    0.49760 0.604 0.260 0.004 0.048 0.084
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.3276    0.77986 0.836 0.000 0.132 0.032 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0162    0.78600 0.996 0.000 0.000 0.004 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     3  0.5916    0.01204 0.000 0.336 0.544 0.120 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1580    0.78168 0.952 0.004 0.016 0.012 0.016
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.3969    0.49206 0.304 0.000 0.692 0.004 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.2984    0.52931 0.032 0.000 0.860 0.108 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1278    0.78346 0.960 0.000 0.020 0.004 0.016
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.4584    0.48716 0.256 0.000 0.708 0.016 0.020
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.5526    0.70484 0.688 0.000 0.180 0.112 0.020
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.3715    0.45622 0.260 0.000 0.736 0.004 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.2067    0.80799 0.048 0.920 0.032 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.4741    0.72550 0.796 0.056 0.016 0.048 0.084
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.4435    0.22885 0.000 0.016 0.648 0.336 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0609    0.81521 0.000 0.980 0.000 0.020 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.5035    0.38950 0.252 0.000 0.672 0.076 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.4377    0.68215 0.036 0.776 0.168 0.016 0.004
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.5104    0.48337 0.192 0.000 0.692 0.116 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.4138    0.21687 0.000 0.000 0.616 0.384 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0162    0.78600 0.996 0.000 0.000 0.004 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1981    0.79972 0.016 0.920 0.064 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.6833    0.59072 0.656 0.084 0.132 0.048 0.080
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.2482    0.77350 0.892 0.000 0.084 0.024 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.4788    0.50478 0.220 0.008 0.728 0.024 0.020
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.2221    0.81332 0.000 0.036 0.000 0.052 0.912
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.6918    0.18361 0.136 0.480 0.004 0.028 0.352
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2719    0.69493 0.852 0.000 0.144 0.004 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.3586    0.28394 0.000 0.000 0.736 0.264 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.5053    0.48084 0.044 0.036 0.780 0.096 0.044
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000    0.78692 1.000 0.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1608    0.81379 0.000 0.928 0.000 0.072 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.2196    0.81303 0.004 0.916 0.000 0.024 0.056
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.6384    0.53511 0.624 0.236 0.008 0.048 0.084
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.3508    0.31301 0.000 0.000 0.748 0.252 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.4764   -0.08628 0.548 0.000 0.436 0.004 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.5335    0.69069 0.676 0.000 0.208 0.112 0.004
#> C075F09E-623C-46ED-B927-889B48F450B3     4  0.3586    0.55315 0.000 0.000 0.264 0.736 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.5304    0.70775 0.700 0.000 0.176 0.112 0.012
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.6692    0.40043 0.264 0.000 0.532 0.184 0.020
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.4793    0.26865 0.000 0.068 0.700 0.232 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3048    0.51971 0.176 0.000 0.820 0.004 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.5122    0.69696 0.688 0.000 0.200 0.112 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3791    0.76360 0.812 0.000 0.076 0.112 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1502    0.81211 0.056 0.940 0.004 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.1699    0.81129 0.004 0.944 0.008 0.036 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5647    0.69929 0.676 0.000 0.184 0.120 0.020
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.3816    0.30343 0.000 0.000 0.696 0.304 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.2900    0.77489 0.864 0.000 0.028 0.108 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.1732    0.76681 0.080 0.000 0.000 0.000 0.920
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1608    0.81379 0.000 0.928 0.000 0.072 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.2068    0.74603 0.904 0.000 0.092 0.004 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.4498    0.73912 0.756 0.000 0.132 0.112 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2127    0.47018 0.000 0.000 0.892 0.108 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0162    0.78600 0.996 0.000 0.000 0.004 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.4218    0.47138 0.324 0.000 0.668 0.004 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.2515    0.79476 0.008 0.904 0.000 0.044 0.044
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.2338    0.76356 0.916 0.004 0.008 0.048 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.4727    0.71986 0.792 0.076 0.008 0.048 0.076
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1205    0.77810 0.956 0.000 0.040 0.004 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.5594    0.42736 0.604 0.012 0.032 0.016 0.336
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0162    0.78737 0.996 0.000 0.000 0.000 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4390   -0.06860 0.568 0.000 0.428 0.004 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.6625    0.40159 0.268 0.000 0.532 0.184 0.016
#> 1122039D-5785-4F70-9916-17C585453512     4  0.5418    0.70298 0.000 0.068 0.364 0.568 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6145    0.12937 0.448 0.000 0.436 0.112 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.6010    0.65953 0.632 0.000 0.168 0.184 0.016
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.1124    0.81151 0.000 0.960 0.000 0.036 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.7749    0.19010 0.440 0.120 0.032 0.052 0.356
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4918    0.57665 0.008 0.716 0.204 0.072 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4857    0.72521 0.792 0.052 0.024 0.048 0.084
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.5566    0.70350 0.000 0.068 0.364 0.564 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3480    0.31871 0.000 0.000 0.752 0.248 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2172    0.79134 0.908 0.000 0.076 0.016 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1908    0.49540 0.000 0.000 0.908 0.092 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.5000    0.26324 0.460 0.000 0.516 0.012 0.012
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1124    0.81151 0.000 0.960 0.000 0.036 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0451    0.78580 0.988 0.000 0.008 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.1671    0.78840 0.076 0.000 0.000 0.000 0.924
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3508    0.31301 0.000 0.000 0.748 0.252 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4541    0.73793 0.752 0.000 0.136 0.112 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.7941    0.31351 0.408 0.000 0.168 0.116 0.308
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3061    0.52318 0.020 0.000 0.844 0.136 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1124    0.81151 0.000 0.960 0.000 0.036 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3639    0.77038 0.824 0.000 0.076 0.100 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5725    0.58752 0.608 0.000 0.280 0.108 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0833    0.78940 0.976 0.000 0.004 0.004 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2522    0.77715 0.880 0.000 0.012 0.108 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.6512    0.37640 0.548 0.320 0.000 0.048 0.084
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4918    0.70640 0.708 0.000 0.192 0.100 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.1768    0.81871 0.000 0.924 0.000 0.072 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     4  0.3003    0.62393 0.000 0.000 0.188 0.812 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.4444    0.67246 0.000 0.088 0.000 0.156 0.756
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4541    0.73854 0.752 0.000 0.136 0.112 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.3670    0.75799 0.796 0.000 0.180 0.004 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.3333    0.51157 0.208 0.000 0.788 0.004 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1442    0.79267 0.952 0.000 0.032 0.004 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.4817    0.28266 0.564 0.012 0.000 0.000 0.388 0.036
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.5707    0.47644 0.108 0.024 0.000 0.280 0.004 0.584
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3396    0.46176 0.116 0.000 0.812 0.072 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.5727    0.62708 0.040 0.628 0.000 0.204 0.004 0.124
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.7215    0.20183 0.012 0.280 0.000 0.144 0.452 0.112
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3789    0.25579 0.416 0.000 0.584 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.3775    0.60202 0.092 0.000 0.780 0.128 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3244    0.48177 0.732 0.000 0.000 0.000 0.000 0.268
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.7197   -0.35820 0.412 0.000 0.364 0.060 0.040 0.124
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.5607    0.10118 0.408 0.000 0.448 0.144 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000    0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2668    0.60649 0.828 0.000 0.004 0.000 0.000 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.1958    0.81577 0.000 0.100 0.000 0.004 0.896 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.4453    0.19893 0.568 0.000 0.000 0.000 0.400 0.032
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.5304    0.46135 0.000 0.000 0.200 0.200 0.000 0.600
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.2593    0.61203 0.844 0.000 0.148 0.000 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.5915    0.39549 0.032 0.116 0.000 0.280 0.004 0.568
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0000    0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5218    0.64946 0.012 0.656 0.000 0.204 0.004 0.124
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0000    0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.3578    0.76801 0.000 0.000 0.340 0.660 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3874    0.72587 0.000 0.760 0.000 0.000 0.172 0.068
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.2762    0.66383 0.196 0.000 0.000 0.000 0.000 0.804
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.8555    0.32996 0.044 0.392 0.064 0.228 0.196 0.076
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.2003    0.67582 0.116 0.000 0.000 0.000 0.000 0.884
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.7179    0.36627 0.124 0.244 0.040 0.064 0.520 0.008
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3532    0.50371 0.064 0.000 0.796 0.140 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     6  0.5288    0.58647 0.164 0.040 0.000 0.108 0.004 0.684
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4406    0.57202 0.696 0.000 0.224 0.000 0.000 0.080
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2805    0.59759 0.812 0.000 0.004 0.000 0.000 0.184
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.5527    0.55364 0.208 0.000 0.560 0.000 0.000 0.232
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0000    0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.5254    0.58832 0.000 0.596 0.004 0.280 0.000 0.120
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2491    0.60590 0.836 0.000 0.000 0.000 0.000 0.164
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1910    0.62495 0.892 0.000 0.000 0.000 0.000 0.108
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     6  0.4795    0.55432 0.112 0.012 0.000 0.180 0.000 0.696
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.7035    0.51683 0.108 0.084 0.556 0.060 0.000 0.192
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.4176    0.63107 0.136 0.000 0.768 0.020 0.000 0.076
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2135    0.66909 0.128 0.000 0.000 0.000 0.000 0.872
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.2762    0.78092 0.000 0.000 0.196 0.804 0.000 0.000
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#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.1753    0.80674 0.084 0.000 0.000 0.004 0.912 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.82219 0.000 1.000 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.2135    0.66909 0.128 0.000 0.000 0.000 0.000 0.872
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.2996    0.54501 0.772 0.000 0.000 0.000 0.000 0.228
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2170    0.60400 0.100 0.000 0.888 0.012 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.2300    0.67098 0.144 0.000 0.000 0.000 0.000 0.856
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.5042    0.50960 0.092 0.000 0.576 0.000 0.000 0.332
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.4261    0.75254 0.012 0.764 0.000 0.128 0.004 0.092
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.0777    0.62470 0.004 0.000 0.000 0.024 0.000 0.972
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.3651    0.56226 0.048 0.000 0.000 0.180 0.000 0.772
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.3046    0.66283 0.188 0.000 0.012 0.000 0.000 0.800
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     6  0.5058    0.42410 0.060 0.004 0.000 0.008 0.336 0.592
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.3175    0.63733 0.256 0.000 0.000 0.000 0.000 0.744
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.5226   -0.23123 0.092 0.000 0.444 0.000 0.000 0.464
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2118    0.60552 0.888 0.000 0.104 0.000 0.000 0.008
#> 1122039D-5785-4F70-9916-17C585453512     4  0.3221    0.79495 0.000 0.000 0.264 0.736 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3172    0.63106 0.816 0.000 0.148 0.000 0.000 0.036
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1556    0.62572 0.920 0.000 0.000 0.000 0.000 0.080
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3052    0.79630 0.000 0.848 0.000 0.080 0.004 0.068
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     6  0.7956    0.23929 0.168 0.032 0.000 0.204 0.204 0.392
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3558    0.58225 0.016 0.736 0.248 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.5062    0.53375 0.108 0.012 0.000 0.204 0.004 0.672
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.3175    0.79582 0.000 0.000 0.256 0.744 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3532    0.50371 0.064 0.000 0.796 0.140 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.3828    0.38317 0.440 0.000 0.000 0.000 0.000 0.560
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1444    0.61694 0.072 0.000 0.928 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.5648    0.42440 0.156 0.000 0.472 0.000 0.000 0.372
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3052    0.79630 0.000 0.848 0.000 0.080 0.004 0.068
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.2135    0.66909 0.128 0.000 0.000 0.000 0.000 0.872
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.2162    0.78985 0.012 0.000 0.000 0.004 0.896 0.088
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3570    0.49979 0.064 0.000 0.792 0.144 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2823    0.58036 0.796 0.000 0.000 0.000 0.000 0.204
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.2605    0.61226 0.864 0.000 0.000 0.000 0.108 0.028
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3833    0.19454 0.444 0.000 0.556 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3052    0.79630 0.000 0.848 0.000 0.080 0.004 0.068
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3756    0.23123 0.600 0.000 0.000 0.000 0.000 0.400
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5354    0.43378 0.580 0.000 0.160 0.000 0.000 0.260
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.3446    0.63046 0.308 0.000 0.000 0.000 0.000 0.692
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3868    0.00167 0.508 0.000 0.000 0.000 0.000 0.492
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.5716    0.37254 0.012 0.136 0.000 0.280 0.004 0.568
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4570    0.48786 0.644 0.000 0.064 0.000 0.000 0.292
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2152    0.81552 0.000 0.904 0.000 0.068 0.004 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     4  0.4223    0.75655 0.076 0.000 0.204 0.720 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.4239    0.70883 0.060 0.028 0.056 0.052 0.804 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2883    0.56808 0.788 0.000 0.000 0.000 0.000 0.212
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.3854   -0.16266 0.536 0.000 0.000 0.000 0.000 0.464
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4931    0.51928 0.084 0.000 0.592 0.000 0.000 0.324
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.3371    0.61456 0.292 0.000 0.000 0.000 0.000 0.708

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 17541 rows and 500 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 0.346           0.743       0.855         0.4642 0.529   0.529
#> 3 3 0.572           0.730       0.845         0.3832 0.747   0.551
#> 4 4 0.561           0.508       0.728         0.1318 0.884   0.689
#> 5 5 0.527           0.367       0.676         0.0413 0.881   0.643
#> 6 6 0.538           0.334       0.622         0.0487 0.883   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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.6973     0.8073 0.188 0.812
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.8144     0.7414 0.252 0.748
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.4431     0.7858 0.092 0.908
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.7917 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.7056     0.8061 0.192 0.808
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.6343     0.7245 0.160 0.840
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.6048     0.7358 0.148 0.852
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.8433 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.8327     0.7781 0.264 0.736
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.4431     0.7858 0.092 0.908
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.7056     0.8061 0.192 0.808
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.8433 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.7056     0.8061 0.192 0.808
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.9996    -0.2262 0.512 0.488
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.9358     0.3083 0.352 0.648
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.8909     0.4278 0.692 0.308
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.4298     0.8146 0.088 0.912
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.7917 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5059     0.8154 0.112 0.888
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.7056     0.8061 0.192 0.808
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.3431     0.7960 0.064 0.936
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.7056     0.8061 0.192 0.808
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8433 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0376     0.7936 0.004 0.996
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.8433 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.6973     0.8074 0.188 0.812
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.4939     0.7745 0.108 0.892
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.7815     0.7950 0.232 0.768
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.8016     0.6903 0.756 0.244
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.8433 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.7376     0.6598 0.208 0.792
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.7056     0.8061 0.192 0.808
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0000     0.7917 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0376     0.8418 0.996 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.6247     0.7077 0.844 0.156
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.7056     0.8061 0.192 0.808
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0376     0.7936 0.004 0.996
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.5059     0.7717 0.112 0.888
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.8433 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.3431     0.7960 0.064 0.936
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.8433 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2236     0.8238 0.964 0.036
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.7056     0.8061 0.192 0.808
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.8433 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.8327     0.6991 0.736 0.264
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.4431     0.7858 0.092 0.908
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.3114     0.7970 0.056 0.944
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.6247     0.8103 0.156 0.844
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.9000     0.4125 0.684 0.316
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.7056     0.8061 0.192 0.808
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.7376     0.7149 0.792 0.208
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.8081     0.6882 0.752 0.248
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.7917 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  1.0000    -0.2428 0.496 0.504
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.7219     0.7186 0.800 0.200
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#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.7528     0.6448 0.216 0.784
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.5519     0.8144 0.128 0.872
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.9580     0.6012 0.620 0.380
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.8433 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.2948     0.7973 0.052 0.948
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.8443     0.5280 0.728 0.272
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0376     0.8418 0.996 0.004
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.7376     0.6566 0.208 0.792
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.9044     0.4115 0.680 0.320
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.8433 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.4815     0.7759 0.896 0.104
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.7745     0.7027 0.772 0.228
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.7056     0.8061 0.192 0.808
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.9988     0.3947 0.480 0.520
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.3431     0.7960 0.064 0.936
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.7056     0.8061 0.192 0.808
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.8555     0.6556 0.720 0.280
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.8207     0.7841 0.256 0.744
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.9970    -0.1412 0.468 0.532
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.4431     0.7858 0.092 0.908
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.8433 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.7056     0.8061 0.192 0.808
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.3431     0.7960 0.064 0.936
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.7219     0.7186 0.800 0.200
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.8661     0.7555 0.288 0.712
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.6623     0.8109 0.172 0.828
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.7056     0.8061 0.192 0.808
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.7453     0.7128 0.788 0.212
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     2  0.4939     0.7745 0.108 0.892
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     2  0.4431     0.7858 0.092 0.908
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.8433 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.7056     0.8061 0.192 0.808
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.7056     0.8061 0.192 0.808
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.4431     0.8159 0.092 0.908
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.4939     0.7745 0.108 0.892
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.8433 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.7219     0.7186 0.800 0.200
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.4431     0.7858 0.092 0.908
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.8433 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.8267     0.7731 0.260 0.740
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.3733     0.7937 0.072 0.928
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.9881     0.4228 0.564 0.436
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.7219     0.7186 0.800 0.200
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.8433 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.7056     0.8061 0.192 0.808
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.8207     0.7838 0.256 0.744
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.9286     0.3429 0.656 0.344
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.3431     0.7960 0.064 0.936
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.8433 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.7056     0.8061 0.192 0.808
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.7056     0.8061 0.192 0.808
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.7219     0.7186 0.800 0.200
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.8433 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.4939     0.7745 0.108 0.892
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.8433 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.8433 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7056     0.8061 0.192 0.808
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.2778     0.8153 0.952 0.048
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.9963     0.4698 0.464 0.536
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.7453     0.7128 0.788 0.212
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.7056     0.8061 0.192 0.808
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.8433 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.8433 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.8661     0.4654 0.712 0.288
#> 1122039D-5785-4F70-9916-17C585453512     2  0.4431     0.7858 0.092 0.908
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.8433 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.8144     0.5471 0.748 0.252
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.2423     0.8060 0.040 0.960
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.7056     0.8061 0.192 0.808
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.8207     0.7838 0.256 0.744
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.8016     0.7909 0.244 0.756
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.4298     0.7876 0.088 0.912
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     2  0.7815     0.6172 0.232 0.768
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8433 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.4431     0.7858 0.092 0.908
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.9170     0.3784 0.668 0.332
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.6973     0.8073 0.188 0.812
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.8433 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.7056     0.8061 0.192 0.808
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.4939     0.7745 0.108 0.892
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.8433 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.5294     0.7552 0.880 0.120
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.4431     0.7858 0.092 0.908
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3879     0.8128 0.076 0.924
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.8433 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.8813     0.6377 0.700 0.300
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.8016     0.5633 0.756 0.244
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.8433 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.4431     0.8142 0.092 0.908
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.7376     0.7149 0.792 0.208
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0376     0.7936 0.004 0.996
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.4431     0.7858 0.092 0.908
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.7056     0.8061 0.192 0.808
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.8433 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.8433 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     2  1.0000    -0.2503 0.500 0.500
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.8433 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.1643    0.89830 0.000 0.956 0.044
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.3713    0.85322 0.032 0.892 0.076
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1860    0.78793 0.052 0.000 0.948
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.6225    0.33025 0.000 0.432 0.568
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0237    0.90295 0.000 0.996 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.5882    0.51978 0.348 0.000 0.652
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.6274    0.21388 0.544 0.000 0.456
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2625    0.84494 0.916 0.084 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.9070    0.09854 0.436 0.136 0.428
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2448    0.78612 0.076 0.000 0.924
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0237    0.90295 0.000 0.996 0.004
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3587    0.83997 0.892 0.088 0.020
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0237    0.90295 0.000 0.996 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.7150    0.37726 0.348 0.616 0.036
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.6721    0.31060 0.380 0.016 0.604
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.6448    0.79934 0.764 0.104 0.132
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.2959    0.82749 0.000 0.900 0.100
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     3  0.6215    0.34063 0.000 0.428 0.572
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1529    0.87750 0.000 0.960 0.040
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0237    0.90295 0.000 0.996 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.1950    0.78754 0.040 0.008 0.952
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0237    0.90295 0.000 0.996 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2625    0.84494 0.916 0.084 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.3340    0.79428 0.000 0.880 0.120
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3805    0.83704 0.884 0.092 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.4178    0.74800 0.000 0.828 0.172
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4291    0.73351 0.180 0.000 0.820
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.1647    0.89809 0.004 0.960 0.036
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3619    0.70948 0.864 0.000 0.136
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2711    0.84496 0.912 0.088 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.5497    0.60726 0.292 0.000 0.708
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0237    0.90295 0.000 0.996 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.6204    0.34145 0.000 0.424 0.576
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3043    0.84508 0.908 0.084 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3637    0.84164 0.892 0.084 0.024
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.1753    0.89724 0.000 0.952 0.048
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4346    0.77406 0.000 0.816 0.184
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6286   -0.08587 0.536 0.000 0.464
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.2711    0.84496 0.912 0.088 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.5298    0.70882 0.032 0.164 0.804
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2711    0.84496 0.912 0.088 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5229    0.81540 0.828 0.104 0.068
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1529    0.89891 0.000 0.960 0.040
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.1289    0.82220 0.968 0.032 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.9695   -0.10537 0.384 0.400 0.216
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2448    0.78612 0.076 0.000 0.924
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4931    0.66476 0.004 0.212 0.784
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.9653    0.11529 0.328 0.448 0.224
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4966    0.82136 0.840 0.100 0.060
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0237    0.90295 0.000 0.996 0.004
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.3340    0.72915 0.880 0.000 0.120
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4062    0.67544 0.836 0.000 0.164
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.6235    0.32182 0.000 0.436 0.564
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4002    0.72473 0.840 0.000 0.160
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.3500    0.73344 0.880 0.004 0.116
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.5319    0.81274 0.824 0.104 0.072
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2165    0.89109 0.000 0.936 0.064
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.1753    0.89724 0.000 0.952 0.048
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.8637   -0.19070 0.448 0.100 0.452
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0237    0.90295 0.000 0.996 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.3267    0.73019 0.884 0.000 0.116
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0237    0.90295 0.000 0.996 0.004
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.4586    0.83165 0.856 0.096 0.048
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.3722    0.83804 0.888 0.088 0.024
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6632    0.29380 0.596 0.012 0.392
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.2448    0.78612 0.076 0.000 0.924
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000    0.90281 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5393    0.81015 0.820 0.108 0.072
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.5678    0.38900 0.684 0.000 0.316
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.3120    0.76869 0.908 0.012 0.080
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.4654    0.67090 0.000 0.792 0.208
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#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.1860    0.83328 0.948 0.052 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.3500    0.73344 0.880 0.004 0.116
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.6215    0.34063 0.000 0.428 0.572
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.3267    0.73019 0.884 0.000 0.116
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.2711    0.84496 0.912 0.088 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.4609    0.82745 0.856 0.092 0.052
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.7980    0.43994 0.572 0.356 0.072
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.3129    0.84497 0.904 0.088 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.2448    0.78612 0.076 0.000 0.924
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.5291    0.64223 0.268 0.000 0.732
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.5115    0.73206 0.016 0.796 0.188
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.8894    0.37987 0.572 0.236 0.192
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.2711    0.84496 0.912 0.088 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     3  0.5982    0.45013 0.004 0.328 0.668
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.7400    0.64351 0.664 0.264 0.072
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.2625    0.84496 0.916 0.084 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.5785    0.54720 0.332 0.000 0.668
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.8273    0.14728 0.476 0.448 0.076
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.3377    0.84398 0.896 0.092 0.012
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.5212    0.81592 0.828 0.108 0.064
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.3267    0.73019 0.884 0.000 0.116
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.1753    0.89724 0.000 0.952 0.048
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.4475    0.82608 0.072 0.864 0.064
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.1129    0.77162 0.004 0.020 0.976
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0424    0.90300 0.000 0.992 0.008
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4555    0.62329 0.800 0.000 0.200
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.6351    0.68809 0.168 0.760 0.072
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.6274    0.05168 0.544 0.000 0.456
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1860    0.78793 0.052 0.000 0.948
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2711    0.84496 0.912 0.088 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1860    0.89614 0.000 0.948 0.052
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     3  0.8371    0.52356 0.116 0.292 0.592
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.3500    0.73344 0.880 0.004 0.116
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.8100    0.32862 0.512 0.420 0.068
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0424    0.90170 0.000 0.992 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0237    0.90295 0.000 0.996 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.3267    0.73019 0.884 0.000 0.116
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.2448    0.78612 0.076 0.000 0.924
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.4796    0.71780 0.220 0.000 0.780
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2711    0.84496 0.912 0.088 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0237    0.90295 0.000 0.996 0.004
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0237    0.90295 0.000 0.996 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.3267    0.82352 0.000 0.884 0.116
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.2448    0.78612 0.076 0.000 0.924
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.3528    0.84225 0.892 0.092 0.016
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.3267    0.73019 0.884 0.000 0.116
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.2448    0.78612 0.076 0.000 0.924
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.3722    0.84159 0.888 0.088 0.024
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.8518    0.15882 0.356 0.104 0.540
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.1989    0.78820 0.048 0.004 0.948
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.6126    0.21092 0.600 0.000 0.400
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.3267    0.73019 0.884 0.000 0.116
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3445    0.84123 0.896 0.088 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1753    0.89724 0.000 0.952 0.048
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.4326    0.79162 0.012 0.844 0.144
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5875    0.78964 0.792 0.136 0.072
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.3112    0.73377 0.004 0.096 0.900
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.3445    0.84126 0.896 0.088 0.016
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0237    0.90295 0.000 0.996 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1643    0.89830 0.000 0.956 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.3500    0.73344 0.880 0.004 0.116
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.2356    0.84203 0.928 0.072 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.3551    0.76658 0.132 0.000 0.868
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2625    0.84494 0.916 0.084 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.2625    0.84496 0.916 0.084 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1753    0.89724 0.000 0.952 0.048
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.4654    0.75624 0.792 0.208 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.8063   -0.03781 0.448 0.488 0.064
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.3267    0.73019 0.884 0.000 0.116
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0237    0.90301 0.000 0.996 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.2711    0.84496 0.912 0.088 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000    0.80031 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.6313    0.43916 0.676 0.016 0.308
#> 1122039D-5785-4F70-9916-17C585453512     3  0.1989    0.78844 0.048 0.004 0.948
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2711    0.84496 0.912 0.088 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4931    0.73893 0.828 0.032 0.140
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.4399    0.70271 0.000 0.812 0.188
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0424    0.90300 0.000 0.992 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5371    0.79368 0.048 0.812 0.140
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.9211    0.22694 0.312 0.512 0.176
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.1989    0.78844 0.048 0.004 0.948
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5138    0.65881 0.252 0.000 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2625    0.84494 0.916 0.084 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3619    0.76466 0.136 0.000 0.864
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5229    0.81540 0.828 0.104 0.068
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0592    0.90295 0.000 0.988 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2711    0.84496 0.912 0.088 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0237    0.90295 0.000 0.996 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.2448    0.78612 0.076 0.000 0.924
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2356    0.84202 0.928 0.072 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3722    0.84039 0.888 0.088 0.024
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3784    0.76633 0.132 0.004 0.864
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1860    0.86560 0.000 0.948 0.052
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2711    0.84496 0.912 0.088 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4178    0.67230 0.828 0.000 0.172
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3850    0.83971 0.884 0.088 0.028
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2711    0.84496 0.912 0.088 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.1753    0.87809 0.000 0.952 0.048
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3267    0.73019 0.884 0.000 0.116
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6215    0.33926 0.000 0.428 0.572
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1860    0.78793 0.052 0.000 0.948
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0237    0.90295 0.000 0.996 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1529    0.82682 0.960 0.040 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.2711    0.84496 0.912 0.088 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5016    0.59165 0.760 0.000 0.240
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4206    0.82930 0.872 0.088 0.040

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.6005    0.70839 0.000 0.616 0.060 0.324
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.5968    0.65363 0.048 0.624 0.004 0.324
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4941    0.32137 0.000 0.000 0.564 0.436
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5292    0.36220 0.000 0.480 0.008 0.512
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2408    0.73925 0.000 0.896 0.000 0.104
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.6567    0.21386 0.308 0.000 0.588 0.104
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     4  0.7921   -0.14551 0.328 0.000 0.324 0.348
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.7259    0.23076 0.208 0.124 0.628 0.040
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4776    0.38295 0.000 0.000 0.624 0.376
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0657    0.78375 0.984 0.004 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.9516    0.09938 0.396 0.196 0.148 0.260
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.7868    0.01889 0.360 0.024 0.144 0.472
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.8294    0.53237 0.560 0.104 0.208 0.128
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.5154    0.68881 0.012 0.660 0.004 0.324
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     4  0.5292    0.36197 0.000 0.480 0.008 0.512
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.5161   -0.00729 0.000 0.008 0.400 0.592
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3400    0.74696 0.000 0.820 0.000 0.180
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0592    0.70828 0.000 0.984 0.000 0.016
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1631    0.77922 0.956 0.020 0.016 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.2081    0.64964 0.000 0.916 0.000 0.084
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.7760    0.24805 0.240 0.000 0.408 0.352
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.6355    0.70853 0.020 0.624 0.048 0.308
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4866    0.47472 0.596 0.000 0.404 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0657    0.78375 0.984 0.004 0.012 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0779    0.41459 0.016 0.000 0.980 0.004
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.4990    0.39487 0.000 0.352 0.008 0.640
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0921    0.77823 0.972 0.000 0.028 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3539    0.72756 0.820 0.004 0.176 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.4790    0.71262 0.000 0.620 0.000 0.380
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4866    0.70437 0.000 0.596 0.000 0.404
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.6508    0.12083 0.344 0.000 0.568 0.088
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.6292    0.09558 0.000 0.076 0.332 0.592
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4333    0.73261 0.840 0.024 0.060 0.076
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.4431    0.74090 0.000 0.696 0.000 0.304
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.2149    0.75396 0.912 0.000 0.088 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.9293   -0.06846 0.264 0.208 0.112 0.416
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4950    0.38486 0.004 0.000 0.620 0.376
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.6912    0.23893 0.000 0.192 0.216 0.592
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.9298    0.19461 0.156 0.432 0.260 0.152
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4786    0.71553 0.800 0.012 0.060 0.128
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0376    0.71483 0.000 0.992 0.004 0.004
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4981    0.40885 0.536 0.000 0.464 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.5163    0.38713 0.516 0.000 0.480 0.004
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#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  0.4981    0.41563 0.536 0.000 0.464 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.2275    0.77049 0.928 0.020 0.048 0.004
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     4  0.5376    0.35351 0.000 0.396 0.016 0.588
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.8362    0.42096 0.544 0.100 0.124 0.232
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     3  0.8314    0.15612 0.240 0.140 0.540 0.080
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0564    0.78439 0.988 0.004 0.004 0.004
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.4776    0.38295 0.000 0.000 0.624 0.376
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.4776    0.50075 0.624 0.000 0.376 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.0000    0.71416 0.000 1.000 0.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.5438    0.22293 0.536 0.008 0.452 0.004
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.0188    0.78389 0.996 0.000 0.004 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.4925    0.32930 0.000 0.000 0.572 0.428
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     4  0.4722    0.39943 0.000 0.300 0.008 0.692
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.4500    0.73793 0.000 0.684 0.000 0.316
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.1624    0.41633 0.020 0.000 0.952 0.028
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.6932    0.60280 0.004 0.496 0.096 0.404
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.3649    0.74600 0.000 0.796 0.000 0.204
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.4164    0.74540 0.000 0.736 0.000 0.264
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.6486    0.64251 0.004 0.536 0.064 0.396
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.4804    0.71533 0.000 0.616 0.000 0.384
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.1902    0.76935 0.932 0.004 0.064 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.2718    0.76825 0.912 0.020 0.056 0.012
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.3487    0.74377 0.872 0.020 0.016 0.092
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.4925    0.32930 0.000 0.000 0.572 0.428
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.3764    0.74550 0.000 0.784 0.000 0.216
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.6617    0.63367 0.000 0.532 0.088 0.380
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.2149    0.64407 0.000 0.912 0.000 0.088
#> 80936433-AA91-4219-98F1-706C36298060     4  0.5279    0.35654 0.000 0.400 0.012 0.588
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.6944    0.12103 0.284 0.040 0.064 0.612
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.7097    0.46078 0.604 0.032 0.088 0.276
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.3569    0.67967 0.804 0.000 0.196 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     4  0.5273    0.36424 0.000 0.456 0.008 0.536
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.3801    0.66333 0.780 0.000 0.220 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.2586    0.76188 0.912 0.008 0.012 0.068
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.7738    0.29664 0.500 0.060 0.072 0.368
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0804    0.78368 0.980 0.008 0.012 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.4898    0.34794 0.000 0.000 0.584 0.416
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0804    0.41711 0.008 0.000 0.980 0.012
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.5696    0.61193 0.024 0.592 0.004 0.380
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4  0.8555   -0.16153 0.336 0.028 0.264 0.372
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     4  0.5055    0.22546 0.000 0.032 0.256 0.712
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.7463    0.36419 0.536 0.036 0.088 0.340
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.1302    0.78178 0.956 0.000 0.044 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3355    0.35694 0.160 0.000 0.836 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.8333    0.20060 0.444 0.080 0.096 0.380
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.3970    0.73176 0.836 0.036 0.124 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.6907    0.48609 0.620 0.028 0.084 0.268
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.4948    0.43822 0.560 0.000 0.440 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.4790    0.71262 0.000 0.620 0.000 0.380
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.7034    0.66905 0.088 0.624 0.036 0.252
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.6109    0.27873 0.016 0.020 0.504 0.460
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.3873    0.74561 0.000 0.772 0.000 0.228
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4955    0.43681 0.556 0.000 0.444 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.7796    0.54483 0.024 0.464 0.132 0.380
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.3157    0.36822 0.144 0.000 0.852 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.4989    0.26692 0.000 0.000 0.528 0.472
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0895    0.78292 0.976 0.004 0.020 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.4790    0.71262 0.000 0.620 0.000 0.380
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.5364    0.38950 0.052 0.192 0.012 0.744
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.4454    0.58944 0.692 0.000 0.308 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.9630    0.24773 0.256 0.348 0.132 0.264
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.3764    0.74660 0.000 0.784 0.000 0.216
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4888    0.47128 0.588 0.000 0.412 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.4950    0.38387 0.004 0.000 0.620 0.376
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.4562    0.42592 0.028 0.000 0.764 0.208
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0804    0.78387 0.980 0.008 0.012 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0188    0.71580 0.000 0.996 0.000 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.5443    0.64007 0.016 0.616 0.004 0.364
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4776    0.38295 0.000 0.000 0.624 0.376
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2667    0.76703 0.912 0.020 0.060 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4661    0.55799 0.652 0.000 0.348 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4817    0.37352 0.000 0.000 0.612 0.388
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0992    0.78385 0.976 0.004 0.012 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.6610    0.21651 0.016 0.196 0.664 0.124
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.4996    0.24609 0.000 0.000 0.516 0.484
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.4804   -0.10002 0.384 0.000 0.616 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4522    0.57690 0.680 0.000 0.320 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4790    0.71262 0.000 0.620 0.000 0.380
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.4579    0.74264 0.004 0.756 0.016 0.224
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.8622    0.38296 0.500 0.076 0.180 0.244
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.6274    0.21571 0.020 0.024 0.520 0.436
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0524    0.71163 0.004 0.988 0.000 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.4643    0.72908 0.000 0.656 0.000 0.344
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.4730    0.51897 0.636 0.000 0.364 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0188    0.78389 0.996 0.000 0.004 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.5093    0.39899 0.012 0.000 0.640 0.348
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1902    0.77411 0.932 0.004 0.064 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.4661    0.72772 0.000 0.652 0.000 0.348
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.3702    0.73669 0.860 0.028 0.100 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.8327    0.17677 0.452 0.364 0.124 0.060
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.4817    0.48685 0.612 0.000 0.388 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.4164    0.74614 0.000 0.736 0.000 0.264
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0524    0.78398 0.988 0.008 0.004 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4454    0.59286 0.692 0.000 0.308 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.5000    0.19215 0.504 0.000 0.496 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.5039   -0.01680 0.000 0.004 0.404 0.592
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0657    0.78375 0.984 0.004 0.012 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4761    0.41811 0.628 0.000 0.372 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3801    0.42008 0.000 0.780 0.000 0.220
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.3649    0.74600 0.000 0.796 0.000 0.204
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.7900    0.52813 0.024 0.452 0.144 0.380
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.9027    0.43008 0.148 0.484 0.152 0.216
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.5161   -0.00853 0.000 0.008 0.400 0.592
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.7699    0.23526 0.220 0.000 0.400 0.380
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4012    0.43220 0.016 0.000 0.800 0.184
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5128    0.69514 0.788 0.032 0.048 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4250    0.74458 0.000 0.724 0.000 0.276
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3356    0.74726 0.000 0.824 0.000 0.176
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4776    0.38295 0.000 0.000 0.624 0.376
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000    0.78351 1.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4173    0.65784 0.804 0.004 0.172 0.020
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.5291    0.36958 0.024 0.000 0.652 0.324
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1940    0.73379 0.000 0.924 0.000 0.076
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0188    0.78360 0.996 0.004 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.4925   -0.21494 0.428 0.000 0.572 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4819    0.43525 0.652 0.004 0.344 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0336    0.78354 0.992 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.4431    0.70317 0.000 0.696 0.000 0.304
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4804    0.48778 0.616 0.000 0.384 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5296   -0.34046 0.000 0.500 0.008 0.492
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.5000    0.21870 0.000 0.000 0.504 0.496
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0336    0.71350 0.000 0.992 0.000 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2704    0.73350 0.876 0.000 0.124 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1593    0.78069 0.956 0.016 0.024 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.3873    0.32128 0.228 0.000 0.772 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1229    0.78188 0.968 0.004 0.008 0.020

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3771   0.527144 0.000 0.796 0.000 0.164 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.7657  -0.019303 0.024 0.404 0.028 0.364 0.180
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0579   0.665633 0.000 0.000 0.984 0.008 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4164   0.445620 0.000 0.024 0.200 0.764 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4235   0.313315 0.000 0.656 0.000 0.336 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     5  0.6791   0.546405 0.312 0.000 0.304 0.000 0.384
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.7596  -0.250717 0.388 0.012 0.384 0.040 0.176
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1915   0.591717 0.928 0.000 0.000 0.032 0.040
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.8141   0.216184 0.264 0.032 0.476 0.112 0.116
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1831   0.653775 0.004 0.000 0.920 0.000 0.076
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#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.3051   0.627379 0.060 0.000 0.864 0.000 0.076
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2763   0.562959 0.848 0.000 0.000 0.004 0.148
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4304  -0.470962 0.516 0.000 0.000 0.000 0.484
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1197   0.660393 0.000 0.000 0.952 0.000 0.048
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.2712   0.593081 0.880 0.000 0.000 0.032 0.088
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.8866   0.307351 0.092 0.140 0.460 0.168 0.140
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.1493   0.664785 0.000 0.000 0.948 0.028 0.024
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     5  0.5920   0.667856 0.328 0.000 0.108 0.004 0.560
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4310  -0.273716 0.604 0.000 0.000 0.004 0.392
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.1668   0.595879 0.940 0.000 0.000 0.032 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0451   0.563072 0.000 0.988 0.000 0.004 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.5607   0.440427 0.000 0.676 0.040 0.220 0.064
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.7992   0.169457 0.460 0.244 0.028 0.052 0.216
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.6751   0.553656 0.060 0.128 0.664 0.088 0.060
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0794   0.599643 0.972 0.000 0.000 0.000 0.028
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4451   0.071577 0.000 0.504 0.000 0.492 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.2020   0.565150 0.000 0.900 0.000 0.100 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.4425  -0.362995 0.544 0.000 0.000 0.004 0.452
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1992   0.589010 0.924 0.000 0.000 0.032 0.044
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.3359   0.612648 0.072 0.000 0.844 0.000 0.084
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2193   0.594536 0.912 0.000 0.000 0.028 0.060
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.3876   0.471142 0.776 0.000 0.000 0.032 0.192
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1704   0.570552 0.000 0.928 0.000 0.068 0.004
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.3413   0.590180 0.836 0.004 0.012 0.012 0.136
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.8610   0.098138 0.392 0.232 0.040 0.080 0.256
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.4437  -0.383931 0.532 0.000 0.000 0.004 0.464
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.1892   0.562340 0.000 0.916 0.000 0.080 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1952   0.603341 0.912 0.000 0.000 0.004 0.084
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4707  -0.259460 0.588 0.000 0.000 0.020 0.392
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.7340  -0.230449 0.424 0.000 0.256 0.032 0.288
#> 1122039D-5785-4F70-9916-17C585453512     3  0.5008   0.541128 0.004 0.004 0.696 0.236 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2570   0.574409 0.888 0.000 0.000 0.028 0.084
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.6943   0.166037 0.516 0.000 0.188 0.032 0.264
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.4693   0.332721 0.000 0.244 0.056 0.700 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.4800   0.434697 0.000 0.716 0.000 0.196 0.088
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.7792   0.255528 0.120 0.576 0.060 0.128 0.116
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.8709   0.138522 0.132 0.412 0.052 0.124 0.280
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.5008   0.541128 0.004 0.004 0.696 0.236 0.060
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5474   0.395942 0.188 0.000 0.668 0.004 0.140
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2260   0.597870 0.908 0.000 0.000 0.028 0.064
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4705   0.507278 0.052 0.000 0.724 0.008 0.216
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4530   0.522046 0.764 0.080 0.000 0.008 0.148
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2011   0.565506 0.000 0.908 0.000 0.088 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1544   0.601018 0.932 0.000 0.000 0.000 0.068
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4067   0.363309 0.000 0.692 0.000 0.300 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3301   0.614635 0.072 0.000 0.848 0.000 0.080
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2067   0.590783 0.920 0.000 0.000 0.032 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.5574   0.479115 0.672 0.004 0.048 0.036 0.240
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.6103   0.406571 0.160 0.020 0.652 0.008 0.160
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.4192   0.270338 0.000 0.596 0.000 0.404 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1341   0.606158 0.944 0.000 0.000 0.000 0.056
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.5018   0.611626 0.268 0.000 0.068 0.000 0.664
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.5895   0.377354 0.624 0.000 0.148 0.008 0.220
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2139   0.597399 0.916 0.000 0.000 0.032 0.052
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.5778   0.039561 0.000 0.460 0.000 0.452 0.088
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4562  -0.426317 0.548 0.000 0.004 0.004 0.444
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.4215   0.468732 0.000 0.052 0.172 0.772 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2580   0.653541 0.000 0.000 0.892 0.064 0.044
#> A0C429D9-0638-4873-BFB4-00056AB4719F     4  0.4448  -0.040806 0.000 0.480 0.000 0.516 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3278   0.467021 0.824 0.000 0.000 0.020 0.156
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1952   0.592459 0.912 0.000 0.000 0.004 0.084
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     5  0.6438   0.623830 0.232 0.000 0.196 0.012 0.560
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1626   0.606938 0.940 0.016 0.000 0.000 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3479   2.86e-01 0.008 0.768 0.000 0.012 0.212 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.6709   1.58e-01 0.008 0.328 0.008 0.380 0.268 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1078   5.92e-01 0.012 0.008 0.964 0.016 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     5  0.6270  -1.09e-01 0.008 0.076 0.060 0.376 0.480 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.3279   4.36e-01 0.000 0.176 0.000 0.028 0.796 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.5918   4.87e-01 0.496 0.004 0.276 0.000 0.000 0.224
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.7934  -1.12e-01 0.244 0.080 0.384 0.060 0.000 0.232
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     6  0.1887   5.93e-01 0.048 0.012 0.000 0.016 0.000 0.924
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.8881   1.73e-01 0.172 0.200 0.364 0.092 0.028 0.144
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1788   6.03e-01 0.076 0.000 0.916 0.004 0.000 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.2655   4.88e-01 0.004 0.140 0.000 0.008 0.848 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     6  0.2968   6.03e-01 0.056 0.032 0.000 0.044 0.000 0.868
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0405   5.58e-01 0.004 0.008 0.000 0.000 0.988 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     4  0.8700  -7.21e-02 0.104 0.260 0.024 0.296 0.064 0.252
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.8860   6.53e-02 0.168 0.112 0.216 0.280 0.004 0.220
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     6  0.7828   1.99e-01 0.220 0.264 0.000 0.116 0.028 0.372
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.6346   9.34e-02 0.004 0.336 0.004 0.368 0.288 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.6171  -1.80e-01 0.008 0.012 0.184 0.288 0.508 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.3487   5.25e-01 0.000 0.168 0.000 0.044 0.788 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0405   5.61e-01 0.004 0.008 0.000 0.000 0.988 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4389   2.93e-01 0.032 0.000 0.596 0.372 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.3731   3.32e-01 0.004 0.240 0.000 0.020 0.736 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.1692   5.90e-01 0.048 0.012 0.000 0.008 0.000 0.932
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.4094   4.93e-01 0.004 0.252 0.000 0.036 0.708 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.4778   5.88e-01 0.076 0.080 0.000 0.104 0.000 0.740
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.4330   4.75e-01 0.008 0.232 0.000 0.052 0.708 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5605   1.48e-01 0.256 0.000 0.560 0.004 0.000 0.180
#> EE97212E-8D5D-4548-8DD2-317049601FDB     5  0.6928  -2.12e-01 0.032 0.372 0.008 0.160 0.412 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     6  0.4128  -2.87e-01 0.488 0.004 0.000 0.004 0.000 0.504
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     6  0.2860   5.96e-01 0.068 0.028 0.000 0.032 0.000 0.872
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.4528   4.52e-02 0.544 0.008 0.428 0.000 0.000 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0508   5.62e-01 0.004 0.012 0.000 0.000 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.7218   3.49e-01 0.004 0.116 0.160 0.412 0.308 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     6  0.4689   5.16e-01 0.088 0.004 0.024 0.152 0.000 0.732
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     6  0.6122   3.03e-01 0.304 0.048 0.040 0.044 0.000 0.564
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.4264   1.89e-01 0.000 0.492 0.000 0.016 0.492 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3731   2.60e-01 0.004 0.736 0.000 0.020 0.240 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6088   5.84e-01 0.564 0.028 0.212 0.004 0.000 0.192
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2231   5.97e-01 0.048 0.016 0.000 0.028 0.000 0.908
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4564   1.16e-01 0.008 0.000 0.500 0.472 0.020 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     6  0.1485   6.11e-01 0.028 0.004 0.000 0.024 0.000 0.944
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     6  0.6656   4.76e-01 0.156 0.140 0.000 0.144 0.004 0.556
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     5  0.4317  -1.41e-01 0.008 0.464 0.000 0.008 0.520 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.3036   5.23e-01 0.124 0.008 0.000 0.028 0.000 0.840
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.7905  -4.20e-02 0.140 0.440 0.016 0.112 0.036 0.256
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3054   5.96e-01 0.116 0.000 0.840 0.004 0.000 0.040
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.6219  -4.39e-03 0.024 0.008 0.440 0.404 0.124 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.8807   1.35e-02 0.088 0.364 0.048 0.260 0.152 0.088
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     6  0.6874   4.43e-01 0.180 0.156 0.000 0.124 0.008 0.532
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.2636   5.17e-01 0.000 0.120 0.004 0.016 0.860 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.5860   5.29e-01 0.552 0.004 0.016 0.140 0.000 0.288
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3448   6.28e-01 0.716 0.000 0.004 0.000 0.000 0.280
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     5  0.6708  -1.87e-01 0.008 0.060 0.132 0.352 0.448 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5939   3.46e-01 0.492 0.052 0.016 0.040 0.000 0.400
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.4291   1.64e-02 0.356 0.008 0.000 0.016 0.000 0.620
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.6981   4.38e-01 0.140 0.200 0.000 0.152 0.004 0.504
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.4411   1.10e-01 0.012 0.628 0.000 0.020 0.340 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4413   1.75e-01 0.008 0.496 0.000 0.012 0.484 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.8857  -7.67e-02 0.224 0.264 0.280 0.040 0.040 0.152
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.0862   5.62e-01 0.004 0.016 0.000 0.008 0.972 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     6  0.4093  -8.15e-02 0.404 0.012 0.000 0.000 0.000 0.584
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     5  0.3121   5.37e-01 0.004 0.180 0.000 0.012 0.804 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     6  0.6365   5.05e-01 0.132 0.120 0.004 0.152 0.000 0.592
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     6  0.2201   6.06e-01 0.032 0.028 0.000 0.028 0.000 0.912
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.8067   2.38e-01 0.344 0.100 0.312 0.064 0.000 0.180
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.1674   6.04e-01 0.068 0.000 0.924 0.004 0.000 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.3583   3.54e-01 0.004 0.260 0.000 0.008 0.728 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     6  0.7009   4.09e-01 0.144 0.228 0.000 0.152 0.000 0.476
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3855   6.38e-01 0.704 0.000 0.024 0.000 0.000 0.272
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.6725   2.77e-01 0.204 0.112 0.000 0.144 0.004 0.536
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     5  0.5641   2.33e-01 0.004 0.180 0.008 0.216 0.592 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.8099   1.52e-02 0.140 0.468 0.060 0.108 0.024 0.200
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.4461  -1.63e-01 0.004 0.512 0.000 0.020 0.464 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     5  0.6139  -2.38e-01 0.008 0.016 0.132 0.412 0.432 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.6701   4.43e-02 0.416 0.056 0.396 0.012 0.000 0.120
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#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.5237   2.25e-01 0.000 0.276 0.004 0.120 0.600 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.7559   3.43e-01 0.096 0.500 0.016 0.060 0.248 0.080
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.8041   3.85e-02 0.072 0.360 0.024 0.328 0.180 0.036
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.4090   3.01e-01 0.008 0.000 0.604 0.384 0.000 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5086   3.12e-01 0.184 0.000 0.648 0.004 0.000 0.164
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.1991   5.92e-01 0.044 0.012 0.000 0.024 0.000 0.920
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4247   4.66e-01 0.296 0.000 0.664 0.000 0.000 0.040
#> 79BA86D9-466F-48D7-B64B-F933B6995716     6  0.6968   4.18e-01 0.164 0.208 0.000 0.140 0.000 0.488
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     5  0.4412  -1.17e-01 0.008 0.480 0.000 0.012 0.500 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.2426   6.04e-01 0.044 0.012 0.000 0.048 0.000 0.896
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.3834   3.54e-01 0.000 0.232 0.000 0.036 0.732 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3362   5.76e-01 0.096 0.000 0.824 0.004 0.000 0.076
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     6  0.1382   5.94e-01 0.036 0.008 0.000 0.008 0.000 0.948
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     6  0.6598   4.63e-01 0.084 0.060 0.040 0.260 0.000 0.556
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.6028   3.03e-01 0.304 0.036 0.544 0.004 0.000 0.112
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     5  0.4009   4.52e-01 0.000 0.288 0.000 0.028 0.684 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     6  0.2893   6.16e-01 0.024 0.032 0.000 0.076 0.000 0.868
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5711   5.91e-01 0.612 0.000 0.040 0.124 0.000 0.224
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.6646   3.76e-01 0.112 0.020 0.104 0.188 0.000 0.576
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.1003   6.01e-01 0.028 0.004 0.000 0.004 0.000 0.964
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     5  0.6034   1.64e-01 0.000 0.328 0.000 0.260 0.412 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     6  0.3944  -1.43e-01 0.428 0.000 0.000 0.004 0.000 0.568
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     5  0.6221  -1.15e-01 0.008 0.108 0.032 0.400 0.452 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3078   5.15e-01 0.012 0.000 0.796 0.192 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.3493   5.08e-01 0.008 0.228 0.000 0.008 0.756 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     6  0.3411   5.02e-01 0.160 0.024 0.000 0.012 0.000 0.804
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.5105   5.72e-01 0.084 0.092 0.000 0.112 0.000 0.712
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5980   6.26e-01 0.604 0.004 0.160 0.044 0.000 0.188
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.3461   6.13e-01 0.048 0.040 0.000 0.076 0.000 0.836

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 17541 rows and 500 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 0.781           0.896       0.950         0.4925 0.508   0.508
#> 3 3 0.803           0.820       0.928         0.3207 0.767   0.574
#> 4 4 0.637           0.715       0.827         0.1302 0.821   0.551
#> 5 5 0.622           0.580       0.755         0.0666 0.895   0.640
#> 6 6 0.656           0.504       0.735         0.0398 0.850   0.469

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9669 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.0000     0.9669 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.0000     0.9321 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.9669 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9669 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.9321 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.0000     0.9321 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1633     0.9297 0.976 0.024
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.7299     0.7854 0.796 0.204
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.9321 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.9669 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4431     0.8901 0.908 0.092
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9669 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9669 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000     0.9321 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.6973     0.8033 0.812 0.188
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0000     0.9669 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.1184     0.9523 0.016 0.984
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000     0.9669 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9669 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.9996     0.0181 0.512 0.488
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9669 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.1633     0.9297 0.976 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9669 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.7376     0.7801 0.792 0.208
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9669 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.9321 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9669 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.9321 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1843     0.9282 0.972 0.028
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0000     0.9321 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9669 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0000     0.9669 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1633     0.9297 0.976 0.024
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.5294     0.8676 0.880 0.120
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0000     0.9669 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9669 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.9321 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1633     0.9297 0.976 0.024
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0672     0.9296 0.992 0.008
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.7139     0.7942 0.804 0.196
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.9896     0.3223 0.560 0.440
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9669 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9321 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.0000     0.9669 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.9321 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.8608     0.6128 0.284 0.716
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.9754     0.2299 0.408 0.592
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.7883     0.7436 0.764 0.236
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9669 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9321 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000     0.9321 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.9669 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000     0.9321 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9321 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.0000     0.9669 0.000 1.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9669 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9669 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.7219     0.7896 0.800 0.200
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9669 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000     0.9321 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9669 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.6887     0.8073 0.816 0.184
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.3879     0.9013 0.924 0.076
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.0000     0.9321 1.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0000     0.9321 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.9669 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.0000     0.9669 0.000 1.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0000     0.9321 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.1414     0.9303 0.980 0.020
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9669 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.0000     0.9669 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9669 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.9669 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.0000     0.9321 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.5059     0.8491 0.888 0.112
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.0000     0.9321 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0376     0.9634 0.004 0.996
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.0000     0.9321 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.2423     0.9122 0.960 0.040
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.2423     0.9289 0.040 0.960
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000     0.9321 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.7219     0.7896 0.800 0.200
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9669 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9669 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.0000     0.9669 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0000     0.9321 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.6531     0.8236 0.832 0.168
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9321 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     1  0.0000     0.9321 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.6048     0.8429 0.852 0.148
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.7376     0.7804 0.792 0.208
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     1  0.0000     0.9321 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.9321 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9321 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.1843     0.9281 0.972 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000     0.9669 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0000     0.9669 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.7745     0.7544 0.772 0.228
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.5842     0.8189 0.860 0.140
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.2423     0.9226 0.960 0.040
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9669 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9669 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9321 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1633     0.9297 0.976 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0000     0.9321 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1414     0.9303 0.980 0.020
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1633     0.9297 0.976 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0000     0.9669 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.3879     0.9012 0.924 0.076
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.9170     0.5842 0.668 0.332
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9321 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000     0.9669 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.7219     0.7896 0.800 0.200
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9321 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.1633     0.9297 0.976 0.024
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000     0.9321 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.1843     0.9281 0.972 0.028
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0938     0.9312 0.988 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.9669 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9669 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9669 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.6801     0.7518 0.180 0.820
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0000     0.9321 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.9321 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1633     0.9297 0.976 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0000     0.9321 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.8443     0.6904 0.728 0.272
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9669 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2043     0.9264 0.968 0.032
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9669 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.9321 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9321 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4161     0.8957 0.916 0.084
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0000     0.9321 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9669 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2236     0.9246 0.964 0.036
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.9321 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1633     0.9297 0.976 0.024
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1184     0.9308 0.984 0.016
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0000     0.9669 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9321 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9669 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.0000     0.9321 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9669 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1633     0.9297 0.976 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.9460     0.5168 0.636 0.364
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.9321 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5294     0.8676 0.880 0.120

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9480 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.0000     0.9480 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8657 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.9480 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9480 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1289     0.8452 0.032 0.000 0.968
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.5058     0.6087 0.244 0.000 0.756
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9154 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.4702     0.6863 0.788 0.000 0.212
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000     0.8657 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.9480 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.9154 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9480 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.2066     0.8904 0.060 0.940 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6140     0.2876 0.596 0.000 0.404
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9154 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0000     0.9480 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9480 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000     0.9480 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9480 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000     0.8657 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9480 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9154 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9480 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9154 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.4654     0.7113 0.000 0.792 0.208
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.8657 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.1163     0.9250 0.028 0.972 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4452     0.7136 0.808 0.000 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9154 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6154     0.3084 0.592 0.000 0.408
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9480 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.2066     0.8959 0.000 0.940 0.060
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0424     0.9117 0.992 0.000 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.6026     0.3862 0.624 0.000 0.376
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0424     0.9433 0.008 0.992 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0237     0.9462 0.004 0.996 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.6274     0.1524 0.456 0.000 0.544
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0237     0.9137 0.996 0.000 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.0000     0.8657 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.9154 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9154 1.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9480 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9154 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.2066     0.8921 0.060 0.940 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.8657 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0237     0.8635 0.000 0.004 0.996
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5733     0.5007 0.676 0.324 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000     0.9154 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9480 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0237     0.9137 0.996 0.000 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.6008     0.3745 0.372 0.000 0.628
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.9480 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000     0.9154 1.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0237     0.9137 0.996 0.000 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000     0.9154 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9480 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0237     0.9462 0.004 0.996 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.9569     0.1561 0.384 0.196 0.420
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9480 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000     0.9154 1.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9480 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.9154 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000     0.9154 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.0000     0.9154 1.000 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000     0.8657 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.9480 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.2796     0.8258 0.908 0.092 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4399     0.7226 0.812 0.000 0.188
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0237     0.9137 0.996 0.000 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9480 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.0424     0.9433 0.008 0.992 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9480 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.5431     0.5818 0.000 0.716 0.284
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.6168     0.2740 0.412 0.000 0.588
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.1860     0.8322 0.000 0.052 0.948
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.8657 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.4351     0.7661 0.004 0.828 0.168
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.1411     0.8422 0.036 0.000 0.964
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.8657 0.000 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0000     0.9154 1.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.6111     0.3293 0.000 0.604 0.396
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000     0.9154 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.6045     0.3708 0.000 0.620 0.380
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0424     0.9096 0.992 0.008 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0237     0.9462 0.004 0.996 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0237     0.9137 0.996 0.000 0.004
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.8657 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0237     0.9137 0.996 0.000 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0237     0.9462 0.004 0.996 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0237     0.9137 0.996 0.000 0.004
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0000     0.9154 1.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.5591     0.5558 0.304 0.696 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9480 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.9154 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.0000     0.9480 0.000 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9480 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9480 0.000 1.000 0.000
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#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0237     0.9137 0.996 0.000 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000     0.8657 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6026     0.3860 0.624 0.000 0.376
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9154 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9480 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9480 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.0000     0.9480 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000     0.8657 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9154 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.1964     0.8780 0.944 0.000 0.056
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8657 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9154 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.9156     0.4419 0.256 0.204 0.540
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8657 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0424     0.9117 0.992 0.000 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9154 1.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.9154 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0237     0.9462 0.004 0.996 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0000     0.9480 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000     0.9154 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0237     0.8633 0.004 0.000 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9154 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9480 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9480 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9154 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.9154 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.8657 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9154 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9154 1.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0237     0.9462 0.004 0.996 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9154 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0237     0.9132 0.996 0.004 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0237     0.9137 0.996 0.000 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000     0.9480 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9154 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0237     0.9137 0.996 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.6140     0.3188 0.596 0.000 0.404
#> 1122039D-5785-4F70-9916-17C585453512     3  0.0000     0.8657 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9154 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.6140     0.3188 0.596 0.000 0.404
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.9480 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9480 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0237     0.9462 0.004 0.996 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.5733     0.5198 0.324 0.676 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0000     0.8657 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.6062     0.3435 0.384 0.000 0.616
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0237     0.9137 0.996 0.000 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.8657 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.9154 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9480 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9154 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9480 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.8657 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9154 1.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.9154 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2165     0.8242 0.064 0.000 0.936
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9480 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9154 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5529     0.5586 0.704 0.000 0.296
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0592     0.9090 0.988 0.000 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9154 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0000     0.9480 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9154 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4605     0.7174 0.000 0.796 0.204
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8657 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9480 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9154 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9154 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0592     0.9090 0.988 0.000 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9154 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.4564     0.6512 0.000 0.328 0.000 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.2329     0.7805 0.012 0.916 0.072 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2704     0.8292 0.000 0.000 0.876 0.124
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0817     0.8040 0.000 0.976 0.024 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2011     0.7984 0.000 0.920 0.000 0.080
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.2892     0.8306 0.068 0.000 0.896 0.036
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.3401     0.7287 0.008 0.000 0.840 0.152
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0817     0.8664 0.976 0.000 0.000 0.024
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6220     0.6314 0.648 0.000 0.104 0.248
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1118     0.8618 0.000 0.000 0.964 0.036
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3528     0.7832 0.000 0.808 0.000 0.192
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3266     0.7694 0.832 0.000 0.000 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2760     0.7994 0.000 0.872 0.000 0.128
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.4855     0.6805 0.004 0.644 0.000 0.352
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.7137     0.3408 0.536 0.304 0.160 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     4  0.4072     0.6134 0.252 0.000 0.000 0.748
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.1247     0.8026 0.012 0.968 0.016 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.2469     0.7961 0.000 0.892 0.000 0.108
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0469     0.8067 0.000 0.988 0.000 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2469     0.7861 0.000 0.892 0.000 0.108
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2469     0.7861 0.000 0.892 0.000 0.108
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2408     0.7833 0.000 0.896 0.000 0.104
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0336     0.8668 0.992 0.008 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.4797     0.7168 0.000 0.720 0.020 0.260
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.1902     0.7841 0.064 0.932 0.000 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.7663    -0.0471 0.408 0.000 0.380 0.212
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0921     0.8659 0.972 0.000 0.000 0.028
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6520     0.6216 0.648 0.008 0.112 0.232
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.3569     0.7850 0.000 0.804 0.000 0.196
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.3157     0.7363 0.000 0.852 0.144 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4158     0.7439 0.768 0.008 0.000 0.224
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.6317     0.6212 0.644 0.000 0.116 0.240
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4820     0.7213 0.012 0.296 0.000 0.692
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     4  0.3942     0.7653 0.000 0.236 0.000 0.764
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4985     0.1370 0.532 0.000 0.468 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0188     0.8677 0.996 0.004 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.3486     0.7044 0.000 0.188 0.812 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0592     0.8677 0.984 0.000 0.000 0.016
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4941     0.1086 0.564 0.000 0.000 0.436
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     4  0.3975     0.7616 0.000 0.240 0.000 0.760
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.4737     0.7454 0.020 0.252 0.000 0.728
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.4888     0.2657 0.412 0.588 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.3873     0.6399 0.228 0.000 0.000 0.772
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.2469     0.7861 0.000 0.892 0.000 0.108
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1722     0.8544 0.944 0.008 0.000 0.048
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.3958     0.7564 0.160 0.000 0.816 0.024
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.1677     0.8012 0.000 0.948 0.040 0.012
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     4  0.5038     0.4721 0.336 0.000 0.012 0.652
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.5151     0.2435 0.464 0.004 0.000 0.532
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     4  0.3975     0.7616 0.000 0.240 0.000 0.760
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     4  0.4040     0.7603 0.000 0.248 0.000 0.752
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.9856     0.0379 0.332 0.196 0.248 0.224
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0336     0.8073 0.000 0.992 0.000 0.008
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0921     0.8656 0.972 0.000 0.000 0.028
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0336     0.8073 0.000 0.992 0.000 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0817     0.8667 0.976 0.000 0.000 0.024
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.5492     0.3867 0.640 0.000 0.032 0.328
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.4933     0.4368 0.000 0.432 0.000 0.568
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     4  0.4538     0.6634 0.216 0.024 0.000 0.760
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.2124     0.8348 0.924 0.000 0.068 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0469     0.8067 0.000 0.988 0.000 0.012
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.3907     0.7659 0.000 0.232 0.000 0.768
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     4  0.4072     0.7515 0.000 0.252 0.000 0.748
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.2844     0.7916 0.000 0.900 0.052 0.048
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     4  0.4769     0.3318 0.008 0.000 0.308 0.684
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.4661     0.4743 0.000 0.348 0.652 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.2345     0.8420 0.000 0.000 0.900 0.100
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     4  0.4509     0.1257 0.004 0.288 0.000 0.708
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0188     0.8659 0.004 0.000 0.996 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     4  0.4304     0.6182 0.284 0.000 0.000 0.716
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.5088     0.6951 0.000 0.688 0.024 0.288
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     4  0.4661     0.5167 0.348 0.000 0.000 0.652
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.6806     0.5661 0.000 0.544 0.112 0.344
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0927     0.8624 0.976 0.008 0.000 0.016
#> 46351E5C-2438-4B6A-8343-DDF329086771     4  0.3942     0.7642 0.000 0.236 0.000 0.764
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0336     0.8668 0.992 0.008 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0921     0.8636 0.000 0.000 0.972 0.028
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#> 241F589C-D559-43D7-8340-31EBCEB36E14     4  0.4422     0.4665 0.008 0.256 0.000 0.736
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0188     0.8684 0.996 0.000 0.000 0.004
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.1174     0.8059 0.000 0.968 0.020 0.012
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0817     0.8664 0.976 0.000 0.000 0.024
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     4  0.4998     0.1616 0.488 0.000 0.000 0.512
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     4  0.4996     0.1991 0.484 0.000 0.000 0.516
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.1474     0.8549 0.948 0.000 0.000 0.052
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1792     0.8533 0.000 0.000 0.932 0.068
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.7342     0.0444 0.432 0.000 0.412 0.156
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.2402     0.7784 0.012 0.912 0.076 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.2530     0.7895 0.888 0.000 0.000 0.112
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     4  0.5018     0.7313 0.000 0.144 0.088 0.768
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.4250     0.5456 0.724 0.000 0.000 0.276
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.2345     0.8334 0.900 0.000 0.000 0.100
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.4663     0.7554 0.148 0.000 0.788 0.064
#> A7ECBC06-1332-4278-8723-85DC8351188A     4  0.4647     0.6130 0.288 0.008 0.000 0.704
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.1022     0.8639 0.968 0.000 0.000 0.032
#> D9364524-CD1F-4C45-A2EF-8CB401487001     4  0.5416     0.6759 0.112 0.148 0.000 0.740
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     4  0.3942     0.7642 0.000 0.236 0.000 0.764
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.1978     0.7792 0.068 0.928 0.000 0.004
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.1474     0.8058 0.000 0.948 0.000 0.052
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4401     0.5751 0.724 0.000 0.272 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     4  0.3907     0.7659 0.000 0.232 0.000 0.768
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.6621     0.5253 0.616 0.000 0.244 0.140
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.3658     0.8139 0.020 0.000 0.836 0.144
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0336     0.8676 0.992 0.008 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     4  0.3942     0.7642 0.000 0.236 0.000 0.764
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.2861     0.7645 0.016 0.888 0.096 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0188     0.8684 0.996 0.000 0.000 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.5558     0.3401 0.608 0.028 0.000 0.364
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4933     0.7067 0.000 0.688 0.016 0.296
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.2408     0.7883 0.000 0.896 0.000 0.104
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4292     0.7664 0.796 0.008 0.016 0.180
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0469     0.8663 0.988 0.012 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     4  0.4072     0.7512 0.000 0.252 0.000 0.748
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.4989    -0.1377 0.000 0.528 0.000 0.472
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.2402     0.7784 0.012 0.912 0.076 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.6703     0.5793 0.612 0.000 0.156 0.232
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1022     0.8650 0.968 0.000 0.000 0.032
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.9458     0.1649 0.136 0.408 0.224 0.232
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.1520     0.8611 0.956 0.000 0.020 0.024
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0707     0.8673 0.980 0.000 0.000 0.020
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0592     0.8677 0.984 0.000 0.000 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     4  0.3942     0.7642 0.000 0.236 0.000 0.764
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0592     0.8073 0.000 0.984 0.000 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     4  0.4406     0.5627 0.300 0.000 0.000 0.700
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     4  0.4389     0.6973 0.000 0.072 0.116 0.812
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0336     0.8678 0.992 0.000 0.000 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4331     0.7310 0.000 0.712 0.000 0.288
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     4  0.3975     0.7616 0.000 0.240 0.000 0.760
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1474     0.8581 0.948 0.000 0.000 0.052
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0592     0.8677 0.984 0.000 0.000 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.4999     0.3893 0.000 0.492 0.000 0.508
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.1792     0.8394 0.932 0.068 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.3311     0.7597 0.828 0.172 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.2011     0.7938 0.000 0.920 0.000 0.080
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0188     0.8677 0.996 0.004 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.7097     0.5225 0.584 0.004 0.180 0.232
#> 1122039D-5785-4F70-9916-17C585453512     3  0.0469     0.8622 0.000 0.012 0.988 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0921     0.8659 0.972 0.000 0.000 0.028
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.5274     0.7060 0.724 0.008 0.036 0.232
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0336     0.8063 0.000 0.992 0.000 0.008
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.2011     0.8009 0.000 0.920 0.000 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     4  0.4720     0.7528 0.000 0.188 0.044 0.768
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.3649     0.6293 0.204 0.796 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0817     0.8569 0.000 0.024 0.976 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.4356     0.5575 0.292 0.000 0.708 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0469     0.8678 0.988 0.000 0.000 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2921     0.8223 0.000 0.000 0.860 0.140
#> 79BA86D9-466F-48D7-B64B-F933B6995716     4  0.4679     0.4960 0.352 0.000 0.000 0.648
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3569     0.6246 0.000 0.804 0.000 0.196
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.8684 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2281     0.7924 0.000 0.904 0.000 0.096
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0592     0.8677 0.984 0.000 0.000 0.016
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4262     0.7372 0.756 0.008 0.000 0.236
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4104     0.7994 0.080 0.000 0.832 0.088
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0592     0.8067 0.000 0.984 0.000 0.016
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0469     0.8678 0.988 0.000 0.000 0.012
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.6371     0.6089 0.664 0.004 0.200 0.132
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3852     0.7678 0.800 0.008 0.000 0.192
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0188     0.8684 0.996 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0376     0.8064 0.004 0.992 0.004 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0188     0.8682 0.996 0.000 0.000 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2469     0.7799 0.000 0.892 0.000 0.108
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8670 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.3400     0.7132 0.000 0.820 0.000 0.180
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0707     0.8673 0.980 0.000 0.000 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.2149     0.8296 0.912 0.000 0.000 0.088
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0657     0.8681 0.984 0.004 0.000 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0592     0.8674 0.984 0.000 0.000 0.016

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5235    0.42988 0.000 0.620 0.000 0.312 0.068
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.3996    0.53957 0.228 0.000 0.012 0.752 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0404    0.81719 0.000 0.012 0.988 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0324    0.70654 0.004 0.000 0.004 0.992 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.3639    0.69583 0.000 0.024 0.000 0.792 0.184
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.5098    0.58366 0.004 0.208 0.696 0.000 0.092
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.1965    0.77021 0.000 0.096 0.904 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4985    0.65453 0.680 0.076 0.000 0.000 0.244
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     5  0.5334    0.40795 0.244 0.104 0.000 0.000 0.652
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1341    0.79850 0.000 0.000 0.944 0.000 0.056
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4  0.4718    0.50674 0.000 0.016 0.000 0.540 0.444
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.6688    0.28536 0.404 0.356 0.000 0.000 0.240
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     4  0.4371    0.61942 0.000 0.012 0.000 0.644 0.344
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3630    0.29267 0.000 0.016 0.000 0.204 0.780
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.4557    0.15589 0.584 0.000 0.000 0.404 0.012
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.4558    0.54739 0.060 0.724 0.000 0.000 0.216
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.2463    0.65593 0.100 0.000 0.004 0.888 0.008
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     4  0.3999    0.62250 0.000 0.000 0.000 0.656 0.344
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.0451    0.71105 0.000 0.004 0.000 0.988 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     4  0.5215    0.59960 0.000 0.056 0.000 0.592 0.352
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000    0.82054 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     4  0.5404    0.66154 0.000 0.152 0.000 0.664 0.184
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.1410    0.72065 0.940 0.000 0.000 0.000 0.060
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     4  0.3835    0.59890 0.000 0.244 0.000 0.744 0.012
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0451    0.70995 0.988 0.000 0.000 0.004 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.4088    0.08411 0.000 0.008 0.000 0.304 0.688
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000    0.82054 0.000 0.000 1.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     4  0.1043    0.69423 0.040 0.000 0.000 0.960 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.8338   -0.23415 0.292 0.348 0.160 0.000 0.200
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.6009    0.54996 0.580 0.180 0.000 0.000 0.240
#> 97C34F1F-2002-4771-8D99-511EA08591CD     5  0.4016    0.47222 0.272 0.000 0.012 0.000 0.716
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     4  0.4726    0.56255 0.000 0.020 0.000 0.580 0.400
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.1788    0.68100 0.004 0.000 0.056 0.932 0.008
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.3561    0.47425 0.260 0.000 0.000 0.000 0.740
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     5  0.5472    0.37330 0.260 0.108 0.000 0.000 0.632
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.5284    0.33932 0.036 0.332 0.000 0.616 0.016
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.2966    0.74920 0.000 0.848 0.000 0.136 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4307    0.07692 0.504 0.000 0.496 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0324    0.70821 0.992 0.000 0.000 0.004 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.2377    0.74901 0.000 0.000 0.872 0.128 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4730    0.66444 0.688 0.052 0.000 0.000 0.260
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.5039   -0.06614 0.456 0.512 0.000 0.000 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.3496    0.68479 0.000 0.788 0.000 0.200 0.012
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.71175 1.000 0.000 0.000 0.000 0.000
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#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3491    0.69343 0.768 0.004 0.000 0.000 0.228
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.5073    0.55312 0.000 0.100 0.688 0.000 0.212
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.3177    0.61280 0.208 0.792 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     4  0.2798    0.66919 0.000 0.140 0.000 0.852 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0324    0.70821 0.992 0.000 0.000 0.004 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.4588    0.68251 0.000 0.060 0.000 0.720 0.220
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000    0.82054 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4904    0.66060 0.688 0.072 0.000 0.000 0.240
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.2891    0.56337 0.176 0.000 0.000 0.000 0.824
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.6909    0.14028 0.008 0.360 0.400 0.000 0.232
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     4  0.0579    0.71173 0.000 0.008 0.000 0.984 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3461    0.69526 0.772 0.004 0.000 0.000 0.224
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.6548    0.04980 0.420 0.000 0.200 0.000 0.380
#> EB7883EB-0079-4548-9132-169E94A698BA     5  0.4101    0.40976 0.372 0.000 0.000 0.000 0.628
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4369    0.69120 0.740 0.052 0.000 0.000 0.208
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0898    0.70015 0.020 0.000 0.000 0.972 0.008
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4305    0.69499 0.748 0.052 0.000 0.000 0.200
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.1671    0.67215 0.000 0.000 0.000 0.924 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000    0.82054 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     4  0.5946    0.60009 0.000 0.224 0.000 0.592 0.184
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5004    0.66799 0.692 0.092 0.000 0.000 0.216
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5526    0.61310 0.648 0.200 0.000 0.000 0.152
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.1478    0.71464 0.936 0.000 0.000 0.000 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4981    0.67757 0.704 0.108 0.000 0.000 0.188

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.6069    0.16372 0.000 0.512 0.000 0.116 0.332 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0806    0.73274 0.000 0.000 0.000 0.972 0.020 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     6  0.4587   -0.06821 0.000 0.036 0.456 0.000 0.000 0.508
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.2838    0.74546 0.000 0.004 0.000 0.808 0.188 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.3695    0.66928 0.000 0.164 0.000 0.060 0.776 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.6590   -0.07827 0.292 0.032 0.424 0.000 0.000 0.252
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.3271    0.57823 0.000 0.232 0.760 0.000 0.000 0.008
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0692    0.55418 0.976 0.004 0.000 0.000 0.000 0.020
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     6  0.4396    0.54782 0.352 0.036 0.000 0.000 0.000 0.612
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0260    0.73703 0.000 0.008 0.000 0.000 0.992 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1644    0.53041 0.932 0.028 0.000 0.000 0.000 0.040
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0146    0.73434 0.000 0.000 0.000 0.000 0.996 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.0937    0.72150 0.000 0.000 0.000 0.000 0.960 0.040
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.5484    0.35330 0.128 0.000 0.012 0.588 0.000 0.272
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5035    0.05701 0.600 0.296 0.000 0.000 0.000 0.104
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.1584    0.75121 0.000 0.000 0.000 0.928 0.064 0.008
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0146    0.73637 0.000 0.004 0.000 0.000 0.996 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.3922    0.59775 0.000 0.016 0.000 0.664 0.320 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.1910    0.72986 0.000 0.108 0.000 0.000 0.892 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0146    0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.5170    0.46495 0.000 0.176 0.000 0.204 0.620 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.3460    0.56276 0.760 0.000 0.000 0.020 0.000 0.220
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     4  0.5183    0.61661 0.000 0.156 0.000 0.644 0.192 0.008
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.5670    0.47940 0.516 0.000 0.000 0.188 0.000 0.296
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.2053    0.68507 0.000 0.000 0.000 0.004 0.888 0.108
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     4  0.5473    0.60073 0.164 0.004 0.000 0.628 0.192 0.012
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2362    0.51882 0.892 0.016 0.080 0.000 0.000 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1124    0.54266 0.956 0.008 0.000 0.000 0.000 0.036
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.7218   -0.32947 0.348 0.000 0.100 0.000 0.212 0.340
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0547    0.73793 0.000 0.020 0.000 0.000 0.980 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.2714    0.75873 0.000 0.004 0.012 0.848 0.136 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.5434   -0.04600 0.576 0.000 0.000 0.000 0.232 0.192
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3993   -0.34159 0.520 0.004 0.000 0.000 0.000 0.476
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5066    0.62452 0.000 0.704 0.000 0.156 0.080 0.060
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.2898    0.74290 0.000 0.868 0.000 0.016 0.060 0.056
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.3975    0.19622 0.544 0.000 0.452 0.000 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.5611    0.48680 0.528 0.000 0.000 0.180 0.000 0.292
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.0146    0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0717    0.55550 0.976 0.000 0.000 0.000 0.008 0.016
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5468    0.03083 0.480 0.440 0.000 0.016 0.008 0.056
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.3559    0.70718 0.000 0.820 0.000 0.020 0.104 0.056
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.4463    0.53551 0.652 0.000 0.000 0.056 0.000 0.292
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.3219    0.73812 0.000 0.852 0.000 0.032 0.056 0.060
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.3482    0.41123 0.000 0.000 0.684 0.316 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.2357    0.75771 0.012 0.000 0.000 0.872 0.116 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  0.6062   -0.18783 0.304 0.408 0.000 0.000 0.000 0.288
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.3337    0.63571 0.000 0.260 0.000 0.004 0.736 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4998    0.50015 0.580 0.000 0.000 0.048 0.016 0.356
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.5130   -0.07786 0.612 0.032 0.048 0.000 0.000 0.308
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.3046    0.74212 0.000 0.012 0.000 0.800 0.188 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5650   -0.25012 0.500 0.168 0.000 0.000 0.000 0.332
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.3670    0.54971 0.704 0.000 0.000 0.012 0.000 0.284
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.4721    0.27899 0.364 0.592 0.000 0.020 0.000 0.024
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0520    0.78036 0.000 0.984 0.000 0.008 0.008 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.3070    0.73454 0.000 0.856 0.000 0.016 0.072 0.056
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     6  0.4710    0.50247 0.400 0.016 0.000 0.016 0.004 0.564
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.3748    0.37995 0.000 0.012 0.000 0.300 0.688 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0717    0.55804 0.976 0.008 0.000 0.000 0.000 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     4  0.3386    0.74199 0.000 0.012 0.000 0.796 0.176 0.016
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.5536    0.49354 0.540 0.000 0.000 0.168 0.000 0.292
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.1049    0.54554 0.960 0.008 0.000 0.000 0.000 0.032
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6971    0.27322 0.484 0.268 0.156 0.012 0.000 0.080
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.3351    0.62267 0.000 0.288 0.000 0.000 0.712 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.4650    0.59301 0.224 0.704 0.000 0.004 0.040 0.028
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3878    0.40001 0.668 0.000 0.320 0.004 0.000 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.5611    0.48680 0.528 0.000 0.000 0.180 0.000 0.292
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.3078    0.73980 0.000 0.012 0.000 0.796 0.192 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.0520    0.78152 0.008 0.984 0.000 0.000 0.000 0.008
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1049    0.77785 0.000 0.960 0.000 0.032 0.000 0.008
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.3611    0.73932 0.000 0.008 0.004 0.780 0.188 0.020
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     6  0.6082    0.27462 0.272 0.360 0.000 0.000 0.000 0.368
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.3979    0.10043 0.000 0.000 0.456 0.540 0.000 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.5629   -0.05446 0.128 0.004 0.456 0.000 0.000 0.412
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.5807    0.15288 0.000 0.376 0.000 0.000 0.440 0.184
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0146    0.81419 0.000 0.000 0.996 0.000 0.000 0.004
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.5020    0.48226 0.000 0.000 0.628 0.244 0.000 0.128
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.3323    0.74672 0.072 0.848 0.000 0.016 0.008 0.056
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.3023    0.54956 0.000 0.000 0.000 0.000 0.768 0.232
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.4159    0.23974 0.588 0.396 0.000 0.000 0.000 0.016
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     6  0.6073    0.58997 0.212 0.052 0.000 0.064 0.044 0.628
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.5359    0.46551 0.636 0.000 0.000 0.020 0.216 0.128
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0146    0.78202 0.000 0.996 0.000 0.000 0.000 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.5647    0.48236 0.520 0.000 0.000 0.184 0.000 0.296
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.2912    0.63559 0.000 0.000 0.784 0.000 0.000 0.216
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.5079    0.46914 0.536 0.000 0.000 0.084 0.000 0.380
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.1444    0.75378 0.000 0.928 0.000 0.000 0.000 0.072
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.3586    0.52836 0.720 0.000 0.000 0.000 0.012 0.268
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.5578   -0.38134 0.456 0.140 0.000 0.000 0.000 0.404
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.3998    0.72435 0.056 0.816 0.000 0.016 0.056 0.056
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     5  0.1957    0.72897 0.000 0.112 0.000 0.000 0.888 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.1268    0.56138 0.952 0.000 0.000 0.036 0.004 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0260    0.73703 0.000 0.008 0.000 0.000 0.992 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     4  0.4469    0.63897 0.000 0.012 0.000 0.676 0.272 0.040
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.0547    0.73894 0.000 0.020 0.000 0.000 0.980 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.0632    0.80568 0.000 0.000 0.976 0.024 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.4835    0.33034 0.000 0.592 0.000 0.336 0.072 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.6494    0.44561 0.488 0.000 0.000 0.132 0.068 0.312
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.5611    0.48680 0.528 0.000 0.000 0.180 0.000 0.292
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0622    0.78082 0.012 0.980 0.000 0.000 0.000 0.008
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     6  0.5720    0.20549 0.000 0.072 0.000 0.340 0.044 0.544
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.5438    0.52250 0.604 0.000 0.024 0.096 0.000 0.276
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     6  0.3907   -0.19837 0.004 0.000 0.000 0.408 0.000 0.588
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.3578    0.00163 0.660 0.000 0.000 0.000 0.000 0.340
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.1219    0.76839 0.000 0.948 0.000 0.004 0.048 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.4130    0.55561 0.716 0.036 0.000 0.008 0.000 0.240
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     5  0.3136    0.66615 0.000 0.228 0.000 0.004 0.768 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.3216    0.73269 0.000 0.848 0.000 0.020 0.072 0.060
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0291    0.78185 0.000 0.992 0.000 0.000 0.004 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.3563    0.39068 0.800 0.092 0.000 0.000 0.000 0.108
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     5  0.5771    0.50681 0.000 0.272 0.000 0.088 0.588 0.052
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#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0547    0.77882 0.000 0.980 0.000 0.000 0.020 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     4  0.4177    0.25988 0.000 0.012 0.000 0.520 0.468 0.000
#> 80936433-AA91-4219-98F1-706C36298060     3  0.4298    0.54895 0.000 0.004 0.732 0.088 0.176 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.3841    0.20703 0.000 0.000 0.380 0.616 0.000 0.004
#> 241F589C-D559-43D7-8340-31EBCEB36E14     5  0.4284    0.66919 0.108 0.136 0.000 0.000 0.748 0.008
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0260    0.56573 0.992 0.000 0.000 0.000 0.000 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.3717    0.55164 0.708 0.000 0.000 0.016 0.000 0.276
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     4  0.3610    0.74487 0.000 0.012 0.020 0.788 0.176 0.004
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0777    0.55195 0.972 0.004 0.000 0.000 0.000 0.024
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.4408    0.53666 0.656 0.000 0.000 0.052 0.000 0.292
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.3592    0.28817 0.656 0.344 0.000 0.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.5573    0.42296 0.316 0.584 0.000 0.016 0.020 0.064
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.1245    0.54323 0.952 0.016 0.000 0.000 0.000 0.032
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.2872    0.69439 0.000 0.000 0.836 0.000 0.024 0.140
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     6  0.3769    0.54542 0.356 0.004 0.000 0.000 0.000 0.640
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.1349    0.74751 0.000 0.000 0.000 0.940 0.056 0.004
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.6647    0.35455 0.460 0.184 0.000 0.004 0.044 0.308
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#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.1152    0.74407 0.000 0.000 0.000 0.952 0.044 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.5611    0.48680 0.528 0.000 0.000 0.180 0.000 0.292
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4616    0.23014 0.708 0.000 0.008 0.000 0.180 0.104
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
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#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.4604    0.01052 0.536 0.432 0.000 0.008 0.000 0.024
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.4499    0.66919 0.024 0.732 0.028 0.016 0.000 0.200
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0260    0.56283 0.992 0.008 0.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.0260    0.73280 0.000 0.000 0.000 0.000 0.992 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.2554    0.73370 0.000 0.876 0.000 0.048 0.000 0.076
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#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1333    0.53323 0.944 0.008 0.000 0.000 0.000 0.048
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0146    0.81419 0.000 0.000 0.996 0.000 0.000 0.004
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#> D9C02B51-F92B-4F5F-89AC-BD526832C915     6  0.5543    0.48445 0.372 0.000 0.000 0.000 0.140 0.488
#> 1122039D-5785-4F70-9916-17C585453512     3  0.0146    0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.1124    0.54266 0.956 0.008 0.000 0.000 0.000 0.036
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.6056   -0.34354 0.412 0.000 0.000 0.000 0.292 0.296
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3078    0.73980 0.000 0.012 0.000 0.796 0.192 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.1462    0.70673 0.000 0.000 0.000 0.056 0.936 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3565    0.49666 0.000 0.692 0.000 0.004 0.000 0.304
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.2668    0.75315 0.004 0.000 0.000 0.828 0.168 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0146    0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0291    0.56515 0.992 0.000 0.000 0.000 0.004 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     6  0.6205    0.44738 0.176 0.044 0.232 0.000 0.000 0.548
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.4066    0.49483 0.272 0.692 0.000 0.000 0.000 0.036
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     4  0.4715    0.66832 0.000 0.136 0.000 0.736 0.080 0.048
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#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.2823    0.68465 0.000 0.204 0.000 0.000 0.796 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
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#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4895   -0.14000 0.496 0.000 0.000 0.000 0.444 0.060
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#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0260    0.56622 0.992 0.000 0.000 0.000 0.000 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5684    0.22739 0.552 0.000 0.276 0.000 0.164 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.6182    0.04442 0.240 0.000 0.000 0.016 0.256 0.488
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0146    0.56516 0.996 0.000 0.000 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.2584    0.75754 0.000 0.004 0.000 0.848 0.144 0.004
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#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     4  0.3732    0.73112 0.000 0.000 0.000 0.780 0.144 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000    0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.3652    0.55272 0.000 0.324 0.000 0.004 0.672 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0806    0.55514 0.972 0.008 0.000 0.000 0.000 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.7125    0.09214 0.464 0.200 0.000 0.156 0.000 0.180
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5213    0.43103 0.488 0.000 0.000 0.092 0.000 0.420
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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-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 17541 rows and 500 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 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-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 0.0736           0.628       0.787         0.4069 0.596   0.596
#> 3 3 0.0856           0.478       0.714         0.2945 0.898   0.835
#> 4 4 0.1500           0.336       0.592         0.2165 0.767   0.586
#> 5 5 0.2381           0.329       0.566         0.1060 0.840   0.606
#> 6 6 0.3177           0.362       0.583         0.0654 0.865   0.605

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.9977    0.15873 0.528 0.472
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0376    0.68834 0.996 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000    0.73162 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.9833    0.37938 0.424 0.576
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.9922    0.33750 0.448 0.552
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.3879    0.77035 0.076 0.924
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9552    0.54231 0.376 0.624
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.7883    0.73561 0.236 0.764
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.2778    0.75699 0.048 0.952
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.7745    0.71461 0.228 0.772
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.8955    0.58806 0.312 0.688
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.8327    0.71350 0.264 0.736
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.7376    0.72103 0.208 0.792
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.6623    0.77486 0.172 0.828
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.9129    0.51127 0.672 0.328
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.6438    0.77192 0.164 0.836
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0376    0.68834 0.996 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.9087    0.59369 0.324 0.676
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.9998   -0.09435 0.508 0.492
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.5519    0.72805 0.128 0.872
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.9896    0.08429 0.440 0.560
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.9358    0.59727 0.352 0.648
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2778    0.70219 0.952 0.048
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.6148    0.71694 0.152 0.848
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.5842    0.69700 0.860 0.140
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.5059    0.73156 0.112 0.888
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.7453    0.75910 0.212 0.788
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.8555    0.70385 0.280 0.720
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.9977    0.21710 0.472 0.528
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     2  0.9963    0.28127 0.464 0.536
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.6801    0.76339 0.180 0.820
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.5519    0.72805 0.128 0.872
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.0376    0.68834 0.996 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.7950    0.73034 0.240 0.760
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.5408    0.77706 0.124 0.876
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.8813    0.55049 0.700 0.300
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.9358    0.45957 0.648 0.352
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.7883    0.74023 0.236 0.764
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1633    0.69588 0.976 0.024
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0376    0.68834 0.996 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.7883    0.73823 0.236 0.764
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.9635    0.53524 0.388 0.612
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.8443    0.69186 0.272 0.728
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.1843    0.69616 0.972 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.8608    0.57206 0.716 0.284
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.2603    0.75710 0.044 0.956
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.9881    0.09694 0.436 0.564
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.8955    0.65365 0.312 0.688
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  1.0000   -0.02246 0.496 0.504
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.9754    0.45882 0.408 0.592
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.7950    0.73034 0.240 0.760
#> 4379559E-E467-49BD-9673-40A486146A3B     2  0.8955    0.64986 0.312 0.688
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.9170    0.49144 0.332 0.668
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.5059    0.77998 0.112 0.888
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.7056    0.67645 0.808 0.192
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.9323    0.47552 0.652 0.348
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.6438    0.75657 0.164 0.836
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.9522    0.38341 0.628 0.372
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.3584    0.76544 0.068 0.932
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.9323    0.57412 0.348 0.652
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.9983    0.20666 0.476 0.524
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.9286    0.57438 0.344 0.656
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.7528    0.65894 0.784 0.216
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.9522    0.56642 0.372 0.628
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     2  0.8713    0.68642 0.292 0.708
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     2  0.4690    0.77255 0.100 0.900
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.9977    0.15873 0.528 0.472
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.9963    0.01790 0.536 0.464
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     2  0.9963    0.25033 0.464 0.536
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.9209    0.49705 0.664 0.336
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.9963    0.21628 0.464 0.536
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.8713    0.53963 0.708 0.292
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.4815    0.76961 0.104 0.896
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.8327    0.59027 0.264 0.736
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.1184    0.74213 0.016 0.984
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.0376    0.68834 0.996 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.3274    0.76473 0.060 0.940
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6438    0.78239 0.164 0.836
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.5737    0.77449 0.136 0.864
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.1414    0.74526 0.020 0.980
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.9775    0.45744 0.412 0.588
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.5059    0.73156 0.112 0.888
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.9393    0.45633 0.644 0.356
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.2236    0.75356 0.036 0.964
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.4022    0.70365 0.920 0.080
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.7376    0.73629 0.208 0.792
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.6343    0.69155 0.840 0.160
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.0672    0.73704 0.008 0.992
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     2  0.9209    0.62296 0.336 0.664
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.7674    0.74117 0.224 0.776
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     2  0.8016    0.72722 0.244 0.756
#> 4D361EA8-1F79-4B89-841B-87F83215D805     2  0.6438    0.77589 0.164 0.836
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.9686    0.32510 0.604 0.396
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.5946    0.73080 0.144 0.856
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     2  0.7602    0.74410 0.220 0.780
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.9209    0.49620 0.336 0.664
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.9286    0.57438 0.344 0.656
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.6343    0.71437 0.160 0.840
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0376    0.68834 0.996 0.004
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.5059    0.77091 0.112 0.888
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     2  0.8016    0.72722 0.244 0.756
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.9833    0.25004 0.576 0.424
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.9552    0.54969 0.376 0.624
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000    0.73162 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.8555    0.60165 0.720 0.280
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.8909    0.51696 0.692 0.308
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.6343    0.77253 0.160 0.840
#> AE903797-7FFB-44A1-B834-C644784B5DC2     2  0.7674    0.75056 0.224 0.776
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.5519    0.76058 0.128 0.872
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.2236    0.69748 0.964 0.036
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.9209    0.61469 0.336 0.664
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.9661    0.33318 0.608 0.392
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.7815    0.71789 0.232 0.768
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     2  0.8443    0.71359 0.272 0.728
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.9977    0.23951 0.472 0.528
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.7299    0.72498 0.204 0.796
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     2  0.5519    0.77761 0.128 0.872
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.4815    0.76961 0.104 0.896
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.2948    0.75845 0.052 0.948
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.6801    0.65497 0.820 0.180
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     2  0.8081    0.73046 0.248 0.752
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.5842    0.70029 0.860 0.140
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1  0.9988   -0.02416 0.520 0.480
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     2  0.9909    0.20096 0.444 0.556
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.7602    0.61386 0.220 0.780
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.0376    0.68834 0.996 0.004
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.9963    0.30349 0.464 0.536
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     2  0.8763    0.68327 0.296 0.704
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.9944    0.10172 0.544 0.456
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.3114    0.69172 0.944 0.056
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     2  0.8267    0.71564 0.260 0.740
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.8608    0.62473 0.284 0.716
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.5294    0.77561 0.120 0.880
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     2  0.7453    0.75748 0.212 0.788
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.8443    0.60884 0.728 0.272
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.1184    0.73382 0.016 0.984
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.0376    0.68834 0.996 0.004
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.4815    0.76961 0.104 0.896
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.9491    0.41041 0.632 0.368
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.5519    0.72805 0.128 0.872
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.2423    0.75351 0.040 0.960
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.6623    0.77128 0.172 0.828
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.6712    0.75702 0.176 0.824
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.6343    0.75740 0.160 0.840
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     2  0.8081    0.73201 0.248 0.752
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.3584    0.75809 0.068 0.932
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.4815    0.73267 0.104 0.896
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#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.3431    0.75903 0.064 0.936
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.5294    0.74389 0.120 0.880
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.6973    0.74078 0.188 0.812
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.9358    0.60135 0.352 0.648
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.8861    0.68252 0.304 0.696
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     2  0.8327    0.70468 0.264 0.736
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.9323    0.47658 0.652 0.348

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2   0.466   0.542479 0.068 0.856 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1   0.148   0.619716 0.968 0.020 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.417   0.547737 0.004 0.156 0.840
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3   0.716   0.357741 0.372 0.032 0.596
#> BE685EF3-953B-483C-A99C-75FBF81D6615     3   0.983   0.146237 0.316 0.264 0.420
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3   0.374   0.640248 0.036 0.072 0.892
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3   0.882   0.458593 0.296 0.148 0.556
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3   0.530   0.640949 0.164 0.032 0.804
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.236   0.598097 0.000 0.072 0.928
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3   0.738   0.277007 0.052 0.320 0.628
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.852   0.462723 0.096 0.508 0.396
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3   0.621   0.631775 0.192 0.052 0.756
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     3   0.850   0.128325 0.104 0.352 0.544
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3   0.492   0.654722 0.108 0.052 0.840
#> 5AB5396F-925B-469C-B240-FB37991004DD     1   0.767   0.487529 0.620 0.068 0.312
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3   0.353   0.658620 0.108 0.008 0.884
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1   0.148   0.619716 0.968 0.020 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.884   0.376606 0.116 0.460 0.424
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     3   0.994   0.028835 0.344 0.284 0.372
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     3   0.704  -0.130786 0.020 0.444 0.536
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2   0.840   0.536157 0.192 0.624 0.184
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     3   0.935   0.334490 0.224 0.260 0.516
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1   0.504   0.629953 0.836 0.104 0.060
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     3   0.702  -0.174428 0.020 0.436 0.544
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1   0.405   0.659611 0.848 0.004 0.148
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3   0.685  -0.044424 0.016 0.416 0.568
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3   0.596   0.653010 0.136 0.076 0.788
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3   0.599   0.628687 0.208 0.036 0.756
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3   0.781   0.258154 0.396 0.056 0.548
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3   0.748   0.291549 0.404 0.040 0.556
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3   0.454   0.644894 0.124 0.028 0.848
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     3   0.704  -0.130786 0.020 0.444 0.536
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1   0.148   0.619716 0.968 0.020 0.012
#> C06D8112-0FA0-4607-988D-589D8694743F     3   0.520   0.634749 0.184 0.020 0.796
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3   0.498   0.635904 0.064 0.096 0.840
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1   0.777   0.501910 0.628 0.080 0.292
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1   0.775   0.434931 0.596 0.064 0.340
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3   0.553   0.647344 0.172 0.036 0.792
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1   0.191   0.630041 0.956 0.016 0.028
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1   0.148   0.619716 0.968 0.020 0.012
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3   0.541   0.640886 0.164 0.036 0.800
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3   0.772   0.511617 0.296 0.076 0.628
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     3   0.902   0.364536 0.176 0.276 0.548
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1   0.584   0.551803 0.768 0.196 0.036
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1   0.750   0.527845 0.652 0.072 0.276
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.399   0.607242 0.020 0.108 0.872
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2   0.844   0.535740 0.192 0.620 0.188
#> 066B10C1-777F-4863-ACCA-6684310B913E     3   0.641   0.606691 0.248 0.036 0.716
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3   0.973  -0.135469 0.352 0.228 0.420
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     3   0.976   0.148184 0.268 0.288 0.444
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3   0.520   0.634749 0.184 0.020 0.796
#> 4379559E-E467-49BD-9673-40A486146A3B     3   0.701   0.594685 0.240 0.064 0.696
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3   0.987  -0.305113 0.256 0.356 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3   0.550   0.642930 0.064 0.124 0.812
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1   0.541   0.646506 0.780 0.020 0.200
#> 311D089C-33F1-4722-9118-F56427C5C128     1   0.835   0.456182 0.568 0.100 0.332
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     3   0.779   0.276085 0.068 0.332 0.600
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1   0.857   0.354665 0.548 0.112 0.340
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3   0.315   0.634631 0.036 0.048 0.916
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     3   0.946   0.236865 0.240 0.260 0.500
#> A77DDA16-167D-4444-8C58-526C99F2B406     3   0.783   0.234357 0.404 0.056 0.540
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     3   0.877   0.401610 0.272 0.156 0.572
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1   0.541   0.636120 0.764 0.012 0.224
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3   0.768   0.521991 0.280 0.080 0.640
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3   0.573   0.622733 0.228 0.020 0.752
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3   0.337   0.644038 0.040 0.052 0.908
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2   0.466   0.542479 0.068 0.856 0.076
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3   0.821   0.029648 0.452 0.072 0.476
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3   0.772   0.292243 0.396 0.052 0.552
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1   0.667   0.429832 0.616 0.016 0.368
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3   0.984  -0.044959 0.376 0.248 0.376
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1   0.956   0.053573 0.444 0.356 0.200
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3   0.640   0.528281 0.056 0.200 0.744
#> DCD81371-253F-4672-AA92-9F27A338F68E     2   0.831   0.547392 0.096 0.568 0.336
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3   0.577   0.452598 0.012 0.260 0.728
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1   0.148   0.619716 0.968 0.020 0.012
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.346   0.619971 0.024 0.076 0.900
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3   0.585   0.630195 0.080 0.124 0.796
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3   0.386   0.650757 0.072 0.040 0.888
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3   0.426   0.572696 0.012 0.140 0.848
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3   0.794   0.437161 0.332 0.076 0.592
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3   0.687  -0.065576 0.016 0.424 0.560
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1   0.723   0.425187 0.600 0.036 0.364
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3   0.346   0.591037 0.012 0.096 0.892
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1   0.329   0.652916 0.900 0.012 0.088
#> 46351E5C-2438-4B6A-8343-DDF329086771     3   0.848   0.425564 0.140 0.260 0.600
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1   0.504   0.656853 0.808 0.020 0.172
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3   0.350   0.569423 0.004 0.116 0.880
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3   0.642   0.562232 0.288 0.024 0.688
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3   0.830   0.491358 0.152 0.220 0.628
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3   0.525   0.632396 0.188 0.020 0.792
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3   0.525   0.658378 0.096 0.076 0.828
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1   0.795   0.309050 0.548 0.064 0.388
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     3   0.732  -0.096113 0.032 0.420 0.548
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3   0.487   0.645049 0.152 0.024 0.824
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2   0.768   0.620527 0.064 0.608 0.328
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     3   0.877   0.401610 0.272 0.156 0.572
#> 31322670-76A2-4308-A71F-D8E00049519D     3   0.707  -0.244432 0.020 0.472 0.508
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1   0.148   0.619716 0.968 0.020 0.012
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3   0.663   0.523979 0.064 0.204 0.732
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3   0.525   0.632396 0.188 0.020 0.792
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1   0.705   0.156142 0.524 0.020 0.456
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3   0.868   0.476153 0.288 0.140 0.572
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3   0.441   0.535995 0.004 0.172 0.824
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1   0.647   0.547155 0.668 0.020 0.312
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1   0.972   0.136011 0.448 0.252 0.300
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3   0.489   0.650490 0.096 0.060 0.844
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3   0.524   0.652142 0.152 0.036 0.812
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     3   0.712   0.294482 0.040 0.324 0.636
#> C44C898C-EEF9-4E03-911A-9D951312C380     1   0.606   0.551447 0.760 0.196 0.044
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3   0.832   0.471749 0.276 0.120 0.604
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1   0.858   0.317212 0.536 0.108 0.356
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     3   0.876   0.403602 0.160 0.264 0.576
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3   0.796   0.564729 0.152 0.188 0.660
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     3   0.983   0.141962 0.340 0.252 0.408
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     3   0.844   0.137900 0.100 0.352 0.548
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3   0.529   0.628571 0.064 0.112 0.824
#> 9980293D-AF0A-4215-9688-C576B1F8B519     3   0.640   0.528281 0.056 0.200 0.744
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3   0.230   0.607291 0.004 0.060 0.936
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1   0.875   0.399340 0.580 0.256 0.164
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3   0.556   0.630819 0.192 0.028 0.780
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1   0.492   0.644678 0.816 0.020 0.164
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1   0.942   0.082503 0.436 0.176 0.388
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     2   0.881   0.572587 0.132 0.536 0.332
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2   0.704   0.467397 0.020 0.536 0.444
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1   0.148   0.619716 0.968 0.020 0.012
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3   0.892   0.240226 0.380 0.128 0.492
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3   0.770   0.601485 0.212 0.116 0.672
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1   0.707   0.030592 0.496 0.020 0.484
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1   0.397   0.568703 0.876 0.100 0.024
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3   0.616   0.632209 0.188 0.052 0.760
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2   0.850   0.432858 0.092 0.492 0.416
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3   0.400   0.641977 0.060 0.056 0.884
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3   0.524   0.657270 0.152 0.036 0.812
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1   0.654   0.577061 0.684 0.028 0.288
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3   0.400   0.566875 0.016 0.116 0.868
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1   0.148   0.619716 0.968 0.020 0.012
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     3   0.640   0.528281 0.056 0.200 0.744
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1   0.747   0.375361 0.580 0.044 0.376
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     3   0.704  -0.130786 0.020 0.444 0.536
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3   0.259   0.591885 0.004 0.072 0.924
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     3   0.500   0.651152 0.124 0.044 0.832
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     3   0.794   0.471682 0.112 0.244 0.644
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     3   0.768   0.488087 0.096 0.244 0.660
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     3   0.573   0.631098 0.196 0.032 0.772
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     3   0.623   0.484340 0.028 0.252 0.720
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     3   0.672  -0.027491 0.012 0.420 0.568
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1   0.802   0.510384 0.652 0.208 0.140
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3   0.338   0.645429 0.044 0.048 0.908
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1   0.177   0.628639 0.960 0.016 0.024
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     3   0.672  -0.051063 0.012 0.420 0.568
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     3   0.277   0.595187 0.004 0.080 0.916
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     3   0.256   0.631458 0.028 0.036 0.936
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     1   0.569   0.562124 0.780 0.184 0.036
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     3   0.795   0.566091 0.148 0.192 0.660
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     1   0.606   0.551447 0.760 0.196 0.044
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#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.459   0.658235 0.120 0.032 0.848
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3   0.715   0.590911 0.236 0.072 0.692
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3   0.491   0.639021 0.068 0.088 0.844
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3   0.550   0.642930 0.064 0.124 0.812
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     3   0.982   0.167378 0.324 0.256 0.420
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3   0.527   0.652142 0.140 0.044 0.816
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3   0.527   0.652142 0.140 0.044 0.816
#> EB7883EB-0079-4548-9132-169E94A698BA     3   0.525   0.632396 0.188 0.020 0.792
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3   0.771   0.192690 0.424 0.048 0.528
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1   0.148   0.619716 0.968 0.020 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3   0.767  -0.000613 0.472 0.044 0.484
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.557   0.542990 0.032 0.184 0.784
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.691   0.237352 0.028 0.344 0.628
#> A0C429D9-0638-4873-BFB4-00056AB4719F     3   0.746   0.073750 0.048 0.352 0.600
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3   0.709   0.551928 0.268 0.056 0.676
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3   0.674   0.619513 0.240 0.052 0.708
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3   0.597   0.617860 0.216 0.032 0.752
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1   0.719   0.444439 0.608 0.036 0.356

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4   0.431   5.69e-01 0.012 0.152 0.024 0.812
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2   0.553   2.12e-01 0.000 0.564 0.416 0.020
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3   0.687   3.78e-01 0.320 0.100 0.572 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615     3   0.972  -7.38e-02 0.264 0.264 0.328 0.144
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3   0.458   3.49e-01 0.000 0.300 0.696 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3   0.807   2.61e-01 0.208 0.240 0.520 0.032
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3   0.373   5.16e-01 0.056 0.092 0.852 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.515   9.64e-02 0.000 0.396 0.596 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3   0.775  -8.51e-02 0.008 0.216 0.496 0.280
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4   0.879   3.16e-01 0.056 0.352 0.200 0.392
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3   0.442   5.21e-01 0.088 0.100 0.812 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.915   2.47e-01 0.076 0.372 0.316 0.236
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3   0.451   4.49e-01 0.032 0.176 0.788 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     1   0.699   4.50e-01 0.544 0.116 0.336 0.004
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3   0.411   4.94e-01 0.040 0.128 0.828 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.914  -2.42e-01 0.076 0.352 0.228 0.344
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     3   0.982  -1.26e-01 0.280 0.260 0.300 0.160
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.765   1.11e-01 0.000 0.460 0.236 0.304
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4   0.783   4.90e-01 0.164 0.256 0.032 0.548
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     3   0.912  -1.31e-01 0.180 0.360 0.368 0.092
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1   0.497   6.05e-01 0.784 0.004 0.112 0.100
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2   0.771   1.95e-01 0.008 0.508 0.236 0.248
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1   0.399   6.51e-01 0.800 0.008 0.188 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2   0.753   1.96e-01 0.000 0.492 0.240 0.268
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3   0.559   4.85e-01 0.052 0.204 0.728 0.016
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3   0.479   5.20e-01 0.108 0.092 0.796 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3   0.681   2.99e-01 0.292 0.088 0.604 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3   0.628   3.41e-01 0.304 0.064 0.624 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3   0.503   4.82e-01 0.064 0.152 0.776 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2   0.765   1.11e-01 0.000 0.460 0.236 0.304
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3   0.475   5.11e-01 0.100 0.088 0.804 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3   0.547   3.96e-01 0.008 0.208 0.728 0.056
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1   0.718   4.74e-01 0.564 0.140 0.288 0.008
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1   0.707   4.11e-01 0.520 0.116 0.360 0.004
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3   0.568   5.05e-01 0.112 0.124 0.748 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1   0.193   6.17e-01 0.936 0.004 0.056 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3   0.404   5.13e-01 0.056 0.100 0.840 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3   0.663   4.61e-01 0.204 0.120 0.660 0.016
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2   0.876   1.97e-01 0.132 0.412 0.368 0.088
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1   0.613   4.82e-01 0.684 0.012 0.080 0.224
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1   0.696   4.82e-01 0.568 0.124 0.304 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.532   1.25e-01 0.004 0.396 0.592 0.008
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4   0.785   4.86e-01 0.164 0.260 0.032 0.544
#> 066B10C1-777F-4863-ACCA-6684310B913E     3   0.581   5.07e-01 0.176 0.096 0.720 0.008
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3   0.977  -3.97e-02 0.280 0.212 0.336 0.172
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     3   0.976  -1.27e-01 0.216 0.280 0.336 0.168
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3   0.475   5.11e-01 0.100 0.088 0.804 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B     3   0.656   4.69e-01 0.160 0.140 0.680 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4   0.982   2.07e-01 0.256 0.288 0.160 0.296
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3   0.531   3.46e-01 0.004 0.296 0.676 0.024
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1   0.486   6.08e-01 0.712 0.008 0.272 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128     1   0.784   4.03e-01 0.492 0.084 0.368 0.056
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2   0.863   3.61e-01 0.048 0.408 0.352 0.192
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1   0.781   3.52e-01 0.484 0.188 0.316 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3   0.428   3.46e-01 0.000 0.280 0.720 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     3   0.966  -1.88e-01 0.204 0.308 0.336 0.152
#> A77DDA16-167D-4444-8C58-526C99F2B406     3   0.672   2.91e-01 0.296 0.080 0.608 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     3   0.848  -7.38e-02 0.236 0.356 0.380 0.028
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1   0.508   6.07e-01 0.700 0.028 0.272 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3   0.657   4.49e-01 0.176 0.136 0.672 0.016
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3   0.574   5.18e-01 0.156 0.116 0.724 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3   0.498   3.84e-01 0.004 0.224 0.740 0.032
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4   0.431   5.69e-01 0.012 0.152 0.024 0.812
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3   0.741   5.59e-02 0.360 0.092 0.520 0.028
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3   0.619   3.37e-01 0.312 0.064 0.620 0.004
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1   0.570   3.45e-01 0.560 0.020 0.416 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     1   0.975   9.58e-03 0.360 0.228 0.236 0.176
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1   0.941  -7.39e-02 0.368 0.136 0.168 0.328
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2   0.681   3.14e-01 0.044 0.516 0.412 0.028
#> DCD81371-253F-4672-AA92-9F27A338F68E     4   0.825   3.89e-01 0.080 0.320 0.100 0.500
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2   0.698   2.57e-01 0.000 0.504 0.376 0.120
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.580   1.96e-01 0.012 0.340 0.624 0.024
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3   0.640   2.70e-01 0.020 0.248 0.660 0.072
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3   0.539   4.13e-01 0.032 0.228 0.724 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3   0.586  -6.32e-02 0.000 0.464 0.504 0.032
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3   0.675   4.32e-01 0.232 0.112 0.640 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2   0.756   1.71e-01 0.000 0.484 0.236 0.280
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1   0.665   3.48e-01 0.512 0.044 0.424 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3   0.562   3.27e-02 0.004 0.428 0.552 0.016
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1   0.311   6.39e-01 0.872 0.016 0.112 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2   0.811   2.01e-01 0.100 0.456 0.384 0.060
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1   0.427   6.36e-01 0.760 0.004 0.232 0.004
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2   0.530   9.14e-02 0.000 0.500 0.492 0.008
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3   0.568   4.93e-01 0.216 0.072 0.708 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3   0.776  -1.08e-01 0.100 0.432 0.432 0.036
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3   0.481   5.10e-01 0.104 0.088 0.800 0.008
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3   0.474   4.73e-01 0.028 0.208 0.760 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1   0.691   2.53e-01 0.476 0.092 0.428 0.004
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2   0.799   1.36e-01 0.012 0.468 0.240 0.280
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3   0.357   5.16e-01 0.048 0.092 0.860 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     4   0.770   4.93e-01 0.020 0.328 0.144 0.508
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     3   0.848  -7.38e-02 0.236 0.356 0.380 0.028
#> 31322670-76A2-4308-A71F-D8E00049519D     2   0.765  -5.85e-02 0.000 0.440 0.220 0.340
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2   0.696   3.20e-01 0.048 0.512 0.408 0.032
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3   0.481   5.10e-01 0.104 0.088 0.800 0.008
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     3   0.602  -6.50e-02 0.452 0.032 0.512 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3   0.797   2.79e-01 0.200 0.232 0.536 0.032
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2   0.557   2.57e-01 0.000 0.580 0.396 0.024
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1   0.562   4.82e-01 0.600 0.016 0.376 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1   0.932   4.61e-03 0.404 0.104 0.240 0.252
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3   0.641   3.77e-01 0.068 0.244 0.664 0.024
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3   0.432   5.23e-01 0.068 0.116 0.816 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2   0.811   4.13e-01 0.028 0.468 0.332 0.172
#> C44C898C-EEF9-4E03-911A-9D951312C380     1   0.630   4.79e-01 0.676 0.016 0.084 0.224
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3   0.813   9.66e-02 0.232 0.276 0.472 0.020
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1   0.780   3.26e-01 0.476 0.180 0.332 0.012
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2   0.833   1.90e-01 0.116 0.444 0.376 0.064
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3   0.732   3.77e-01 0.064 0.244 0.616 0.076
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     3   0.966  -7.91e-02 0.284 0.256 0.328 0.132
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2   0.910   2.51e-01 0.072 0.380 0.312 0.236
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3   0.560   3.73e-01 0.008 0.192 0.728 0.072
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2   0.681   3.14e-01 0.044 0.516 0.412 0.028
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3   0.510   1.38e-01 0.000 0.380 0.612 0.008
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1   0.829   2.59e-01 0.488 0.040 0.184 0.288
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3   0.528   5.11e-01 0.120 0.096 0.772 0.012
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1   0.401   6.30e-01 0.788 0.004 0.204 0.004
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     1   0.880   1.93e-01 0.384 0.264 0.308 0.044
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     4   0.859   4.48e-01 0.060 0.232 0.220 0.488
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2   0.766  -2.14e-01 0.004 0.428 0.180 0.388
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3   0.822   2.09e-01 0.288 0.196 0.484 0.032
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3   0.650   4.57e-01 0.108 0.184 0.684 0.024
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     3   0.612   5.86e-02 0.432 0.048 0.520 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1   0.345   5.32e-01 0.872 0.028 0.008 0.092
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3   0.448   5.21e-01 0.084 0.108 0.808 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     4   0.860   2.68e-01 0.036 0.364 0.228 0.372
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3   0.530   3.54e-01 0.024 0.272 0.696 0.008
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3   0.494   5.19e-01 0.072 0.144 0.780 0.004
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3   0.481   5.21e-01 0.088 0.104 0.800 0.008
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1   0.430   6.42e-01 0.756 0.004 0.236 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2   0.733   3.03e-01 0.044 0.480 0.420 0.056
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2   0.812   3.00e-01 0.016 0.452 0.300 0.232
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3   0.402   4.59e-01 0.016 0.168 0.812 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3   0.625   4.89e-01 0.224 0.088 0.676 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7     3   0.573   3.64e-01 0.008 0.192 0.720 0.080
#> C075F09E-623C-46ED-B927-889B48F450B3     3   0.406   4.49e-01 0.016 0.172 0.808 0.004
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3   0.514   4.10e-01 0.008 0.168 0.764 0.060
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3   0.495   3.43e-01 0.004 0.272 0.708 0.016
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3   0.563   2.06e-01 0.020 0.352 0.620 0.008
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3   0.477   5.15e-01 0.068 0.116 0.804 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3   0.561   4.87e-01 0.164 0.100 0.732 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3   0.404   5.17e-01 0.088 0.076 0.836 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1   0.871   2.05e-01 0.388 0.252 0.320 0.040
#> 816CF68B-8476-4960-9F05-FB959A686323     3   0.645   4.69e-01 0.144 0.156 0.684 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3   0.388   5.16e-01 0.048 0.100 0.848 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2   0.620   2.24e-01 0.000 0.544 0.400 0.056
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3   0.669   1.63e-02 0.404 0.068 0.520 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     4   0.811   3.88e-01 0.020 0.348 0.192 0.440
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2   0.667   3.37e-01 0.028 0.572 0.356 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1   0.461   6.31e-01 0.744 0.008 0.240 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3   0.502   4.60e-01 0.020 0.248 0.724 0.008
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.499   2.50e-01 0.004 0.344 0.648 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1   0.503   6.04e-01 0.700 0.012 0.280 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3   0.561   5.01e-01 0.088 0.168 0.736 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1   0.879   4.15e-01 0.516 0.128 0.192 0.164
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1   0.149   6.09e-01 0.956 0.004 0.036 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1   0.149   6.09e-01 0.956 0.004 0.036 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1   0.407   6.47e-01 0.792 0.004 0.196 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1   0.960   1.68e-01 0.332 0.248 0.296 0.124
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1   0.449   6.18e-01 0.732 0.004 0.260 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     3   0.638   4.97e-01 0.200 0.096 0.684 0.020
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3   0.521   3.13e-01 0.004 0.280 0.692 0.024
#> 1122039D-5785-4F70-9916-17C585453512     1   0.345   5.32e-01 0.872 0.028 0.008 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1   0.828   3.21e-01 0.496 0.036 0.232 0.236
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3   0.541   3.90e-01 0.008 0.180 0.744 0.068
#> C56C7ED7-A684-40CC-B426-B108E2248467     1   0.975   9.58e-03 0.360 0.228 0.236 0.176
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2   0.935  -1.57e-01 0.088 0.332 0.272 0.308
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3   0.771  -1.19e-01 0.096 0.428 0.440 0.036
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3   0.612   4.50e-01 0.276 0.064 0.652 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1   0.345   5.32e-01 0.872 0.028 0.008 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1   0.528   5.34e-01 0.636 0.008 0.348 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3   0.510   4.96e-01 0.184 0.056 0.756 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2   0.614   2.19e-01 0.000 0.544 0.404 0.052
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3   0.691   4.19e-01 0.220 0.124 0.636 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3   0.860  -1.06e-01 0.352 0.252 0.364 0.032
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1   0.405   6.46e-01 0.768 0.000 0.228 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     3   0.977  -1.45e-01 0.208 0.288 0.332 0.172
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.442   4.90e-01 0.032 0.184 0.784 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3   0.599   4.81e-01 0.132 0.148 0.712 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3   0.513   4.11e-01 0.008 0.160 0.768 0.064
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3   0.531   3.46e-01 0.004 0.296 0.676 0.024
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     3   0.969  -6.54e-02 0.272 0.264 0.328 0.136
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3   0.494   5.03e-01 0.060 0.108 0.804 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3   0.494   5.03e-01 0.060 0.108 0.804 0.028
#> EB7883EB-0079-4548-9132-169E94A698BA     3   0.481   5.10e-01 0.104 0.088 0.800 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3   0.655   2.82e-01 0.320 0.076 0.596 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1   0.104   5.98e-01 0.972 0.008 0.020 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3   0.670   9.98e-02 0.380 0.072 0.540 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2   0.627   2.78e-01 0.020 0.520 0.436 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2   0.810   2.63e-01 0.016 0.460 0.284 0.240
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.809   2.58e-01 0.032 0.508 0.276 0.184
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3   0.578   4.79e-01 0.160 0.116 0.720 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3   0.627   5.08e-01 0.152 0.108 0.712 0.028
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3   0.584   4.94e-01 0.148 0.120 0.724 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1   0.650   3.58e-01 0.520 0.036 0.424 0.020

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5   0.576    0.62444 0.000 0.356 0.068 0.012 0.564
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.390    0.57726 0.196 0.024 0.776 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1   0.727    0.35184 0.504 0.028 0.172 0.280 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2   0.844    0.26624 0.256 0.408 0.040 0.232 0.064
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1   0.548    0.04182 0.560 0.024 0.388 0.000 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1   0.848    0.31144 0.500 0.140 0.128 0.164 0.068
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1   0.335    0.48496 0.876 0.032 0.044 0.016 0.032
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.495    0.44023 0.396 0.024 0.576 0.000 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1   0.808   -0.05796 0.364 0.340 0.144 0.000 0.152
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.549    0.38549 0.088 0.752 0.028 0.052 0.080
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1   0.462    0.49785 0.808 0.032 0.076 0.048 0.036
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.668    0.51741 0.188 0.624 0.112 0.068 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1   0.559    0.39500 0.712 0.156 0.096 0.012 0.024
#> 5AB5396F-925B-469C-B240-FB37991004DD     4   0.738    0.36254 0.368 0.084 0.036 0.468 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1   0.521    0.32637 0.692 0.036 0.244 0.012 0.016
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.621    0.41963 0.120 0.700 0.032 0.072 0.076
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2   0.867    0.21369 0.232 0.396 0.044 0.244 0.084
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.437    0.49214 0.052 0.772 0.164 0.000 0.012
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     5   0.742    0.68588 0.000 0.128 0.296 0.092 0.484
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2   0.942    0.25223 0.284 0.324 0.152 0.132 0.108
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4   0.560    0.59363 0.140 0.068 0.000 0.712 0.080
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2   0.667    0.42545 0.104 0.592 0.244 0.004 0.056
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4   0.381    0.61695 0.200 0.012 0.004 0.780 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2   0.506    0.49099 0.068 0.704 0.216 0.000 0.012
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1   0.598    0.39627 0.664 0.032 0.228 0.024 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1   0.476    0.49930 0.800 0.064 0.052 0.060 0.024
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1   0.613    0.32118 0.644 0.012 0.036 0.236 0.072
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1   0.563    0.39176 0.664 0.004 0.044 0.248 0.040
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1   0.591    0.32193 0.660 0.056 0.232 0.044 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2   0.437    0.49214 0.052 0.772 0.164 0.000 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F     1   0.552    0.42393 0.740 0.044 0.128 0.064 0.024
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1   0.641    0.28175 0.628 0.168 0.152 0.000 0.052
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4   0.756    0.40287 0.296 0.116 0.028 0.504 0.056
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     4   0.737    0.31518 0.396 0.080 0.036 0.444 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1   0.661    0.37629 0.628 0.052 0.220 0.076 0.024
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4   0.193    0.61314 0.072 0.000 0.004 0.920 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1   0.344    0.48581 0.872 0.040 0.040 0.016 0.032
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1   0.653    0.47911 0.664 0.064 0.076 0.164 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2   0.914    0.22193 0.300 0.332 0.192 0.100 0.076
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4   0.660    0.44651 0.084 0.116 0.000 0.620 0.180
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4   0.749    0.40405 0.308 0.092 0.032 0.508 0.060
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.509    0.37914 0.436 0.028 0.532 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     5   0.740    0.68346 0.000 0.124 0.300 0.092 0.484
#> 066B10C1-777F-4863-ACCA-6684310B913E     1   0.620    0.48758 0.688 0.052 0.112 0.128 0.020
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3   0.961    0.05687 0.260 0.092 0.264 0.232 0.152
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2   0.818    0.35549 0.252 0.460 0.040 0.188 0.060
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1   0.552    0.42393 0.740 0.044 0.128 0.064 0.024
#> 4379559E-E467-49BD-9673-40A486146A3B     1   0.665    0.42921 0.620 0.012 0.192 0.132 0.044
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3   0.934   -0.39645 0.052 0.200 0.308 0.232 0.208
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1   0.536    0.23150 0.612 0.004 0.320 0.000 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4   0.465    0.54307 0.312 0.004 0.012 0.664 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128     4   0.732    0.27032 0.400 0.072 0.020 0.440 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2   0.788    0.42454 0.244 0.512 0.140 0.044 0.060
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     4   0.826    0.27277 0.300 0.168 0.040 0.428 0.064
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1   0.519   -0.01743 0.572 0.032 0.388 0.000 0.008
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2   0.868    0.40320 0.224 0.436 0.112 0.180 0.048
#> A77DDA16-167D-4444-8C58-526C99F2B406     1   0.595    0.31393 0.648 0.008 0.028 0.240 0.076
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     1   0.927   -0.15129 0.292 0.264 0.192 0.208 0.044
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4   0.501    0.53554 0.320 0.012 0.008 0.644 0.016
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1   0.622    0.46394 0.700 0.032 0.076 0.116 0.076
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1   0.634    0.46294 0.656 0.028 0.180 0.112 0.024
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1   0.619    0.09109 0.572 0.096 0.308 0.000 0.024
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5   0.576    0.62444 0.000 0.356 0.068 0.012 0.564
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1   0.733    0.11671 0.532 0.044 0.044 0.296 0.084
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1   0.537    0.36745 0.672 0.004 0.044 0.256 0.024
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4   0.566    0.25299 0.432 0.020 0.024 0.516 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4   0.961   -0.14656 0.108 0.236 0.184 0.316 0.156
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4   0.952   -0.11723 0.112 0.188 0.124 0.320 0.256
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3   0.795    0.29077 0.260 0.252 0.424 0.024 0.040
#> DCD81371-253F-4672-AA92-9F27A338F68E     5   0.784    0.56467 0.008 0.208 0.348 0.056 0.380
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3   0.603    0.52568 0.208 0.032 0.644 0.000 0.116
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.514    0.40614 0.424 0.016 0.544 0.000 0.016
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1   0.703    0.19590 0.520 0.280 0.164 0.008 0.028
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1   0.521    0.00836 0.580 0.020 0.384 0.008 0.008
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3   0.498    0.54093 0.296 0.016 0.660 0.000 0.028
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1   0.686    0.45689 0.636 0.060 0.072 0.184 0.048
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#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2   0.454    0.20999 0.040 0.784 0.020 0.012 0.144
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2   0.739    0.48622 0.164 0.568 0.188 0.036 0.044
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3   0.498    0.42539 0.412 0.024 0.560 0.000 0.004
#> A9195281-8CAE-45A8-8493-744E577907FA     1   0.855    0.30965 0.492 0.136 0.120 0.176 0.076
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     1   0.874    0.07550 0.392 0.244 0.144 0.192 0.028
#> E789661A-C027-405D-9F76-E6D52CE3018B     4   0.896   -0.01052 0.296 0.248 0.068 0.316 0.072
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     4   0.721    0.45771 0.272 0.096 0.028 0.552 0.052
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     3   0.698    0.43743 0.300 0.120 0.532 0.012 0.036
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     4   0.456    0.57097 0.276 0.004 0.008 0.696 0.016
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     4   0.333    0.61644 0.160 0.004 0.004 0.824 0.008
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1   0.476    0.50044 0.800 0.064 0.048 0.064 0.024
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1   0.682   -0.24044 0.452 0.048 0.032 0.432 0.036
#> B57C849C-28B1-4315-885C-330B9C9482B3     3   0.466    0.55213 0.284 0.016 0.684 0.000 0.016
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     1   0.927   -0.15129 0.292 0.264 0.192 0.208 0.044
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     5   0.708    0.56301 0.008 0.336 0.064 0.088 0.504
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     3   0.727    0.43273 0.228 0.212 0.516 0.012 0.032
#> 80936433-AA91-4219-98F1-706C36298060     3   0.847    0.12417 0.200 0.292 0.400 0.048 0.060
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1   0.588    0.36893 0.676 0.204 0.080 0.016 0.024
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1   0.538    0.48628 0.760 0.036 0.048 0.100 0.056
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4   0.651    0.45748 0.084 0.116 0.000 0.632 0.168
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     5   0.784    0.56467 0.008 0.208 0.348 0.056 0.380
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1   0.339    0.48291 0.872 0.020 0.060 0.020 0.028
#> 17CA5D73-4384-4645-83F8-587847043DD2     4   0.469    0.56624 0.280 0.004 0.012 0.688 0.016
#> 40467950-A95C-4731-AD93-0A128442C837     4   0.634    0.26798 0.432 0.012 0.024 0.476 0.056
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1   0.706   -0.14969 0.472 0.056 0.028 0.392 0.052
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1   0.642    0.48262 0.656 0.056 0.064 0.196 0.028
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1   0.545    0.26553 0.668 0.044 0.260 0.016 0.012
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3   0.487    0.43758 0.396 0.020 0.580 0.000 0.004
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4   0.682    0.53125 0.252 0.132 0.012 0.572 0.032
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4   0.670    0.44254 0.092 0.116 0.000 0.612 0.180
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     1   0.924   -0.15636 0.308 0.284 0.232 0.084 0.092
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4   0.435    0.56139 0.296 0.004 0.004 0.688 0.008
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1   0.553    0.32689 0.676 0.020 0.244 0.044 0.016
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1   0.547   -0.01382 0.560 0.032 0.388 0.000 0.020
#> A7ECBC06-1332-4278-8723-85DC8351188A     4   0.499    0.53938 0.316 0.012 0.008 0.648 0.016
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1   0.585    0.23136 0.604 0.024 0.312 0.056 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1   0.588    0.36893 0.676 0.204 0.080 0.016 0.024
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4   0.545    0.39765 0.412 0.008 0.012 0.544 0.024
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     4   0.881    0.05917 0.292 0.244 0.048 0.336 0.080
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4   0.613    0.42974 0.340 0.032 0.044 0.572 0.012
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3   0.704    0.45205 0.256 0.136 0.552 0.008 0.048
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3   0.807    0.27309 0.256 0.252 0.420 0.028 0.044
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1   0.655   -0.16327 0.480 0.036 0.024 0.420 0.040
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1   0.915   -0.08703 0.332 0.260 0.240 0.072 0.096
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1   0.593    0.21495 0.632 0.076 0.256 0.000 0.036
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1   0.525   -0.11643 0.520 0.028 0.444 0.004 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4   0.670    0.44254 0.092 0.116 0.000 0.612 0.180
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2   0.852    0.25469 0.320 0.404 0.140 0.060 0.076
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     4   0.600    0.28528 0.440 0.008 0.020 0.488 0.044
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1   0.610    0.47814 0.676 0.028 0.148 0.132 0.016
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2   0.481    0.49134 0.052 0.736 0.192 0.000 0.020
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1   0.873    0.08661 0.396 0.240 0.144 0.192 0.028
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     4   0.543    0.33658 0.440 0.012 0.012 0.520 0.016
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1   0.568    0.30563 0.672 0.056 0.236 0.016 0.020
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1   0.508    0.46520 0.772 0.064 0.100 0.048 0.016
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4   0.430    0.59060 0.268 0.004 0.004 0.712 0.012
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     3   0.826    0.19343 0.308 0.236 0.372 0.024 0.060
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2   0.666    0.51345 0.148 0.628 0.168 0.020 0.036
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1   0.540    0.26040 0.664 0.044 0.268 0.012 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1   0.631    0.47283 0.660 0.016 0.124 0.164 0.036
#> EE40EE80-4520-4643-B906-48246BA616A7     1   0.654    0.26944 0.612 0.204 0.124 0.000 0.060
#> C075F09E-623C-46ED-B927-889B48F450B3     1   0.549    0.25250 0.660 0.044 0.268 0.016 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1   0.593    0.32326 0.664 0.196 0.096 0.000 0.044
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1   0.639   -0.03185 0.532 0.096 0.344 0.000 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3   0.530    0.31741 0.460 0.024 0.504 0.008 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1   0.483    0.37408 0.728 0.016 0.216 0.032 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1   0.517    0.49162 0.768 0.020 0.052 0.104 0.056
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1   0.370    0.49666 0.860 0.032 0.032 0.048 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     4   0.871    0.07198 0.296 0.244 0.040 0.340 0.080
#> 816CF68B-8476-4960-9F05-FB959A686323     1   0.700    0.30297 0.568 0.052 0.260 0.104 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1   0.509    0.41864 0.740 0.048 0.176 0.020 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3   0.464    0.55993 0.180 0.020 0.752 0.000 0.048
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1   0.603    0.09050 0.564 0.004 0.024 0.348 0.060
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2   0.484    0.32581 0.052 0.788 0.048 0.016 0.096
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     3   0.812    0.20996 0.264 0.216 0.432 0.020 0.068
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4   0.469    0.56624 0.280 0.004 0.012 0.688 0.016
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1   0.542    0.33496 0.668 0.036 0.260 0.004 0.032
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.540    0.27814 0.472 0.024 0.488 0.004 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4   0.489    0.53134 0.320 0.004 0.016 0.648 0.012
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1   0.597    0.32050 0.632 0.024 0.272 0.056 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4   0.850    0.35530 0.148 0.192 0.036 0.464 0.160
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4   0.164    0.60221 0.048 0.000 0.008 0.940 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4   0.164    0.60221 0.048 0.000 0.008 0.940 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4   0.407    0.61273 0.232 0.004 0.008 0.748 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2   0.876    0.09599 0.232 0.348 0.036 0.288 0.096
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4   0.461    0.55382 0.284 0.004 0.016 0.688 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1   0.647    0.44542 0.636 0.024 0.160 0.160 0.020
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1   0.637   -0.18130 0.484 0.084 0.408 0.004 0.020
#> 1122039D-5785-4F70-9916-17C585453512     4   0.358    0.50721 0.012 0.000 0.048 0.840 0.100
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4   0.872    0.28300 0.212 0.128 0.044 0.432 0.184
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1   0.624    0.29614 0.640 0.196 0.112 0.000 0.052
#> C56C7ED7-A684-40CC-B426-B108E2248467     4   0.961   -0.14656 0.108 0.236 0.184 0.316 0.156
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2   0.648    0.42617 0.168 0.664 0.028 0.076 0.064
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3   0.884    0.15670 0.320 0.176 0.356 0.064 0.084
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1   0.649    0.45379 0.628 0.040 0.084 0.228 0.020
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4   0.358    0.50721 0.012 0.000 0.048 0.840 0.100
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4   0.503    0.45167 0.388 0.004 0.012 0.584 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1   0.559    0.47370 0.732 0.048 0.056 0.140 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.448    0.55691 0.192 0.012 0.752 0.000 0.044
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1   0.711    0.44814 0.624 0.080 0.080 0.168 0.048
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1   0.881   -0.12807 0.320 0.248 0.064 0.308 0.060
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4   0.425    0.59444 0.260 0.004 0.004 0.720 0.012
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2   0.818    0.37978 0.248 0.468 0.044 0.180 0.060
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1   0.448    0.38952 0.744 0.020 0.216 0.008 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1   0.575    0.47628 0.740 0.040 0.080 0.076 0.064
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1   0.611    0.31398 0.652 0.188 0.112 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1   0.536    0.23150 0.612 0.004 0.320 0.000 0.064
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2   0.852    0.25513 0.256 0.396 0.044 0.240 0.064
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1   0.504    0.44241 0.776 0.088 0.080 0.020 0.036
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1   0.504    0.44241 0.776 0.088 0.080 0.020 0.036
#> EB7883EB-0079-4548-9132-169E94A698BA     1   0.550    0.42391 0.740 0.044 0.128 0.068 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1   0.622    0.30450 0.616 0.004 0.052 0.264 0.064
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4   0.128    0.58810 0.020 0.000 0.004 0.960 0.016
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1   0.624    0.15571 0.576 0.008 0.028 0.320 0.068
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.703    0.49152 0.248 0.160 0.548 0.012 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.659    0.23983 0.112 0.060 0.616 0.004 0.208
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.664    0.46832 0.152 0.604 0.204 0.012 0.028
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1   0.530    0.48828 0.764 0.032 0.048 0.100 0.056
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1   0.677    0.46957 0.640 0.072 0.152 0.116 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1   0.624    0.39389 0.656 0.044 0.184 0.108 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     4   0.630    0.22720 0.452 0.016 0.020 0.460 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4   0.626   4.34e-01 0.000 0.092 0.052 0.432 0.420 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6   0.155   6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.274   5.99e-01 0.072 0.028 0.880 0.016 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1   0.680   3.83e-01 0.492 0.044 0.164 0.008 0.008 0.284
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2   0.684   3.79e-01 0.136 0.568 0.000 0.036 0.084 0.176
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1   0.574   1.29e-02 0.480 0.060 0.424 0.016 0.020 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1   0.800   5.36e-02 0.404 0.312 0.116 0.040 0.024 0.104
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1   0.342   5.61e-01 0.860 0.024 0.048 0.012 0.040 0.016
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.369   5.60e-01 0.288 0.012 0.700 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5   0.744   8.73e-02 0.320 0.076 0.144 0.040 0.420 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.622  -3.00e-01 0.052 0.448 0.016 0.012 0.436 0.036
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1   0.460   5.73e-01 0.792 0.044 0.076 0.016 0.036 0.036
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.726   2.66e-01 0.128 0.508 0.056 0.008 0.252 0.048
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1   0.577   4.63e-01 0.680 0.128 0.096 0.004 0.076 0.016
#> 5AB5396F-925B-469C-B240-FB37991004DD     6   0.700   3.18e-01 0.280 0.228 0.000 0.036 0.020 0.436
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1   0.484   3.64e-01 0.648 0.020 0.292 0.008 0.032 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6   0.155   6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.683  -2.02e-01 0.080 0.432 0.020 0.012 0.400 0.056
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2   0.714   3.63e-01 0.124 0.544 0.000 0.056 0.088 0.188
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.606  -3.43e-02 0.016 0.508 0.136 0.008 0.332 0.000
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#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3   0.485   2.10e-01 0.452 0.012 0.512 0.008 0.012 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     6   0.582   4.08e-01 0.068 0.000 0.012 0.032 0.340 0.548
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2   0.653   4.77e-01 0.184 0.616 0.096 0.028 0.060 0.016
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     6   0.155   6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     6   0.624   1.95e-01 0.428 0.032 0.020 0.024 0.036 0.460
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1   0.576   5.45e-01 0.660 0.056 0.168 0.004 0.008 0.104
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2   0.635  -1.13e-02 0.012 0.484 0.156 0.020 0.328 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2   0.773   3.07e-01 0.332 0.392 0.080 0.012 0.032 0.152
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     6   0.546   2.68e-01 0.424 0.012 0.020 0.008 0.028 0.508
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1   0.558   3.29e-01 0.620 0.024 0.284 0.016 0.044 0.012
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1   0.477   5.40e-01 0.764 0.040 0.116 0.004 0.036 0.040
#> 887E7408-C7D7-420F-A763-0EE70A316D17     6   0.421   5.98e-01 0.260 0.012 0.000 0.008 0.016 0.704
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2   0.643   2.96e-01 0.124 0.476 0.360 0.012 0.016 0.012
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2   0.706   2.39e-01 0.084 0.520 0.144 0.020 0.228 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     6   0.155   6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1   0.525   2.54e-01 0.604 0.028 0.328 0.008 0.020 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1   0.656   5.42e-01 0.624 0.032 0.140 0.028 0.036 0.140
#> EE40EE80-4520-4643-B906-48246BA616A7     1   0.677   3.47e-01 0.560 0.104 0.120 0.020 0.196 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     1   0.514   2.35e-01 0.600 0.020 0.340 0.008 0.020 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1   0.625   4.04e-01 0.616 0.096 0.096 0.016 0.176 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1   0.647  -1.18e-01 0.440 0.048 0.404 0.016 0.092 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3   0.440   4.38e-01 0.376 0.012 0.600 0.000 0.008 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1   0.439   4.17e-01 0.700 0.008 0.256 0.008 0.004 0.024
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1   0.527   5.61e-01 0.752 0.048 0.032 0.044 0.040 0.084
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1   0.378   5.71e-01 0.844 0.028 0.036 0.016 0.036 0.040
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2   0.660   3.24e-01 0.176 0.508 0.000 0.040 0.012 0.264
#> 816CF68B-8476-4960-9F05-FB959A686323     1   0.686   2.90e-01 0.516 0.076 0.284 0.008 0.016 0.100
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1   0.460   4.95e-01 0.728 0.032 0.200 0.008 0.028 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3   0.408   5.40e-01 0.068 0.036 0.808 0.072 0.016 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1   0.634   2.02e-01 0.556 0.032 0.012 0.044 0.048 0.308
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5   0.583   3.89e-01 0.028 0.404 0.040 0.016 0.504 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2   0.619   2.66e-01 0.112 0.464 0.392 0.012 0.016 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6   0.461   5.59e-01 0.276 0.008 0.004 0.016 0.020 0.676
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1   0.569   3.89e-01 0.620 0.052 0.268 0.016 0.040 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.492   4.11e-01 0.368 0.016 0.580 0.000 0.032 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6   0.472   5.16e-01 0.316 0.008 0.008 0.012 0.016 0.640
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1   0.543   3.31e-01 0.592 0.028 0.328 0.008 0.008 0.036
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     6   0.756   1.77e-01 0.060 0.304 0.008 0.024 0.212 0.392
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6   0.160   6.31e-01 0.032 0.016 0.000 0.012 0.000 0.940
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6   0.160   6.31e-01 0.032 0.016 0.000 0.012 0.000 0.940
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6   0.400   6.20e-01 0.228 0.004 0.000 0.012 0.020 0.736
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2   0.704   3.49e-01 0.124 0.532 0.000 0.052 0.064 0.228
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6   0.412   5.63e-01 0.276 0.000 0.008 0.008 0.012 0.696
#> C33059A9-A313-4806-B43B-0031365F3BE4     1   0.611   5.10e-01 0.624 0.016 0.172 0.020 0.016 0.152
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3   0.641   2.64e-01 0.392 0.040 0.460 0.012 0.092 0.004
#> 1122039D-5785-4F70-9916-17C585453512     6   0.353   5.15e-01 0.000 0.032 0.000 0.168 0.008 0.792
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6   0.763   1.76e-01 0.196 0.008 0.048 0.040 0.340 0.368
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1   0.654   3.70e-01 0.584 0.104 0.112 0.016 0.184 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2   0.864   7.90e-02 0.060 0.380 0.092 0.168 0.048 0.252
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2   0.712  -1.16e-01 0.124 0.432 0.016 0.016 0.360 0.052
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2   0.660   2.60e-01 0.144 0.472 0.340 0.016 0.008 0.020
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1   0.603   5.18e-01 0.628 0.052 0.088 0.008 0.012 0.212
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6   0.353   5.15e-01 0.000 0.032 0.000 0.168 0.008 0.792
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6   0.501   4.16e-01 0.384 0.008 0.008 0.012 0.020 0.568
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1   0.521   5.46e-01 0.728 0.024 0.068 0.008 0.036 0.136
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.404   5.46e-01 0.080 0.028 0.808 0.068 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1   0.727   4.77e-01 0.564 0.160 0.084 0.032 0.028 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2   0.717   3.41e-01 0.208 0.472 0.028 0.024 0.016 0.252
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6   0.404   5.94e-01 0.264 0.012 0.000 0.004 0.012 0.708
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2   0.669   3.64e-01 0.128 0.600 0.004 0.028 0.108 0.132
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1   0.454   4.55e-01 0.692 0.020 0.260 0.008 0.012 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1   0.607   5.44e-01 0.700 0.084 0.048 0.056 0.052 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1   0.637   3.91e-01 0.604 0.092 0.112 0.016 0.176 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1   0.653   2.83e-01 0.532 0.068 0.304 0.056 0.040 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2   0.696   3.87e-01 0.136 0.564 0.008 0.028 0.080 0.184
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1   0.496   5.20e-01 0.756 0.064 0.088 0.008 0.068 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1   0.496   5.20e-01 0.756 0.064 0.088 0.008 0.068 0.016
#> EB7883EB-0079-4548-9132-169E94A698BA     1   0.495   4.98e-01 0.744 0.016 0.132 0.008 0.036 0.064
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1   0.664   3.94e-01 0.600 0.040 0.036 0.044 0.056 0.224
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6   0.155   6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1   0.657   2.57e-01 0.560 0.044 0.016 0.044 0.052 0.284
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.613   3.05e-01 0.120 0.256 0.580 0.020 0.020 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.575   1.15e-01 0.048 0.024 0.572 0.324 0.032 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.743   9.60e-02 0.104 0.476 0.168 0.012 0.228 0.012
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1   0.539   5.56e-01 0.744 0.068 0.028 0.044 0.040 0.076
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1   0.647   5.32e-01 0.632 0.092 0.136 0.012 0.024 0.104
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1   0.568   4.48e-01 0.648 0.016 0.212 0.008 0.020 0.096
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1   0.648  -1.50e-01 0.448 0.060 0.008 0.028 0.040 0.416

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

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 17541 rows and 500 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 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-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 0.410           0.740       0.860         0.4908 0.503   0.503
#> 3 3 0.680           0.824       0.896         0.3304 0.640   0.402
#> 4 4 0.558           0.655       0.780         0.1066 0.807   0.526
#> 5 5 0.623           0.576       0.757         0.0701 0.920   0.739
#> 6 6 0.643           0.506       0.702         0.0478 0.853   0.501

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0672     0.7906 0.008 0.992
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.7602     0.7226 0.780 0.220
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.7674     0.7710 0.224 0.776
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.7528     0.7342 0.784 0.216
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.9866     0.4616 0.568 0.432
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.8763     0.7408 0.296 0.704
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.5737     0.6757 0.136 0.864
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0672     0.8586 0.992 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.8763     0.7408 0.296 0.704
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.8813     0.7426 0.300 0.700
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0672     0.7906 0.008 0.992
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.6531     0.6797 0.832 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0376     0.7922 0.004 0.996
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.9608     0.6106 0.384 0.616
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.7528     0.7264 0.784 0.216
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.8763     0.7408 0.296 0.704
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.7745     0.7245 0.772 0.228
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#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0672     0.8586 0.992 0.008
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.0000     0.7940 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0376     0.8575 0.996 0.004
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     2  0.9358     0.6759 0.352 0.648
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.0672     0.8586 0.992 0.008
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.0376     0.7922 0.004 0.996
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.9522     0.1113 0.628 0.372
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.9881    -0.1564 0.564 0.436
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.7376     0.7755 0.208 0.792
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.7815     0.7210 0.768 0.232
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.0672     0.7906 0.008 0.992
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0376     0.7924 0.004 0.996
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.8763     0.7408 0.296 0.704
#> A9195281-8CAE-45A8-8493-744E577907FA     1  0.9944     0.4107 0.544 0.456
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.9795    -0.0262 0.416 0.584
#> E789661A-C027-405D-9F76-E6D52CE3018B     1  0.9993     0.3451 0.516 0.484
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.7745     0.7245 0.772 0.228
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0000     0.7940 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0672     0.8586 0.992 0.008
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0376     0.8575 0.996 0.004
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.5294     0.7507 0.880 0.120
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0376     0.8575 0.996 0.004
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.7602     0.7719 0.220 0.780
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.9850    -0.0729 0.428 0.572
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0672     0.7906 0.008 0.992
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000     0.7940 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000     0.7940 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.7674     0.7237 0.776 0.224
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.8443     0.7567 0.272 0.728
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0672     0.8586 0.992 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000     0.8560 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0000     0.7940 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.3733     0.8063 0.928 0.072
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0672     0.8586 0.992 0.008
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0000     0.8560 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0672     0.8586 0.992 0.008
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0672     0.8586 0.992 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     2  0.8763     0.7408 0.296 0.704
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.8763     0.7408 0.296 0.704
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.7745     0.7245 0.772 0.228
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.6887     0.7524 0.816 0.184
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.8560 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.7940 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0672     0.8586 0.992 0.008
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.9954    -0.2215 0.540 0.460
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.8763     0.7408 0.296 0.704
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0672     0.8586 0.992 0.008
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.7056     0.6404 0.808 0.192
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.8207     0.7600 0.256 0.744
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0672     0.8586 0.992 0.008
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.8813     0.6405 0.700 0.300
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.5946     0.7824 0.856 0.144
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.7940 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.7940 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0672     0.8586 0.992 0.008
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000     0.7940 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.8763     0.7408 0.296 0.704
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.8713     0.7433 0.292 0.708
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.8560 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.7940 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.7745     0.7245 0.772 0.228
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0672     0.8586 0.992 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.9754     0.5850 0.408 0.592
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.7940 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.9933     0.4209 0.548 0.452
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0672     0.8586 0.992 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.9491     0.1566 0.632 0.368
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.2043     0.8361 0.968 0.032
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0672     0.8586 0.992 0.008
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.7940 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.7940 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.7745     0.7245 0.772 0.228
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.8763     0.7408 0.296 0.704
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0672     0.8586 0.992 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.8861     0.7395 0.304 0.696
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.8763     0.7408 0.296 0.704
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.8861     0.7395 0.304 0.696
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.8763     0.7408 0.296 0.704
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.7674     0.7710 0.224 0.776
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.6623     0.6626 0.828 0.172
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0672     0.8586 0.992 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0672     0.8586 0.992 0.008
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.8813     0.6359 0.700 0.300
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.9460     0.6025 0.364 0.636
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.8861     0.7395 0.304 0.696
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.6148     0.7863 0.152 0.848
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0672     0.8586 0.992 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0672     0.7906 0.008 0.992
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.7940 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0672     0.8586 0.992 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.8763     0.7408 0.296 0.704
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.8763     0.7408 0.296 0.704
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0672     0.8586 0.992 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.8608     0.4186 0.716 0.284
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.8763     0.6398 0.704 0.296
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.6531     0.7694 0.832 0.168
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.6973     0.7553 0.812 0.188
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0672     0.8586 0.992 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.8861     0.6324 0.696 0.304
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0672     0.8586 0.992 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0672     0.8586 0.992 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.8763     0.7408 0.296 0.704
#> 1122039D-5785-4F70-9916-17C585453512     1  0.7745     0.7245 0.772 0.228
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6048     0.6997 0.852 0.148
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.8861     0.7395 0.304 0.696
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.8955     0.6336 0.688 0.312
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.9491     0.1813 0.368 0.632
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.7940 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0672     0.8586 0.992 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.7674     0.7237 0.776 0.224
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0672     0.8586 0.992 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8560 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.8713     0.7433 0.292 0.708
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.6712     0.6659 0.824 0.176
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.8207     0.4694 0.256 0.744
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0672     0.8586 0.992 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.9998     0.3036 0.508 0.492
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.8813     0.7367 0.300 0.700
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3114     0.8220 0.944 0.056
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.8861     0.7395 0.304 0.696
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.8763     0.7408 0.296 0.704
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.9552     0.1276 0.376 0.624
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.8560 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.8560 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0672     0.8586 0.992 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0672     0.8586 0.992 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.7674     0.7237 0.776 0.224
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0672     0.8586 0.992 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.7940 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.6343     0.7859 0.160 0.840
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.7940 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.8560 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0938     0.8578 0.988 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0672     0.8586 0.992 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0672     0.8586 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.2982     0.8634 0.024 0.920 0.056
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2584     0.8678 0.928 0.064 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1163     0.8987 0.000 0.028 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.2651     0.8721 0.928 0.060 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.6600     0.3751 0.384 0.604 0.012
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0592     0.9050 0.000 0.012 0.988
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.6154     0.7151 0.204 0.752 0.044
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.3038     0.8727 0.104 0.000 0.896
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0747     0.9045 0.000 0.016 0.984
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2879     0.8872 0.024 0.052 0.924
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.1170     0.8743 0.016 0.976 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.2711     0.8822 0.088 0.000 0.912
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1765     0.8977 0.004 0.956 0.040
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.4339     0.8602 0.048 0.084 0.868
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.2313     0.8862 0.944 0.032 0.024
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0237     0.9058 0.000 0.004 0.996
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.2749     0.8699 0.924 0.064 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.1765     0.8977 0.004 0.956 0.040
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2651     0.8485 0.060 0.928 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.1529     0.8983 0.000 0.960 0.040
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.6511     0.7341 0.180 0.748 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1765     0.8977 0.004 0.956 0.040
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0592     0.8870 0.988 0.000 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1529     0.8983 0.000 0.960 0.040
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1031     0.8916 0.976 0.000 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.2625     0.8838 0.000 0.916 0.084
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.1399     0.9042 0.028 0.004 0.968
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.6204     0.2818 0.424 0.000 0.576
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.5016     0.7223 0.240 0.000 0.760
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.2796     0.8802 0.092 0.000 0.908
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.1015     0.9059 0.008 0.012 0.980
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1529     0.8983 0.000 0.960 0.040
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.2749     0.8699 0.924 0.064 0.012
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.2625     0.8843 0.084 0.000 0.916
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.0592     0.9054 0.000 0.012 0.988
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.2879     0.8784 0.924 0.052 0.024
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#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.6126     0.3573 0.600 0.000 0.400
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.2261     0.8908 0.000 0.932 0.068
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.2625     0.8838 0.000 0.916 0.084
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.5058     0.7060 0.756 0.000 0.244
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.1453     0.8713 0.024 0.968 0.008
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     3  0.1163     0.8987 0.000 0.028 0.972
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.1411     0.8922 0.964 0.000 0.036
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.1529     0.8983 0.000 0.960 0.040
#> 457090A2-AE7F-4E68-85EA-032DE8411110     3  0.4178     0.8140 0.172 0.000 0.828
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.0424     0.9054 0.000 0.008 0.992
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.1529     0.8919 0.960 0.000 0.040
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.1765     0.8977 0.004 0.956 0.040
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     3  0.2584     0.8952 0.064 0.008 0.928
#> 34ED910C-7470-4552-8561-D01D59190521     3  0.5346     0.8178 0.152 0.040 0.808
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.1163     0.8987 0.000 0.028 0.972
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.2749     0.8699 0.924 0.064 0.012
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.1453     0.8713 0.024 0.968 0.008
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.1529     0.8983 0.000 0.960 0.040
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.0747     0.9045 0.000 0.016 0.984
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.7475     0.3759 0.376 0.580 0.044
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.5798     0.7531 0.176 0.780 0.044
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.6380     0.6886 0.224 0.732 0.044
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     1  0.3083     0.8743 0.916 0.060 0.024
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.2796     0.8795 0.000 0.908 0.092
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.1411     0.8922 0.964 0.000 0.036
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.1163     0.8918 0.972 0.000 0.028
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     3  0.2796     0.8802 0.092 0.000 0.908
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.1529     0.8919 0.960 0.000 0.040
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.1163     0.8987 0.000 0.028 0.972
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.6423     0.6824 0.228 0.728 0.044
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.1620     0.8701 0.024 0.964 0.012
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.2356     0.8895 0.000 0.928 0.072
#> 80936433-AA91-4219-98F1-706C36298060     2  0.1529     0.8983 0.000 0.960 0.040
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.2384     0.8731 0.936 0.056 0.008
#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.5330     0.8252 0.044 0.144 0.812
#> D85CB054-7F54-4383-96C0-6C99761B84E7     3  0.6111     0.3722 0.396 0.000 0.604
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.2116     0.8729 0.948 0.040 0.012
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.2356     0.8894 0.000 0.928 0.072
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.2711     0.8822 0.088 0.000 0.912
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.1411     0.8922 0.964 0.000 0.036
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.2261     0.8831 0.932 0.000 0.068
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.4842     0.7320 0.776 0.000 0.224
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.3482     0.8449 0.872 0.000 0.128
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.0592     0.9053 0.000 0.012 0.988
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0747     0.9045 0.000 0.016 0.984
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.2749     0.8699 0.924 0.064 0.012
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.3695     0.8438 0.880 0.108 0.012
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.2116     0.8729 0.948 0.040 0.012
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1643     0.8981 0.000 0.956 0.044
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.1411     0.8922 0.964 0.000 0.036
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.2486     0.8981 0.060 0.008 0.932
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0592     0.9050 0.000 0.012 0.988
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1529     0.8919 0.960 0.000 0.040
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.2955     0.8900 0.080 0.008 0.912
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.6302     0.6968 0.048 0.208 0.744
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.1411     0.8922 0.964 0.000 0.036
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.6724     0.2745 0.420 0.568 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.1636     0.8896 0.964 0.016 0.020
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.2878     0.8778 0.000 0.904 0.096
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.1765     0.8977 0.004 0.956 0.040
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.3038     0.8634 0.896 0.000 0.104
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.1643     0.8981 0.000 0.956 0.044
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.0747     0.9045 0.000 0.016 0.984
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0747     0.9045 0.000 0.016 0.984
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2116     0.8729 0.948 0.040 0.012
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1643     0.8981 0.000 0.956 0.044
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.2749     0.8699 0.924 0.064 0.012
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.3482     0.8441 0.872 0.000 0.128
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.1832     0.9032 0.036 0.008 0.956
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.2356     0.8895 0.000 0.928 0.072
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.7263     0.4087 0.372 0.592 0.036
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4931     0.7187 0.768 0.000 0.232
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.2261     0.8920 0.068 0.000 0.932
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.3481     0.8881 0.052 0.044 0.904
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1411     0.8922 0.964 0.000 0.036
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1529     0.8983 0.000 0.960 0.040
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1529     0.8983 0.000 0.960 0.040
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.2749     0.8699 0.924 0.064 0.012
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0592     0.9053 0.000 0.012 0.988
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.4887     0.7281 0.772 0.000 0.228
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.2383     0.8912 0.016 0.044 0.940
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0747     0.9045 0.000 0.016 0.984
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.3263     0.8879 0.048 0.040 0.912
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.0747     0.9045 0.000 0.016 0.984
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0892     0.9029 0.000 0.020 0.980
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.2866     0.8917 0.076 0.008 0.916
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.2796     0.8802 0.092 0.000 0.908
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.3038     0.8727 0.104 0.000 0.896
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.6490     0.3992 0.360 0.628 0.012
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.4802     0.7707 0.156 0.020 0.824
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.2550     0.8937 0.024 0.040 0.936
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.4682     0.7308 0.004 0.192 0.804
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.3038     0.8634 0.896 0.000 0.104
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0829     0.8775 0.012 0.984 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1529     0.8983 0.000 0.960 0.040
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1411     0.8922 0.964 0.000 0.036
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.1753     0.8994 0.048 0.000 0.952
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0747     0.9045 0.000 0.016 0.984
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1411     0.8922 0.964 0.000 0.036
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.2537     0.8862 0.080 0.000 0.920
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6510     0.4091 0.364 0.624 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.1620     0.8864 0.964 0.024 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.2116     0.8811 0.948 0.040 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1411     0.8922 0.964 0.000 0.036
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.4861     0.7335 0.180 0.808 0.012
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1411     0.8922 0.964 0.000 0.036
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1529     0.8918 0.960 0.000 0.040
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0592     0.9053 0.000 0.012 0.988
#> 1122039D-5785-4F70-9916-17C585453512     1  0.2486     0.8690 0.932 0.060 0.008
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.5524     0.8094 0.164 0.040 0.796
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.2173     0.8943 0.008 0.048 0.944
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3752     0.8057 0.144 0.856 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0848     0.8765 0.008 0.984 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4504     0.7878 0.000 0.804 0.196
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.6307     0.0535 0.512 0.000 0.488
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.2486     0.8690 0.932 0.060 0.008
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1643     0.8910 0.956 0.000 0.044
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3  0.4605     0.7800 0.204 0.000 0.796
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0747     0.9045 0.000 0.016 0.984
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.6498     0.3329 0.396 0.008 0.596
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1878     0.8971 0.004 0.952 0.044
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1411     0.8922 0.964 0.000 0.036
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5268     0.6766 0.212 0.776 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1453     0.9054 0.024 0.008 0.968
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.2959     0.8754 0.100 0.000 0.900
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.3042     0.8887 0.040 0.040 0.920
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0592     0.9050 0.000 0.012 0.988
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1878     0.8971 0.004 0.952 0.044
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.4136     0.8569 0.116 0.020 0.864
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.4449     0.8615 0.100 0.040 0.860
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.4399     0.7997 0.188 0.000 0.812
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3116     0.8605 0.892 0.000 0.108
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.2749     0.8699 0.924 0.064 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.5560     0.6031 0.700 0.000 0.300
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5529     0.6455 0.000 0.704 0.296
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3784     0.8109 0.004 0.132 0.864
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1529     0.8983 0.000 0.960 0.040
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.3752     0.8719 0.096 0.020 0.884
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.5678     0.5751 0.316 0.000 0.684
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.3213     0.8862 0.092 0.008 0.900
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2796     0.8714 0.908 0.000 0.092

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.6006    0.71147 0.096 0.700 0.008 0.196
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4163    0.84425 0.220 0.004 0.004 0.772
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1256    0.84301 0.000 0.008 0.964 0.028
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4198    0.84228 0.224 0.004 0.004 0.768
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.5565    0.56438 0.056 0.684 0.000 0.260
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.2032    0.83893 0.036 0.000 0.936 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4599    0.71962 0.088 0.800 0.000 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4382    0.66704 0.704 0.000 0.296 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0779    0.84884 0.016 0.004 0.980 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4130    0.72869 0.108 0.000 0.828 0.064
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3836    0.80703 0.028 0.840 0.004 0.128
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4967    0.44963 0.548 0.000 0.452 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2589    0.82101 0.000 0.884 0.000 0.116
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7653    0.48717 0.512 0.204 0.276 0.008
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.5244    0.59245 0.436 0.008 0.000 0.556
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.2530    0.76578 0.112 0.000 0.888 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4163    0.84425 0.220 0.004 0.004 0.772
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.2704    0.81850 0.000 0.876 0.000 0.124
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.4889    0.61670 0.000 0.636 0.004 0.360
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#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.2859    0.56605 0.880 0.000 0.008 0.112
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4040    0.69584 0.752 0.000 0.248 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1590    0.84136 0.008 0.008 0.956 0.028
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.7065    0.64588 0.644 0.120 0.200 0.036
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2589    0.77276 0.000 0.884 0.000 0.116
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.4800    0.01981 0.656 0.000 0.004 0.340
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4343    0.72682 0.000 0.732 0.004 0.264
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.2149    0.79159 0.088 0.000 0.912 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4746    0.59428 0.632 0.000 0.368 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.5959    0.43970 0.568 0.000 0.388 0.044
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2364    0.83677 0.036 0.008 0.928 0.028
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3444    0.74949 0.000 0.816 0.000 0.184
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4993    0.68056 0.712 0.000 0.260 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5272    0.66198 0.680 0.000 0.288 0.032
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4606    0.69196 0.724 0.000 0.264 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3015    0.67065 0.884 0.000 0.092 0.024
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4163    0.84425 0.220 0.004 0.004 0.772
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3653    0.68921 0.844 0.000 0.128 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.5466    0.48027 0.000 0.292 0.668 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2282    0.82488 0.000 0.024 0.924 0.052
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2647    0.81838 0.000 0.880 0.000 0.120
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5022    0.68064 0.708 0.000 0.264 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5515    0.70647 0.728 0.052 0.208 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4220    0.57865 0.248 0.000 0.748 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2949    0.66783 0.888 0.000 0.088 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.4534   0.329475 0.028 0.224 0.000 0.016 0.732
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1741   0.814755 0.000 0.024 0.936 0.000 0.040
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0932   0.835943 0.020 0.004 0.000 0.972 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3519   0.555158 0.008 0.776 0.000 0.216 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4817   0.767750 0.060 0.024 0.760 0.004 0.152
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.3846   0.556951 0.080 0.840 0.040 0.004 0.036
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4558   0.684212 0.740 0.000 0.080 0.000 0.180
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0324   0.819640 0.004 0.000 0.992 0.000 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.5236   0.356033 0.048 0.000 0.544 0.000 0.408
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.4302   0.357343 0.000 0.520 0.000 0.000 0.480
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5454   0.611881 0.672 0.000 0.148 0.004 0.176
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.4549   0.379785 0.000 0.528 0.000 0.008 0.464
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7996   0.192662 0.436 0.196 0.128 0.000 0.240
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6529   0.069884 0.456 0.172 0.000 0.368 0.004
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.3927   0.761462 0.040 0.000 0.792 0.004 0.164
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.5974   0.404408 0.000 0.548 0.000 0.320 0.132
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.6483   0.348208 0.000 0.172 0.024 0.580 0.224
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3003   0.576796 0.000 0.812 0.000 0.000 0.188
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.3857   0.643092 0.808 0.000 0.000 0.084 0.108
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.4415   0.392705 0.000 0.552 0.000 0.004 0.444
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.4118   0.433004 0.660 0.000 0.000 0.336 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.4648   0.369260 0.000 0.524 0.012 0.000 0.464
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.7099   0.450195 0.560 0.072 0.232 0.004 0.132
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4838   0.708605 0.768 0.016 0.072 0.012 0.132
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2540   0.732328 0.904 0.004 0.036 0.004 0.052
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3826   0.710431 0.812 0.000 0.056 0.004 0.128
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.3507   0.762731 0.052 0.000 0.828 0.000 0.120
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.5440   0.613575 0.660 0.000 0.184 0.000 0.156
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.3812   0.765642 0.036 0.000 0.800 0.004 0.160
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.6804  -0.040164 0.404 0.232 0.000 0.360 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5120   0.254922 0.540 0.428 0.000 0.008 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4905   0.637314 0.696 0.000 0.224 0.000 0.080
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.4298   0.508546 0.352 0.000 0.000 0.640 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4914   0.661505 0.712 0.000 0.108 0.000 0.180
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3550   0.728675 0.848 0.008 0.080 0.004 0.060
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0404   0.640171 0.000 0.988 0.000 0.000 0.012
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.5409   0.378632 0.612 0.000 0.000 0.084 0.304
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.6884  -0.028397 0.396 0.268 0.000 0.332 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.1205   0.821209 0.000 0.000 0.956 0.004 0.040
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.6322   0.181324 0.000 0.144 0.532 0.008 0.316
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3037   0.731225 0.860 0.000 0.100 0.000 0.040
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.8369   0.148041 0.300 0.104 0.192 0.016 0.388
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.4262   0.400578 0.000 0.560 0.000 0.000 0.440
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4886   0.685650 0.744 0.000 0.124 0.012 0.120
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.6107   0.511699 0.620 0.020 0.248 0.004 0.108
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.6059   0.320773 0.000 0.184 0.000 0.572 0.244
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.5074   0.755888 0.080 0.028 0.748 0.004 0.140
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.2300   0.722034 0.904 0.000 0.000 0.072 0.024
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2956   0.693037 0.848 0.004 0.000 0.140 0.008
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0703   0.639067 0.000 0.976 0.000 0.000 0.024
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4468   0.505617 0.044 0.716 0.000 0.240 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.3340   0.792150 0.032 0.000 0.840 0.004 0.124
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.6121   0.347881 0.000 0.464 0.000 0.128 0.408
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.2673   0.730966 0.892 0.000 0.044 0.004 0.060
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1571   0.631592 0.000 0.936 0.000 0.060 0.004
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.1461   0.730585 0.952 0.028 0.000 0.016 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.2331   0.733482 0.912 0.004 0.020 0.004 0.060
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.7132  -0.154267 0.356 0.004 0.368 0.008 0.264
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.2843   0.787362 0.008 0.000 0.848 0.000 0.144
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.4353   0.326748 0.024 0.224 0.000 0.012 0.740
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.3462   0.619950 0.792 0.000 0.000 0.012 0.196
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3142   0.728125 0.864 0.000 0.076 0.004 0.056
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.3038   0.718482 0.872 0.000 0.016 0.088 0.024
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.6237   0.253913 0.000 0.196 0.000 0.540 0.264
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.7687  -0.124243 0.164 0.408 0.040 0.020 0.368
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0324   0.640215 0.000 0.992 0.000 0.004 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.6558  -0.032656 0.000 0.156 0.448 0.008 0.388
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3149   0.806693 0.012 0.032 0.872 0.004 0.080
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.1978   0.813425 0.000 0.024 0.928 0.004 0.044
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.5864   0.328273 0.004 0.536 0.092 0.000 0.368
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.3372   0.765226 0.104 0.008 0.852 0.004 0.032
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.2125   0.812922 0.000 0.024 0.920 0.004 0.052
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.5216   0.387649 0.604 0.344 0.000 0.004 0.048
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.2321   0.724009 0.916 0.044 0.000 0.016 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.1074   0.818429 0.004 0.016 0.968 0.000 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.3928   0.509598 0.700 0.000 0.000 0.296 0.004
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0566   0.636950 0.004 0.984 0.000 0.000 0.012
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.2624   0.703637 0.872 0.000 0.000 0.116 0.012
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0963   0.821076 0.000 0.000 0.964 0.000 0.036
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.3561   0.735958 0.852 0.000 0.068 0.028 0.052
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.1960   0.620315 0.012 0.936 0.028 0.004 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.4788   0.681086 0.740 0.000 0.136 0.004 0.120
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.4817   0.766507 0.084 0.028 0.772 0.004 0.112
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.2267   0.724599 0.916 0.048 0.000 0.008 0.028
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.4417   0.689412 0.760 0.000 0.092 0.000 0.148
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.3835   0.298529 0.012 0.244 0.000 0.000 0.744
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.3242   0.584533 0.000 0.816 0.000 0.172 0.012
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0794   0.638760 0.000 0.972 0.000 0.000 0.028
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.4919   0.700079 0.756 0.000 0.100 0.028 0.116
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.2523   0.736563 0.908 0.000 0.040 0.024 0.028
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.3630   0.563433 0.032 0.852 0.076 0.004 0.036
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.5995   0.256118 0.000 0.468 0.112 0.000 0.420
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.2444   0.736561 0.912 0.000 0.036 0.028 0.024
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.5783   0.357106 0.040 0.016 0.604 0.016 0.324
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.5016   0.619830 0.076 0.000 0.184 0.724 0.016
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.4545   0.739014 0.084 0.000 0.756 0.004 0.156
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.4262   0.399511 0.000 0.560 0.000 0.000 0.440
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.6374   0.233855 0.504 0.000 0.000 0.196 0.300
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.5503   0.453060 0.184 0.712 0.020 0.064 0.020
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.3555   0.574128 0.052 0.824 0.000 0.124 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0727   0.636987 0.004 0.980 0.000 0.004 0.012
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.6923   0.345818 0.516 0.028 0.120 0.012 0.324
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.4323   0.449661 0.012 0.656 0.000 0.332 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3  0.5771   0.294039 0.076 0.000 0.500 0.004 0.420
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.1059   0.641111 0.000 0.968 0.008 0.004 0.020
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0324   0.819640 0.004 0.000 0.992 0.000 0.004
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.4401   0.406936 0.656 0.000 0.000 0.016 0.328
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#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.2730   0.715750 0.892 0.044 0.000 0.056 0.008
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.5443   0.381078 0.604 0.000 0.000 0.084 0.312
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1560   0.624544 0.004 0.948 0.028 0.000 0.020
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.2054   0.721819 0.916 0.004 0.000 0.072 0.008
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.3814   0.755207 0.116 0.004 0.816 0.000 0.064
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3433   0.788583 0.032 0.000 0.832 0.004 0.132
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.2269   0.728392 0.920 0.028 0.000 0.032 0.020
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.5434  -0.013238 0.452 0.004 0.496 0.000 0.048
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.7165   0.500586 0.568 0.124 0.132 0.000 0.176
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.1484   0.729484 0.944 0.000 0.000 0.048 0.008
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.3477   0.572715 0.040 0.824 0.000 0.136 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.4383   0.308210 0.572 0.000 0.000 0.424 0.004
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.5114   0.110821 0.000 0.560 0.404 0.004 0.032
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0898   0.640198 0.000 0.972 0.000 0.008 0.020
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.1997   0.728711 0.932 0.028 0.000 0.016 0.024
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.1989   0.616978 0.016 0.932 0.020 0.000 0.032
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.3011   0.787965 0.016 0.000 0.844 0.000 0.140
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0324   0.819640 0.004 0.000 0.992 0.000 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.6162   0.282114 0.532 0.000 0.000 0.160 0.308
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0451   0.640101 0.004 0.988 0.000 0.000 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.1978   0.734703 0.932 0.000 0.012 0.032 0.024
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.5852   0.170677 0.400 0.008 0.524 0.004 0.064
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.3789   0.542853 0.016 0.760 0.000 0.224 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2902   0.737537 0.888 0.000 0.028 0.028 0.056
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.3622   0.753707 0.048 0.000 0.816 0.000 0.136
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     5  0.6748  -0.091681 0.368 0.000 0.260 0.000 0.372
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2540   0.715980 0.888 0.000 0.000 0.088 0.024
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0794   0.638760 0.000 0.972 0.000 0.000 0.028
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.4291   0.383533 0.000 0.536 0.000 0.000 0.464
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.2046   0.807215 0.016 0.000 0.916 0.000 0.068
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2140   0.737492 0.924 0.000 0.040 0.024 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7     5  0.6464  -0.084629 0.156 0.000 0.408 0.004 0.432
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0566   0.819322 0.004 0.000 0.984 0.000 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.5991   0.554562 0.616 0.000 0.172 0.008 0.204
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.2886   0.789423 0.008 0.000 0.844 0.000 0.148
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0324   0.819640 0.004 0.000 0.992 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3238   0.754989 0.136 0.000 0.836 0.000 0.028
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4019   0.701025 0.792 0.000 0.052 0.004 0.152
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.3506   0.719358 0.824 0.000 0.044 0.000 0.132
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.3012   0.591977 0.024 0.852 0.000 0.124 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.3241   0.747166 0.036 0.100 0.856 0.000 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.6684  -0.084272 0.352 0.000 0.408 0.000 0.240
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.3123   0.797714 0.004 0.040 0.876 0.012 0.068
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1667   0.734341 0.948 0.012 0.012 0.004 0.024
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4306   0.338593 0.000 0.508 0.000 0.000 0.492
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0613   0.637642 0.004 0.984 0.000 0.004 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.2338   0.706431 0.884 0.000 0.000 0.112 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.6068   0.559831 0.632 0.012 0.176 0.004 0.176
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2873   0.794515 0.016 0.000 0.856 0.000 0.128
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2300   0.721852 0.904 0.000 0.000 0.072 0.024
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.3495   0.728924 0.160 0.000 0.812 0.000 0.028
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7198   0.127004 0.040 0.476 0.000 0.192 0.292
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0609   0.837972 0.020 0.000 0.000 0.980 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0609   0.837972 0.020 0.000 0.000 0.980 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.2597   0.714385 0.884 0.000 0.000 0.092 0.024
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.7507  -0.000529 0.036 0.340 0.000 0.272 0.352
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.2540   0.715980 0.888 0.000 0.000 0.088 0.024
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1830   0.723068 0.924 0.000 0.000 0.068 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.2727   0.786631 0.016 0.000 0.868 0.000 0.116
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0566   0.837952 0.012 0.004 0.000 0.984 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6430   0.148697 0.448 0.000 0.112 0.016 0.424
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.4289   0.725624 0.064 0.000 0.760 0.000 0.176
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.1756   0.799868 0.008 0.016 0.000 0.940 0.036
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.5648   0.350980 0.000 0.476 0.000 0.076 0.448
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5480   0.102146 0.016 0.548 0.400 0.000 0.036
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3671   0.732638 0.844 0.000 0.060 0.024 0.072
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0566   0.837952 0.012 0.004 0.000 0.984 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1978   0.731431 0.928 0.000 0.004 0.044 0.024
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4025   0.700923 0.792 0.000 0.076 0.000 0.132
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2285   0.812631 0.004 0.024 0.916 0.004 0.052
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5563   0.251490 0.512 0.432 0.004 0.004 0.048
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2339   0.613555 0.004 0.892 0.000 0.100 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.3224   0.670845 0.824 0.000 0.000 0.160 0.016
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.6091   0.448477 0.000 0.560 0.000 0.172 0.268
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4139   0.750216 0.052 0.000 0.780 0.004 0.164
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4703   0.671135 0.744 0.000 0.096 0.004 0.156
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.6677   0.057656 0.328 0.000 0.212 0.004 0.456
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4492   0.782890 0.048 0.028 0.788 0.004 0.132
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3488   0.585551 0.000 0.808 0.000 0.168 0.024
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4283   0.696930 0.780 0.000 0.080 0.004 0.136
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5038   0.664482 0.716 0.000 0.128 0.004 0.152
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4930   0.682838 0.740 0.000 0.128 0.012 0.120
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1612   0.735333 0.948 0.000 0.012 0.016 0.024
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0671   0.840676 0.016 0.004 0.000 0.980 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.2067   0.735784 0.924 0.000 0.028 0.004 0.044
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.2387   0.779674 0.004 0.048 0.908 0.000 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2521   0.806489 0.000 0.024 0.900 0.008 0.068
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.4287   0.386439 0.000 0.540 0.000 0.000 0.460
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3209   0.720858 0.848 0.000 0.028 0.004 0.120
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6806   0.460512 0.568 0.272 0.080 0.004 0.076
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4848   0.640708 0.176 0.000 0.736 0.012 0.076
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1997   0.733022 0.936 0.012 0.008 0.020 0.024

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.4510   0.405394 0.000 0.024 0.004 0.004 0.600 0.368
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0291   0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2987   0.741780 0.088 0.020 0.864 0.000 0.020 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1401   0.842822 0.004 0.000 0.020 0.948 0.000 0.028
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3722   0.690688 0.000 0.764 0.000 0.196 0.004 0.036
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.4384  -0.370689 0.520 0.016 0.460 0.000 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.2129   0.764593 0.056 0.904 0.000 0.000 0.000 0.040
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2094   0.436219 0.908 0.000 0.008 0.000 0.016 0.068
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0436   0.742423 0.004 0.004 0.988 0.000 0.004 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.7068   0.260111 0.328 0.000 0.376 0.000 0.080 0.216
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3046   0.873997 0.000 0.188 0.000 0.000 0.800 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1503   0.454564 0.944 0.000 0.032 0.000 0.008 0.016
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.3133   0.876276 0.000 0.212 0.000 0.000 0.780 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7804   0.262979 0.452 0.068 0.144 0.000 0.228 0.108
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.6996   0.163600 0.068 0.256 0.000 0.276 0.000 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.4815  -0.269265 0.532 0.000 0.424 0.000 0.012 0.032
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0291   0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.3133   0.876276 0.000 0.212 0.000 0.000 0.780 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.6663  -0.043564 0.000 0.388 0.000 0.312 0.268 0.032
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.2854   0.879174 0.000 0.208 0.000 0.000 0.792 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.6344   0.403826 0.000 0.052 0.024 0.536 0.312 0.076
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2431   0.706155 0.000 0.860 0.000 0.000 0.132 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.3968   0.456357 0.148 0.008 0.000 0.048 0.012 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.4227   0.794861 0.000 0.256 0.000 0.000 0.692 0.052
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.5879   0.447935 0.228 0.004 0.000 0.260 0.000 0.508
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.3417   0.848760 0.000 0.160 0.044 0.000 0.796 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.3141   0.438346 0.852 0.040 0.084 0.000 0.000 0.024
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.5201   0.305581 0.644 0.000 0.112 0.000 0.016 0.228
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3816   0.075343 0.688 0.016 0.000 0.000 0.000 0.296
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2500   0.382727 0.868 0.012 0.004 0.000 0.000 0.116
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4185   0.597125 0.168 0.000 0.752 0.000 0.012 0.068
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.2854   0.879174 0.000 0.208 0.000 0.000 0.792 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0146   0.875508 0.004 0.000 0.000 0.996 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.5378   0.402912 0.632 0.000 0.232 0.000 0.024 0.112
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.4939   0.438466 0.456 0.000 0.496 0.000 0.024 0.024
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     6  0.7025   0.104514 0.064 0.288 0.000 0.280 0.000 0.368
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4750   0.536061 0.100 0.656 0.000 0.000 0.000 0.244
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6149   0.249311 0.448 0.000 0.308 0.000 0.008 0.236
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.4876   0.203523 0.048 0.004 0.000 0.444 0.000 0.504
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000   0.874345 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2613   0.442461 0.884 0.000 0.032 0.000 0.016 0.068
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5129   0.282105 0.668 0.020 0.120 0.000 0.000 0.192
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0858   0.790516 0.000 0.968 0.000 0.000 0.028 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.4893   0.404917 0.108 0.004 0.000 0.040 0.120 0.728
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.7160   0.183632 0.088 0.388 0.000 0.256 0.000 0.268
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3013   0.733220 0.152 0.004 0.828 0.000 0.012 0.004
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#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4110  -0.109583 0.608 0.016 0.000 0.000 0.000 0.376
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.2948   0.874255 0.000 0.188 0.000 0.000 0.804 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0653   0.792262 0.000 0.980 0.004 0.000 0.012 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.4942   0.459115 0.412 0.008 0.000 0.048 0.000 0.532
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1657   0.451138 0.936 0.012 0.040 0.000 0.000 0.012
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4009   0.621438 0.304 0.000 0.676 0.000 0.008 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.4366   0.444205 0.428 0.000 0.000 0.024 0.000 0.548
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.5216   0.082327 0.344 0.004 0.568 0.000 0.004 0.080
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7361   0.252657 0.004 0.388 0.000 0.180 0.124 0.304
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0508   0.870393 0.004 0.000 0.000 0.984 0.000 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0291   0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.4654   0.458987 0.412 0.000 0.000 0.044 0.000 0.544
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.7474   0.157556 0.000 0.336 0.000 0.228 0.140 0.296
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.4597   0.456849 0.412 0.000 0.000 0.040 0.000 0.548
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.4289   0.424353 0.444 0.004 0.000 0.012 0.000 0.540
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3710   0.631169 0.196 0.000 0.768 0.000 0.012 0.024
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0458   0.870339 0.000 0.000 0.000 0.984 0.016 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6  0.6675  -0.030016 0.376 0.012 0.040 0.004 0.128 0.440
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.5249   0.361971 0.444 0.000 0.488 0.000 0.032 0.036
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.1003   0.860618 0.000 0.004 0.000 0.964 0.028 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.4103   0.847629 0.000 0.192 0.004 0.040 0.752 0.012
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3513   0.669240 0.016 0.800 0.164 0.000 0.016 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.5751   0.095011 0.520 0.000 0.136 0.000 0.012 0.332
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0458   0.870339 0.000 0.000 0.000 0.984 0.016 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.4304   0.417882 0.448 0.000 0.008 0.008 0.000 0.536
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.5021   0.220013 0.628 0.000 0.068 0.000 0.016 0.288
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3718   0.725589 0.148 0.028 0.800 0.000 0.016 0.008
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.5119   0.499375 0.220 0.624 0.000 0.000 0.000 0.156
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1930   0.787708 0.000 0.924 0.000 0.036 0.012 0.028
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.5001   0.470398 0.384 0.000 0.000 0.076 0.000 0.540
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.6005   0.514871 0.000 0.328 0.000 0.124 0.516 0.032
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4029   0.231643 0.688 0.000 0.288 0.000 0.012 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.1116   0.438960 0.960 0.004 0.008 0.000 0.000 0.028
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.6119   0.306935 0.572 0.000 0.116 0.000 0.068 0.244
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5111  -0.395374 0.492 0.024 0.456 0.000 0.012 0.016
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3721   0.709585 0.000 0.784 0.000 0.168 0.016 0.032
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4686   0.328106 0.700 0.000 0.068 0.000 0.020 0.212
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5393   0.369223 0.656 0.000 0.160 0.000 0.032 0.152
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.6009   0.266284 0.548 0.000 0.192 0.000 0.024 0.236
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4199  -0.204258 0.568 0.016 0.000 0.000 0.000 0.416
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0291   0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4088  -0.080215 0.616 0.016 0.000 0.000 0.000 0.368
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.1719   0.741762 0.000 0.008 0.928 0.000 0.056 0.008
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.5127   0.706350 0.116 0.024 0.732 0.000 0.056 0.072
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.2994   0.878568 0.000 0.208 0.000 0.000 0.788 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2805   0.332002 0.828 0.012 0.000 0.000 0.000 0.160
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6550   0.087343 0.452 0.348 0.064 0.000 0.000 0.136
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5789  -0.020864 0.316 0.000 0.516 0.000 0.008 0.160
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4224  -0.238381 0.552 0.016 0.000 0.000 0.000 0.432

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)

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 17541 rows and 500 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 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-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 0.815           0.879       0.947         0.5008 0.499   0.499
#> 3 3 0.861           0.885       0.952         0.3334 0.675   0.438
#> 4 4 0.688           0.700       0.857         0.1197 0.838   0.567
#> 5 5 0.652           0.323       0.655         0.0653 0.865   0.544
#> 6 6 0.722           0.577       0.777         0.0418 0.850   0.426

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000     0.9446 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.1633     0.9323 0.976 0.024
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.1633     0.9423 0.024 0.976
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.1633     0.9323 0.976 0.024
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.4815     0.8684 0.896 0.104
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.1633     0.9423 0.024 0.976
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.8443     0.6081 0.272 0.728
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9401 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.1633     0.9423 0.024 0.976
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.1633     0.9423 0.024 0.976
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000     0.9446 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.6801     0.7559 0.820 0.180
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9446 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.7815     0.7120 0.232 0.768
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.1633     0.9323 0.976 0.024
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.1633     0.9423 0.024 0.976
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.1633     0.9323 0.976 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9446 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.8386     0.6506 0.732 0.268
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9446 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000     0.9446 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9446 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9401 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9446 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1633     0.9323 0.976 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9446 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.1633     0.9423 0.024 0.976
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000     0.9401 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.9401 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9401 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.9988     0.1198 0.480 0.520
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9446 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.1633     0.9323 0.976 0.024
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3584     0.8877 0.932 0.068
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.1633     0.9423 0.024 0.976
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.1633     0.9323 0.976 0.024
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.1633     0.9323 0.976 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.9401 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9401 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.1633     0.9323 0.976 0.024
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0938     0.9339 0.988 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9401 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9446 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9401 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.1633     0.9323 0.976 0.024
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.1633     0.9423 0.024 0.976
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000     0.9446 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000     0.9401 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     2  0.7674     0.7215 0.224 0.776
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.6712     0.7608 0.176 0.824
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9401 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.3274     0.8954 0.940 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.9446 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.1633     0.9423 0.024 0.976
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9401 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.1633     0.9323 0.976 0.024
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#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.1633     0.9323 0.976 0.024
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.9401 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9446 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000     0.9401 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.1633     0.9268 0.976 0.024
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.1633     0.9423 0.024 0.976
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000     0.9401 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0000     0.9401 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.8763     0.5966 0.296 0.704
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.9401 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.1633     0.9323 0.976 0.024
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.1633     0.9323 0.976 0.024
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9446 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.9446 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0000     0.9401 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000     0.9446 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.1633     0.9423 0.024 0.976
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.1633     0.9423 0.024 0.976
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9401 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9446 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.1633     0.9323 0.976 0.024
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.9401 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.9661     0.3913 0.392 0.608
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.9446 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.8016     0.6926 0.756 0.244
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9401 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.9286     0.4627 0.656 0.344
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000     0.9401 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9401 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9446 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9446 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.1633     0.9323 0.976 0.024
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.1843     0.9401 0.028 0.972
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9401 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.1633     0.9423 0.024 0.976
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.1633     0.9423 0.024 0.976
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.9922     0.1710 0.552 0.448
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.1633     0.9423 0.024 0.976
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.1633     0.9423 0.024 0.976
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0376     0.9383 0.996 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9401 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000     0.9401 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.1633     0.9323 0.976 0.024
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.6801     0.7571 0.180 0.820
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.2236     0.9349 0.036 0.964
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.1633     0.9423 0.024 0.976
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9401 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9446 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9446 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9401 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  1.0000     0.0100 0.500 0.500
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.1633     0.9423 0.024 0.976
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9401 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0938     0.9340 0.988 0.012
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.1633     0.9323 0.976 0.024
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.1633     0.9323 0.976 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.1633     0.9323 0.976 0.024
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9401 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.1633     0.9323 0.976 0.024
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9401 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9401 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.1633     0.9423 0.024 0.976
#> 1122039D-5785-4F70-9916-17C585453512     1  0.1633     0.9323 0.976 0.024
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4022     0.8758 0.920 0.080
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.1633     0.9423 0.024 0.976
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.2603     0.9211 0.956 0.044
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.9552     0.4280 0.624 0.376
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9446 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.9401 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.1633     0.9323 0.976 0.024
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.9401 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9401 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.1633     0.9423 0.024 0.976
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.3431     0.8929 0.936 0.064
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.9358     0.4353 0.352 0.648
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9401 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.8144     0.6771 0.748 0.252
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.9998     0.0147 0.508 0.492
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9401 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.1633     0.9423 0.024 0.976
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.1633     0.9423 0.024 0.976
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.9833     0.2340 0.424 0.576
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9401 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.9401 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9401 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9401 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.1633     0.9323 0.976 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9401 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9446 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.1633     0.9423 0.024 0.976
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9446 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9401 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1633     0.9323 0.976 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.9401 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9401 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000      0.948 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000      0.955 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000      0.944 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.0000      0.955 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1643      0.917 0.044 0.956 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000      0.944 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.2448      0.889 0.076 0.924 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.6274      0.159 0.544 0.000 0.456
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0000      0.944 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0000      0.944 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000      0.948 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0592      0.936 0.012 0.000 0.988
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000      0.948 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.8876      0.105 0.120 0.412 0.468
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000      0.955 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0000      0.944 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000      0.955 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000      0.948 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000      0.948 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000      0.948 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.5915      0.770 0.128 0.792 0.080
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000      0.948 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000      0.955 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000      0.948 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000      0.955 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000      0.948 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000      0.944 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000      0.955 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4178      0.776 0.828 0.000 0.172
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.0592      0.936 0.012 0.000 0.988
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000      0.944 0.000 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000      0.948 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.0000      0.955 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.0892      0.930 0.020 0.000 0.980
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.0000      0.944 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000      0.955 1.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.6095      0.307 0.608 0.392 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.1964      0.911 0.944 0.000 0.056
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000      0.955 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0000      0.955 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.5650      0.539 0.312 0.000 0.688
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5948      0.446 0.640 0.000 0.360
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000      0.948 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000      0.955 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0000      0.955 1.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000      0.944 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.5327      0.611 0.000 0.728 0.272
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000      0.955 1.000 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.1289      0.920 0.032 0.000 0.968
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000      0.948 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1031      0.936 0.976 0.000 0.024
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.0000      0.944 0.000 0.000 1.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000      0.948 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0000      0.944 0.000 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000      0.955 1.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000      0.955 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000      0.948 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.6126      0.379 0.400 0.600 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0000      0.944 0.000 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000      0.948 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0592      0.947 0.988 0.000 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000      0.948 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0000      0.955 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000      0.955 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.6026      0.398 0.376 0.000 0.624
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.0000      0.944 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000      0.948 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000      0.955 1.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.6192      0.286 0.580 0.000 0.420
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000      0.955 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000      0.948 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.4399      0.755 0.188 0.812 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000      0.948 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.1860      0.906 0.000 0.948 0.052
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000      0.944 0.000 0.000 1.000
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#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0000      0.944 0.000 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0000      0.944 0.000 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000      0.955 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.3816      0.799 0.148 0.000 0.852
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.6587      0.428 0.016 0.632 0.352
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000      0.955 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.5810      0.527 0.336 0.664 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.0000      0.955 1.000 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000      0.948 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000      0.948 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0000      0.955 1.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000      0.948 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.0000      0.944 0.000 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000      0.944 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000      0.955 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000      0.948 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.0000      0.955 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000      0.955 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.0000      0.944 0.000 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000      0.948 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.5760      0.544 0.328 0.672 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000      0.955 1.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000      0.944 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.5988      0.434 0.368 0.000 0.632
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000      0.955 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000      0.948 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000      0.948 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.0000      0.955 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000      0.944 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000      0.955 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.0000      0.944 0.000 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000      0.944 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.0592      0.936 0.012 0.000 0.988
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.0000      0.944 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0000      0.944 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.0000      0.944 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.3340      0.834 0.120 0.000 0.880
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.5678      0.552 0.684 0.000 0.316
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1163      0.929 0.028 0.972 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.8399      0.486 0.136 0.256 0.608
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.0000      0.944 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0424      0.939 0.000 0.008 0.992
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000      0.955 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000      0.948 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000      0.948 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000      0.955 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0000      0.944 0.000 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000      0.944 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000      0.955 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.0000      0.944 0.000 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.2066      0.903 0.060 0.940 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000      0.955 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000      0.955 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000      0.955 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0237      0.946 0.004 0.996 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000      0.955 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000      0.955 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000      0.944 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000      0.955 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.6154      0.313 0.408 0.000 0.592
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.0000      0.944 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000      0.948 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000      0.948 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.1643      0.913 0.000 0.956 0.044
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000      0.955 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0000      0.955 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000      0.955 1.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1643      0.919 0.956 0.000 0.044
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000      0.944 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.6448      0.437 0.636 0.012 0.352
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000      0.948 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000      0.955 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0237      0.946 0.004 0.996 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000      0.944 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.4452      0.743 0.192 0.000 0.808
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.0000      0.944 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000      0.944 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000      0.948 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2796      0.873 0.908 0.000 0.092
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.6267      0.178 0.452 0.000 0.548
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4605      0.730 0.796 0.000 0.204
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000      0.955 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000      0.955 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000      0.955 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.6295      0.101 0.000 0.472 0.528
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000      0.944 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000      0.948 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3482      0.832 0.872 0.000 0.128
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000      0.955 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.3482      0.823 0.128 0.000 0.872
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000      0.955 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3726     0.6828 0.212 0.788 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0921     0.8665 0.028 0.000 0.972 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0336     0.7871 0.000 0.000 0.008 0.992
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4761     0.5522 0.000 0.628 0.000 0.372
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4500     0.5013 0.316 0.000 0.684 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4697     0.6510 0.000 0.696 0.008 0.296
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0592     0.7546 0.984 0.000 0.000 0.016
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4522     0.5112 0.320 0.000 0.680 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0592     0.8686 0.016 0.984 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3074     0.7062 0.848 0.000 0.152 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0188     0.8744 0.000 0.996 0.000 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5698     0.3586 0.608 0.356 0.036 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.4888     0.2676 0.412 0.000 0.588 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0188     0.8744 0.000 0.996 0.000 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.4522     0.6252 0.000 0.680 0.000 0.320
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.6973     0.3273 0.000 0.556 0.300 0.144
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.4981    -0.1550 0.536 0.000 0.000 0.464
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0188     0.7900 0.004 0.000 0.000 0.996
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4972     0.1126 0.456 0.000 0.544 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2214     0.7413 0.928 0.000 0.028 0.044
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0657     0.7557 0.984 0.000 0.012 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.7541 1.000 0.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.1118     0.8531 0.036 0.000 0.964 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.2973     0.7366 0.856 0.000 0.144 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.4477     0.5234 0.312 0.000 0.688 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4989     0.3488 0.000 0.528 0.000 0.472
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.6776     0.5601 0.216 0.000 0.176 0.608
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.3311     0.7515 0.172 0.000 0.000 0.828
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0188     0.7879 0.000 0.004 0.000 0.996
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0921     0.7547 0.972 0.000 0.028 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.5432     0.6285 0.716 0.000 0.216 0.068
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.4679     0.2232 0.648 0.000 0.000 0.352
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.1022     0.8666 0.032 0.000 0.968 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4877     0.3397 0.000 0.408 0.592 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.6068    -0.1767 0.508 0.000 0.044 0.448
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4679     0.4165 0.648 0.000 0.352 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.5587     0.1102 0.600 0.000 0.028 0.372
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4713     0.4010 0.360 0.000 0.640 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.4564     0.4758 0.328 0.000 0.672 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.4585     0.6095 0.332 0.000 0.000 0.668
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.4164     0.5048 0.264 0.000 0.000 0.736
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4888     0.4841 0.000 0.588 0.000 0.412
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.1022     0.8666 0.032 0.000 0.968 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.4356     0.6579 0.000 0.708 0.000 0.292
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0336     0.7541 0.992 0.000 0.000 0.008
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3074     0.7856 0.000 0.848 0.000 0.152
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4  0.3400     0.7475 0.180 0.000 0.000 0.820
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0707     0.7527 0.980 0.000 0.000 0.020
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.4697     0.3889 0.356 0.000 0.644 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.1867     0.8489 0.072 0.000 0.928 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0921     0.8621 0.028 0.972 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.1302     0.7459 0.956 0.000 0.000 0.044
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.6113     0.5327 0.636 0.000 0.284 0.080
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#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4817     0.5271 0.000 0.612 0.000 0.388
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.4564     0.6151 0.000 0.672 0.000 0.328
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.4713     0.5717 0.000 0.640 0.000 0.360
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.1022     0.8599 0.000 0.968 0.032 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     4  0.4522     0.6220 0.320 0.000 0.000 0.680
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     4  0.3356     0.7498 0.176 0.000 0.000 0.824
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.2032     0.7466 0.936 0.000 0.036 0.028
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.2530     0.7130 0.888 0.000 0.000 0.112
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.0921     0.8665 0.028 0.000 0.972 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.4907     0.4702 0.000 0.580 0.000 0.420
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.3791     0.6966 0.200 0.796 0.004 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.3074     0.7062 0.848 0.000 0.152 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0707     0.7542 0.980 0.000 0.000 0.020
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.4948    -0.0897 0.560 0.000 0.000 0.440
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.4898     0.2173 0.000 0.584 0.416 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.2011     0.7439 0.920 0.000 0.080 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     4  0.4522     0.6220 0.320 0.000 0.000 0.680
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.1389     0.7445 0.952 0.000 0.000 0.048
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.2216     0.7241 0.908 0.000 0.000 0.092
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     4  0.4730     0.5658 0.364 0.000 0.000 0.636
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.0336     0.8652 0.008 0.000 0.992 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4  0.4817     0.4011 0.388 0.000 0.000 0.612
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.4948    -0.0897 0.560 0.000 0.000 0.440
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0188     0.8745 0.000 0.996 0.004 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4  0.3400     0.7475 0.180 0.000 0.000 0.820
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0592     0.8615 0.016 0.000 0.984 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3123     0.7602 0.156 0.000 0.844 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     4  0.3400     0.7477 0.180 0.000 0.000 0.820
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.3219     0.7121 0.164 0.000 0.836 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.6416     0.5587 0.648 0.200 0.152 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4  0.4522     0.6220 0.320 0.000 0.000 0.680
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.4877     0.4916 0.000 0.592 0.000 0.408
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.4866     0.2602 0.000 0.596 0.404 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.2281     0.7216 0.904 0.000 0.000 0.096
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0188     0.8745 0.000 0.996 0.004 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.1022     0.8666 0.032 0.000 0.968 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.4907     0.4456 0.420 0.000 0.000 0.580
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.4643     0.3317 0.656 0.000 0.000 0.344
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.2216     0.7986 0.092 0.000 0.908 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.4888     0.4841 0.000 0.588 0.000 0.412
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.5708     0.0226 0.556 0.000 0.028 0.416
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1389     0.8484 0.048 0.000 0.952 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4925     0.2169 0.572 0.000 0.428 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.4040     0.6973 0.248 0.000 0.000 0.752
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0336     0.8652 0.008 0.000 0.992 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     4  0.3266     0.7533 0.168 0.000 0.000 0.832
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4406     0.5084 0.700 0.000 0.300 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.3219     0.6955 0.836 0.000 0.164 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.1118     0.8660 0.036 0.000 0.964 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0188     0.8657 0.004 0.000 0.996 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.2345     0.7911 0.100 0.000 0.900 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0336     0.7560 0.992 0.000 0.008 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0921     0.7523 0.972 0.000 0.000 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4761     0.5537 0.000 0.628 0.000 0.372
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.3626     0.7086 0.000 0.004 0.812 0.184
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.4746     0.3928 0.632 0.000 0.368 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0921     0.8665 0.028 0.000 0.972 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1940     0.7346 0.924 0.000 0.000 0.076
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0469     0.8706 0.012 0.988 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0188     0.8745 0.000 0.996 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.4454     0.6363 0.308 0.000 0.000 0.692
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.4134     0.6119 0.740 0.000 0.260 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.1022     0.8666 0.032 0.000 0.968 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.4564     0.6145 0.328 0.000 0.000 0.672
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.0921     0.8548 0.028 0.000 0.972 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7599     0.2655 0.200 0.424 0.000 0.376
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.4564     0.6145 0.328 0.000 0.000 0.672
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.5404     0.5986 0.028 0.644 0.000 0.328
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.4564     0.6145 0.328 0.000 0.000 0.672
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.4543     0.6185 0.324 0.000 0.000 0.676
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0336     0.8652 0.008 0.000 0.992 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3219     0.6988 0.836 0.000 0.164 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4855     0.2966 0.600 0.000 0.400 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3801     0.5690 0.000 0.220 0.000 0.780
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.4820     0.6487 0.012 0.692 0.000 0.296
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.4996     0.1068 0.000 0.484 0.516 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.5364     0.6120 0.320 0.000 0.028 0.652
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.5423     0.5924 0.332 0.000 0.028 0.640
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0921     0.7509 0.972 0.000 0.028 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0921     0.8665 0.028 0.000 0.972 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.8058     0.3200 0.468 0.016 0.288 0.228
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3873     0.7234 0.000 0.772 0.000 0.228
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.3356     0.7498 0.176 0.000 0.000 0.824
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4585     0.6101 0.000 0.668 0.000 0.332
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.3688     0.7003 0.208 0.000 0.792 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.1211     0.7532 0.960 0.000 0.040 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3356     0.6860 0.824 0.000 0.176 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4500     0.5013 0.316 0.000 0.684 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.4250     0.6755 0.000 0.724 0.000 0.276
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0921     0.7509 0.972 0.000 0.028 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.1118     0.7511 0.964 0.000 0.036 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.5756     0.5215 0.372 0.000 0.036 0.592
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1716     0.7392 0.936 0.000 0.000 0.064
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000     0.7900 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.3942     0.5496 0.764 0.000 0.000 0.236
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.3764     0.6810 0.000 0.216 0.784 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0921     0.8665 0.028 0.000 0.972 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.8756 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.7541 1.000 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.0804     0.7835 0.008 0.000 0.012 0.980
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.7231     0.2272 0.192 0.000 0.540 0.268
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2408     0.7157 0.896 0.000 0.000 0.104

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4114   0.343929 0.376 0.624 0.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     5  0.4294  -0.087458 0.000 0.000 0.468 0.000 0.532
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.6710   0.359717 0.000 0.424 0.000 0.304 0.272
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.5504   0.114546 0.224 0.000 0.644 0.000 0.132
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     5  0.6518  -0.353327 0.000 0.376 0.008 0.152 0.464
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.4256  -0.383235 0.436 0.000 0.564 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     5  0.4443  -0.002555 0.004 0.000 0.472 0.000 0.524
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4599   0.203003 0.384 0.000 0.600 0.000 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.4114   0.343929 0.376 0.624 0.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.4201  -0.355891 0.408 0.000 0.592 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1121   0.639657 0.000 0.956 0.000 0.044 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.6613   0.224442 0.288 0.560 0.104 0.000 0.048
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0579   0.762593 0.008 0.000 0.008 0.984 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.5274   0.355340 0.132 0.000 0.676 0.000 0.192
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0963   0.642593 0.000 0.964 0.000 0.036 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.3715   0.519163 0.000 0.736 0.000 0.260 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000   0.652604 0.000 1.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.5713   0.232750 0.000 0.600 0.016 0.068 0.316
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1270   0.648016 0.000 0.948 0.000 0.000 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.5028   0.543315 0.400 0.000 0.036 0.564 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0162   0.652382 0.000 0.996 0.000 0.000 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.3209   0.747799 0.180 0.000 0.008 0.812 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.1965   0.590478 0.000 0.904 0.000 0.000 0.096
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5684  -0.206465 0.340 0.000 0.564 0.000 0.096
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#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.4706   0.696053 0.256 0.000 0.052 0.692 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.5484  -0.307326 0.392 0.000 0.540 0.000 0.068
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4227   0.165086 0.000 0.000 0.580 0.000 0.420
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.4924   0.673866 0.272 0.000 0.060 0.668 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     5  0.4549  -0.003918 0.008 0.000 0.464 0.000 0.528
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.7297  -0.079079 0.376 0.024 0.000 0.260 0.340
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.4777   0.685280 0.268 0.000 0.052 0.680 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.6884  -0.137574 0.376 0.360 0.000 0.260 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.4863   0.677631 0.272 0.000 0.056 0.672 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.4840   0.681763 0.268 0.000 0.056 0.676 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.4522   0.100014 0.008 0.000 0.552 0.000 0.440
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3577   0.439667 0.808 0.000 0.160 0.000 0.032
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.4723  -0.010642 0.536 0.000 0.448 0.000 0.016
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.4015   0.316693 0.000 0.348 0.000 0.652 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.6396   0.197513 0.376 0.452 0.000 0.172 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     5  0.3109  -0.037704 0.000 0.200 0.000 0.000 0.800
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.5566   0.704541 0.196 0.000 0.064 0.692 0.048
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.4885   0.676941 0.276 0.000 0.056 0.668 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3757   0.531579 0.772 0.000 0.208 0.000 0.020
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4297   0.171037 0.000 0.000 0.528 0.000 0.472
#> 79BA86D9-466F-48D7-B64B-F933B6995716     5  0.6427  -0.248752 0.152 0.000 0.392 0.004 0.452
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     5  0.6532  -0.354127 0.000 0.384 0.000 0.196 0.420
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.4325   0.725126 0.220 0.000 0.044 0.736 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3305   0.539912 0.000 0.776 0.000 0.224 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4367   0.137864 0.192 0.000 0.748 0.000 0.060
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.4300  -0.428190 0.476 0.000 0.524 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.4196   0.417597 0.768 0.024 0.192 0.000 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.5555   0.099799 0.232 0.000 0.636 0.000 0.132
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.5886   0.488437 0.000 0.600 0.000 0.224 0.176
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3942   0.534630 0.748 0.000 0.232 0.000 0.020
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3043   0.479224 0.864 0.000 0.080 0.000 0.056
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.6696   0.544358 0.232 0.000 0.128 0.584 0.056
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4310   0.543158 0.604 0.000 0.392 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000   0.761441 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4310   0.543158 0.604 0.000 0.392 0.004 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     5  0.6322   0.002370 0.000 0.156 0.408 0.000 0.436
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4300   0.166672 0.000 0.000 0.524 0.000 0.476
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000   0.652604 0.000 1.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4182   0.539571 0.600 0.000 0.400 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.5139   0.442928 0.000 0.000 0.060 0.624 0.316
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.7071   0.081990 0.032 0.000 0.444 0.168 0.356
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.4866   0.542729 0.580 0.000 0.392 0.028 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.3765    0.35081 0.000 0.000 0.000 0.000 0.596 0.404
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1584    0.80379 0.000 0.008 0.928 0.000 0.000 0.064
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.6035    0.17089 0.000 0.248 0.000 0.376 0.376 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.5679    0.50396 0.612 0.028 0.172 0.000 0.000 0.188
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000    0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3636    0.54825 0.676 0.000 0.004 0.000 0.000 0.320
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0363    0.80069 0.000 0.000 0.988 0.000 0.000 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     6  0.2805    0.36580 0.000 0.000 0.184 0.000 0.004 0.812
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0508    0.82322 0.000 0.004 0.000 0.000 0.984 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3650    0.58915 0.708 0.000 0.012 0.000 0.000 0.280
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.5453    0.40920 0.040 0.012 0.040 0.000 0.604 0.304
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1464    0.61802 0.016 0.004 0.000 0.944 0.000 0.036
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.6088    0.11486 0.296 0.000 0.392 0.000 0.000 0.312
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.4403    0.41257 0.000 0.028 0.000 0.408 0.564 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     5  0.6370    0.18227 0.000 0.016 0.328 0.244 0.412 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.3428    0.52842 0.000 0.304 0.000 0.000 0.696 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.5902    0.32713 0.304 0.000 0.000 0.184 0.008 0.504
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     5  0.0713    0.82396 0.000 0.028 0.000 0.000 0.972 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.4695    0.54763 0.232 0.000 0.000 0.684 0.012 0.072
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.0520    0.82528 0.000 0.008 0.008 0.000 0.984 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.5157    0.57801 0.692 0.056 0.084 0.000 0.000 0.168
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.5166    0.11931 0.528 0.000 0.060 0.000 0.012 0.400
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0458    0.64237 0.984 0.000 0.000 0.000 0.000 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1531    0.65115 0.928 0.000 0.004 0.000 0.000 0.068
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2697    0.68228 0.000 0.000 0.812 0.000 0.000 0.188
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     6  0.4695    0.27056 0.232 0.000 0.072 0.000 0.012 0.684
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.6073    0.12750 0.268 0.000 0.380 0.000 0.000 0.352
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.1511    0.61760 0.012 0.012 0.000 0.944 0.000 0.032
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3534    0.76102 0.076 0.800 0.000 0.124 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.6859    0.09506 0.024 0.000 0.328 0.368 0.012 0.268
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.5483    0.50292 0.280 0.000 0.000 0.584 0.012 0.124
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.3817    0.43021 0.568 0.000 0.000 0.000 0.000 0.432
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1700    0.62276 0.928 0.000 0.048 0.000 0.000 0.024
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0547    0.86508 0.000 0.980 0.000 0.000 0.020 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.5654    0.36949 0.304 0.000 0.000 0.160 0.004 0.532
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.2114    0.58260 0.012 0.076 0.000 0.904 0.000 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2454    0.78549 0.000 0.000 0.840 0.000 0.000 0.160
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4671    0.19491 0.000 0.000 0.532 0.044 0.424 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     6  0.6302    0.41830 0.104 0.000 0.184 0.116 0.004 0.592
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     6  0.6036    0.12294 0.300 0.076 0.064 0.000 0.004 0.556
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.6887    0.22364 0.180 0.000 0.080 0.212 0.012 0.516
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4582    0.60206 0.732 0.032 0.068 0.000 0.000 0.168
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     5  0.4853    0.54160 0.000 0.004 0.000 0.292 0.628 0.076
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.5693    0.50235 0.616 0.032 0.176 0.000 0.000 0.176
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.6061    0.38538 0.384 0.000 0.000 0.432 0.012 0.172
#> 311D089C-33F1-4722-9118-F56427C5C128     6  0.5898    0.10549 0.204 0.000 0.000 0.380 0.000 0.416
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0865    0.86090 0.000 0.964 0.000 0.000 0.036 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.3695    0.51663 0.000 0.624 0.000 0.376 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.5296    0.55185 0.184 0.000 0.600 0.000 0.000 0.216
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     5  0.2932    0.71997 0.000 0.016 0.000 0.164 0.820 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0632    0.64454 0.976 0.000 0.000 0.000 0.000 0.024
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.2482    0.79488 0.000 0.848 0.000 0.148 0.004 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     4  0.5839    0.44493 0.360 0.000 0.000 0.488 0.012 0.140
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0632    0.64454 0.976 0.000 0.000 0.000 0.000 0.024
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.4120    0.01452 0.004 0.000 0.524 0.000 0.004 0.468
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.3866    0.45235 0.000 0.000 0.516 0.000 0.000 0.484
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.3578    0.46862 0.000 0.000 0.000 0.000 0.660 0.340
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.3937   -0.16018 0.572 0.000 0.000 0.000 0.004 0.424
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0622    0.63307 0.980 0.000 0.008 0.000 0.000 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.6898    0.41604 0.284 0.000 0.056 0.468 0.012 0.180
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     5  0.3314    0.65129 0.000 0.004 0.000 0.256 0.740 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.4135    0.28539 0.008 0.584 0.000 0.000 0.004 0.404
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0713    0.86343 0.000 0.972 0.000 0.000 0.028 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     5  0.4338   -0.02068 0.000 0.000 0.484 0.020 0.496 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3875    0.75760 0.020 0.036 0.776 0.000 0.000 0.168
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.1588    0.80322 0.000 0.004 0.924 0.000 0.000 0.072
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.2883    0.66182 0.000 0.000 0.000 0.000 0.788 0.212
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0260    0.80144 0.008 0.000 0.992 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.3210    0.77759 0.000 0.036 0.812 0.000 0.000 0.152
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.2092    0.57218 0.876 0.124 0.000 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.0520    0.82528 0.000 0.008 0.008 0.000 0.984 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0547    0.62220 0.980 0.000 0.000 0.000 0.000 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0777    0.80552 0.000 0.004 0.972 0.000 0.000 0.024
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.5015    0.52212 0.284 0.000 0.000 0.628 0.012 0.076
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.5830    0.43545 0.372 0.000 0.000 0.480 0.012 0.136
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.1387    0.80430 0.000 0.000 0.932 0.000 0.000 0.068
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     4  0.7165    0.32218 0.316 0.000 0.060 0.396 0.012 0.216
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000    0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     6  0.7262    0.05025 0.204 0.000 0.080 0.284 0.012 0.420
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.5720    0.49591 0.612 0.032 0.184 0.000 0.000 0.172
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0777    0.61948 0.972 0.004 0.000 0.000 0.000 0.024
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#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.5864    0.39621 0.408 0.000 0.000 0.444 0.012 0.136
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3151    0.71288 0.000 0.000 0.748 0.000 0.000 0.252
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6  0.3409    0.43375 0.184 0.000 0.024 0.000 0.004 0.788
#> E678189F-D5CF-4C45-8E53-58ECB8448058     6  0.3344    0.38207 0.044 0.000 0.152 0.000 0.000 0.804
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.2730    0.44869 0.000 0.000 0.000 0.808 0.192 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.1686    0.79180 0.000 0.000 0.000 0.064 0.924 0.012
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0458    0.85658 0.000 0.984 0.016 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.7308    0.26984 0.232 0.000 0.076 0.404 0.012 0.276
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.6058    0.39044 0.380 0.000 0.000 0.436 0.012 0.172
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.4607    0.28875 0.356 0.000 0.028 0.000 0.012 0.604
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3210    0.77759 0.000 0.036 0.812 0.000 0.000 0.152
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.2697    0.72796 0.188 0.812 0.000 0.000 0.000 0.000
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#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.3778    0.59006 0.000 0.016 0.000 0.288 0.696 0.000
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#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3052    0.62593 0.780 0.000 0.004 0.000 0.000 0.216
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     6  0.2728    0.42234 0.032 0.000 0.004 0.000 0.100 0.864
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5721    0.49789 0.612 0.032 0.180 0.000 0.000 0.176
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#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     6  0.4189    0.25933 0.376 0.000 0.020 0.000 0.000 0.604
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     6  0.3172    0.50084 0.092 0.000 0.076 0.000 0.000 0.832
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.7075    0.13893 0.176 0.000 0.084 0.252 0.012 0.476
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0547    0.62220 0.980 0.000 0.000 0.000 0.000 0.020
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000    0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000    0.63513 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.2871    0.70169 0.000 0.000 0.804 0.000 0.192 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3054    0.78401 0.000 0.036 0.828 0.000 0.000 0.136
#> A0C429D9-0638-4873-BFB4-00056AB4719F     5  0.0458    0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.1204    0.64802 0.944 0.000 0.000 0.000 0.000 0.056
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.6092    0.03535 0.092 0.484 0.000 0.384 0.012 0.028
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5161    0.40648 0.000 0.000 0.640 0.112 0.012 0.236
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0547    0.62220 0.980 0.000 0.000 0.000 0.000 0.020

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 17541 rows and 500 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 0.456           0.784       0.894         0.4754 0.526   0.526
#> 3 3 0.442           0.706       0.814         0.3016 0.843   0.710
#> 4 4 0.505           0.581       0.789         0.1539 0.759   0.474
#> 5 5 0.634           0.582       0.791         0.0707 0.897   0.670
#> 6 6 0.609           0.440       0.694         0.0429 0.855   0.532

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.7219     0.6800 0.200 0.800
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.7219     0.7498 0.800 0.200
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.5842     0.8170 0.140 0.860
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.9608     0.5597 0.616 0.384
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.9710     0.5296 0.600 0.400
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.8615 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.2423     0.8761 0.040 0.960
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.8615 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.6247     0.8025 0.156 0.844
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.6438     0.7728 0.836 0.164
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.9661     0.5453 0.608 0.392
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.8615 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.8977 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.7299     0.7456 0.796 0.204
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6623     0.7692 0.828 0.172
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5946     0.7882 0.856 0.144
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.7139     0.7522 0.804 0.196
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.7453     0.6589 0.212 0.788
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.9850     0.4681 0.572 0.428
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.8977 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000     0.8977 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.8977 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8615 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.8977 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1633     0.8562 0.976 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.8977 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0376     0.8609 0.996 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000     0.8615 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.8615 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.8615 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6887     0.7537 0.816 0.184
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.8977 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.9608     0.5597 0.616 0.384
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.8615 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000     0.8615 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.6973     0.7585 0.812 0.188
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.2423     0.8522 0.960 0.040
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0672     0.8601 0.992 0.008
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1184     0.8581 0.984 0.016
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.9608     0.5597 0.616 0.384
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.8615 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1843     0.8553 0.972 0.028
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.8977 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.8615 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.6712     0.7658 0.824 0.176
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.6247     0.7800 0.844 0.156
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000     0.8977 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.4298     0.8313 0.912 0.088
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.8661     0.5459 0.712 0.288
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.9988    -0.1972 0.480 0.520
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.8615 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000     0.8615 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.9732     0.5217 0.596 0.404
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000     0.8615 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.8615 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.3114     0.8426 0.944 0.056
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8977 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.9608     0.5597 0.616 0.384
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.7139     0.7434 0.804 0.196
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.9608     0.5597 0.616 0.384
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0000     0.8615 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.8977 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.8016     0.7038 0.756 0.244
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000     0.8615 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     2  0.9988     0.0616 0.480 0.520
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.7139     0.7434 0.804 0.196
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.8977 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.8615 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0000     0.8615 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.8615 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     1  0.9661     0.5453 0.608 0.392
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.9552     0.5047 0.624 0.376
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.8977 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.8977 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.8081     0.7033 0.248 0.752
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.9608     0.5597 0.616 0.384
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.6973     0.7717 0.188 0.812
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9661     0.1704 0.392 0.608
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.7056     0.7652 0.192 0.808
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.7528     0.7270 0.784 0.216
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.2043     0.8536 0.968 0.032
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.8977 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0000     0.8615 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.4431     0.8512 0.092 0.908
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.1184     0.8579 0.984 0.016
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.8977 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.8615 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.6623     0.7881 0.172 0.828
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0000     0.8615 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.8977 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000     0.8615 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.4690     0.7958 0.900 0.100
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0000     0.8615 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.8977 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.8615 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.9710     0.5297 0.600 0.400
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.8977 0.000 1.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.8977 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.7299     0.7475 0.796 0.204
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.8977 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0000     0.8615 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.8615 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.4431     0.8512 0.092 0.908
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.8977 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0000     0.8615 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  1.0000     0.1167 0.504 0.496
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.2423     0.8760 0.040 0.960
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0000     0.8615 1.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000     0.8977 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000     0.8615 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.9552     0.5714 0.624 0.376
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.9686     0.5360 0.604 0.396
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000     0.8977 0.000 1.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.0000     0.8615 1.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     1  0.9608     0.5597 0.616 0.384
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.8977 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0000     0.8615 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000     0.8977 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.6438     0.7953 0.164 0.836
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0000     0.8615 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.4690     0.8137 0.900 0.100
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000     0.8615 1.000 0.000
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#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.9881     0.4447 0.564 0.436
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.8615 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.8615 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.6623     0.7875 0.172 0.828
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.5408     0.8296 0.124 0.876
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.7139     0.6871 0.196 0.804
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0672     0.8601 0.992 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.9608     0.5597 0.616 0.384
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.8615 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.8615 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.8615 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0938     0.8574 0.988 0.012
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.8977 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.8615 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.8615 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.8615 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.8615 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.9608     0.5597 0.616 0.384
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.8615 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.8977 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.5737     0.8205 0.136 0.864
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.8977 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.8615 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.9491     0.5812 0.632 0.368
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4298     0.8281 0.912 0.088
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.8615 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5216     0.5957 0.260 0.740 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.4399     0.8267 0.000 0.188 0.812
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.5558     0.7498 0.152 0.800 0.048
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.9206     0.4885 0.524 0.288 0.188
#> BE685EF3-953B-483C-A99C-75FBF81D6615     3  0.8717     0.5402 0.220 0.188 0.592
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.7435 1.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.1411     0.8133 0.036 0.964 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3038     0.7651 0.896 0.000 0.104
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.5442     0.7570 0.132 0.812 0.056
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.2173     0.7381 0.944 0.008 0.048
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.6865     0.5413 0.596 0.384 0.020
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.7435 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0592     0.8294 0.000 0.988 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.6808     0.7565 0.732 0.084 0.184
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.3028     0.7716 0.032 0.048 0.920
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0424     0.7423 0.992 0.008 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.4399     0.8267 0.000 0.188 0.812
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.5268     0.5845 0.212 0.776 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     3  0.4399     0.8267 0.000 0.188 0.812
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.8373 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.8478     0.5497 0.204 0.180 0.616
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.6252    -0.0696 0.000 0.556 0.444
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.5591     0.7259 0.696 0.000 0.304
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.8373 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.1753     0.7523 0.048 0.000 0.952
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.8373 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0661     0.7458 0.988 0.004 0.008
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.6297     0.7215 0.640 0.008 0.352
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3619     0.7696 0.864 0.000 0.136
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3686     0.7632 0.860 0.000 0.140
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6677     0.6934 0.740 0.180 0.080
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.8373 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.4399     0.8267 0.000 0.188 0.812
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.1964     0.7431 0.944 0.000 0.056
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1753     0.7397 0.952 0.000 0.048
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.8824     0.5477 0.572 0.168 0.260
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.6284     0.7254 0.680 0.016 0.304
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.7826     0.7237 0.612 0.076 0.312
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.1753     0.7521 0.048 0.000 0.952
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4399     0.8267 0.000 0.188 0.812
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.1964     0.7431 0.944 0.000 0.056
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.7412     0.7420 0.700 0.124 0.176
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.8373 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     3  0.2711     0.7213 0.088 0.000 0.912
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.4629     0.8254 0.004 0.188 0.808
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0592     0.7412 0.988 0.012 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.3116     0.7958 0.108 0.892 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.8605     0.6828 0.604 0.208 0.188
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.5016     0.4682 0.760 0.240 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.9710     0.1208 0.408 0.220 0.372
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.5650     0.7389 0.688 0.000 0.312
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000     0.7435 1.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.4399     0.8267 0.000 0.188 0.812
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0000     0.7435 1.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.5591     0.7259 0.696 0.000 0.304
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.6008     0.6729 0.628 0.000 0.372
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8373 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.8688     0.5657 0.596 0.196 0.208
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.0424     0.7423 0.992 0.008 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.8681     0.5619 0.596 0.188 0.216
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.3551     0.7637 0.868 0.000 0.132
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.8373 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.8137     0.6837 0.640 0.220 0.140
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.5291     0.7431 0.732 0.000 0.268
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     2  0.9306    -0.0253 0.336 0.488 0.176
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.2173     0.7381 0.944 0.008 0.048
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.0000     0.8373 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5497     0.7323 0.708 0.000 0.292
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3686     0.7632 0.860 0.000 0.140
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.6111     0.6895 0.604 0.000 0.396
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.4555     0.8168 0.000 0.200 0.800
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.7858     0.4958 0.572 0.364 0.064
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.8373 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.8373 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.6286     0.4626 0.464 0.536 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.4399     0.8267 0.000 0.188 0.812
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.5678     0.6480 0.316 0.684 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6314     0.1045 0.392 0.604 0.004
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.5371     0.7000 0.048 0.812 0.140
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.3340     0.7101 0.880 0.120 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.7500     0.7238 0.696 0.164 0.140
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.8373 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.5591     0.7259 0.696 0.000 0.304
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.5371     0.7562 0.140 0.812 0.048
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.1753     0.7542 0.048 0.000 0.952
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.8373 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.6111     0.6895 0.604 0.000 0.396
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.6523     0.6925 0.228 0.724 0.048
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.7782     0.7423 0.652 0.100 0.248
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.8373 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.4399     0.7629 0.812 0.000 0.188
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.2625     0.6888 0.916 0.084 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.5591     0.7259 0.696 0.000 0.304
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0424     0.8320 0.000 0.992 0.008
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.4654     0.7619 0.792 0.000 0.208
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.6168     0.5124 0.588 0.412 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.8373 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.8373 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.4399     0.8267 0.000 0.188 0.812
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.8373 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.5650     0.7389 0.688 0.000 0.312
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.5291     0.7547 0.732 0.000 0.268
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.1964     0.8129 0.056 0.944 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.8373 0.000 1.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.4887     0.7555 0.772 0.000 0.228
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.8561     0.2172 0.484 0.420 0.096
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.5254     0.6289 0.000 0.264 0.736
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0000     0.7435 1.000 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000     0.8373 0.000 1.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     3  0.1860     0.7518 0.052 0.000 0.948
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.6498     0.5324 0.596 0.396 0.008
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.8275     0.5714 0.596 0.296 0.108
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000     0.8373 0.000 1.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.0000     0.7435 1.000 0.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     3  0.4399     0.8267 0.000 0.188 0.812
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.8373 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0000     0.7435 1.000 0.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000     0.8373 0.000 1.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.5442     0.7570 0.132 0.812 0.056
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.5591     0.7259 0.696 0.000 0.304
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.9061     0.6245 0.548 0.264 0.188
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     3  0.3192     0.6270 0.112 0.000 0.888
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.4062     0.6362 0.000 0.836 0.164
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.1753     0.7397 0.952 0.000 0.048
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.4750     0.7308 0.216 0.784 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     3  0.1964     0.7950 0.000 0.056 0.944
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     1  0.8255     0.6161 0.636 0.196 0.168
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.0000     0.7435 1.000 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.5706     0.7378 0.680 0.000 0.320
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.5905     0.5746 0.000 0.352 0.648
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0000     0.7435 1.000 0.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.1643     0.8032 0.000 0.956 0.044
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.8206    -0.2293 0.448 0.480 0.072
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.0237     0.7431 0.996 0.004 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.4842     0.7548 0.776 0.000 0.224
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.6481     0.6958 0.224 0.728 0.048
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     3  0.4399     0.8267 0.000 0.188 0.812
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.0000     0.8373 0.000 1.000 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.5815     0.7257 0.692 0.004 0.304
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#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2173     0.7381 0.944 0.008 0.048
#> 1122039D-5785-4F70-9916-17C585453512     3  0.4399     0.8267 0.000 0.188 0.812
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.3551     0.7661 0.868 0.000 0.132
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1753     0.7397 0.952 0.000 0.048
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.4399     0.8267 0.000 0.188 0.812
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.6345     0.5272 0.596 0.400 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.8373 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.7388     0.7074 0.600 0.044 0.356
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.2066     0.7972 0.000 0.060 0.940
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.5621     0.7263 0.692 0.000 0.308
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.5254     0.7562 0.736 0.000 0.264
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.5650     0.6513 0.312 0.688 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.5981     0.6825 0.080 0.788 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4504     0.6198 0.196 0.804 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.6111     0.6895 0.604 0.000 0.396
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.8685     0.5640 0.596 0.192 0.212
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.1753     0.7397 0.952 0.000 0.048
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3482     0.7641 0.872 0.000 0.128
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.1753     0.7397 0.952 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0000     0.7435 1.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.4235     0.6201 0.000 0.824 0.176
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.5058     0.7609 0.756 0.000 0.244
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4399     0.7629 0.812 0.000 0.188
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.7388     0.7462 0.692 0.100 0.208
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4842     0.7548 0.776 0.000 0.224
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.4399     0.8267 0.000 0.188 0.812
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.5591     0.7259 0.696 0.000 0.304
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.8373 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.6481     0.6958 0.224 0.728 0.048
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.8373 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3551     0.7637 0.868 0.000 0.132
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6140     0.5234 0.596 0.404 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.8681     0.6771 0.596 0.216 0.188
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5591     0.7259 0.696 0.000 0.304

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5310    0.41947 0.012 0.576 0.412 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.4277    0.60391 0.000 0.720 0.280 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5311    0.30700 0.392 0.004 0.008 0.596
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.6616    0.54016 0.220 0.156 0.000 0.624
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4830    0.56649 0.392 0.000 0.608 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.3052    0.73872 0.136 0.860 0.004 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0921    0.71650 0.972 0.000 0.028 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.5198    0.62493 0.040 0.708 0.252 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1389    0.56554 0.048 0.000 0.952 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.6969    0.42298 0.192 0.584 0.224 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4977   -0.34362 0.540 0.000 0.460 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1302    0.79417 0.000 0.956 0.000 0.044
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5109    0.58411 0.744 0.060 0.196 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1389    0.77598 0.048 0.000 0.000 0.952
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.4222    0.57928 0.272 0.000 0.728 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.6065    0.56520 0.216 0.688 0.008 0.088
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.4746    0.67303 0.000 0.056 0.168 0.776
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.6621    0.42063 0.000 0.140 0.244 0.616
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.4679    0.40830 0.000 0.648 0.000 0.352
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.4267    0.60650 0.788 0.000 0.188 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.4103    0.59466 0.256 0.000 0.000 0.744
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.1302    0.79296 0.000 0.956 0.044 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2611    0.71374 0.896 0.000 0.096 0.008
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.5290    0.19968 0.404 0.000 0.584 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3486    0.60474 0.812 0.000 0.188 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6353    0.44591 0.652 0.140 0.208 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4643    0.34799 0.656 0.000 0.344 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.4605    0.52996 0.336 0.000 0.664 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4916    0.22828 0.424 0.000 0.000 0.576
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.2949    0.69285 0.888 0.088 0.000 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.2773    0.70705 0.880 0.004 0.116 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.4981    0.19685 0.464 0.000 0.000 0.536
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4193    0.51869 0.732 0.000 0.268 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0188    0.72871 0.996 0.000 0.004 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.6994    0.33049 0.560 0.000 0.288 0.152
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.3099    0.74136 0.020 0.104 0.000 0.876
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3837    0.59791 0.224 0.000 0.776 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.2973    0.72959 0.000 0.856 0.144 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3758    0.68982 0.848 0.048 0.104 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.4194    0.49492 0.228 0.008 0.764 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     4  0.9459    0.29400 0.236 0.284 0.112 0.368
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.4948   -0.28484 0.560 0.000 0.440 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.3356    0.69076 0.000 0.176 0.000 0.824
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0469    0.72931 0.988 0.000 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.6162    0.55442 0.676 0.000 0.168 0.156
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.7894   -0.03708 0.372 0.332 0.000 0.296
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     4  0.7060    0.18044 0.400 0.124 0.000 0.476
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.4356    0.24595 0.708 0.000 0.292 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1211    0.79328 0.040 0.960 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3751    0.57330 0.800 0.196 0.000 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0895    0.72695 0.976 0.000 0.004 0.020
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.7900   -0.13157 0.344 0.296 0.360 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.3266    0.58595 0.168 0.000 0.832 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.4331    0.58914 0.000 0.712 0.288 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5198    0.49766 0.688 0.008 0.288 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0000    0.72730 1.000 0.000 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.3649    0.66285 0.000 0.204 0.000 0.796
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     3  0.7734    0.02541 0.160 0.372 0.456 0.012
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.1722    0.79136 0.008 0.944 0.048 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.6769    0.58457 0.172 0.220 0.608 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.6495    0.50692 0.108 0.284 0.608 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6769    0.45907 0.172 0.608 0.220 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.5619    0.55552 0.268 0.676 0.056 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.5805    0.55925 0.388 0.036 0.576 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0188    0.72728 0.996 0.000 0.000 0.004
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0657    0.80324 0.012 0.984 0.004 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0817    0.72793 0.976 0.000 0.000 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.4220    0.64184 0.004 0.748 0.248 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.0707    0.78657 0.020 0.000 0.000 0.980
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.2647    0.69744 0.880 0.000 0.000 0.120
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4564    0.42449 0.000 0.328 0.672 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0707    0.72775 0.980 0.000 0.000 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.1211    0.79463 0.000 0.960 0.000 0.040
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.1389    0.72810 0.952 0.000 0.048 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     2  0.6324    0.46816 0.076 0.584 0.340 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2473    0.77741 0.012 0.908 0.000 0.080
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.3266    0.69845 0.000 0.832 0.168 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.2149    0.71814 0.912 0.000 0.088 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.1940    0.77459 0.076 0.924 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.1389    0.79173 0.000 0.952 0.048 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0336    0.72966 0.992 0.000 0.008 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.7120   -0.14919 0.136 0.368 0.496 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.1004    0.77926 0.004 0.024 0.000 0.972
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     4  0.6136    0.57665 0.080 0.000 0.288 0.632
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.7154    0.03048 0.432 0.436 0.000 0.132
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.6228    0.29880 0.364 0.572 0.000 0.064
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     3  0.3569    0.57630 0.196 0.000 0.804 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     4  0.3796    0.73296 0.000 0.096 0.056 0.848
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     3  0.3074    0.56203 0.152 0.000 0.848 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.5256    0.61209 0.040 0.700 0.260 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.4883    0.49885 0.696 0.000 0.288 0.016
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#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.7246    0.07380 0.408 0.448 0.000 0.144
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.4948    0.34143 0.440 0.000 0.560 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4222    0.59478 0.728 0.000 0.272 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.3569    0.64539 0.804 0.000 0.000 0.196
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4605    0.52996 0.336 0.000 0.664 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.6292    0.20639 0.548 0.396 0.052 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.3400    0.58892 0.180 0.000 0.820 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4690    0.57059 0.276 0.012 0.712 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.4277    0.48866 0.280 0.000 0.720 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.2704    0.59687 0.124 0.000 0.876 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.4420    0.64761 0.012 0.748 0.240 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.1610    0.73011 0.952 0.016 0.032 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0000    0.72730 1.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.7461    0.13357 0.004 0.492 0.164 0.340
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.3110    0.76552 0.056 0.892 0.048 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.4804    0.20600 0.384 0.000 0.616 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.5698    0.41227 0.036 0.356 0.608 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0592    0.72709 0.984 0.000 0.000 0.016
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.6769    0.42228 0.000 0.608 0.172 0.220
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.80436 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1022    0.72979 0.968 0.000 0.000 0.032
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.4948    0.53598 0.440 0.000 0.560 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4605    0.52996 0.336 0.000 0.664 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2611    0.71374 0.896 0.000 0.096 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.1356    0.72411 0.960 0.032 0.008 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.8062    0.41534 0.072 0.536 0.288 0.104
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.2089    0.72735 0.932 0.000 0.020 0.048
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.6576    0.57510 0.000 0.200 0.168 0.632
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.2882    0.71079 0.892 0.000 0.024 0.084
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000    0.72730 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.4888    0.40154 0.412 0.000 0.588 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4643    0.44488 0.656 0.000 0.344 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.3311    0.58419 0.172 0.000 0.828 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.2469    0.73807 0.000 0.108 0.000 0.892
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.8379    0.33264 0.252 0.500 0.200 0.048
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.2002    0.79017 0.020 0.936 0.044 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.2593    0.71074 0.892 0.004 0.104 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0804    0.73116 0.980 0.000 0.008 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.6466    0.50133 0.104 0.288 0.608 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.4313    0.61296 0.260 0.736 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3751    0.63953 0.196 0.800 0.000 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2647    0.69744 0.880 0.000 0.000 0.120
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.9019    0.37553 0.224 0.128 0.168 0.480
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4605    0.52996 0.336 0.000 0.664 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.4406    0.21281 0.700 0.000 0.300 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.3311    0.58419 0.172 0.000 0.828 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.4830    0.56649 0.392 0.000 0.608 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1867    0.78239 0.000 0.928 0.000 0.072
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4103    0.61209 0.744 0.000 0.256 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.4222    0.59478 0.728 0.000 0.272 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.2408    0.71158 0.896 0.000 0.104 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0188    0.72728 0.996 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000    0.79195 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0817    0.72793 0.976 0.000 0.000 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2928    0.76796 0.012 0.880 0.108 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4761    0.38056 0.000 0.372 0.628 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1302    0.79359 0.000 0.956 0.044 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4948    0.06546 0.560 0.000 0.440 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6503    0.04861 0.480 0.448 0.072 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4285    0.66593 0.820 0.076 0.104 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0592    0.72709 0.984 0.000 0.000 0.016

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.3264     0.4608 0.004 0.132 0.024 0.000 0.840
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.4009     0.5400 0.000 0.684 0.312 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.4273     0.0884 0.448 0.000 0.000 0.552 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     4  0.6788     0.3771 0.192 0.136 0.000 0.596 0.076
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1386     0.8448 0.016 0.000 0.952 0.000 0.032
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.3038     0.6979 0.040 0.872 0.080 0.000 0.008
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.1836     0.7004 0.932 0.000 0.036 0.000 0.032
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.4470     0.6727 0.052 0.796 0.100 0.000 0.052
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.1399     0.8459 0.028 0.000 0.952 0.000 0.020
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.6074    -0.0784 0.440 0.104 0.004 0.000 0.452
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5014     0.1937 0.536 0.000 0.432 0.000 0.032
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.3772     0.6996 0.000 0.792 0.000 0.036 0.172
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5930     0.5173 0.676 0.064 0.084 0.000 0.176
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.1557     0.7521 0.052 0.000 0.000 0.940 0.008
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.2074     0.8482 0.044 0.000 0.920 0.000 0.036
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.7323     0.2776 0.208 0.476 0.000 0.048 0.268
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.1661     0.7521 0.000 0.036 0.000 0.940 0.024
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.4403     0.4913 0.000 0.560 0.004 0.000 0.436
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.6660     0.3601 0.000 0.060 0.156 0.604 0.180
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.6745     0.1689 0.000 0.408 0.000 0.280 0.312
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.4448    -0.2027 0.516 0.000 0.000 0.004 0.480
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1410     0.7526 0.000 0.940 0.000 0.000 0.060
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.4270     0.3832 0.320 0.000 0.000 0.668 0.012
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.5221     0.5253 0.000 0.552 0.048 0.000 0.400
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.2278     0.8426 0.060 0.000 0.908 0.000 0.032
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1557     0.7024 0.940 0.000 0.008 0.000 0.052
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.5123     0.4046 0.336 0.000 0.616 0.004 0.044
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.1121     0.7038 0.956 0.000 0.000 0.000 0.044
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6007     0.5211 0.672 0.128 0.148 0.000 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.4256     0.4936 0.000 0.564 0.000 0.000 0.436
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4823     0.4652 0.672 0.000 0.276 0.000 0.052
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.1907     0.8472 0.028 0.000 0.928 0.000 0.044
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4305    -0.0450 0.488 0.000 0.000 0.512 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.3078     0.6526 0.848 0.132 0.000 0.004 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.1095     0.7108 0.968 0.008 0.012 0.000 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.4297     0.1543 0.472 0.000 0.000 0.528 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.4429     0.5623 0.744 0.000 0.192 0.000 0.064
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2077     0.7034 0.920 0.040 0.000 0.000 0.040
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1341     0.7472 0.000 0.944 0.000 0.000 0.056
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.4747    -0.2217 0.500 0.000 0.000 0.016 0.484
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.2416     0.7083 0.012 0.100 0.000 0.888 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0290     0.8415 0.008 0.000 0.992 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.4841     0.6848 0.000 0.708 0.084 0.000 0.208
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3881     0.6364 0.812 0.128 0.008 0.000 0.052
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.3845     0.7430 0.124 0.004 0.812 0.000 0.060
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     1  0.7927    -0.0403 0.380 0.184 0.000 0.100 0.336
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1557     0.7024 0.940 0.000 0.008 0.000 0.052
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4100     0.6704 0.192 0.000 0.764 0.000 0.044
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.2707     0.6915 0.000 0.100 0.000 0.876 0.024
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.2209     0.8442 0.056 0.000 0.912 0.000 0.032
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0404     0.7071 0.988 0.000 0.000 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2519     0.6628 0.884 0.000 0.000 0.100 0.016
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2329     0.7321 0.000 0.876 0.000 0.000 0.124
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.6858     0.2273 0.476 0.248 0.000 0.264 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.1907     0.8503 0.044 0.000 0.928 0.000 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     1  0.7685     0.2026 0.468 0.124 0.000 0.276 0.132
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.5102     0.3298 0.376 0.000 0.580 0.000 0.044
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1251     0.7399 0.036 0.956 0.000 0.000 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3480     0.5443 0.752 0.248 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.1282     0.7035 0.952 0.000 0.000 0.004 0.044
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.5165     0.2029 0.512 0.448 0.000 0.000 0.040
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.1493     0.8450 0.028 0.000 0.948 0.000 0.024
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.2848     0.4216 0.000 0.156 0.004 0.000 0.840
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.4264     0.4484 0.732 0.008 0.012 0.004 0.244
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.1043     0.7046 0.960 0.000 0.000 0.000 0.040
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0693     0.7087 0.980 0.000 0.008 0.000 0.012
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.5002     0.4970 0.000 0.132 0.000 0.708 0.160
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     5  0.6469     0.3676 0.064 0.320 0.052 0.004 0.560
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.7434 0.000 1.000 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.4780     0.6696 0.000 0.692 0.060 0.000 0.248
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0798     0.8436 0.008 0.000 0.976 0.000 0.016
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0771     0.8436 0.004 0.000 0.976 0.000 0.020
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.6499     0.1416 0.364 0.464 0.004 0.000 0.168
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#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.1331     0.7110 0.952 0.000 0.008 0.000 0.040
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.1117     0.8468 0.020 0.000 0.964 0.000 0.016
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.0963     0.7049 0.964 0.000 0.000 0.000 0.036
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.4264     0.5429 0.000 0.620 0.000 0.004 0.376
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.5077     0.5221 0.692 0.240 0.016 0.000 0.052
#> 34ED910C-7470-4552-8561-D01D59190521     5  0.6413     0.3418 0.224 0.000 0.268 0.000 0.508
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.3835     0.6963 0.032 0.836 0.076 0.000 0.056
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     5  0.5162     0.3440 0.000 0.152 0.004 0.140 0.704
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.2891     0.7119 0.000 0.824 0.000 0.000 0.176
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.5052     0.5849 0.024 0.696 0.240 0.000 0.040
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4908    -0.0139 0.416 0.560 0.000 0.004 0.020
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     1  0.6210     0.2367 0.484 0.388 0.000 0.004 0.124
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0290     0.7434 0.000 0.992 0.000 0.008 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     4  0.4632     0.0613 0.448 0.012 0.000 0.540 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.4402     0.3272 0.004 0.620 0.372 0.000 0.004
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.1041     0.7055 0.964 0.000 0.000 0.004 0.032
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     4  0.0510     0.7814 0.016 0.000 0.000 0.984 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.5937     0.4958 0.664 0.084 0.200 0.000 0.052
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.1124     0.7050 0.960 0.000 0.000 0.004 0.036
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.0324     0.8381 0.000 0.004 0.992 0.000 0.004
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.2139     0.7304 0.052 0.916 0.000 0.032 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     5  0.4651     0.1123 0.008 0.428 0.004 0.000 0.560
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.3327     0.7212 0.028 0.828 0.000 0.000 0.144
#> 80936433-AA91-4219-98F1-706C36298060     2  0.3242     0.6937 0.000 0.784 0.000 0.000 0.216
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.5853    -0.0245 0.432 0.000 0.472 0.000 0.096
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.1121     0.7038 0.956 0.000 0.000 0.000 0.044
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.4827    -0.2072 0.504 0.000 0.000 0.020 0.476
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.4125     0.7223 0.008 0.780 0.040 0.000 0.172
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.3536     0.7391 0.156 0.000 0.812 0.000 0.032
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0609     0.7061 0.980 0.000 0.000 0.000 0.020
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.3461     0.5090 0.772 0.000 0.000 0.004 0.224
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0566     0.7097 0.984 0.000 0.000 0.004 0.012
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0960     0.7093 0.972 0.000 0.008 0.004 0.016
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.5419     0.3777 0.588 0.008 0.352 0.000 0.052
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.6215    -0.1404 0.108 0.428 0.456 0.000 0.008
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.2629     0.6601 0.880 0.004 0.000 0.104 0.012
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.4978    -0.2221 0.496 0.000 0.000 0.028 0.476
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1410     0.7456 0.000 0.940 0.000 0.000 0.060
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0404     0.7071 0.988 0.000 0.000 0.000 0.012
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.5149     0.5322 0.692 0.232 0.016 0.000 0.060
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.1485     0.8467 0.020 0.000 0.948 0.000 0.032
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0566     0.7083 0.984 0.004 0.000 0.012 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.5468     0.3851 0.568 0.368 0.004 0.000 0.060
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.7426     0.3286 0.496 0.268 0.084 0.000 0.152
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0404     0.7071 0.988 0.000 0.000 0.000 0.012
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.3579     0.4847 0.240 0.756 0.000 0.004 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.4306    -0.0639 0.492 0.000 0.000 0.508 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.1430     0.7392 0.000 0.944 0.052 0.000 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0794     0.7408 0.028 0.972 0.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.1282     0.7035 0.952 0.000 0.000 0.004 0.044
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0794     0.7408 0.028 0.972 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.1403     0.8455 0.024 0.000 0.952 0.000 0.024
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.4288     0.6788 0.044 0.800 0.120 0.000 0.036
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     5  0.5998    -0.0187 0.112 0.000 0.000 0.424 0.464
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.2424     0.7291 0.000 0.868 0.000 0.000 0.132
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0963     0.7051 0.964 0.000 0.000 0.000 0.036
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.4532     0.4747 0.672 0.304 0.004 0.000 0.020
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.4793     0.4801 0.000 0.544 0.020 0.000 0.436
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.6527     0.2797 0.488 0.392 0.000 0.076 0.044
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0898     0.7079 0.972 0.000 0.008 0.000 0.020
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.2570     0.8033 0.084 0.000 0.888 0.000 0.028
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.1774     0.7016 0.932 0.000 0.016 0.000 0.052
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2230     0.6637 0.884 0.000 0.000 0.116 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1671     0.7439 0.000 0.924 0.000 0.000 0.076
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.3837     0.6138 0.000 0.692 0.000 0.000 0.308
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1493     0.8448 0.028 0.000 0.948 0.000 0.024
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.4688     0.4067 0.616 0.364 0.004 0.000 0.016
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.1753     0.8492 0.032 0.000 0.936 0.000 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0290     0.8390 0.000 0.000 0.992 0.000 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.5668     0.2054 0.504 0.000 0.416 0.000 0.080
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.1493     0.8450 0.028 0.000 0.948 0.000 0.024
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.3602     0.6656 0.000 0.796 0.180 0.000 0.024
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.2172     0.7046 0.916 0.004 0.020 0.000 0.060
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.2278     0.8426 0.060 0.000 0.908 0.000 0.032
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.1608     0.7074 0.928 0.000 0.000 0.000 0.072
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     4  0.5869     0.0890 0.004 0.428 0.000 0.484 0.084
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.2125     0.7301 0.052 0.920 0.000 0.004 0.024
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.5188     0.3957 0.328 0.000 0.612 0.000 0.060
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0566     0.8369 0.000 0.012 0.984 0.000 0.004
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1282     0.7035 0.952 0.000 0.000 0.004 0.044
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.6037     0.3122 0.000 0.444 0.000 0.116 0.440
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.7434 0.000 1.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0404     0.7071 0.988 0.000 0.000 0.000 0.012
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.2221     0.8454 0.052 0.000 0.912 0.000 0.036
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.1582     0.8435 0.028 0.000 0.944 0.000 0.028
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0898     0.7079 0.972 0.000 0.008 0.000 0.020
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.3157     0.6887 0.872 0.052 0.016 0.000 0.060
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6814     0.0508 0.188 0.520 0.000 0.024 0.268
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0912     0.7057 0.972 0.000 0.000 0.016 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.6015     0.2351 0.000 0.124 0.000 0.516 0.360
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0566     0.7081 0.984 0.000 0.000 0.012 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0703     0.7062 0.976 0.000 0.000 0.000 0.024
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.5351     0.1541 0.484 0.000 0.464 0.000 0.052
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.5227     0.2433 0.448 0.000 0.044 0.000 0.508
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.2054     0.8303 0.028 0.000 0.920 0.000 0.052
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.2074     0.7061 0.000 0.104 0.000 0.896 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.6412     0.2704 0.492 0.384 0.004 0.012 0.108
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.1043     0.7408 0.000 0.960 0.040 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.1717     0.7021 0.936 0.004 0.008 0.000 0.052
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0510     0.7077 0.984 0.000 0.000 0.000 0.016
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1082     0.7091 0.964 0.000 0.008 0.000 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0324     0.8398 0.004 0.000 0.992 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.3182     0.6723 0.124 0.844 0.000 0.000 0.032
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2929     0.5824 0.180 0.820 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0609     0.7069 0.980 0.000 0.000 0.020 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.7345     0.2031 0.472 0.076 0.000 0.320 0.132
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1668     0.8464 0.028 0.000 0.940 0.000 0.032
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.5080     0.3470 0.368 0.000 0.588 0.000 0.044
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.2304     0.8334 0.044 0.000 0.908 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1485     0.8451 0.020 0.000 0.948 0.000 0.032
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3692     0.7057 0.000 0.812 0.000 0.052 0.136
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0992     0.7082 0.968 0.000 0.008 0.000 0.024
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.1557     0.7024 0.940 0.000 0.008 0.000 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1557     0.7024 0.940 0.000 0.008 0.000 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2179     0.6578 0.888 0.000 0.000 0.000 0.112
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000     0.7886 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0865     0.7089 0.972 0.000 0.000 0.004 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.2494     0.7409 0.008 0.904 0.056 0.000 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0324     0.8381 0.000 0.004 0.992 0.000 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1544     0.7477 0.000 0.932 0.000 0.000 0.068
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.5529     0.2072 0.420 0.000 0.512 0.000 0.068
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5042     0.2677 0.512 0.460 0.004 0.000 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3345     0.6757 0.864 0.060 0.024 0.000 0.052
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1282     0.7035 0.952 0.000 0.000 0.004 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.2592   0.295108 0.000 0.116 0.004 0.000 0.864 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.5403   0.244270 0.000 0.124 0.516 0.000 0.000 0.360
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.4185   0.168569 0.496 0.012 0.000 0.492 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.4949   0.005558 0.000 0.696 0.000 0.196 0.052 0.056
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3830   0.546730 0.004 0.000 0.620 0.000 0.000 0.376
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4629   0.595265 0.028 0.596 0.012 0.000 0.000 0.364
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2730   0.639815 0.808 0.000 0.000 0.000 0.000 0.192
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6143  -0.186787 0.276 0.120 0.548 0.000 0.000 0.056
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.5445   0.596686 0.124 0.000 0.548 0.000 0.004 0.324
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#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.4717   0.597771 0.032 0.584 0.000 0.000 0.012 0.372
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.2854   0.622801 0.792 0.000 0.000 0.000 0.000 0.208
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.4002   0.614595 0.008 0.588 0.000 0.000 0.000 0.404
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.4918   0.591122 0.088 0.000 0.604 0.000 0.000 0.308
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.6322  -0.172356 0.276 0.124 0.532 0.000 0.000 0.068
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.6560   0.233974 0.104 0.000 0.000 0.408 0.404 0.084
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.4395   0.621726 0.000 0.568 0.000 0.000 0.028 0.404
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.2300   0.636044 0.856 0.000 0.000 0.000 0.000 0.144
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.3155   0.641302 0.840 0.068 0.004 0.000 0.000 0.088
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.3765   0.552191 0.000 0.404 0.000 0.000 0.596 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.6545   0.373573 0.532 0.296 0.000 0.092 0.044 0.036
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.2053   0.643578 0.888 0.000 0.004 0.000 0.000 0.108
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.5354   0.571160 0.160 0.000 0.580 0.000 0.000 0.260
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.3592   0.553261 0.656 0.000 0.344 0.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.2837   0.639375 0.856 0.000 0.000 0.088 0.000 0.056
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.4395   0.621726 0.000 0.568 0.000 0.000 0.028 0.404
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.5742   0.531138 0.000 0.432 0.000 0.000 0.168 0.400
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.5214   0.593276 0.120 0.000 0.576 0.000 0.000 0.304
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.2250   0.649591 0.888 0.092 0.020 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.5713   0.579045 0.172 0.000 0.476 0.000 0.000 0.352
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.2730   0.471893 0.000 0.000 0.808 0.000 0.000 0.192
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.5232   0.453393 0.536 0.000 0.360 0.000 0.000 0.104
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.4461   0.532187 0.104 0.000 0.704 0.000 0.000 0.192
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.6729  -0.099207 0.188 0.140 0.528 0.000 0.000 0.144
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4032   0.508834 0.572 0.000 0.420 0.000 0.000 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.5633   0.558926 0.148 0.000 0.440 0.000 0.000 0.412
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.4498   0.568563 0.644 0.000 0.300 0.000 0.000 0.056
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5438   0.537742 0.000 0.492 0.000 0.068 0.020 0.420
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.5495   0.129402 0.472 0.448 0.036 0.000 0.004 0.040
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5958  -0.169166 0.396 0.000 0.384 0.000 0.000 0.220
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.4696   0.484103 0.000 0.056 0.588 0.000 0.000 0.356
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.2941   0.619405 0.780 0.000 0.000 0.000 0.000 0.220
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.3765   0.552191 0.000 0.404 0.000 0.000 0.596 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.3765   0.616762 0.000 0.596 0.000 0.000 0.000 0.404
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1957   0.642815 0.888 0.000 0.000 0.000 0.000 0.112
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.5838   0.569005 0.192 0.000 0.440 0.000 0.000 0.368
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4932   0.562185 0.128 0.000 0.644 0.000 0.000 0.228
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.2053   0.643578 0.888 0.000 0.004 0.000 0.000 0.108
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.4002   0.522497 0.588 0.000 0.404 0.000 0.000 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.7442   0.003810 0.356 0.360 0.000 0.036 0.192 0.056
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.2053   0.642796 0.888 0.000 0.000 0.004 0.000 0.108
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.5536  -0.152656 0.000 0.572 0.000 0.324 0.048 0.056
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0603   0.660239 0.980 0.000 0.000 0.004 0.000 0.016
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.2092   0.639416 0.876 0.000 0.000 0.000 0.000 0.124
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3995  -0.416737 0.480 0.000 0.516 0.000 0.000 0.004
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.6120   0.043953 0.384 0.000 0.008 0.000 0.404 0.204
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.3168   0.343809 0.172 0.000 0.804 0.000 0.000 0.024
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.3797   0.477909 0.000 0.292 0.000 0.692 0.000 0.016
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.5885  -0.044359 0.192 0.624 0.132 0.008 0.044 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.4018   0.610369 0.000 0.580 0.008 0.000 0.000 0.412
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.3499   0.566882 0.680 0.000 0.320 0.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1910   0.642760 0.892 0.000 0.000 0.000 0.000 0.108
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2948   0.661621 0.848 0.000 0.060 0.000 0.000 0.092
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3515   0.538196 0.000 0.000 0.676 0.000 0.000 0.324
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4827   0.410710 0.620 0.296 0.000 0.000 0.000 0.084
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4587   0.592065 0.048 0.596 0.000 0.000 0.000 0.356
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1349   0.652890 0.940 0.000 0.000 0.004 0.000 0.056
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.7078  -0.189454 0.144 0.548 0.000 0.180 0.072 0.056
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.5451   0.595779 0.140 0.000 0.532 0.000 0.000 0.328
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.5807  -0.062589 0.440 0.000 0.376 0.000 0.000 0.184
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.4641   0.407381 0.200 0.000 0.684 0.000 0.000 0.116
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3930   0.533771 0.004 0.000 0.576 0.000 0.000 0.420
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.4395   0.142962 0.068 0.788 0.000 0.016 0.072 0.056
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2489   0.646666 0.860 0.000 0.012 0.000 0.000 0.128
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3835   0.561994 0.668 0.000 0.320 0.000 0.000 0.012
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3499   0.566882 0.680 0.000 0.320 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.2980   0.612946 0.800 0.000 0.000 0.000 0.008 0.192
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000   0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1814   0.655646 0.900 0.000 0.000 0.000 0.000 0.100
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.7391   0.138886 0.132 0.480 0.212 0.000 0.024 0.152
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3563   0.532334 0.000 0.000 0.664 0.000 0.000 0.336
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2527   0.134952 0.000 0.832 0.000 0.000 0.168 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5744   0.046239 0.476 0.000 0.344 0.000 0.000 0.180
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4500   0.333651 0.572 0.392 0.036 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.3804   0.507483 0.576 0.000 0.424 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.2854   0.622801 0.792 0.000 0.000 0.000 0.000 0.208

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 17541 rows and 500 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 0.980           0.948       0.969          0.480 0.521   0.521
#> 3 3 0.617           0.666       0.841          0.245 0.902   0.813
#> 4 4 0.486           0.532       0.741          0.134 0.838   0.646
#> 5 5 0.496           0.367       0.670          0.083 0.884   0.681
#> 6 6 0.559           0.347       0.681          0.073 0.799   0.423

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.5629     0.8642 0.132 0.868
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.0938     0.9695 0.012 0.988
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.0672     0.9747 0.992 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.3114     0.9389 0.056 0.944
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0938     0.9695 0.012 0.988
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0938     0.9714 0.988 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4161     0.9149 0.084 0.916
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0376     0.9749 0.996 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0672     0.9747 0.992 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0672     0.9747 0.992 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.1414     0.9711 0.020 0.980
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#> 985FEEC2-9737-4018-80DF-21A07AB47900     1  0.0672     0.9747 0.992 0.008
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  0.0672     0.9747 0.992 0.008
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.0938     0.9742 0.988 0.012
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.1414     0.9711 0.020 0.980
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.1414     0.9711 0.020 0.980
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     1  0.0672     0.9738 0.992 0.008
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.1414     0.9711 0.020 0.980
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     1  0.0938     0.9714 0.988 0.012
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0938     0.9728 0.988 0.012
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.1414     0.9711 0.020 0.980
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0938     0.9742 0.988 0.012
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     1  0.0938     0.9714 0.988 0.012
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.1414     0.9698 0.980 0.020
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.1414     0.9711 0.020 0.980
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.0672     0.9747 0.992 0.008
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.0938     0.9735 0.988 0.012
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     1  0.0672     0.9747 0.992 0.008
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.0938     0.9695 0.012 0.988
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.1414     0.9711 0.020 0.980
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.1184     0.9666 0.016 0.984
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     1  0.0672     0.9747 0.992 0.008
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.4431     0.9028 0.092 0.908
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.1184     0.9705 0.016 0.984
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.1184     0.9679 0.016 0.984
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.0672     0.9647 0.008 0.992
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.1184     0.9666 0.016 0.984
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.1414     0.9698 0.980 0.020
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.1414     0.9721 0.980 0.020
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.0672     0.9747 0.992 0.008
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.1633     0.9693 0.976 0.024
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.0938     0.9714 0.988 0.012
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.1184     0.9705 0.016 0.984
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.1184     0.9666 0.016 0.984
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1414     0.9711 0.020 0.980
#> 80936433-AA91-4219-98F1-706C36298060     2  0.1414     0.9711 0.020 0.980
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     2  0.0938     0.9695 0.012 0.988
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0938     0.9735 0.988 0.012
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.1184     0.9710 0.984 0.016
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.1414     0.9721 0.980 0.020
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.1414     0.9711 0.020 0.980
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0672     0.9747 0.992 0.008
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.1414     0.9698 0.980 0.020
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.1184     0.9710 0.984 0.016
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.1633     0.9693 0.976 0.024
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0938     0.9742 0.988 0.012
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.0672     0.9747 0.992 0.008
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.0672     0.9747 0.992 0.008
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.0938     0.9695 0.012 0.988
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.9491     0.4349 0.368 0.632
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.1414     0.9721 0.980 0.020
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.1184     0.9666 0.016 0.984
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0938     0.9728 0.988 0.012
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0000     0.9745 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.0938     0.9714 0.988 0.012
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.1414     0.9721 0.980 0.020
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0672     0.9747 0.992 0.008
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0938     0.9735 0.988 0.012
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0938     0.9728 0.988 0.012
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0672     0.9647 0.008 0.992
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.6438     0.8157 0.164 0.836
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.1184     0.9666 0.016 0.984
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.1414     0.9711 0.020 0.980
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.1414     0.9698 0.980 0.020
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.1184     0.9666 0.016 0.984
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.0672     0.9747 0.992 0.008
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1  0.0672     0.9747 0.992 0.008
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.1414     0.9721 0.980 0.020
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.1184     0.9666 0.016 0.984
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.0938     0.9695 0.012 0.988
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.1414     0.9698 0.980 0.020
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0672     0.9728 0.992 0.008
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.1414     0.9711 0.020 0.980
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0938     0.9695 0.012 0.988
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.1184     0.9729 0.984 0.016
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0672     0.9747 0.992 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0938     0.9742 0.988 0.012
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1414     0.9721 0.980 0.020
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1843     0.9702 0.028 0.972
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.1414     0.9711 0.020 0.980
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.0938     0.9695 0.012 0.988
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0672     0.9747 0.992 0.008
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0672     0.9738 0.992 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0672     0.9747 0.992 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3     1  0.0672     0.9747 0.992 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0672     0.9747 0.992 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0672     0.9747 0.992 0.008
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     1  0.0672     0.9747 0.992 0.008
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.9745 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0938     0.9714 0.988 0.012
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0376     0.9749 0.996 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0672     0.9647 0.008 0.992
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.1184     0.9712 0.984 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0672     0.9747 0.992 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.4161     0.9096 0.916 0.084
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1184     0.9710 0.984 0.016
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1414     0.9711 0.020 0.980
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1184     0.9666 0.016 0.984
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1414     0.9698 0.980 0.020
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0938     0.9714 0.988 0.012
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0672     0.9747 0.992 0.008
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.1184     0.9729 0.984 0.016
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0672     0.9747 0.992 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.1184     0.9697 0.016 0.984
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.3584     0.9274 0.068 0.932
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.0938     0.9695 0.012 0.988
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1184     0.9729 0.984 0.016
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0938     0.9667 0.012 0.988
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.1184     0.9729 0.984 0.016
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0938     0.9728 0.988 0.012
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0672     0.9747 0.992 0.008
#> 1122039D-5785-4F70-9916-17C585453512     2  0.1414     0.9690 0.020 0.980
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0376     0.9739 0.996 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0672     0.9747 0.992 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0938     0.9695 0.012 0.988
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.1414     0.9711 0.020 0.980
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.3114     0.9414 0.056 0.944
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0938     0.9742 0.988 0.012
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.1184     0.9697 0.016 0.984
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.1184     0.9729 0.984 0.016
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0938     0.9742 0.988 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0938     0.9714 0.988 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1184     0.9710 0.984 0.016
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1414     0.9708 0.020 0.980
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1414     0.9721 0.980 0.020
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0938     0.9695 0.012 0.988
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0672     0.9747 0.992 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0938     0.9714 0.988 0.012
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0672     0.9747 0.992 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0938     0.9714 0.988 0.012
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1184     0.9705 0.016 0.984
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0938     0.9742 0.988 0.012
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0672     0.9747 0.992 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0938     0.9742 0.988 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1414     0.9698 0.980 0.020
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0938     0.9695 0.012 0.988
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1414     0.9698 0.980 0.020
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.1414     0.9711 0.020 0.980
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.6531     0.7993 0.832 0.168
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1414     0.9711 0.020 0.980
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0938     0.9714 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0672     0.9747 0.992 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0938     0.9742 0.988 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1414     0.9698 0.980 0.020

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.2774   0.826048 0.072 0.920 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.6309  -0.159321 0.500 0.500 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3619   0.797254 0.136 0.000 0.864
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.6824   0.134828 0.576 0.408 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1529   0.852464 0.040 0.960 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0424   0.836314 0.008 0.000 0.992
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.9421   0.425633 0.436 0.388 0.176
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.0424   0.834898 0.008 0.000 0.992
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.2066   0.827073 0.060 0.000 0.940
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.2448   0.830292 0.076 0.000 0.924
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.2356   0.831813 0.072 0.928 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0424   0.834898 0.008 0.000 0.992
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0237   0.868166 0.004 0.996 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.5538   0.740921 0.132 0.060 0.808
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.8058   0.464346 0.640 0.236 0.124
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0000   0.835249 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.6309   0.138053 0.500 0.500 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0237   0.867987 0.004 0.996 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2537   0.823900 0.080 0.920 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0424   0.867239 0.008 0.992 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000   0.868795 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000   0.868795 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     3  0.3192   0.804499 0.112 0.000 0.888
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000   0.868795 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.4974   0.413303 0.764 0.000 0.236
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0424   0.867239 0.008 0.992 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.6111   0.450571 0.396 0.000 0.604
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.3038   0.805619 0.104 0.000 0.896
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#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.0000   0.868795 0.000 1.000 0.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     3  0.0237   0.835239 0.004 0.000 0.996
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.0424   0.867239 0.008 0.992 0.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.0000   0.868795 0.000 1.000 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     3  0.7517   0.297724 0.420 0.040 0.540
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     3  0.5621   0.601968 0.308 0.000 0.692
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.0000   0.868795 0.000 1.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     3  0.5178   0.672292 0.256 0.000 0.744
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     3  0.1964   0.822825 0.056 0.000 0.944
#> 985FEEC2-9737-4018-80DF-21A07AB47900     3  0.1031   0.832108 0.024 0.000 0.976
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     3  0.2448   0.820498 0.076 0.000 0.924
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     3  0.3340   0.796880 0.120 0.000 0.880
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.0237   0.867987 0.004 0.996 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.0424   0.867239 0.008 0.992 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     3  0.4178   0.757833 0.172 0.000 0.828
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.2356   0.831451 0.072 0.928 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     3  0.3686   0.799795 0.140 0.000 0.860
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     3  0.6309   0.174813 0.496 0.000 0.504
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.0424   0.867239 0.008 0.992 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110     3  0.0424   0.834898 0.008 0.000 0.992
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     3  0.1411   0.828602 0.036 0.000 0.964
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     3  0.1411   0.834342 0.036 0.000 0.964
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.0237   0.868166 0.004 0.996 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     3  0.1753   0.826787 0.048 0.000 0.952
#> 34ED910C-7470-4552-8561-D01D59190521     3  0.2066   0.824540 0.060 0.000 0.940
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     3  0.8574   0.121861 0.432 0.096 0.472
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.6309  -0.159321 0.500 0.500 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     2  0.2448   0.831200 0.076 0.924 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0000   0.868795 0.000 1.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.1753   0.822895 0.048 0.000 0.952
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.8582  -0.269507 0.452 0.452 0.096
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.4589   0.657795 0.172 0.820 0.008
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0424   0.866113 0.008 0.992 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.6379   0.389451 0.368 0.624 0.008
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.5098   0.522322 0.248 0.752 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     3  0.3879   0.777842 0.152 0.000 0.848
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     3  0.6215   0.332962 0.428 0.000 0.572
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     3  0.2165   0.823049 0.064 0.000 0.936
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     3  0.6267   0.334173 0.452 0.000 0.548
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.2261   0.828453 0.068 0.000 0.932
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0000   0.868795 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.2261   0.831626 0.068 0.932 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0424   0.867239 0.008 0.992 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0424   0.867239 0.008 0.992 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.6309  -0.159321 0.500 0.500 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.3715   0.791084 0.128 0.004 0.868
#> D85CB054-7F54-4383-96C0-6C99761B84E7     3  0.0424   0.834898 0.008 0.000 0.992
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     3  0.3267   0.802098 0.116 0.000 0.884
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0000   0.868795 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.0424   0.834898 0.008 0.000 0.992
#> 17CA5D73-4384-4645-83F8-587847043DD2     3  0.5327   0.587254 0.272 0.000 0.728
#> 40467950-A95C-4731-AD93-0A128442C837     3  0.2356   0.822832 0.072 0.000 0.928
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     3  0.4931   0.716062 0.212 0.004 0.784
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     3  0.3879   0.774702 0.152 0.000 0.848
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1860   0.820989 0.052 0.000 0.948
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.1753   0.822895 0.048 0.000 0.952
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.6309  -0.159321 0.500 0.500 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.9159   0.448263 0.508 0.328 0.164
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     3  0.2959   0.809967 0.100 0.000 0.900
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000   0.868795 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     3  0.6274   0.304699 0.456 0.000 0.544
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0892   0.833159 0.020 0.000 0.980
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0747   0.833807 0.016 0.000 0.984
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.6302  -0.127655 0.520 0.000 0.480
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.3116   0.812070 0.108 0.000 0.892
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.8743  -0.000782 0.440 0.108 0.452
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.0747   0.835643 0.016 0.000 0.984
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.2625   0.821059 0.084 0.916 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.6266   0.515152 0.768 0.076 0.156
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0237   0.867443 0.004 0.996 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000   0.868795 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.5327   0.655762 0.272 0.000 0.728
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.1529   0.840666 0.040 0.960 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.1031   0.832108 0.024 0.000 0.976
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.2261   0.825481 0.068 0.000 0.932
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     3  0.4931   0.703505 0.232 0.000 0.768
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000   0.868795 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.6309   0.138053 0.500 0.500 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.0747   0.835643 0.016 0.000 0.984
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.4702   0.720676 0.212 0.000 0.788
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0424   0.867239 0.008 0.992 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0892   0.862021 0.020 0.980 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.0000   0.835249 0.000 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1289   0.829838 0.032 0.000 0.968
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.1163   0.837893 0.028 0.000 0.972
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.6286  -0.084116 0.536 0.000 0.464
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000   0.868795 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0237   0.868166 0.004 0.996 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.6309  -0.159321 0.500 0.500 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1753   0.822895 0.048 0.000 0.952
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.5529   0.618456 0.296 0.000 0.704
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.0592   0.836635 0.012 0.000 0.988
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1753   0.822895 0.048 0.000 0.952
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.1860   0.827653 0.052 0.000 0.948
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.1529   0.826919 0.040 0.000 0.960
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.7672   0.215089 0.468 0.044 0.488
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.1411   0.828263 0.036 0.000 0.964
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.0424   0.834898 0.008 0.000 0.992
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0424   0.834898 0.008 0.000 0.992
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.2448   0.826739 0.076 0.924 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.9560   0.338302 0.464 0.212 0.324
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.0892   0.835365 0.020 0.000 0.980
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.7744   0.219574 0.448 0.048 0.504
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.2711   0.817771 0.088 0.000 0.912
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1643   0.853220 0.044 0.956 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000   0.868795 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     3  0.5905   0.455347 0.352 0.000 0.648
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0592   0.835405 0.012 0.000 0.988
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.1289   0.829602 0.032 0.000 0.968
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     3  0.2959   0.789464 0.100 0.000 0.900
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.0424   0.834820 0.008 0.000 0.992
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.2537   0.823900 0.080 0.920 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.3983   0.372019 0.852 0.144 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.6307  -0.139059 0.512 0.488 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.4750   0.679219 0.216 0.000 0.784
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.2537   0.823900 0.080 0.920 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     3  0.2796   0.815185 0.092 0.000 0.908
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.0592   0.834994 0.012 0.000 0.988
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.1643   0.825018 0.044 0.000 0.956
#> 1122039D-5785-4F70-9916-17C585453512     2  0.6309   0.138053 0.500 0.500 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.1753   0.829053 0.048 0.000 0.952
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.0892   0.833431 0.020 0.000 0.980
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.4702   0.654339 0.212 0.788 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0892   0.861204 0.020 0.980 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.8820  -0.271142 0.408 0.476 0.116
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.2796   0.811650 0.092 0.000 0.908
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.6309   0.138053 0.500 0.500 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.0000   0.835249 0.000 0.000 1.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3  0.0424   0.834898 0.008 0.000 0.992
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1753   0.826201 0.048 0.000 0.952
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.6386   0.409608 0.412 0.004 0.584
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000   0.868795 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.6244   0.301478 0.440 0.000 0.560
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2066   0.839266 0.060 0.940 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0747   0.833807 0.016 0.000 0.984
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.0424   0.834898 0.008 0.000 0.992
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.1753   0.831104 0.048 0.000 0.952
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1031   0.837569 0.024 0.000 0.976
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000   0.868795 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.0424   0.834898 0.008 0.000 0.992
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.0747   0.835832 0.016 0.000 0.984
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.0892   0.833595 0.020 0.000 0.980
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.0892   0.835533 0.020 0.000 0.980
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.6309  -0.159321 0.500 0.500 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0592   0.835405 0.012 0.000 0.988
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4810   0.660591 0.140 0.832 0.028
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.7759   0.175865 0.476 0.048 0.476
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000   0.868795 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.0747   0.835582 0.016 0.000 0.984
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.6244   0.357141 0.440 0.000 0.560
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.1753   0.822895 0.048 0.000 0.952
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.4399   0.746296 0.188 0.000 0.812

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.4284    0.60373 0.224 0.764 0.000 0.012
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.4134    0.92109 0.000 0.260 0.000 0.740
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4795    0.43059 0.292 0.000 0.696 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.8732   -0.29268 0.384 0.316 0.040 0.260
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2081    0.78149 0.000 0.916 0.000 0.084
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3958    0.59433 0.160 0.000 0.816 0.024
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.8371    0.09272 0.456 0.360 0.072 0.112
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#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.2174    0.80548 0.020 0.928 0.000 0.052
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     3  0.6229    0.05862 0.416 0.000 0.528 0.056
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.5590    0.28754 0.456 0.000 0.524 0.020
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.1733    0.60480 0.024 0.000 0.948 0.028
#> 1122039D-5785-4F70-9916-17C585453512     4  0.4477    0.88188 0.000 0.312 0.000 0.688
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     3  0.5602    0.35883 0.408 0.000 0.568 0.024
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.1488    0.60824 0.012 0.000 0.956 0.032
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3074    0.68312 0.000 0.848 0.000 0.152
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0804    0.82811 0.012 0.980 0.000 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.8877    0.10463 0.412 0.356 0.100 0.132
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.5163   -0.03814 0.480 0.000 0.516 0.004
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.4304    0.90922 0.000 0.284 0.000 0.716
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.4720    0.43663 0.324 0.000 0.672 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3  0.3545    0.59023 0.164 0.000 0.828 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.4035    0.58997 0.176 0.000 0.804 0.020
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5097    0.23332 0.568 0.000 0.428 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0469    0.82684 0.012 0.988 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.7059    0.39187 0.528 0.000 0.332 0.140
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.1576    0.81094 0.004 0.948 0.000 0.048
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1211    0.63126 0.040 0.000 0.960 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.4642    0.56780 0.240 0.000 0.740 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.3606    0.56797 0.132 0.000 0.844 0.024
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.3991    0.58790 0.172 0.000 0.808 0.020
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0707    0.82400 0.000 0.980 0.000 0.020
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.2976    0.61158 0.120 0.000 0.872 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.3659    0.60619 0.136 0.000 0.840 0.024
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.4833    0.50653 0.228 0.000 0.740 0.032
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.5250    0.52211 0.316 0.000 0.660 0.024
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4164    0.92058 0.000 0.264 0.000 0.736
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.5036    0.54968 0.280 0.000 0.696 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5564    0.51608 0.232 0.712 0.012 0.044
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.6767    0.40835 0.548 0.080 0.364 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1059    0.82904 0.012 0.972 0.000 0.016
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.5137    0.52737 0.296 0.000 0.680 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4621    0.44836 0.708 0.008 0.284 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4963    0.43738 0.284 0.000 0.696 0.020
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5650    0.08447 0.544 0.000 0.432 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.5877   -0.04961 0.016 0.348 0.000 0.072 0.564
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.5779    0.45590 0.148 0.000 0.628 0.004 0.220
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5809    0.41738 0.280 0.028 0.044 0.636 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.6396    0.18659 0.000 0.452 0.000 0.376 0.172
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.4748    0.48526 0.300 0.000 0.660 0.000 0.040
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.5375   -0.01306 0.380 0.568 0.008 0.000 0.044
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.3967    0.53540 0.264 0.000 0.724 0.000 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3994    0.48962 0.040 0.000 0.772 0.000 0.188
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.5265    0.33967 0.248 0.000 0.656 0.000 0.096
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.5694    0.05466 0.000 0.460 0.000 0.080 0.460
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.4451    0.46630 0.340 0.000 0.644 0.000 0.016
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.5684    0.17043 0.000 0.488 0.000 0.080 0.432
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.4552    0.18664 0.352 0.004 0.632 0.000 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.7277    0.00588 0.464 0.176 0.000 0.312 0.048
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.3319    0.58178 0.160 0.000 0.820 0.000 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.5684    0.17043 0.000 0.488 0.000 0.080 0.432
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.6658    0.17774 0.000 0.444 0.000 0.264 0.292
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.5680    0.15528 0.000 0.492 0.000 0.080 0.428
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.3538    0.41290 0.020 0.848 0.000 0.044 0.088
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.5192    0.31441 0.000 0.644 0.000 0.076 0.280
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2426    0.53884 0.900 0.000 0.064 0.000 0.036
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.4373    0.39688 0.000 0.760 0.000 0.080 0.160
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3656    0.54790 0.844 0.000 0.024 0.080 0.052
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.5203    0.33409 0.000 0.648 0.000 0.080 0.272
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.5474    0.20397 0.576 0.000 0.348 0.000 0.076
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4449    0.16899 0.512 0.000 0.484 0.000 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4815   -0.06165 0.524 0.000 0.456 0.000 0.020
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     3  0.4435    0.47406 0.336 0.000 0.648 0.000 0.016
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2674    0.54548 0.012 0.000 0.868 0.000 0.120
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.5684    0.16692 0.000 0.488 0.000 0.080 0.432
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.1753    0.58192 0.032 0.000 0.936 0.000 0.032
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.2561    0.59500 0.096 0.000 0.884 0.000 0.020
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.7504    0.11110 0.188 0.292 0.000 0.456 0.064
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.3663    0.44822 0.776 0.208 0.000 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.4288    0.14926 0.384 0.000 0.612 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3549    0.54817 0.852 0.000 0.032 0.076 0.040
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.2583    0.74520 0.000 0.004 0.000 0.864 0.132
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.3421    0.48602 0.204 0.000 0.788 0.000 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4276    0.18479 0.616 0.000 0.380 0.000 0.004
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.41902 0.000 1.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.3496    0.52555 0.788 0.000 0.012 0.000 0.200
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.7034   -0.13760 0.368 0.332 0.000 0.292 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.4527    0.56089 0.204 0.000 0.732 0.000 0.064
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.5203    0.33409 0.000 0.648 0.000 0.080 0.272
#> 066B10C1-777F-4863-ACCA-6684310B913E     3  0.4367    0.07481 0.416 0.000 0.580 0.000 0.004
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.5616    0.12187 0.552 0.000 0.364 0.000 0.084
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.5828    0.18641 0.000 0.520 0.000 0.100 0.380
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3  0.3863    0.45162 0.200 0.000 0.772 0.000 0.028
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4437    0.48072 0.316 0.000 0.664 0.000 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.5715    0.21620 0.000 0.524 0.000 0.088 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.5126    0.46936 0.300 0.000 0.636 0.000 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.6032    0.08511 0.476 0.000 0.436 0.072 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2366    0.55749 0.908 0.004 0.016 0.004 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.4233    0.36967 0.000 0.748 0.000 0.044 0.208
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.6363    0.17702 0.000 0.444 0.000 0.392 0.164
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.4342    0.53981 0.232 0.000 0.728 0.000 0.040
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.6024    0.16191 0.000 0.472 0.000 0.116 0.412
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.4829    0.17187 0.484 0.000 0.496 0.000 0.020
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.5354    0.35091 0.000 0.664 0.000 0.128 0.208
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.2139    0.55304 0.916 0.000 0.052 0.000 0.032
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.4649    0.11828 0.580 0.000 0.404 0.000 0.016
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4697    0.19030 0.592 0.000 0.388 0.000 0.020
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     3  0.3055    0.57537 0.072 0.000 0.864 0.000 0.064
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.5689    0.09726 0.000 0.480 0.000 0.080 0.440
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.3530    0.52600 0.784 0.000 0.012 0.000 0.204
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.4387    0.46538 0.348 0.000 0.640 0.000 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.6017   -0.15443 0.436 0.000 0.480 0.064 0.020
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.5718    0.18456 0.000 0.496 0.000 0.084 0.420
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.6608   -0.05240 0.276 0.492 0.004 0.000 0.228
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.3471    0.41858 0.000 0.836 0.000 0.072 0.092
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.5203    0.33409 0.000 0.648 0.000 0.080 0.272
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.6587    0.36023 0.332 0.024 0.528 0.004 0.112
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.5551    0.48261 0.284 0.000 0.612 0.000 0.104
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.8875   -0.18412 0.332 0.348 0.144 0.056 0.120
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.4823    0.49318 0.316 0.000 0.644 0.000 0.040
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     1  0.6377    0.00951 0.484 0.000 0.336 0.000 0.180
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.3988    0.40801 0.732 0.000 0.252 0.000 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.5203    0.33409 0.000 0.648 0.000 0.080 0.272
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1943    0.54974 0.924 0.000 0.056 0.000 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.6626    0.06224 0.332 0.000 0.464 0.004 0.200
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.3516    0.54325 0.836 0.000 0.004 0.108 0.052
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0404    0.41659 0.000 0.988 0.000 0.000 0.012
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.5330    0.44041 0.668 0.000 0.248 0.072 0.012
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4054    0.50707 0.036 0.000 0.760 0.000 0.204
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.3845    0.50448 0.208 0.000 0.768 0.000 0.024
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0609    0.41162 0.000 0.980 0.000 0.000 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3  0.2054    0.58093 0.052 0.000 0.920 0.000 0.028
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.4603    0.48895 0.300 0.000 0.668 0.000 0.032
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.3419    0.48453 0.804 0.000 0.180 0.000 0.016
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.5680    0.17393 0.000 0.492 0.000 0.080 0.428
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.2193    0.58713 0.092 0.000 0.900 0.000 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.5691   -0.14970 0.000 0.444 0.000 0.080 0.476
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.5805    0.32376 0.000 0.612 0.000 0.172 0.216
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.5693    0.08678 0.000 0.468 0.000 0.080 0.452
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.5181    0.34046 0.000 0.652 0.000 0.080 0.268
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3  0.3650    0.49420 0.176 0.000 0.796 0.000 0.028
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     3  0.3690    0.52660 0.200 0.000 0.780 0.000 0.020
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.5854    0.29569 0.596 0.012 0.300 0.000 0.092
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.5158    0.33985 0.000 0.656 0.000 0.080 0.264
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.3231    0.53600 0.196 0.000 0.800 0.000 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.6630    0.07916 0.316 0.000 0.472 0.004 0.208
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.6568    0.23278 0.496 0.000 0.336 0.012 0.156
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.4213    0.49018 0.308 0.000 0.680 0.000 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.5680    0.17393 0.000 0.492 0.000 0.080 0.428
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.5822    0.41522 0.640 0.012 0.000 0.132 0.216
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#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.2763    0.51152 0.848 0.000 0.148 0.000 0.004
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.4283    0.37109 0.644 0.000 0.348 0.000 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.3282    0.49418 0.008 0.000 0.804 0.000 0.188
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.3123    0.49853 0.004 0.000 0.812 0.000 0.184
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.4463    0.46434 0.764 0.168 0.004 0.004 0.060
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.5877    0.40488 0.596 0.000 0.244 0.000 0.160
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0510    0.41513 0.000 0.984 0.000 0.000 0.016
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.3362    0.55112 0.864 0.000 0.040 0.064 0.032
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.3969    0.50438 0.304 0.000 0.692 0.000 0.004
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.4318    0.49917 0.292 0.000 0.688 0.000 0.020
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.3496    0.53192 0.832 0.000 0.124 0.004 0.040
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.4232    0.46108 0.312 0.000 0.676 0.000 0.012
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.5652   -0.14354 0.464 0.000 0.468 0.004 0.064
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.4383   -0.03772 0.572 0.000 0.424 0.000 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.4624    0.33654 0.000 0.740 0.000 0.096 0.164
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.5814    0.29166 0.620 0.016 0.016 0.300 0.048
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.2409    0.35750 0.068 0.900 0.000 0.000 0.032
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.5191    0.34565 0.000 0.660 0.000 0.088 0.252
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.2448    0.54281 0.892 0.000 0.088 0.000 0.020
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.3961    0.15118 0.248 0.736 0.000 0.000 0.016
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.1670    0.59134 0.052 0.000 0.936 0.000 0.012
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.4571    0.45590 0.076 0.000 0.736 0.000 0.188
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.5880    0.41071 0.600 0.000 0.228 0.000 0.172
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0703    0.41870 0.000 0.976 0.000 0.000 0.024
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.4565    0.39396 0.408 0.000 0.580 0.000 0.012
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.4517    0.15758 0.600 0.000 0.388 0.000 0.012
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.5673    0.18367 0.000 0.500 0.000 0.080 0.420
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.4576    0.25416 0.000 0.608 0.000 0.376 0.016
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.2753    0.57565 0.136 0.000 0.856 0.000 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1408    0.57689 0.008 0.000 0.948 0.000 0.044
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.3804    0.48025 0.160 0.000 0.796 0.000 0.044
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.5620    0.43665 0.660 0.000 0.244 0.064 0.032
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.4558    0.38611 0.000 0.740 0.000 0.080 0.180
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.5668    0.17425 0.000 0.504 0.000 0.080 0.416
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1952    0.56191 0.004 0.000 0.912 0.000 0.084
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.3530    0.46952 0.784 0.000 0.204 0.000 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.4221    0.43441 0.236 0.000 0.732 0.000 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.3282    0.49291 0.008 0.000 0.804 0.000 0.188
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.4213    0.33862 0.308 0.000 0.680 0.000 0.012
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.2879    0.57496 0.032 0.000 0.868 0.000 0.100
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.6566    0.08379 0.316 0.000 0.484 0.004 0.196
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.3689    0.54432 0.256 0.000 0.740 0.000 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.4401    0.47319 0.328 0.000 0.656 0.000 0.016
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.3863    0.54420 0.248 0.000 0.740 0.000 0.012
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4537    0.33133 0.000 0.740 0.000 0.076 0.184
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.6966    0.27753 0.480 0.008 0.280 0.008 0.224
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.3910    0.45432 0.272 0.000 0.720 0.000 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.8444    0.27279 0.388 0.204 0.216 0.004 0.188
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4752    0.08473 0.568 0.000 0.412 0.000 0.020
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.5693    0.13455 0.000 0.468 0.000 0.080 0.452
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0404    0.41764 0.000 0.988 0.000 0.000 0.012
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.3065    0.54384 0.872 0.000 0.048 0.072 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.4445    0.48909 0.300 0.000 0.676 0.000 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2230    0.58955 0.044 0.000 0.912 0.000 0.044
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.5780    0.26076 0.508 0.000 0.420 0.060 0.012
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.2674    0.59059 0.140 0.000 0.856 0.000 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.6632    0.16311 0.000 0.428 0.000 0.344 0.228
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.1728    0.82767 0.036 0.004 0.000 0.940 0.020
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.5305    0.45678 0.672 0.000 0.244 0.072 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.6495    0.19658 0.000 0.480 0.000 0.304 0.216
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.5419    0.41520 0.640 0.000 0.284 0.064 0.012
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.4448    0.28191 0.480 0.000 0.516 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.1792    0.56348 0.000 0.000 0.916 0.000 0.084
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.5783    0.16233 0.540 0.000 0.360 0.000 0.100
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.2221    0.58110 0.052 0.000 0.912 0.000 0.036
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.6633   -0.21321 0.000 0.220 0.000 0.396 0.384
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.5700    0.22659 0.000 0.532 0.000 0.088 0.380
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.5543    0.01919 0.320 0.612 0.024 0.000 0.044
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4446    0.18692 0.520 0.000 0.476 0.000 0.004
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.3715    0.48562 0.260 0.000 0.736 0.000 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     3  0.3495    0.54064 0.160 0.000 0.812 0.000 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.5968    0.45492 0.268 0.000 0.576 0.000 0.156
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4219    0.39616 0.716 0.000 0.260 0.000 0.024
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.5659    0.33216 0.000 0.632 0.000 0.204 0.164
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.5685    0.43368 0.656 0.000 0.240 0.076 0.028
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.6498    0.18926 0.000 0.452 0.000 0.352 0.196
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.1732    0.59505 0.080 0.000 0.920 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.4508    0.47156 0.332 0.000 0.648 0.000 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.4589    0.35775 0.248 0.000 0.704 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.5068    0.47276 0.300 0.000 0.640 0.000 0.060
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.6351    0.21863 0.000 0.508 0.000 0.192 0.300
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.3841    0.50687 0.188 0.000 0.780 0.000 0.032
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.3650    0.48123 0.176 0.000 0.796 0.000 0.028
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.1997    0.57737 0.036 0.000 0.924 0.000 0.040
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.4610    0.33500 0.432 0.000 0.556 0.000 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0162    0.87850 0.000 0.004 0.000 0.996 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.4505    0.41724 0.384 0.000 0.604 0.000 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     5  0.8397    0.19749 0.244 0.256 0.024 0.080 0.396
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     5  0.7811   -0.41343 0.324 0.008 0.284 0.040 0.344
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.5136    0.34286 0.000 0.660 0.000 0.080 0.260
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.4890   -0.08487 0.524 0.000 0.452 0.000 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.3708    0.53881 0.816 0.000 0.136 0.004 0.044
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4022    0.50530 0.100 0.000 0.796 0.000 0.104
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.3224    0.50086 0.824 0.000 0.160 0.000 0.016

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.3864   1.72e-01 0.000 0.520 0.000 0.000 0.480 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4165   3.86e-01 0.420 0.000 0.568 0.004 0.000 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.1959   8.17e-01 0.000 0.032 0.020 0.924 0.000 0.024
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.5854  -1.05e-01 0.000 0.416 0.000 0.392 0.192 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0547   4.98e-01 0.980 0.000 0.020 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     5  0.6598   4.84e-01 0.012 0.296 0.056 0.004 0.520 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4469   4.30e-01 0.736 0.000 0.128 0.000 0.012 0.124
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3330   5.74e-01 0.284 0.000 0.716 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.4086   3.62e-01 0.464 0.000 0.528 0.000 0.000 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3464   3.70e-01 0.000 0.688 0.000 0.000 0.312 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2518   5.19e-01 0.880 0.000 0.016 0.000 0.012 0.092
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1444   5.57e-01 0.000 0.928 0.000 0.000 0.072 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     3  0.6590   3.23e-01 0.312 0.000 0.464 0.000 0.056 0.168
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.7263   2.63e-01 0.000 0.148 0.012 0.428 0.108 0.304
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3200   3.31e-01 0.788 0.000 0.196 0.000 0.000 0.016
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0713   5.72e-01 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.6068  -2.46e-01 0.000 0.364 0.000 0.372 0.264 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2597   4.88e-01 0.000 0.824 0.000 0.000 0.176 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.4408  -3.15e-02 0.000 0.644 0.004 0.012 0.324 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     5  0.3789   4.21e-01 0.000 0.416 0.000 0.000 0.584 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.4616   6.43e-01 0.124 0.000 0.092 0.000 0.040 0.744
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2562   4.02e-01 0.000 0.828 0.000 0.000 0.172 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.2065   6.61e-01 0.052 0.000 0.000 0.032 0.004 0.912
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000   5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.4120   4.62e-01 0.776 0.000 0.044 0.000 0.040 0.140
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.6680   1.82e-01 0.204 0.000 0.388 0.000 0.044 0.364
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.4007   4.79e-01 0.756 0.000 0.024 0.000 0.028 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2443   5.18e-01 0.880 0.000 0.020 0.000 0.004 0.096
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4684   5.46e-01 0.372 0.000 0.576 0.000 0.000 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2178   5.09e-01 0.000 0.868 0.000 0.000 0.132 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4806  -2.20e-01 0.560 0.000 0.380 0.000 0.000 0.060
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3728  -6.00e-02 0.652 0.000 0.344 0.000 0.000 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.5579   4.40e-01 0.000 0.168 0.000 0.644 0.144 0.044
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     6  0.8112  -2.59e-01 0.096 0.288 0.044 0.004 0.248 0.320
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.6198   4.24e-01 0.248 0.000 0.484 0.000 0.016 0.252
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2450   6.68e-01 0.064 0.000 0.012 0.024 0.004 0.896
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0632   8.40e-01 0.000 0.024 0.000 0.976 0.000 0.000
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#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4246   4.78e-01 0.452 0.000 0.532 0.000 0.000 0.016
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     6  0.5148   5.18e-01 0.240 0.000 0.100 0.000 0.016 0.644
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4478  -1.70e-01 0.532 0.000 0.444 0.000 0.012 0.012
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.3592   5.71e-01 0.344 0.000 0.656 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.5510   1.13e-01 0.424 0.000 0.488 0.000 0.036 0.052
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.3982  -3.57e-01 0.536 0.000 0.460 0.000 0.000 0.004
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.3136   5.54e-01 0.228 0.000 0.768 0.000 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4168   2.99e-01 0.696 0.000 0.256 0.000 0.000 0.048
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.2712   5.16e-01 0.864 0.000 0.016 0.000 0.012 0.108
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.4789   4.08e-01 0.692 0.000 0.124 0.000 0.008 0.176
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     5  0.4078   5.12e-01 0.000 0.340 0.000 0.020 0.640 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.5332   4.13e-01 0.168 0.000 0.628 0.004 0.004 0.196
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.4570   8.42e-02 0.644 0.000 0.308 0.000 0.012 0.036
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.6648   1.51e-01 0.552 0.004 0.172 0.004 0.188 0.080
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4345   2.90e-01 0.628 0.000 0.012 0.000 0.016 0.344
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.2697   4.78e-01 0.000 0.812 0.000 0.000 0.188 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.3774  -2.16e-01 0.000 0.592 0.000 0.000 0.408 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.2628   6.68e-01 0.068 0.000 0.024 0.024 0.000 0.884
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1434   5.13e-01 0.948 0.000 0.012 0.000 0.012 0.028
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.3996  -3.72e-01 0.512 0.000 0.484 0.000 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.2745   6.37e-01 0.068 0.000 0.068 0.000 0.000 0.864
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.4241  -1.07e-01 0.608 0.000 0.368 0.000 0.000 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     5  0.6100   1.71e-01 0.000 0.284 0.000 0.356 0.360 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0632   8.29e-01 0.000 0.000 0.000 0.976 0.000 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.2007   6.64e-01 0.036 0.000 0.032 0.012 0.000 0.920
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.5993   2.44e-01 0.000 0.288 0.000 0.272 0.440 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.1863   6.61e-01 0.044 0.000 0.036 0.000 0.000 0.920
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.4604   2.24e-01 0.432 0.000 0.024 0.000 0.008 0.536
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3864   4.39e-01 0.480 0.000 0.520 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.5982   3.60e-01 0.596 0.000 0.220 0.000 0.064 0.120
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.3899  -2.10e-01 0.592 0.000 0.404 0.000 0.000 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.4015   3.46e-01 0.000 0.372 0.000 0.616 0.012 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.1285   5.58e-01 0.000 0.944 0.000 0.004 0.052 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     5  0.6648   3.47e-01 0.052 0.356 0.136 0.000 0.448 0.008
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.5668  -1.47e-01 0.100 0.000 0.408 0.000 0.016 0.476
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.5323   3.01e-01 0.272 0.000 0.120 0.000 0.008 0.600
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.5748  -1.44e-01 0.464 0.000 0.360 0.000 0.000 0.176
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.2805   3.80e-01 0.828 0.000 0.160 0.000 0.000 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5966   3.60e-01 0.576 0.000 0.164 0.000 0.036 0.224
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.5559  -1.62e-01 0.000 0.540 0.000 0.176 0.284 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.1490   6.53e-01 0.008 0.000 0.016 0.024 0.004 0.948
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     4  0.6039  -2.30e-01 0.000 0.356 0.000 0.392 0.252 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4206  -1.11e-01 0.620 0.000 0.356 0.000 0.000 0.024
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2711   5.16e-01 0.860 0.000 0.012 0.000 0.012 0.116
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.5024   2.04e-01 0.408 0.000 0.536 0.000 0.028 0.028
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0260   5.00e-01 0.992 0.000 0.008 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.5789   1.96e-02 0.000 0.496 0.000 0.288 0.216 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.5646  -1.16e-01 0.500 0.000 0.356 0.000 0.004 0.140
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5479  -1.45e-01 0.500 0.000 0.368 0.000 0.000 0.132
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.5798   3.57e-01 0.396 0.000 0.456 0.000 0.008 0.140
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4436   3.51e-01 0.652 0.000 0.028 0.000 0.012 0.308
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0260   8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4246   4.33e-01 0.692 0.000 0.028 0.000 0.012 0.268
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.3371   4.05e-01 0.008 0.796 0.180 0.000 0.012 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.7112   1.79e-01 0.328 0.196 0.416 0.008 0.036 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000   5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5172   3.65e-01 0.660 0.000 0.116 0.000 0.020 0.204
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.5337   5.16e-01 0.236 0.000 0.060 0.004 0.048 0.652
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.5491   5.14e-01 0.332 0.000 0.524 0.000 0.000 0.144
#> 2785594A-571A-46B4-A901-CB9C62DC6174     6  0.4433   2.39e-01 0.416 0.000 0.008 0.000 0.016 0.560

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 17541 rows and 500 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 0.797           0.881       0.951         0.4983 0.502   0.502
#> 3 3 0.528           0.716       0.852         0.3294 0.711   0.485
#> 4 4 0.511           0.506       0.705         0.1029 0.773   0.470
#> 5 5 0.709           0.703       0.858         0.0681 0.842   0.533
#> 6 6 0.734           0.667       0.809         0.0431 0.925   0.692

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     2  0.0000    0.94890 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000    0.94406 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000    0.94890 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.0000    0.94406 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.1633    0.92800 0.976 0.024
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000    0.94890 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.9686    0.36511 0.396 0.604
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.6438    0.79874 0.836 0.164
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.0000    0.94890 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     2  0.0000    0.94890 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0000    0.94890 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.8909    0.58116 0.692 0.308
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.5519    0.82914 0.128 0.872
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.4161    0.87929 0.084 0.916
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000    0.94406 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.0000    0.94890 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000    0.94406 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0672    0.94327 0.008 0.992
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.9954    0.17124 0.460 0.540
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.94890 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.0000    0.94890 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.94890 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.94406 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.94890 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000    0.94406 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.94890 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0376    0.94612 0.004 0.996
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000    0.94406 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2043    0.92362 0.968 0.032
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.6247    0.80793 0.844 0.156
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.9710    0.37184 0.600 0.400
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.94890 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.0000    0.94406 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.8909    0.58119 0.692 0.308
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#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0000    0.94890 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000    0.94406 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0000    0.94406 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.1843    0.92678 0.972 0.028
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0000    0.94406 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.0000    0.94890 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     1  0.5294    0.83936 0.880 0.120
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.0000    0.94890 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000    0.94890 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000    0.94890 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.0000    0.94406 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.0376    0.94612 0.004 0.996
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000    0.94406 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000    0.94406 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0000    0.94890 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.7602    0.72625 0.780 0.220
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000    0.94406 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0000    0.94406 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0000    0.94406 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000    0.94406 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     2  0.0000    0.94890 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.0000    0.94890 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.0000    0.94406 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.0000    0.94406 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000    0.94406 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000    0.94890 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0000    0.94406 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.8499    0.63901 0.724 0.276
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.0000    0.94890 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0000    0.94406 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.1633    0.92939 0.976 0.024
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0376    0.94612 0.004 0.996
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000    0.94406 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.0000    0.94406 1.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.0000    0.94406 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000    0.94890 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.2603    0.91451 0.044 0.956
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0000    0.94406 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000    0.94890 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.0000    0.94890 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.0000    0.94890 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000    0.94406 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000    0.94890 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.0000    0.94406 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000    0.94406 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.9686    0.38481 0.604 0.396
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000    0.94890 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.2043    0.92210 0.968 0.032
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000    0.94406 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.9881    0.26824 0.564 0.436
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000    0.94406 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000    0.94406 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.94890 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.94890 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.0000    0.94406 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.6148    0.79464 0.152 0.848
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000    0.94406 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.0000    0.94890 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.0000    0.94890 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.9922    0.15009 0.448 0.552
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.0000    0.94890 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000    0.94890 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4431    0.87386 0.908 0.092
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.5629    0.83417 0.868 0.132
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0376    0.94186 0.996 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.6048    0.80627 0.852 0.148
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.6801    0.76530 0.180 0.820
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.1414    0.93362 0.020 0.980
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000    0.94890 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000    0.94406 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000    0.94890 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.94890 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000    0.94406 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.9996   -0.00146 0.488 0.512
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.0000    0.94890 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000    0.94406 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.8081    0.68488 0.752 0.248
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.4690    0.86041 0.900 0.100
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000    0.94406 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000    0.94406 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000    0.94406 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9460    0.41493 0.636 0.364
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000    0.94406 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000    0.94406 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.0000    0.94890 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000    0.94406 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.8861    0.58905 0.696 0.304
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.0000    0.94890 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.9963    0.15752 0.464 0.536
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.9286    0.48727 0.344 0.656
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000    0.94890 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000    0.94406 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0672    0.93921 0.992 0.008
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000    0.94406 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000    0.94406 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.0000    0.94890 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000    0.94406 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.9286    0.48655 0.344 0.656
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000    0.94406 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.8661    0.58562 0.712 0.288
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.9996   -0.00208 0.488 0.512
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.7139    0.75887 0.804 0.196
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.0000    0.94890 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000    0.94890 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.9850    0.27302 0.428 0.572
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000    0.94406 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2043    0.92379 0.968 0.032
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000    0.94406 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000    0.94406 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000    0.94406 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000    0.94406 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000    0.94890 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.0000    0.94890 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.94890 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0938    0.93710 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0376    0.94188 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000    0.94406 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000    0.94406 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     3  0.5327    0.57635 0.000 0.272 0.728
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.4504    0.70680 0.196 0.804 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0424    0.79746 0.000 0.008 0.992
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.5016    0.65063 0.240 0.760 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1031    0.80072 0.024 0.976 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.3192    0.77575 0.112 0.000 0.888
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.1647    0.80789 0.004 0.960 0.036
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2537    0.86620 0.920 0.000 0.080
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0592    0.80119 0.012 0.000 0.988
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.0892    0.80102 0.020 0.000 0.980
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.5650    0.57222 0.000 0.688 0.312
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4702    0.74636 0.788 0.000 0.212
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0892    0.80681 0.000 0.980 0.020
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.8967    0.14439 0.488 0.132 0.380
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.5291    0.61085 0.268 0.732 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.4002    0.73353 0.160 0.000 0.840
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.5678    0.53451 0.316 0.684 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.2625    0.79947 0.000 0.916 0.084
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0661    0.80461 0.008 0.988 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.6260    0.24474 0.000 0.552 0.448
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.3482    0.72505 0.000 0.128 0.872
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2356    0.80225 0.000 0.928 0.072
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0892    0.86822 0.980 0.020 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.5529    0.59830 0.000 0.704 0.296
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.3482    0.77905 0.872 0.128 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.4178    0.68017 0.000 0.172 0.828
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5529    0.55050 0.296 0.000 0.704
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0237    0.87464 0.996 0.004 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.2261    0.87202 0.932 0.000 0.068
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3038    0.85177 0.896 0.000 0.104
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.6154    0.38202 0.592 0.000 0.408
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.6045    0.43275 0.000 0.620 0.380
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.4291    0.71915 0.180 0.820 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.3879    0.81387 0.848 0.000 0.152
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.3038    0.78127 0.104 0.000 0.896
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.4452    0.70784 0.192 0.808 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.5948    0.42885 0.360 0.640 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.1529    0.87985 0.960 0.000 0.040
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.1753    0.85131 0.952 0.048 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.3879    0.74247 0.152 0.848 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.2959    0.85574 0.900 0.000 0.100
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1860    0.87779 0.948 0.000 0.052
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.6235    0.28195 0.000 0.564 0.436
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0237    0.87464 0.996 0.004 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.6095    0.37597 0.392 0.608 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2537    0.79100 0.080 0.000 0.920
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.2711    0.75558 0.000 0.088 0.912
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.1337    0.87826 0.972 0.012 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     3  0.7273    0.70015 0.132 0.156 0.712
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.1163    0.80736 0.000 0.972 0.028
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.1753    0.87858 0.952 0.000 0.048
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.5591    0.61289 0.696 0.000 0.304
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#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.3482    0.78085 0.000 0.872 0.128
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     3  0.2356    0.79375 0.072 0.000 0.928
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.1999    0.80368 0.036 0.952 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.1163    0.80271 0.028 0.972 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0424    0.80422 0.008 0.992 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.5650    0.54175 0.312 0.688 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     3  0.3267    0.74105 0.000 0.116 0.884
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0237    0.87464 0.996 0.004 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.2959    0.80768 0.900 0.100 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.2165    0.87399 0.936 0.000 0.064
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0592    0.87190 0.988 0.012 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.0237    0.80000 0.004 0.000 0.996
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.3941    0.73619 0.156 0.844 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     2  0.6309    0.07455 0.000 0.504 0.496
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     3  0.6307   -0.11544 0.000 0.488 0.512
#> 80936433-AA91-4219-98F1-706C36298060     2  0.3038    0.79236 0.000 0.896 0.104
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     2  0.5363    0.60169 0.276 0.724 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     3  0.8982    0.47644 0.284 0.168 0.548
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.1643    0.87915 0.956 0.000 0.044
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0747    0.87006 0.984 0.016 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.4842    0.60927 0.000 0.224 0.776
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.3816    0.81719 0.852 0.000 0.148
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0592    0.87179 0.988 0.012 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0892    0.87950 0.980 0.000 0.020
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0237    0.87464 0.996 0.004 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0747    0.87887 0.984 0.000 0.016
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.2711    0.78854 0.088 0.000 0.912
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.2796    0.78653 0.092 0.000 0.908
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.4974    0.65630 0.236 0.764 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.6267    0.18176 0.548 0.452 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0237    0.87464 0.996 0.004 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.4887    0.69358 0.000 0.772 0.228
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.2165    0.83893 0.936 0.064 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.4702    0.75148 0.788 0.000 0.212
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.4002    0.73327 0.160 0.000 0.840
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.2356    0.83265 0.928 0.072 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.2356    0.87043 0.928 0.000 0.072
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.9243    0.49774 0.232 0.236 0.532
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000    0.87576 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.1411    0.79739 0.036 0.964 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.6252    0.14127 0.556 0.444 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.2959    0.74776 0.000 0.100 0.900
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.1163    0.80717 0.000 0.972 0.028
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0237    0.87464 0.996 0.004 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.5678    0.56673 0.000 0.684 0.316
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.3412    0.76637 0.124 0.000 0.876
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000    0.79929 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.1964    0.84501 0.944 0.056 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.2878    0.79547 0.000 0.904 0.096
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.5016    0.65121 0.240 0.760 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.1031    0.87980 0.976 0.000 0.024
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.4796    0.73904 0.780 0.000 0.220
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     3  0.5678    0.49626 0.000 0.316 0.684
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.1163    0.79965 0.028 0.972 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.1289    0.88009 0.968 0.000 0.032
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.6308   -0.05845 0.492 0.000 0.508
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4121    0.79863 0.832 0.000 0.168
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1964    0.84516 0.944 0.056 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.3619    0.77603 0.000 0.864 0.136
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.6305    0.12166 0.000 0.516 0.484
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.3619    0.75412 0.136 0.864 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4974    0.63842 0.236 0.000 0.764
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.1163    0.86479 0.972 0.028 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.2959    0.78309 0.100 0.000 0.900
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1753    0.79956 0.048 0.000 0.952
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.8126    0.35354 0.564 0.080 0.356
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.1163    0.80080 0.028 0.000 0.972
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0892    0.79371 0.000 0.020 0.980
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4235    0.79176 0.824 0.000 0.176
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.2625    0.86404 0.916 0.000 0.084
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.2165    0.87373 0.936 0.000 0.064
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.1031    0.80072 0.024 0.976 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.5988    0.33807 0.000 0.368 0.632
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.6849    0.35416 0.380 0.020 0.600
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1163    0.79000 0.000 0.028 0.972
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0892    0.87950 0.980 0.000 0.020
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.3340    0.78535 0.000 0.880 0.120
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.3619    0.77629 0.000 0.864 0.136
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1163    0.86367 0.972 0.028 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.5988    0.46706 0.632 0.000 0.368
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.3412    0.76621 0.124 0.000 0.876
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0237    0.87464 0.996 0.004 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.3879    0.81386 0.848 0.000 0.152
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.0892    0.80151 0.020 0.980 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.6267    0.11703 0.548 0.452 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.6126    0.35449 0.400 0.600 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0424    0.87336 0.992 0.008 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.1129    0.80269 0.020 0.976 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0747    0.87006 0.984 0.016 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1289    0.88009 0.968 0.000 0.032
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.3752    0.74889 0.144 0.000 0.856
#> 1122039D-5785-4F70-9916-17C585453512     2  0.4654    0.68698 0.208 0.792 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.6224    0.68092 0.728 0.032 0.240
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.3267    0.77255 0.116 0.000 0.884
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000    0.80492 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0424    0.80586 0.000 0.992 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.6274   -0.00811 0.000 0.456 0.544
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0424    0.87336 0.992 0.008 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.3879    0.74264 0.152 0.848 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0892    0.87950 0.980 0.000 0.020
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1753    0.87858 0.952 0.000 0.048
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0747    0.80102 0.016 0.000 0.984
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0424    0.87795 0.992 0.000 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0424    0.80586 0.000 0.992 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2448    0.82934 0.924 0.076 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0983    0.80338 0.016 0.980 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.6192    0.21388 0.420 0.000 0.580
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2796    0.85980 0.908 0.000 0.092
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.6332    0.74107 0.144 0.088 0.768
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.2356    0.79383 0.072 0.000 0.928
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0424    0.80586 0.000 0.992 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1753    0.87858 0.952 0.000 0.048
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2448    0.86826 0.924 0.000 0.076
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.1860    0.87770 0.948 0.000 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1411    0.87997 0.964 0.000 0.036
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.2878    0.77560 0.096 0.904 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1163    0.88013 0.972 0.000 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.2356    0.76613 0.000 0.072 0.928
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1163    0.79000 0.000 0.028 0.972
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.5216    0.65165 0.000 0.740 0.260
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2165    0.87375 0.936 0.000 0.064
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5292    0.65798 0.764 0.228 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.2165    0.87450 0.936 0.000 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000    0.87576 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     3  0.8265   0.118834 0.016 0.360 0.380 0.244
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.5414   0.600729 0.020 0.376 0.000 0.604
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.5711   0.682921 0.012 0.028 0.656 0.304
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.5467   0.608698 0.024 0.364 0.000 0.612
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3400   0.530860 0.000 0.820 0.000 0.180
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.7283   0.375721 0.556 0.016 0.120 0.308
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4262   0.602716 0.008 0.756 0.000 0.236
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0804   0.720068 0.980 0.000 0.008 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.3862   0.663809 0.060 0.004 0.852 0.084
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.3455   0.545179 0.044 0.012 0.880 0.064
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.6743   0.308044 0.004 0.504 0.412 0.080
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3088   0.707897 0.864 0.000 0.008 0.128
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.3942   0.444131 0.000 0.764 0.000 0.236
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.8019   0.313988 0.480 0.072 0.368 0.080
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.6637   0.616548 0.132 0.260 0.000 0.608
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5859   0.527882 0.652 0.000 0.064 0.284
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.5920   0.616384 0.052 0.336 0.000 0.612
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4953   0.552072 0.000 0.776 0.104 0.120
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2011   0.622667 0.000 0.920 0.000 0.080
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.5161   0.512121 0.000 0.676 0.300 0.024
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.6308   0.651344 0.000 0.120 0.648 0.232
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1792   0.631207 0.000 0.932 0.000 0.068
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2345   0.675261 0.900 0.000 0.000 0.100
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.1929   0.660192 0.000 0.940 0.024 0.036
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.5628   0.337137 0.420 0.024 0.000 0.556
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.2081   0.587390 0.000 0.084 0.916 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.7042   0.421616 0.580 0.036 0.064 0.320
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2011   0.688918 0.920 0.000 0.000 0.080
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3751   0.675419 0.800 0.004 0.000 0.196
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2081   0.719491 0.916 0.000 0.000 0.084
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.4103   0.627413 0.744 0.000 0.256 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.4663   0.559348 0.000 0.716 0.272 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.5050   0.567922 0.004 0.408 0.000 0.588
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4837   0.514634 0.648 0.000 0.348 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.6752   0.454582 0.588 0.000 0.280 0.132
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#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3229   0.713990 0.880 0.000 0.048 0.072
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.4562   0.627221 0.792 0.000 0.056 0.152
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0469   0.716584 0.988 0.000 0.000 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.5150   0.583924 0.008 0.396 0.000 0.596
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0817   0.714858 0.976 0.000 0.000 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4966   0.609978 0.000 0.156 0.768 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.5496   0.686794 0.008 0.028 0.676 0.288
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.1109   0.653444 0.000 0.968 0.004 0.028
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2737   0.712054 0.888 0.008 0.000 0.104
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.6433   0.356779 0.648 0.188 0.000 0.164
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.5127   0.307316 0.632 0.000 0.012 0.356
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0707   0.714883 0.980 0.000 0.000 0.020

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.5880     0.0979 0.000 0.100 0.416 0.000 0.484
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.0162     0.8197 0.000 0.004 0.000 0.996 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1205     0.8675 0.000 0.956 0.000 0.040 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.1444     0.8304 0.948 0.012 0.040 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.2378     0.8370 0.048 0.904 0.048 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0404     0.8204 0.000 0.000 0.988 0.000 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.0162     0.7254 0.004 0.000 0.000 0.000 0.996
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.1121     0.7245 0.000 0.044 0.000 0.000 0.956
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.8468 1.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.4334     0.7243 0.000 0.764 0.000 0.080 0.156
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3562     0.6486 0.196 0.016 0.000 0.000 0.788
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0609     0.8117 0.000 0.020 0.000 0.980 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.8468 1.000 0.000 0.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0290     0.8187 0.000 0.008 0.000 0.992 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.3530     0.6118 0.000 0.204 0.000 0.012 0.784
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.1579     0.8657 0.000 0.944 0.000 0.032 0.024
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2329     0.8048 0.000 0.876 0.000 0.000 0.124
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0566     0.8724 0.000 0.984 0.000 0.012 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.5880     0.4981 0.600 0.000 0.000 0.228 0.172
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.4270     0.5062 0.000 0.656 0.336 0.004 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0609     0.8172 0.020 0.000 0.000 0.980 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.4283     0.2190 0.000 0.000 0.456 0.000 0.544
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.2054     0.8176 0.920 0.028 0.052 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2069     0.8161 0.912 0.000 0.000 0.012 0.076
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0290     0.8462 0.992 0.008 0.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.8468 1.000 0.000 0.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.4517     0.5659 0.708 0.000 0.016 0.016 0.260
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.1965     0.8378 0.000 0.904 0.000 0.000 0.096
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.3196     0.6672 0.192 0.000 0.000 0.004 0.804
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0451     0.8465 0.988 0.000 0.008 0.000 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.4302    -0.0530 0.000 0.480 0.000 0.520 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.3143     0.6600 0.204 0.796 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.2074     0.7747 0.104 0.000 0.000 0.896 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.0880     0.8138 0.032 0.000 0.000 0.968 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0451     0.8172 0.000 0.008 0.000 0.988 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0451     0.8464 0.988 0.000 0.000 0.004 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.6164     0.3304 0.520 0.000 0.000 0.152 0.328
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.1484     0.8660 0.008 0.944 0.000 0.048 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3796     0.5711 0.300 0.000 0.700 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0290     0.8221 0.000 0.000 0.992 0.000 0.008
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.5964     0.4548 0.232 0.000 0.000 0.588 0.180
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4589     0.7030 0.764 0.056 0.020 0.000 0.160
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0579     0.8718 0.000 0.984 0.000 0.008 0.008
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     5  0.3389     0.6815 0.116 0.000 0.000 0.048 0.836
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.1043     0.8363 0.960 0.000 0.040 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.6513     0.3254 0.000 0.248 0.516 0.232 0.004
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.2189     0.8010 0.904 0.012 0.084 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.2280     0.7875 0.880 0.000 0.000 0.120 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.5934     0.4260 0.596 0.312 0.000 0.044 0.048
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8725 0.000 1.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.1043     0.8680 0.000 0.960 0.000 0.040 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.1282     0.8341 0.952 0.004 0.044 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.2304     0.8374 0.000 0.892 0.000 0.100 0.008
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0290     0.8462 0.992 0.008 0.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.1792     0.8482 0.000 0.916 0.000 0.084 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.4182     0.3086 0.600 0.000 0.000 0.400 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0162     0.8467 0.996 0.004 0.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.8190    -0.1119 0.276 0.020 0.328 0.052 0.324
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     5  0.2338     0.7000 0.112 0.000 0.004 0.000 0.884
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     2  0.4015     0.4275 0.000 0.652 0.000 0.000 0.348
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.6010     0.4303 0.584 0.208 0.000 0.000 0.208
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0566     0.8464 0.984 0.000 0.004 0.012 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.2127     0.7716 0.108 0.000 0.000 0.892 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.3351     0.7912 0.000 0.828 0.020 0.148 0.004
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     2  0.7120     0.0882 0.028 0.456 0.204 0.000 0.312
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1331     0.8651 0.000 0.952 0.040 0.008 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0703     0.8150 0.000 0.000 0.976 0.000 0.024
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.3612     0.6572 0.228 0.008 0.764 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0703     0.8188 0.024 0.000 0.976 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.0510     0.7265 0.000 0.016 0.000 0.000 0.984
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.3707     0.5897 0.284 0.000 0.716 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.1544     0.7982 0.068 0.000 0.932 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0703     0.8429 0.976 0.024 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     5  0.3913     0.4795 0.000 0.000 0.324 0.000 0.676
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1121     0.8342 0.956 0.044 0.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.1121     0.8103 0.044 0.000 0.000 0.956 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0798     0.8710 0.008 0.976 0.016 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.2605     0.7376 0.148 0.000 0.000 0.852 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.3949     0.4842 0.668 0.000 0.000 0.332 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.1638     0.8545 0.004 0.932 0.064 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.3749     0.7464 0.816 0.000 0.000 0.080 0.104
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.1168     0.8371 0.960 0.008 0.032 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.2054     0.8224 0.920 0.028 0.000 0.000 0.052
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.3455     0.7051 0.000 0.784 0.000 0.008 0.208
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0510     0.7262 0.000 0.016 0.000 0.000 0.984
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2890     0.7906 0.000 0.836 0.000 0.160 0.004
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.3366     0.6176 0.000 0.232 0.000 0.000 0.768
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0162     0.8197 0.000 0.004 0.000 0.996 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.1205     0.8672 0.000 0.956 0.000 0.040 0.004
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     5  0.6190     0.0789 0.136 0.000 0.000 0.420 0.444
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.3366     0.6678 0.768 0.000 0.000 0.232 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.3300     0.6649 0.204 0.792 0.004 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.3636     0.6009 0.728 0.000 0.000 0.272 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     3  0.4734     0.3687 0.000 0.000 0.604 0.024 0.372
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.0794     0.8079 0.000 0.000 0.028 0.972 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0290     0.8466 0.992 0.000 0.008 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0566     0.8713 0.000 0.984 0.000 0.004 0.012
#> C44C898C-EEF9-4E03-911A-9D951312C380     4  0.6337     0.2946 0.064 0.048 0.000 0.544 0.344
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.4306     0.1449 0.000 0.508 0.000 0.492 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.2628     0.7958 0.884 0.028 0.000 0.000 0.088
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.1956     0.8529 0.000 0.916 0.000 0.076 0.008
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.1661     0.8652 0.000 0.940 0.000 0.024 0.036
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     5  0.3421     0.6150 0.204 0.008 0.000 0.000 0.788
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.3031     0.8081 0.000 0.856 0.120 0.020 0.004
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0290     0.8238 0.008 0.000 0.992 0.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.5188     0.4361 0.600 0.056 0.000 0.000 0.344
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     3  0.5663     0.2474 0.088 0.000 0.548 0.364 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     4  0.2732     0.7278 0.160 0.000 0.000 0.840 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     5  0.0671     0.7269 0.004 0.016 0.000 0.000 0.980
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     5  0.4981     0.6025 0.000 0.172 0.120 0.000 0.708
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     4  0.0000     0.8197 0.000 0.000 0.000 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.0404     0.8706 0.012 0.988 0.000 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     1  0.0703     0.8426 0.976 0.024 0.000 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     4  0.3949     0.4976 0.332 0.000 0.000 0.668 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     4  0.4341     0.3544 0.000 0.008 0.364 0.628 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.3224     0.7656 0.000 0.824 0.000 0.016 0.160
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3  0.3395     0.6482 0.236 0.000 0.764 0.000 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     1  0.0404     0.8456 0.988 0.012 0.000 0.000 0.000
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#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.5168     0.3731 0.052 0.000 0.000 0.592 0.356
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0162     0.8197 0.000 0.004 0.000 0.996 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0404     0.8462 0.988 0.000 0.012 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     5  0.3980     0.4952 0.000 0.284 0.008 0.000 0.708
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.4015     0.5331 0.000 0.652 0.000 0.348 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.1270     0.8315 0.948 0.000 0.000 0.052 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     5  0.6586     0.4380 0.300 0.000 0.208 0.004 0.488
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     5  0.3562     0.5669 0.016 0.000 0.000 0.196 0.788
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.2471     0.7511 0.136 0.000 0.000 0.864 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0898     0.8713 0.000 0.972 0.020 0.008 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0162     0.8725 0.000 0.996 0.000 0.000 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.1410     0.8298 0.940 0.000 0.060 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     4  0.4201     0.3510 0.408 0.000 0.000 0.592 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.4653     0.2162 0.516 0.012 0.000 0.000 0.472
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.1041     0.8097 0.004 0.000 0.964 0.000 0.032
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.3983     0.5211 0.660 0.000 0.000 0.000 0.340
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     5  0.4546     0.5063 0.028 0.000 0.304 0.000 0.668
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0162     0.8235 0.000 0.000 0.996 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.2388     0.8120 0.900 0.000 0.072 0.028 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.8468 1.000 0.000 0.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0162     0.8722 0.004 0.996 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.3816     0.5058 0.000 0.000 0.696 0.304 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.3774     0.5861 0.704 0.000 0.000 0.000 0.296
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.0566     0.8219 0.012 0.004 0.984 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0290     0.8467 0.992 0.008 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.0162     0.7257 0.000 0.004 0.000 0.000 0.996
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1121     0.8638 0.000 0.956 0.044 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.4302     0.0814 0.520 0.000 0.000 0.480 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0404     0.8456 0.988 0.012 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.2648     0.7554 0.848 0.000 0.152 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.3586     0.6200 0.736 0.000 0.000 0.264 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0807     0.8458 0.976 0.000 0.012 0.012 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     2  0.4009     0.4849 0.000 0.684 0.000 0.004 0.312
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000     0.8197 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0162     0.8197 0.000 0.004 0.000 0.996 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.4305     0.0383 0.488 0.000 0.000 0.512 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0898     0.8694 0.000 0.972 0.000 0.008 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.3913     0.5170 0.324 0.000 0.000 0.676 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.3983     0.4741 0.660 0.000 0.000 0.340 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4856     0.2685 0.584 0.000 0.028 0.000 0.388
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0162     0.8197 0.000 0.004 0.000 0.996 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.4218     0.5206 0.660 0.008 0.000 0.000 0.332
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.0963     0.7266 0.036 0.000 0.000 0.000 0.964
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.4452    -0.1194 0.000 0.496 0.000 0.500 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.1701     0.7160 0.000 0.016 0.000 0.048 0.936
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.4496     0.6162 0.056 0.216 0.728 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.1965     0.7809 0.096 0.000 0.000 0.904 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.4088     0.4094 0.368 0.000 0.000 0.632 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4046     0.5869 0.696 0.000 0.000 0.008 0.296
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2648     0.7338 0.152 0.000 0.848 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.2300     0.8108 0.908 0.040 0.052 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0963     0.8692 0.000 0.964 0.000 0.036 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.1121     0.8094 0.044 0.000 0.000 0.956 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0566     0.8713 0.000 0.984 0.000 0.004 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0162     0.8467 0.996 0.000 0.004 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.8468 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.0880     0.7268 0.032 0.000 0.000 0.000 0.968
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.4003     0.5420 0.704 0.008 0.288 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.1282     0.8661 0.000 0.952 0.000 0.044 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.3895     0.5544 0.680 0.000 0.000 0.000 0.320
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.2813     0.6583 0.168 0.000 0.000 0.000 0.832
#> EB7883EB-0079-4548-9132-169E94A698BA     5  0.3165     0.6728 0.036 0.000 0.000 0.116 0.848
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0290     0.8186 0.000 0.008 0.000 0.992 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0162     0.8465 0.996 0.000 0.000 0.004 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.0510     0.8191 0.000 0.000 0.984 0.000 0.016
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8247 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0451     0.8724 0.000 0.988 0.000 0.008 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0290     0.8462 0.992 0.008 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4021     0.6766 0.780 0.168 0.000 0.052 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.2909     0.7428 0.140 0.000 0.012 0.848 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0162     0.8470 0.996 0.004 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.4677     0.4810 0.000 0.032 0.256 0.684 0.012 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.0260     0.7042 0.000 0.000 0.000 0.008 0.000 0.992
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8566 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     6  0.1141     0.7149 0.000 0.000 0.000 0.052 0.000 0.948
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2668     0.7926 0.000 0.828 0.000 0.000 0.004 0.168
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0891     0.8167 0.968 0.024 0.008 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0881     0.8370 0.012 0.972 0.008 0.008 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0146     0.8221 0.996 0.000 0.000 0.004 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0146     0.8562 0.000 0.000 0.996 0.004 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.3823     0.1851 0.000 0.000 0.000 0.436 0.564 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.1649     0.7181 0.000 0.036 0.000 0.032 0.932 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0146     0.8221 0.996 0.000 0.000 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.5019     0.6151 0.000 0.604 0.000 0.000 0.104 0.292
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.1341     0.7268 0.028 0.024 0.000 0.000 0.948 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     6  0.3489     0.7124 0.000 0.004 0.000 0.288 0.000 0.708
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0632     0.8190 0.976 0.000 0.000 0.024 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.0520     0.7012 0.000 0.008 0.000 0.008 0.000 0.984
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     5  0.4651     0.4851 0.000 0.056 0.000 0.004 0.636 0.304
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.4735     0.6440 0.000 0.628 0.000 0.076 0.000 0.296
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2854     0.7273 0.000 0.792 0.000 0.000 0.208 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.2799     0.7980 0.000 0.000 0.860 0.064 0.000 0.076
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1141     0.8390 0.000 0.948 0.000 0.000 0.000 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.3874     0.5750 0.172 0.000 0.000 0.760 0.000 0.068
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.5475     0.6199 0.000 0.620 0.164 0.016 0.000 0.200
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.4060     0.7126 0.032 0.000 0.000 0.284 0.000 0.684
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     5  0.2427     0.7026 0.000 0.032 0.032 0.000 0.900 0.036
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.1267     0.7988 0.940 0.060 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0146     0.8230 0.996 0.000 0.000 0.000 0.004 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0777     0.8206 0.972 0.004 0.000 0.024 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0458     0.8207 0.984 0.000 0.000 0.016 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.5353     0.4806 0.600 0.000 0.000 0.152 0.244 0.004
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.3833     0.6369 0.000 0.708 0.000 0.004 0.272 0.016
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     6  0.1225     0.6764 0.000 0.012 0.000 0.036 0.000 0.952
#> C06D8112-0FA0-4607-988D-589D8694743F     5  0.0713     0.7269 0.028 0.000 0.000 0.000 0.972 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0820     0.8197 0.972 0.000 0.012 0.016 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.5162     0.1177 0.000 0.504 0.000 0.088 0.000 0.408
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.1500     0.8121 0.052 0.936 0.000 0.012 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     6  0.4481     0.6989 0.056 0.000 0.000 0.296 0.000 0.648
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.4165     0.7083 0.036 0.000 0.000 0.292 0.000 0.672
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     6  0.1462     0.6662 0.000 0.008 0.000 0.056 0.000 0.936
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0260     0.8224 0.992 0.008 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0260     0.8407 0.000 0.992 0.000 0.008 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.2398     0.5933 0.080 0.000 0.000 0.888 0.004 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.0653     0.8400 0.012 0.980 0.000 0.004 0.000 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.1387     0.8141 0.068 0.000 0.932 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.2801     0.7990 0.000 0.000 0.860 0.068 0.000 0.072
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.4886    -0.3360 0.064 0.000 0.000 0.540 0.000 0.396
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.5409     0.5349 0.076 0.044 0.248 0.632 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0922     0.8422 0.000 0.968 0.000 0.004 0.004 0.024
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     5  0.3204     0.6461 0.068 0.000 0.000 0.092 0.836 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.1010     0.8171 0.960 0.000 0.036 0.004 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.5356     0.4825 0.000 0.020 0.560 0.072 0.000 0.348
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.1168     0.8149 0.956 0.016 0.028 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.3141     0.6890 0.788 0.000 0.000 0.200 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.6893     0.4225 0.232 0.280 0.000 0.424 0.000 0.064
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.8408 0.000 1.000 0.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0508     0.8426 0.004 0.984 0.000 0.000 0.000 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.0993     0.8163 0.964 0.012 0.024 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.3835     0.6724 0.000 0.668 0.000 0.000 0.012 0.320
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0603     0.8210 0.980 0.016 0.000 0.004 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3314     0.7385 0.004 0.740 0.000 0.000 0.000 0.256
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.5990     0.0117 0.440 0.000 0.000 0.296 0.000 0.264
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0508     0.8217 0.984 0.004 0.000 0.012 0.000 0.000
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#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6  0.1806     0.6760 0.000 0.000 0.004 0.088 0.000 0.908
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.5691     0.4812 0.276 0.000 0.000 0.204 0.000 0.520
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1176     0.8136 0.956 0.000 0.000 0.020 0.024 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0146     0.8560 0.004 0.000 0.996 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5629     0.4783 0.600 0.284 0.060 0.052 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.1219     0.8382 0.000 0.948 0.000 0.004 0.000 0.048
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.4229     0.7070 0.040 0.000 0.000 0.292 0.000 0.668
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3043     0.7760 0.000 0.796 0.000 0.004 0.004 0.196
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0291     0.8224 0.992 0.004 0.000 0.004 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.3974     0.5304 0.048 0.000 0.000 0.224 0.728 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.2243     0.7620 0.880 0.004 0.112 0.004 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.3547     0.6962 0.000 0.696 0.000 0.004 0.000 0.300
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.1176     0.8124 0.956 0.000 0.000 0.020 0.024 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.5411     0.2928 0.168 0.000 0.000 0.260 0.572 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     5  0.0790     0.7249 0.032 0.000 0.000 0.000 0.968 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0260     0.8220 0.992 0.000 0.000 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.0622     0.6992 0.000 0.012 0.000 0.008 0.000 0.980
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4096     0.6434 0.000 0.000 0.700 0.012 0.020 0.268
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.1204     0.8410 0.000 0.000 0.944 0.056 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.3298     0.7453 0.000 0.756 0.000 0.000 0.008 0.236
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0777     0.8185 0.972 0.024 0.000 0.004 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4938     0.5928 0.700 0.200 0.004 0.052 0.000 0.044
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.5154     0.6664 0.104 0.000 0.004 0.292 0.000 0.600
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.1643     0.8033 0.924 0.008 0.000 0.068 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-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 17541 rows and 500 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 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-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 0.190           0.676       0.825         0.4159 0.556   0.556
#> 3 3 0.223           0.506       0.656         0.3871 0.664   0.478
#> 4 4 0.305           0.462       0.694         0.1383 0.778   0.541
#> 5 5 0.394           0.495       0.683         0.0848 0.842   0.598
#> 6 6 0.459           0.491       0.689         0.0454 0.920   0.743

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000    0.76246 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000    0.76246 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.9209    0.60813 0.336 0.664
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.9087    0.63046 0.324 0.676
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000    0.77412 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.5519    0.78713 0.128 0.872
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.4431    0.79224 0.092 0.908
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.8955    0.65147 0.312 0.688
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.9775    0.43621 0.412 0.588
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.6531    0.73628 0.832 0.168
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.9248    0.53683 0.340 0.660
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.9044    0.64202 0.320 0.680
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.77412 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000    0.77412 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.9954    0.25827 0.460 0.540
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.9775    0.43730 0.412 0.588
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.8713    0.60569 0.708 0.292
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.5294    0.76722 0.120 0.880
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.9087    0.57118 0.324 0.676
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.77412 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000    0.76246 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.77412 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.76246 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.77412 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.5408    0.77316 0.876 0.124
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.77412 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.5737    0.78682 0.136 0.864
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.6148    0.78227 0.152 0.848
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.9044    0.63861 0.320 0.680
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3733    0.77587 0.928 0.072
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.6887    0.76590 0.184 0.816
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.77412 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.9129    0.62407 0.328 0.672
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.9983    0.20282 0.476 0.524
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.9909    0.31747 0.444 0.556
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.8909    0.64185 0.308 0.692
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.1414    0.78244 0.020 0.980
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.9686    0.47944 0.396 0.604
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.76246 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.6048    0.76530 0.852 0.148
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.7815    0.74332 0.232 0.768
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.8443    0.70130 0.272 0.728
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.77412 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.76246 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.8081    0.72445 0.248 0.752
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.9580    0.51532 0.380 0.620
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.9686    0.48143 0.396 0.604
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.9170    0.52593 0.668 0.332
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.3733    0.77587 0.928 0.072
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.3879    0.77934 0.076 0.924
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.9988    0.01494 0.520 0.480
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.9000    0.56183 0.684 0.316
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.9909    0.34872 0.444 0.556
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.2423    0.78769 0.040 0.960
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.5059    0.77690 0.888 0.112
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.9635    0.37686 0.612 0.388
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.77412 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000    0.77412 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.4690    0.79218 0.100 0.900
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.77412 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.7139    0.76059 0.196 0.804
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.77412 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.6712    0.77587 0.176 0.824
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.9850    0.37189 0.428 0.572
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.9393    0.46585 0.644 0.356
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.5519    0.76319 0.872 0.128
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.1184    0.76855 0.984 0.016
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.9970    0.23055 0.468 0.532
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     2  0.9358    0.58043 0.352 0.648
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.6623    0.74976 0.828 0.172
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.9635    0.50141 0.388 0.612
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000    0.76246 1.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.1843    0.78448 0.028 0.972
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.9635    0.50141 0.388 0.612
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.4161    0.79246 0.084 0.916
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.6048    0.76530 0.852 0.148
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.9795    0.42702 0.416 0.584
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9087    0.63032 0.324 0.676
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.7453    0.75342 0.212 0.788
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.2043    0.78498 0.032 0.968
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.7950    0.73070 0.240 0.760
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.5178    0.79035 0.116 0.884
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.5178    0.79283 0.116 0.884
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.9580    0.52442 0.380 0.620
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     2  0.6623    0.77527 0.172 0.828
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.8081    0.65604 0.752 0.248
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.8661    0.61281 0.712 0.288
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.77412 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.77412 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.8207    0.66346 0.744 0.256
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.9896    0.18662 0.560 0.440
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     2  0.9944    0.29163 0.456 0.544
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.9988    0.16702 0.480 0.520
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.7745    0.74159 0.228 0.772
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.9815    0.40363 0.420 0.580
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.9850    0.38322 0.428 0.572
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.2043    0.78498 0.032 0.968
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  1.0000   -0.08877 0.504 0.496
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.9775    0.29735 0.588 0.412
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.8327    0.70977 0.264 0.736
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5629    0.76994 0.132 0.868
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.8661    0.67985 0.288 0.712
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.9963    0.06375 0.536 0.464
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.2603    0.78735 0.044 0.956
#> B23A1419-0406-48BF-813B-B6ED6FD98789     2  0.9000    0.64854 0.316 0.684
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.7219    0.72977 0.200 0.800
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.77412 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.5408    0.77316 0.876 0.124
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.5737    0.78682 0.136 0.864
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.6438    0.77591 0.164 0.836
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.5408    0.77316 0.876 0.124
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.9998   -0.05509 0.508 0.492
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000    0.76246 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000    0.76246 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000    0.76246 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.6623    0.74976 0.828 0.172
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.9044    0.57441 0.320 0.680
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.4562    0.77844 0.904 0.096
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.1184    0.76826 0.984 0.016
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.7602    0.74493 0.220 0.780
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000    0.76246 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000    0.76246 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.9608    0.48549 0.384 0.616
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.9635    0.50141 0.388 0.612
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.8327    0.70588 0.264 0.736
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.7950    0.73131 0.240 0.760
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.9393    0.57857 0.356 0.644
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0000    0.76246 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.3431    0.77959 0.936 0.064
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.5946    0.77022 0.856 0.144
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.9993    0.18692 0.484 0.516
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.4161    0.79204 0.084 0.916
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.5842    0.76695 0.140 0.860
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.6887    0.74164 0.816 0.184
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5519    0.76900 0.128 0.872
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.8081    0.72469 0.248 0.752
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.9087    0.63017 0.324 0.676
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.8081    0.66139 0.752 0.248
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.8499    0.69853 0.276 0.724
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.77412 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.8909    0.56401 0.692 0.308
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.8909    0.56401 0.692 0.308
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.5519    0.77525 0.872 0.128
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.6148    0.76732 0.848 0.152
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.8207    0.66346 0.744 0.256
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.8144    0.72046 0.252 0.748
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4939    0.78953 0.108 0.892
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.9795    0.42628 0.416 0.584
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.77412 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.9977    0.21169 0.472 0.528
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.9608    0.51116 0.384 0.616
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.9170    0.52960 0.668 0.332
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.9044    0.63476 0.320 0.680

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1   0.535   0.707248 0.796 0.176 0.028
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1   0.277   0.731985 0.920 0.008 0.072
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3   0.547   0.611736 0.112 0.072 0.816
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3   0.549   0.613884 0.104 0.080 0.816
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2   0.593   0.865575 0.000 0.644 0.356
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3   0.450   0.428237 0.000 0.196 0.804
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3   0.565   0.105522 0.000 0.312 0.688
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3   0.456   0.615150 0.036 0.112 0.852
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3   0.530   0.616146 0.108 0.068 0.824
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1   0.927   0.536166 0.528 0.240 0.232
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2   0.804  -0.118825 0.064 0.508 0.428
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3   0.401   0.621550 0.028 0.096 0.876
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2   0.581   0.872184 0.000 0.664 0.336
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2   0.593   0.865575 0.000 0.644 0.356
#> 5AB5396F-925B-469C-B240-FB37991004DD     3   0.784   0.500456 0.120 0.220 0.660
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3   0.566   0.612176 0.100 0.092 0.808
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3   0.663  -0.166244 0.444 0.008 0.548
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2   0.620   0.700342 0.012 0.676 0.312
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2   0.790  -0.102052 0.056 0.508 0.436
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2   0.581   0.872184 0.000 0.664 0.336
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1   0.296   0.732419 0.912 0.008 0.080
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2   0.581   0.872184 0.000 0.664 0.336
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1   0.455   0.718856 0.844 0.132 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2   0.581   0.872184 0.000 0.664 0.336
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1   0.615   0.616828 0.664 0.008 0.328
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2   0.581   0.872184 0.000 0.664 0.336
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3   0.468   0.440633 0.004 0.192 0.804
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3   0.441   0.479781 0.004 0.172 0.824
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3   0.429   0.618493 0.032 0.104 0.864
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1   0.713   0.691395 0.720 0.164 0.116
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3   0.390   0.536005 0.008 0.128 0.864
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2   0.581   0.872184 0.000 0.664 0.336
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3   0.532   0.616055 0.104 0.072 0.824
#> C06D8112-0FA0-4607-988D-589D8694743F     3   0.701   0.527192 0.176 0.100 0.724
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3   0.766   0.536472 0.144 0.172 0.684
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3   0.638   0.493341 0.032 0.256 0.712
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2   0.623   0.762754 0.000 0.564 0.436
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3   0.498   0.620107 0.096 0.064 0.840
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1   0.287   0.732092 0.916 0.008 0.076
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1   0.636   0.578475 0.628 0.008 0.364
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3   0.463   0.575228 0.012 0.164 0.824
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3   0.315   0.616942 0.036 0.048 0.916
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2   0.581   0.872184 0.000 0.664 0.336
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1   0.455   0.718856 0.844 0.132 0.024
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3   0.295   0.608213 0.020 0.060 0.920
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3   0.534   0.614883 0.084 0.092 0.824
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3   0.506   0.602408 0.148 0.032 0.820
#> 066B10C1-777F-4863-ACCA-6684310B913E     3   0.922  -0.161079 0.408 0.152 0.440
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1   0.713   0.691395 0.720 0.164 0.116
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2   0.615   0.779688 0.008 0.664 0.328
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3   0.753   0.434291 0.228 0.096 0.676
#> 4379559E-E467-49BD-9673-40A486146A3B     3   0.718  -0.079366 0.408 0.028 0.564
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3   0.546   0.552642 0.204 0.020 0.776
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3   0.611  -0.304239 0.000 0.396 0.604
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1   0.602   0.654439 0.700 0.012 0.288
#> 311D089C-33F1-4722-9118-F56427C5C128     3   0.967   0.099828 0.272 0.264 0.464
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2   0.590   0.865982 0.000 0.648 0.352
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2   0.608   0.838188 0.000 0.612 0.388
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3   0.502   0.325303 0.000 0.240 0.760
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2   0.581   0.872184 0.000 0.664 0.336
#> A77DDA16-167D-4444-8C58-526C99F2B406     3   0.527   0.495620 0.016 0.200 0.784
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2   0.608   0.835923 0.000 0.612 0.388
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3   0.447   0.503762 0.004 0.176 0.820
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3   0.738   0.515665 0.088 0.228 0.684
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3   0.914  -0.081449 0.404 0.144 0.452
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1   0.793   0.653336 0.660 0.140 0.200
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1   0.882   0.626297 0.564 0.280 0.156
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3   0.806   0.478435 0.124 0.236 0.640
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3   0.329   0.627237 0.088 0.012 0.900
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1   0.651   0.525581 0.592 0.008 0.400
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3   0.498   0.608823 0.136 0.036 0.828
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1   0.455   0.718856 0.844 0.132 0.024
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3   0.631  -0.625927 0.000 0.500 0.500
#> DCD81371-253F-4672-AA92-9F27A338F68E     3   0.498   0.608823 0.136 0.036 0.828
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3   0.634  -0.046083 0.008 0.360 0.632
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1   0.636   0.578475 0.628 0.008 0.364
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3   0.521   0.615628 0.108 0.064 0.828
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3   0.576   0.583687 0.056 0.152 0.792
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3   0.498   0.561355 0.036 0.136 0.828
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2   0.631   0.625076 0.000 0.504 0.496
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3   0.270   0.600485 0.016 0.056 0.928
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3   0.537   0.300509 0.004 0.252 0.744
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3   0.562   0.306113 0.008 0.260 0.732
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3   0.524   0.618420 0.072 0.100 0.828
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3   0.410   0.518101 0.008 0.140 0.852
#> 46351E5C-2438-4B6A-8343-DDF329086771     2   0.583   0.871459 0.000 0.660 0.340
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1   0.645   0.550818 0.608 0.008 0.384
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3   0.456   0.585271 0.036 0.112 0.852
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3   0.399   0.612622 0.052 0.064 0.884
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3   0.631  -0.600436 0.000 0.488 0.512
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3   0.672   0.085783 0.380 0.016 0.604
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3   0.590  -0.130591 0.000 0.352 0.648
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     3   0.638   0.493341 0.032 0.256 0.712
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2   0.581   0.872184 0.000 0.664 0.336
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3   0.327   0.591596 0.016 0.080 0.904
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1   0.915   0.596192 0.536 0.272 0.192
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2   0.595   0.862664 0.000 0.640 0.360
#> 31322670-76A2-4308-A71F-D8E00049519D     2   0.620   0.811590 0.008 0.656 0.336
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#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3   0.483   0.611838 0.068 0.084 0.848
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1   0.455   0.718856 0.844 0.132 0.024
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     3   0.445   0.431996 0.000 0.192 0.808
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1   0.575   0.647047 0.700 0.004 0.296
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3   0.542   0.479641 0.240 0.008 0.752
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3   0.429   0.623492 0.060 0.068 0.872
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2   0.581   0.872184 0.000 0.664 0.336
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2   0.590   0.867815 0.000 0.648 0.352
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1   0.654   0.517133 0.584 0.008 0.408
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1   0.668   0.300714 0.500 0.008 0.492
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1   0.903   0.437160 0.532 0.160 0.308
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3   0.664  -0.183667 0.448 0.008 0.544
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2   0.581   0.872184 0.000 0.664 0.336
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2   0.581   0.872184 0.000 0.664 0.336
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3   0.683  -0.308767 0.492 0.012 0.496
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3   0.654   0.322312 0.304 0.024 0.672
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3   0.507   0.544277 0.196 0.012 0.792
#> EE40EE80-4520-4643-B906-48246BA616A7     3   0.817   0.447534 0.120 0.256 0.624
#> C075F09E-623C-46ED-B927-889B48F450B3     3   0.456   0.585271 0.036 0.112 0.852
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3   0.734   0.526570 0.100 0.204 0.696
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3   0.665   0.582330 0.136 0.112 0.752
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2   0.631   0.625076 0.000 0.504 0.496
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3   0.546   0.460033 0.244 0.008 0.748
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3   0.669   0.278533 0.308 0.028 0.664
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3   0.436   0.611858 0.052 0.080 0.868
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     3   0.706  -0.249938 0.020 0.460 0.520
#> 816CF68B-8476-4960-9F05-FB959A686323     3   0.483   0.611838 0.068 0.084 0.848
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3   0.843   0.377684 0.240 0.148 0.612
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3   0.627  -0.461995 0.000 0.452 0.548
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3   0.389   0.621276 0.024 0.096 0.880
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2   0.737   0.222394 0.032 0.524 0.444
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2   0.586   0.871176 0.000 0.656 0.344
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1   0.623   0.607843 0.652 0.008 0.340
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3   0.468   0.440633 0.004 0.192 0.804
#> 5E03E52F-957D-455B-A007-19714FAA818A     3   0.341   0.530377 0.000 0.124 0.876
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1   0.623   0.607843 0.652 0.008 0.340
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3   0.701   0.486775 0.208 0.080 0.712
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1   0.547   0.708267 0.792 0.176 0.032
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1   0.287   0.732092 0.916 0.008 0.076
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1   0.287   0.732092 0.916 0.008 0.076
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1   0.651   0.525581 0.592 0.008 0.400
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2   0.789  -0.087348 0.056 0.512 0.432
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1   0.588   0.665249 0.716 0.012 0.272
#> C33059A9-A313-4806-B43B-0031365F3BE4     1   0.329   0.731132 0.900 0.012 0.088
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3   0.312   0.586767 0.012 0.080 0.908
#> 1122039D-5785-4F70-9916-17C585453512     1   0.296   0.732419 0.912 0.008 0.080
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1   0.455   0.718856 0.844 0.132 0.024
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3   0.757   0.498848 0.088 0.248 0.664
#> C56C7ED7-A684-40CC-B426-B108E2248467     3   0.498   0.608823 0.136 0.036 0.828
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3   0.475   0.582690 0.024 0.144 0.832
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3   0.537   0.567054 0.048 0.140 0.812
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3   0.523   0.632614 0.104 0.068 0.828
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1   0.296   0.732419 0.912 0.008 0.080
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1   0.468   0.709250 0.804 0.004 0.192
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1   0.693   0.619943 0.640 0.032 0.328
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3   0.516   0.491625 0.216 0.008 0.776
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3   0.533   0.224554 0.000 0.272 0.728
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3   0.707  -0.238753 0.020 0.472 0.508
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1   0.658   0.498103 0.572 0.008 0.420
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2   0.655   0.619858 0.012 0.616 0.372
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3   0.321   0.605663 0.028 0.060 0.912
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3   0.667   0.534824 0.040 0.264 0.696
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1   0.965   0.390229 0.452 0.228 0.320
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3   0.397   0.613643 0.024 0.100 0.876
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2   0.581   0.872184 0.000 0.664 0.336
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1   0.925   0.255065 0.452 0.156 0.392
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1   0.925   0.255065 0.452 0.156 0.392
#> EB7883EB-0079-4548-9132-169E94A698BA     1   0.688   0.629969 0.648 0.032 0.320
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1   0.692   0.582424 0.608 0.024 0.368
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3   0.683  -0.308767 0.492 0.012 0.496
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3   0.288   0.609157 0.024 0.052 0.924
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3   0.654  -0.367020 0.008 0.408 0.584
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3   0.512   0.583482 0.160 0.028 0.812
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2   0.581   0.872184 0.000 0.664 0.336
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3   0.806   0.473132 0.132 0.224 0.644
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3   0.455   0.616852 0.132 0.024 0.844
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3   0.651  -0.004992 0.400 0.008 0.592
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3   0.432   0.620706 0.044 0.088 0.868

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.4222     0.4929 0.728 0.000 0.000 0.272
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.4212     0.6402 0.772 0.000 0.216 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3345     0.5981 0.012 0.124 0.860 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.3326     0.6009 0.008 0.132 0.856 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.1837     0.7756 0.000 0.944 0.028 0.028
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.5371     0.4037 0.000 0.364 0.616 0.020
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.5696     0.0350 0.000 0.484 0.492 0.024
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.6594     0.5255 0.012 0.152 0.664 0.172
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.7104     0.5003 0.056 0.104 0.656 0.184
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.6626     0.1010 0.384 0.000 0.088 0.528
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4  0.7198     0.4573 0.016 0.244 0.144 0.596
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.6333     0.5236 0.008 0.136 0.680 0.176
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0469     0.7724 0.000 0.988 0.000 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.1837     0.7756 0.000 0.944 0.028 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.7140     0.1596 0.040 0.048 0.436 0.476
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.7271     0.4705 0.052 0.104 0.632 0.212
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.5321     0.2939 0.256 0.004 0.704 0.036
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4922     0.5321 0.000 0.736 0.036 0.228
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.7296     0.4363 0.016 0.260 0.144 0.580
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.4364     0.6357 0.764 0.000 0.220 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0469     0.7724 0.000 0.988 0.000 0.012
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2408     0.6216 0.896 0.000 0.000 0.104
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.6079    -0.2774 0.464 0.000 0.492 0.044
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0376     0.7769 0.000 0.992 0.004 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.5436     0.4172 0.000 0.356 0.620 0.024
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.5423     0.4634 0.000 0.332 0.640 0.028
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.6782     0.4893 0.008 0.148 0.632 0.212
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.6079     0.4640 0.628 0.000 0.072 0.300
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.4567     0.5427 0.000 0.276 0.716 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.3216     0.6010 0.008 0.124 0.864 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.6515     0.4672 0.084 0.048 0.700 0.168
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.7965     0.1533 0.076 0.076 0.504 0.344
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.7625     0.0237 0.000 0.208 0.432 0.360
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.4174     0.7262 0.000 0.816 0.140 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.6896     0.5168 0.048 0.108 0.672 0.172
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3982     0.6386 0.776 0.000 0.220 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.6055    -0.2005 0.436 0.000 0.520 0.044
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.6438     0.5271 0.004 0.208 0.656 0.132
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.4303     0.6042 0.004 0.184 0.792 0.020
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0376     0.7767 0.000 0.992 0.004 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.2408     0.6216 0.896 0.000 0.000 0.104
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.4356     0.5970 0.004 0.200 0.780 0.016
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.7180     0.4725 0.040 0.120 0.636 0.204
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.3030     0.5791 0.020 0.060 0.900 0.020
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.8737     0.2322 0.308 0.036 0.300 0.356
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.6079     0.4640 0.628 0.000 0.072 0.300
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.4050     0.6234 0.000 0.808 0.024 0.168
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3  0.7220     0.4113 0.128 0.048 0.644 0.180
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.6311     0.3325 0.240 0.008 0.660 0.092
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.4227     0.5620 0.076 0.060 0.844 0.020
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.4964     0.3824 0.000 0.616 0.380 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.5928     0.3721 0.508 0.000 0.456 0.036
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.5513     0.5349 0.060 0.012 0.192 0.736
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.1833     0.7698 0.000 0.944 0.024 0.032
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.2402     0.7674 0.000 0.912 0.076 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.5744     0.2253 0.000 0.436 0.536 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.7302     0.3835 0.000 0.332 0.500 0.168
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.2281     0.7614 0.000 0.904 0.096 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.6483     0.4614 0.000 0.312 0.592 0.096
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     4  0.6500     0.1229 0.008 0.052 0.448 0.492
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.8917     0.3278 0.272 0.056 0.272 0.400
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.7255     0.3554 0.556 0.016 0.116 0.312
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.4535     0.1467 0.292 0.000 0.004 0.704
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     4  0.6868     0.2481 0.028 0.048 0.404 0.520
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.4830     0.6056 0.036 0.136 0.800 0.028
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.5969    -0.0814 0.392 0.000 0.564 0.044
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.2563     0.5811 0.012 0.060 0.916 0.012
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.2868     0.6147 0.864 0.000 0.000 0.136
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.4252     0.6355 0.000 0.744 0.252 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.2563     0.5811 0.012 0.060 0.916 0.012
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.6532     0.1569 0.000 0.504 0.420 0.076
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.6055    -0.2005 0.436 0.000 0.520 0.044
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.7050     0.5004 0.056 0.100 0.660 0.184
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3  0.7722     0.3248 0.016 0.176 0.520 0.288
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.4485     0.5746 0.000 0.248 0.740 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.4675     0.6463 0.000 0.736 0.244 0.020
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.4979     0.5936 0.004 0.224 0.740 0.032
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#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.5273     0.1453 0.000 0.536 0.456 0.008
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.2704     0.7485 0.000 0.876 0.124 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     1  0.4331     0.4850 0.712 0.000 0.000 0.288
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.5615     0.5247 0.612 0.000 0.356 0.032
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.6607     0.4596 0.000 0.592 0.296 0.112
#> D85CB054-7F54-4383-96C0-6C99761B84E7     3  0.6435     0.5262 0.008 0.164 0.672 0.156
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.2408     0.6216 0.896 0.000 0.000 0.104
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.2563     0.5811 0.012 0.060 0.916 0.012
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     3  0.6895     0.0357 0.012 0.072 0.488 0.428
#> 17CA5D73-4384-4645-83F8-587847043DD2     3  0.6060    -0.2128 0.440 0.000 0.516 0.044
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.6238     0.4678 0.620 0.000 0.084 0.296
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.3377     0.7362 0.000 0.848 0.140 0.012
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     3  0.6933     0.4274 0.108 0.044 0.664 0.184
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.5464     0.4559 0.184 0.028 0.748 0.040
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.5382     0.4636 0.176 0.028 0.756 0.040
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.5244     0.5170 0.600 0.000 0.388 0.012
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     4  0.7252     0.1120 0.000 0.420 0.144 0.436
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.2408     0.6216 0.896 0.000 0.000 0.104
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.7205     0.2996 0.000 0.532 0.172 0.296
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     3  0.5844     0.5681 0.008 0.168 0.720 0.104
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.4408     0.5883 0.004 0.232 0.756 0.008
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.6120     0.5280 0.000 0.296 0.628 0.076
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.6102     0.2197 0.000 0.532 0.420 0.048
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.3699     0.5701 0.052 0.056 0.872 0.020
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.5865     0.2532 0.000 0.552 0.412 0.036
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.6810    -0.1948 0.424 0.004 0.488 0.084
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.7509     0.0900 0.000 0.452 0.188 0.360
#> 72DDC907-0901-4E61-83CF-38500D03FABC     3  0.8589    -0.0590 0.244 0.036 0.416 0.304
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.5435     0.2404 0.000 0.420 0.564 0.016
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.4188     0.5786 0.004 0.244 0.752 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.4524     0.5929 0.000 0.204 0.768 0.028
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.5430     0.6096 0.036 0.180 0.752 0.032
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.7246    -0.0126 0.008 0.112 0.468 0.412
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.3585     0.6008 0.004 0.164 0.828 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2408     0.6216 0.896 0.000 0.000 0.104
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     3  0.5220     0.4202 0.000 0.352 0.632 0.016
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.6060     0.3821 0.516 0.000 0.440 0.044
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.4959     0.5408 0.096 0.056 0.808 0.040
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.6542     0.5235 0.028 0.116 0.688 0.168
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0469     0.7724 0.000 0.988 0.000 0.012
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.1109     0.7783 0.000 0.968 0.028 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.5947    -0.0654 0.384 0.000 0.572 0.044
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.6217     0.1820 0.316 0.016 0.624 0.044
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.8347    -0.0830 0.424 0.036 0.176 0.364
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3  0.5279     0.2870 0.252 0.000 0.704 0.044
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3  0.5790     0.1879 0.304 0.004 0.648 0.044
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4832     0.4982 0.144 0.036 0.796 0.024
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.4161     0.5664 0.068 0.064 0.848 0.020
#> EE40EE80-4520-4643-B906-48246BA616A7     4  0.6398     0.2538 0.020 0.032 0.408 0.540
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4284     0.5891 0.000 0.224 0.764 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.7010    -0.0616 0.016 0.072 0.460 0.452
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     3  0.8072     0.3230 0.072 0.108 0.540 0.280
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.4675     0.6463 0.000 0.736 0.244 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.4649     0.5374 0.092 0.048 0.824 0.036
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.6186     0.4563 0.160 0.028 0.716 0.096
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.3969     0.6018 0.000 0.180 0.804 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.7468     0.1383 0.000 0.464 0.184 0.352
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.3585     0.6008 0.004 0.164 0.828 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.8592    -0.1311 0.140 0.068 0.412 0.380
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.5206     0.5372 0.000 0.668 0.308 0.024
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.6165     0.5290 0.008 0.132 0.696 0.164
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     4  0.7149     0.1394 0.000 0.416 0.132 0.452
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0672     0.7783 0.000 0.984 0.008 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     3  0.6071    -0.2537 0.452 0.000 0.504 0.044
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.5436     0.4172 0.000 0.356 0.620 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.4722     0.5202 0.000 0.300 0.692 0.008
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     3  0.6071    -0.2537 0.452 0.000 0.504 0.044
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.8082     0.4264 0.140 0.092 0.584 0.184
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.4331     0.4850 0.712 0.000 0.000 0.288
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.3982     0.6386 0.776 0.000 0.220 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.3982     0.6386 0.776 0.000 0.220 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.5969    -0.0814 0.392 0.000 0.564 0.044
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.7319     0.4306 0.016 0.264 0.144 0.576
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.6140     0.3913 0.500 0.000 0.452 0.048
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.4122     0.6322 0.760 0.000 0.236 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.4475     0.5858 0.004 0.240 0.748 0.008
#> 1122039D-5785-4F70-9916-17C585453512     1  0.4364     0.6357 0.764 0.000 0.220 0.016
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2704     0.6171 0.876 0.000 0.000 0.124
#> E678189F-D5CF-4C45-8E53-58ECB8448058     4  0.7474     0.1303 0.020 0.104 0.420 0.456
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.2563     0.5811 0.012 0.060 0.916 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3  0.7346     0.4138 0.004 0.224 0.552 0.220
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.4188     0.5786 0.004 0.244 0.752 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.5726     0.5901 0.040 0.120 0.760 0.080
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.4364     0.6357 0.764 0.000 0.220 0.016
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.5436     0.5341 0.620 0.000 0.356 0.024
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.7107     0.3089 0.464 0.012 0.436 0.088
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3720     0.5440 0.064 0.032 0.872 0.032
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.5277     0.1604 0.000 0.460 0.532 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.7502     0.1114 0.000 0.456 0.188 0.356
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.5911    -0.0375 0.372 0.000 0.584 0.044
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5759     0.4531 0.000 0.668 0.064 0.268
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.4137     0.5976 0.000 0.208 0.780 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.7213     0.2841 0.008 0.136 0.552 0.304
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     4  0.7044     0.3117 0.276 0.000 0.164 0.560
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.6549     0.5496 0.004 0.200 0.648 0.148
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     4  0.8634     0.2730 0.320 0.036 0.248 0.396
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.8634     0.2730 0.320 0.036 0.248 0.396
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.6949     0.3130 0.468 0.008 0.440 0.084
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.7009    -0.2267 0.440 0.012 0.468 0.080
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.5790     0.1879 0.304 0.004 0.648 0.044
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.3978     0.5989 0.000 0.192 0.796 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4776     0.4142 0.000 0.624 0.376 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.2894     0.5712 0.024 0.048 0.908 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0188     0.7761 0.000 0.996 0.000 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     4  0.6922     0.1576 0.032 0.044 0.436 0.488
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.4010     0.5954 0.036 0.100 0.848 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.4831     0.3736 0.208 0.000 0.752 0.040
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.6839     0.5128 0.016 0.144 0.644 0.196

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.5000     0.7817 0.004 0.000 0.068 0.240 0.688
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.2771     0.2367 0.012 0.000 0.000 0.860 0.128
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.3896     0.6328 0.828 0.020 0.024 0.116 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.3491     0.6457 0.852 0.020 0.028 0.096 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2605     0.7878 0.056 0.896 0.044 0.000 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.4587     0.6005 0.748 0.188 0.052 0.000 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.5524     0.4445 0.632 0.292 0.056 0.000 0.020
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.5052     0.5817 0.744 0.040 0.164 0.048 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.5794     0.5289 0.692 0.020 0.132 0.144 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.7537    -0.1356 0.048 0.000 0.400 0.224 0.328
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     3  0.4746     0.4604 0.060 0.076 0.792 0.008 0.064
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4728     0.5884 0.768 0.036 0.156 0.032 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.1116     0.7788 0.004 0.964 0.028 0.000 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.2605     0.7878 0.056 0.896 0.044 0.000 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.7032     0.2745 0.388 0.008 0.464 0.084 0.056
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5981     0.4834 0.676 0.012 0.164 0.124 0.024
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.4594     0.2783 0.484 0.000 0.004 0.508 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4836     0.4406 0.016 0.660 0.308 0.004 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     3  0.4787     0.4642 0.060 0.088 0.788 0.008 0.056
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0451     0.7912 0.008 0.988 0.004 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.2464     0.2863 0.012 0.000 0.004 0.892 0.092
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1329     0.7765 0.004 0.956 0.032 0.000 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.4060     0.8473 0.000 0.000 0.000 0.360 0.640
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0451     0.7912 0.008 0.988 0.004 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.3766     0.6342 0.268 0.000 0.000 0.728 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0510     0.7939 0.016 0.984 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.4892     0.6045 0.740 0.184 0.056 0.008 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.4546     0.6192 0.764 0.164 0.060 0.004 0.008
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.5455     0.5465 0.712 0.048 0.188 0.044 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.7318    -0.4047 0.040 0.000 0.188 0.392 0.380
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.3949     0.6513 0.828 0.108 0.036 0.016 0.012
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0451     0.7912 0.008 0.988 0.004 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.3308     0.6432 0.860 0.016 0.024 0.096 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.6233     0.3991 0.624 0.008 0.140 0.212 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.7378     0.1114 0.508 0.024 0.304 0.120 0.044
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.7098     0.2446 0.388 0.136 0.436 0.036 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.5248     0.6562 0.192 0.700 0.096 0.000 0.012
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#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.7356     0.2988 0.380 0.052 0.464 0.060 0.044
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.3558     0.5903 0.824 0.008 0.008 0.148 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.6650     0.4425 0.612 0.124 0.208 0.048 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.4440     0.6568 0.812 0.088 0.036 0.048 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.5254     0.6310 0.748 0.052 0.060 0.132 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.2464     0.2863 0.012 0.000 0.004 0.892 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.3386     0.5373 0.128 0.000 0.000 0.832 0.040
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.5369     0.6147 0.280 0.000 0.040 0.652 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.3809     0.4569 0.736 0.000 0.000 0.256 0.008
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.5134     0.4957 0.664 0.280 0.036 0.000 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3  0.6599     0.3806 0.172 0.268 0.544 0.004 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.4286     0.5647 0.340 0.000 0.004 0.652 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5610     0.2532 0.040 0.540 0.404 0.004 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.3067     0.6733 0.880 0.068 0.016 0.032 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.5771     0.2935 0.596 0.044 0.332 0.008 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.7972     0.1688 0.112 0.000 0.428 0.212 0.248
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5154     0.6196 0.760 0.064 0.120 0.044 0.012
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0740     0.7930 0.008 0.980 0.008 0.000 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.8555     0.2266 0.228 0.004 0.336 0.264 0.168
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.8555     0.2266 0.228 0.004 0.336 0.264 0.168
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.5112     0.6237 0.276 0.000 0.036 0.668 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072     4  0.4791     0.6015 0.316 0.000 0.024 0.652 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.4758     0.3962 0.432 0.000 0.012 0.552 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.2481     0.6717 0.908 0.056 0.008 0.024 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.5688     0.1552 0.452 0.496 0.024 0.016 0.012
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.3825     0.5591 0.796 0.004 0.012 0.176 0.012
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0451     0.7912 0.008 0.988 0.004 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.6978     0.2685 0.388 0.008 0.468 0.084 0.052
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.3767     0.5965 0.800 0.024 0.000 0.168 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4557    -0.1555 0.516 0.000 0.000 0.476 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5353     0.5675 0.732 0.040 0.156 0.064 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.3649    0.66628 0.000 0.000 0.196 0.764 0.000 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.4742    0.16705 0.000 0.000 0.052 0.292 0.012 0.644
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.3509    0.56340 0.788 0.000 0.016 0.000 0.016 0.180
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.3898    0.57994 0.776 0.008 0.016 0.004 0.016 0.180
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3249    0.73648 0.096 0.836 0.008 0.000 0.060 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.3232    0.61432 0.840 0.112 0.008 0.000 0.032 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.4337    0.48607 0.724 0.200 0.008 0.000 0.068 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.5896    0.55479 0.652 0.008 0.104 0.000 0.108 0.128
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6488    0.41849 0.548 0.008 0.132 0.000 0.068 0.244
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     3  0.7244    0.13198 0.016 0.000 0.480 0.236 0.136 0.132
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3592    0.29962 0.012 0.004 0.184 0.016 0.784 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5767    0.55818 0.664 0.008 0.120 0.000 0.088 0.120
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0937    0.74361 0.000 0.960 0.000 0.000 0.040 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.3249    0.73648 0.096 0.836 0.008 0.000 0.060 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.7667    0.24618 0.252 0.000 0.364 0.008 0.228 0.148
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.6547    0.39589 0.532 0.000 0.152 0.000 0.088 0.228
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.3883    0.51273 0.332 0.000 0.012 0.000 0.000 0.656
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4041    0.22488 0.004 0.584 0.004 0.000 0.408 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.3344    0.32818 0.012 0.008 0.164 0.008 0.808 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0405    0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     6  0.4686    0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.1075    0.74007 0.000 0.952 0.000 0.000 0.048 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0405    0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.3719    0.65380 0.148 0.000 0.012 0.048 0.000 0.792
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0363    0.76717 0.012 0.988 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.3534    0.61989 0.828 0.108 0.008 0.000 0.036 0.020
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.3787    0.63407 0.824 0.088 0.016 0.000 0.040 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.6319    0.51443 0.616 0.016 0.132 0.000 0.096 0.140
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.7032    0.36190 0.020 0.000 0.284 0.424 0.036 0.236
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.2257    0.64607 0.904 0.048 0.000 0.000 0.008 0.040
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0405    0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.3898    0.57629 0.776 0.008 0.016 0.004 0.016 0.180
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.6688    0.17834 0.460 0.004 0.128 0.000 0.072 0.336
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.8097   -0.04123 0.368 0.008 0.244 0.024 0.152 0.204
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     5  0.8323    0.13053 0.284 0.100 0.152 0.000 0.348 0.116
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.5159    0.53237 0.240 0.636 0.004 0.000 0.116 0.004
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.6207    0.44355 0.580 0.004 0.128 0.000 0.064 0.224
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.4684    0.20807 0.000 0.000 0.056 0.268 0.012 0.664
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     6  0.3897    0.66134 0.164 0.000 0.016 0.036 0.004 0.780
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.5328    0.60190 0.720 0.028 0.088 0.000 0.104 0.060
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.3169    0.62897 0.832 0.008 0.008 0.000 0.016 0.136
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0820    0.76793 0.016 0.972 0.000 0.000 0.012 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.2809    0.64423 0.872 0.012 0.020 0.000 0.008 0.088
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.6648    0.44910 0.564 0.004 0.168 0.008 0.080 0.176
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.4491    0.47788 0.692 0.000 0.024 0.004 0.024 0.256
#> 066B10C1-777F-4863-ACCA-6684310B913E     3  0.8452    0.32497 0.176 0.000 0.308 0.108 0.112 0.296
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.7032    0.36190 0.020 0.000 0.284 0.424 0.036 0.236
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.3804    0.39734 0.008 0.656 0.000 0.000 0.336 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.6839    0.00709 0.412 0.004 0.124 0.004 0.072 0.384
#> 4379559E-E467-49BD-9673-40A486146A3B     6  0.5155    0.43659 0.348 0.000 0.044 0.008 0.016 0.584
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.5120    0.41473 0.656 0.000 0.024 0.032 0.024 0.264
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4537    0.10595 0.572 0.400 0.008 0.000 0.016 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.4107    0.63427 0.124 0.000 0.020 0.080 0.000 0.776
#> 311D089C-33F1-4722-9118-F56427C5C128     3  0.6367    0.28517 0.032 0.004 0.556 0.020 0.272 0.116
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.3316    0.69596 0.052 0.812 0.000 0.000 0.136 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.4341    0.62733 0.216 0.712 0.004 0.000 0.068 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.4430    0.52773 0.732 0.188 0.004 0.000 0.064 0.012
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0260    0.76671 0.008 0.992 0.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.7344    0.42831 0.540 0.148 0.084 0.000 0.132 0.096
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3301    0.66768 0.216 0.772 0.004 0.000 0.008 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.6000    0.58378 0.672 0.112 0.052 0.000 0.092 0.072
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3  0.7600    0.20135 0.264 0.004 0.344 0.000 0.248 0.140
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     3  0.8664    0.35885 0.216 0.004 0.348 0.132 0.124 0.176
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.7860    0.16480 0.072 0.000 0.288 0.356 0.052 0.232
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     3  0.4951    0.05321 0.000 0.000 0.600 0.332 0.056 0.012
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3  0.7569    0.23918 0.212 0.004 0.392 0.004 0.256 0.132
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.3651    0.54757 0.736 0.008 0.004 0.000 0.004 0.248
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.3329    0.66081 0.180 0.000 0.012 0.012 0.000 0.796
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     1  0.4345    0.49105 0.708 0.000 0.024 0.004 0.020 0.244
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.1856    0.77605 0.000 0.000 0.032 0.920 0.000 0.048
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.4709    0.40696 0.400 0.556 0.004 0.000 0.040 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     1  0.4345    0.49105 0.708 0.000 0.024 0.004 0.020 0.244
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.5892    0.30492 0.588 0.252 0.036 0.000 0.120 0.004
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     6  0.3897    0.66134 0.164 0.000 0.016 0.036 0.004 0.780
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.6387    0.41488 0.552 0.004 0.132 0.000 0.068 0.244
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.8042    0.22745 0.424 0.068 0.204 0.000 0.172 0.132
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.3064    0.64558 0.860 0.056 0.004 0.000 0.012 0.068
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.5293    0.34703 0.408 0.500 0.004 0.000 0.088 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.3296    0.65243 0.852 0.020 0.024 0.000 0.020 0.084
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     1  0.3887    0.54732 0.776 0.172 0.008 0.000 0.036 0.008
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.5706    0.49123 0.668 0.140 0.028 0.000 0.132 0.032
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.7050    0.42139 0.528 0.024 0.176 0.000 0.096 0.176
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.3241    0.65927 0.852 0.080 0.008 0.000 0.016 0.044
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.2263    0.75674 0.056 0.896 0.000 0.000 0.048 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     6  0.3338    0.66310 0.172 0.000 0.008 0.020 0.000 0.800
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     1  0.3056    0.64653 0.856 0.048 0.004 0.000 0.008 0.084
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.2711    0.63136 0.860 0.012 0.000 0.000 0.012 0.116
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.5169    0.38383 0.380 0.536 0.004 0.000 0.080 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     6  0.4254    0.33225 0.404 0.000 0.020 0.000 0.000 0.576
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.4329    0.27298 0.624 0.352 0.008 0.000 0.012 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     5  0.8323    0.13053 0.284 0.100 0.152 0.000 0.348 0.116
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0405    0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.2823    0.65593 0.884 0.036 0.012 0.000 0.020 0.048
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     3  0.4868    0.11030 0.000 0.000 0.632 0.296 0.060 0.012
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2695    0.72812 0.144 0.844 0.004 0.000 0.008 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.3490    0.51499 0.008 0.724 0.000 0.000 0.268 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     6  0.4578    0.50657 0.056 0.000 0.044 0.136 0.008 0.756
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.4676    0.43129 0.384 0.572 0.004 0.000 0.040 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.3914    0.55929 0.740 0.012 0.016 0.000 0.004 0.228
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     6  0.4376    0.52025 0.056 0.000 0.036 0.140 0.004 0.764
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.7056    0.35513 0.536 0.200 0.048 0.000 0.152 0.064
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     1  0.5151    0.45855 0.676 0.200 0.012 0.000 0.100 0.012
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     6  0.4864    0.63888 0.196 0.000 0.044 0.036 0.012 0.712
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> D09064DF-70AE-4A49-9F70-2A8093C96724     6  0.4521    0.60498 0.268 0.000 0.004 0.036 0.012 0.680
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.4300    0.62721 0.768 0.024 0.032 0.000 0.020 0.156
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     5  0.6661    0.42017 0.284 0.180 0.044 0.000 0.484 0.008
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#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     6  0.3863    0.66304 0.164 0.000 0.012 0.048 0.000 0.776
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     6  0.4684    0.20807 0.000 0.000 0.056 0.268 0.012 0.664
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     1  0.3787    0.63407 0.824 0.088 0.016 0.000 0.040 0.032
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.6681    0.45802 0.560 0.008 0.148 0.000 0.120 0.164
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.4078    0.37102 0.676 0.300 0.008 0.000 0.016 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.3895    0.60411 0.272 0.708 0.008 0.000 0.008 0.004
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     4  0.3766    0.65065 0.000 0.000 0.212 0.748 0.000 0.040
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0260    0.76671 0.008 0.992 0.000 0.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0405    0.76571 0.008 0.988 0.000 0.000 0.004 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     6  0.4578    0.50657 0.056 0.000 0.044 0.136 0.008 0.756
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.6225   -0.12027 0.408 0.340 0.008 0.000 0.244 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.5658    0.56817 0.676 0.008 0.112 0.000 0.108 0.096
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     1  0.4345    0.49105 0.708 0.000 0.024 0.004 0.020 0.244
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.7699   -0.19082 0.324 0.008 0.304 0.000 0.216 0.148
#> 17CA5D73-4384-4645-83F8-587847043DD2     6  0.3601    0.66164 0.160 0.000 0.008 0.040 0.000 0.792
#> 40467950-A95C-4731-AD93-0A128442C837     4  0.7159    0.32652 0.024 0.000 0.272 0.400 0.036 0.268
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.4770    0.53882 0.284 0.640 0.004 0.000 0.072 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.6918    0.06458 0.420 0.004 0.132 0.004 0.076 0.364
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     6  0.4304    0.23736 0.448 0.000 0.008 0.000 0.008 0.536
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     6  0.4312    0.21236 0.456 0.000 0.008 0.000 0.008 0.528
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     6  0.4835    0.54795 0.088 0.000 0.032 0.152 0.004 0.724
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     5  0.2468    0.51011 0.016 0.096 0.008 0.000 0.880 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     5  0.5820    0.54997 0.152 0.252 0.024 0.000 0.572 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.4936    0.61505 0.740 0.016 0.084 0.000 0.044 0.116
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.2812    0.64801 0.868 0.040 0.004 0.000 0.004 0.084
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.4814    0.64807 0.764 0.080 0.060 0.000 0.032 0.064
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.5163    0.32750 0.608 0.276 0.004 0.000 0.112 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.4052    0.35824 0.628 0.000 0.016 0.000 0.000 0.356
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.5192    0.29542 0.596 0.292 0.004 0.000 0.108 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     6  0.4864    0.63888 0.196 0.000 0.044 0.036 0.012 0.712
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     5  0.5963    0.57429 0.144 0.172 0.052 0.000 0.624 0.008
#> 72DDC907-0901-4E61-83CF-38500D03FABC     6  0.7840   -0.07845 0.228 0.000 0.256 0.044 0.088 0.384
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     1  0.4917    0.52765 0.708 0.192 0.008 0.000 0.056 0.036
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     1  0.3815    0.63077 0.820 0.052 0.012 0.000 0.028 0.088
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.3041    0.65088 0.864 0.016 0.016 0.000 0.020 0.084
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.4532    0.60379 0.728 0.028 0.020 0.000 0.020 0.204
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.7849   -0.20582 0.324 0.020 0.256 0.000 0.276 0.124
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     1  0.3284    0.60850 0.832 0.016 0.012 0.000 0.012 0.128
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.1588    0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     1  0.3558    0.62061 0.832 0.088 0.008 0.000 0.052 0.020
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     6  0.4188    0.58962 0.096 0.000 0.036 0.076 0.004 0.788
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.4256    0.20558 0.564 0.000 0.012 0.004 0.000 0.420
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.6148    0.49269 0.604 0.008 0.128 0.000 0.064 0.196
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0937    0.74361 0.000 0.960 0.000 0.000 0.040 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.2488    0.73868 0.124 0.864 0.004 0.000 0.008 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     6  0.3673    0.66242 0.204 0.000 0.008 0.024 0.000 0.764
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     6  0.4172    0.57636 0.300 0.000 0.012 0.016 0.000 0.672
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     3  0.8461    0.21596 0.116 0.000 0.348 0.232 0.108 0.196
#> 887E7408-C7D7-420F-A763-0EE70A316D17     6  0.3986    0.51849 0.316 0.000 0.020 0.000 0.000 0.664
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0260    0.76671 0.008 0.992 0.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0260    0.76671 0.008 0.992 0.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     6  0.4103    0.57871 0.292 0.000 0.008 0.008 0.008 0.684
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.4403   -0.00910 0.520 0.000 0.012 0.000 0.008 0.460
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.4088    0.33104 0.616 0.000 0.016 0.000 0.000 0.368
#> EE40EE80-4520-4643-B906-48246BA616A7     3  0.7534    0.25105 0.208 0.004 0.384 0.000 0.252 0.152
#> C075F09E-623C-46ED-B927-889B48F450B3     1  0.3056    0.64685 0.856 0.048 0.004 0.000 0.008 0.084
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     3  0.7606    0.18186 0.304 0.004 0.320 0.000 0.232 0.140
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.7627    0.18583 0.440 0.004 0.232 0.024 0.104 0.196
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.5293    0.34703 0.408 0.500 0.004 0.000 0.088 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.4344    0.16703 0.556 0.000 0.016 0.000 0.004 0.424
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     6  0.5198    0.12234 0.456 0.000 0.048 0.004 0.012 0.480
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.2957    0.63724 0.860 0.020 0.008 0.000 0.012 0.100
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     5  0.5743    0.57660 0.152 0.180 0.036 0.000 0.628 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.3406    0.60689 0.820 0.016 0.012 0.000 0.012 0.140
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     3  0.8321    0.27040 0.288 0.004 0.332 0.056 0.136 0.184
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     1  0.5411   -0.16267 0.472 0.432 0.008 0.000 0.088 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.5643    0.56904 0.676 0.008 0.112 0.000 0.084 0.120
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.2804    0.51700 0.016 0.108 0.016 0.000 0.860 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1649    0.76481 0.036 0.932 0.000 0.000 0.032 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.3627    0.65787 0.152 0.000 0.012 0.040 0.000 0.796
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.3534    0.61989 0.828 0.108 0.008 0.000 0.036 0.020
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.2767    0.65196 0.880 0.068 0.004 0.000 0.020 0.028
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.3627    0.65787 0.152 0.000 0.012 0.040 0.000 0.796
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.6555    0.17795 0.460 0.000 0.124 0.004 0.060 0.352
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.3766    0.65065 0.000 0.000 0.212 0.748 0.000 0.040
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.4684    0.20807 0.000 0.000 0.056 0.268 0.012 0.664
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.4684    0.20807 0.000 0.000 0.056 0.268 0.012 0.664
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.3329    0.66081 0.180 0.000 0.012 0.012 0.000 0.796
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.3308    0.33072 0.012 0.008 0.160 0.008 0.812 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.4587    0.62021 0.128 0.000 0.048 0.076 0.000 0.748
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.4885    0.24217 0.008 0.000 0.056 0.260 0.012 0.664
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2773    0.64957 0.872 0.044 0.004 0.000 0.004 0.076
#> 1122039D-5785-4F70-9916-17C585453512     6  0.4686    0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.1682    0.78021 0.000 0.000 0.020 0.928 0.000 0.052
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.7956    0.14088 0.260 0.016 0.300 0.004 0.288 0.132
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.4345    0.49105 0.708 0.000 0.024 0.004 0.020 0.244
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.7689    0.42020 0.500 0.092 0.120 0.000 0.156 0.132
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.3815    0.63077 0.820 0.052 0.012 0.000 0.028 0.088
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.5504    0.53734 0.648 0.020 0.064 0.000 0.032 0.236
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6  0.4686    0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.4553    0.50351 0.056 0.000 0.040 0.152 0.004 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.5541    0.59787 0.168 0.000 0.076 0.060 0.016 0.680
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.4689    0.27564 0.580 0.000 0.020 0.000 0.020 0.380
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.3719    0.52635 0.764 0.200 0.008 0.000 0.028 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     5  0.5923    0.57418 0.152 0.172 0.052 0.000 0.620 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.3262    0.66041 0.196 0.000 0.008 0.008 0.000 0.788
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.4297    0.14221 0.012 0.452 0.004 0.000 0.532 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.2597    0.64424 0.880 0.020 0.004 0.000 0.008 0.088
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.6781    0.30252 0.544 0.024 0.180 0.000 0.192 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.7613    0.34567 0.056 0.000 0.492 0.132 0.156 0.164
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5550    0.59171 0.696 0.024 0.096 0.000 0.060 0.124
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0508    0.76586 0.004 0.984 0.000 0.000 0.012 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.8467    0.38661 0.152 0.000 0.368 0.140 0.120 0.220
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.8467    0.38661 0.152 0.000 0.368 0.140 0.120 0.220
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.5247    0.60970 0.152 0.000 0.072 0.052 0.016 0.708
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.5229    0.62765 0.196 0.000 0.048 0.056 0.012 0.688
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.4103    0.57871 0.292 0.000 0.008 0.008 0.008 0.684
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.2536    0.64103 0.880 0.020 0.004 0.000 0.004 0.092
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     1  0.5268   -0.08118 0.480 0.456 0.008 0.000 0.016 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.4520    0.44987 0.676 0.000 0.020 0.004 0.024 0.276
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0405    0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.7471    0.25908 0.248 0.000 0.380 0.000 0.196 0.176
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.3670    0.49411 0.704 0.000 0.012 0.000 0.000 0.284
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.4161    0.42404 0.372 0.000 0.008 0.000 0.008 0.612
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.6066    0.52478 0.628 0.008 0.136 0.000 0.080 0.148

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 17541 rows and 500 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 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-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 0.878           0.949       0.976         0.4948 0.506   0.506
#> 3 3 0.777           0.831       0.933         0.2343 0.626   0.415
#> 4 4 0.657           0.781       0.889         0.1602 0.755   0.473
#> 5 5 0.875           0.851       0.939         0.0798 0.866   0.592
#> 6 6 0.717           0.607       0.794         0.0549 0.943   0.773

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000      0.983 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000      0.983 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000      0.969 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.6887      0.799 0.184 0.816
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000      0.969 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000      0.969 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000      0.969 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000      0.983 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0000      0.983 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000      0.983 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.0376      0.966 0.004 0.996
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000      0.969 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000      0.969 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000      0.969 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000      0.983 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000      0.983 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000      0.983 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000      0.969 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0000      0.969 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000      0.969 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000      0.983 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000      0.969 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000      0.983 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000      0.969 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000      0.983 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000      0.969 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0000      0.969 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000      0.969 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.7674      0.744 0.224 0.776
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000      0.983 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.0000      0.969 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000      0.969 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.6148      0.837 0.152 0.848
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000      0.983 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000      0.983 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000      0.983 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000      0.969 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000      0.983 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000      0.983 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0000      0.983 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.0000      0.969 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.7219      0.778 0.200 0.800
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000      0.969 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000      0.983 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.6438      0.824 0.164 0.836
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.7745      0.693 0.772 0.228
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.0000      0.983 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000      0.983 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000      0.983 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000      0.969 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000      0.983 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000      0.983 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.0000      0.983 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.0000      0.969 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000      0.983 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000      0.983 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000      0.969 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000      0.969 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0000      0.969 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000      0.969 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.0000      0.969 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000      0.969 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.0000      0.969 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000      0.983 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.0000      0.983 1.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0000      0.983 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0000      0.983 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000      0.983 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0000      0.983 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000      0.983 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000      0.969 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000      0.983 1.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000      0.969 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000      0.969 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.0000      0.969 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.0000      0.983 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.0000      0.983 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.9129      0.520 0.328 0.672
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.0000      0.969 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000      0.969 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.6343      0.828 0.160 0.840
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000      0.969 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.0000      0.969 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.0000      0.983 1.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     2  0.2236      0.942 0.036 0.964
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000      0.969 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000      0.983 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.0000      0.969 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     2  0.6531      0.819 0.168 0.832
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000      0.969 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0000      0.983 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     2  0.0000      0.969 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.0000      0.969 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000      0.969 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     2  0.6531      0.819 0.168 0.832
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.0000      0.983 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000      0.969 0.000 1.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000      0.969 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0000      0.983 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000      0.969 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.7056      0.752 0.808 0.192
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000      0.983 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0000      0.969 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000      0.969 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0000      0.983 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.0000      0.983 1.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.0000      0.983 1.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     2  0.6343      0.828 0.160 0.840
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000      0.969 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000      0.983 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.0000      0.969 0.000 1.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0000      0.969 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0000      0.969 0.000 1.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.0000      0.983 1.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0000      0.969 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000      0.969 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0000      0.983 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000      0.969 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.6438      0.824 0.164 0.836
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0000      0.983 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.0000      0.983 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0000      0.983 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000      0.969 0.000 1.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.0000      0.983 1.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     2  0.0672      0.963 0.008 0.992
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.0000      0.983 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.0000      0.969 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     2  0.0000      0.969 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0000      0.983 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.0000      0.983 1.000 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     2  0.9170      0.550 0.332 0.668
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0000      0.969 0.000 1.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.0000      0.969 0.000 1.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     2  0.0000      0.969 0.000 1.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0000      0.983 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     1  0.0000      0.983 1.000 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.0000      0.983 1.000 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.0000      0.969 0.000 1.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.0000      0.983 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.0000      0.969 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.0000      0.969 0.000 1.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.6531      0.819 0.168 0.832
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0000      0.969 0.000 1.000
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#> 1469D134-06E6-42EF-9C5A-C30DC2B34C01     2  0.0000      0.969 0.000 1.000
#> F3F32D39-7ACE-4462-8866-FDCD35DA4599     1  0.0000      0.983 1.000 0.000
#> E56486B8-FAAE-42BF-B67E-D253783B1043     1  0.0000      0.983 1.000 0.000
#> F8E9F501-DECA-4A6A-8CF1-1A54915E6FA6     1  0.0000      0.983 1.000 0.000
#> B3AFCDBB-95EF-4028-84F7-9DBC39B25E70     2  0.0000      0.969 0.000 1.000
#> 864ACE9F-29B4-4BB2-A966-E6F601637A79     2  0.0000      0.969 0.000 1.000
#> 932BAFF1-A2A8-404F-A9E9-44DCAA8CFF83     1  0.0000      0.983 1.000 0.000
#> 1C82688E-01A7-4723-8266-F614FB7EABE5     1  0.0000      0.983 1.000 0.000
#> 8FED16FD-AFBF-475D-A19F-1BC84D0AA571     2  0.0000      0.969 0.000 1.000
#> 9EF7685F-CA09-4869-94EA-12A1129093B1     2  0.0000      0.969 0.000 1.000
#> 18AB08E8-6C1A-49E4-9DF0-79D80D9BEC78     2  0.0376      0.966 0.004 0.996
#> 97FB3176-395F-475B-8EAE-332C5BEE8155     1  0.0000      0.983 1.000 0.000
#> E1876307-DFD9-4688-876F-D71B37466068     2  0.0000      0.969 0.000 1.000
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04     2  0.0000      0.969 0.000 1.000
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00     1  0.0000      0.983 1.000 0.000
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79     2  0.0000      0.969 0.000 1.000
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A     2  0.0000      0.969 0.000 1.000
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18     2  0.5294      0.869 0.120 0.880
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D     2  0.0000      0.969 0.000 1.000
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854     2  0.0000      0.969 0.000 1.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90     1  0.0000      0.983 1.000 0.000
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     2  0.0000      0.969 0.000 1.000
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     1  0.0000      0.983 1.000 0.000
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.0000      0.969 0.000 1.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     2  0.0000      0.969 0.000 1.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.0000      0.969 0.000 1.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.0000      0.969 0.000 1.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     2  0.0000      0.969 0.000 1.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     1  0.0000      0.983 1.000 0.000
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.0000      0.969 0.000 1.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     1  0.0000      0.983 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     1  0.0000      0.983 1.000 0.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900     2  0.0000      0.969 0.000 1.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     1  0.9866      0.248 0.568 0.432
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     1  0.0000      0.983 1.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.0000      0.969 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.0000      0.969 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     2  0.8608      0.643 0.284 0.716
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     2  0.0672      0.963 0.008 0.992
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     2  0.0000      0.969 0.000 1.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     1  0.0000      0.983 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.0000      0.969 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.0000      0.983 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     1  0.0000      0.983 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     1  0.0000      0.983 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.0000      0.969 0.000 1.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     1  0.0000      0.983 1.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.0000      0.983 1.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.0000      0.969 0.000 1.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     1  0.9635      0.340 0.612 0.388
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     1  0.0000      0.983 1.000 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.0000      0.969 0.000 1.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     1  0.0000      0.983 1.000 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.0000      0.969 0.000 1.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.0000      0.969 0.000 1.000
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0000      0.969 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.6531      0.819 0.168 0.832
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0000      0.969 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000      0.983 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0000      0.983 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     2  0.0000      0.969 0.000 1.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0000      0.983 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.0000      0.969 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0000      0.969 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     1  0.0000      0.983 1.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000      0.969 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000      0.969 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.0000      0.983 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.0000      0.969 0.000 1.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.3584      0.913 0.932 0.068
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.0000      0.983 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0000      0.969 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0000      0.983 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000      0.983 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.0000      0.983 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.0000      0.969 0.000 1.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000      0.983 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.0000      0.983 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.0000      0.983 1.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.0000      0.983 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.0000      0.969 0.000 1.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000      0.983 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000      0.969 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.0000      0.969 0.000 1.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     2  0.6531      0.819 0.168 0.832
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.0000      0.969 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0000      0.969 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     2  0.6531      0.819 0.168 0.832
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000      0.969 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000      0.983 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0000      0.969 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.0000      0.983 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000      0.969 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000      0.969 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     2  0.5294      0.869 0.120 0.880
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.0000      0.983 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.0000      0.969 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.6531      0.819 0.168 0.832
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000      0.983 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000      0.969 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.0000      0.983 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000      0.983 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0000      0.983 1.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000      0.969 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000      0.969 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000      0.983 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0000      0.983 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000      0.983 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000      0.983 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000      0.969 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000      0.969 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.0000      0.983 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0000      0.983 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000      0.983 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000      0.983 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.3431      0.920 0.064 0.936
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000      0.983 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0000      0.983 1.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000      0.969 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000      0.983 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000      0.983 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.5059      0.877 0.112 0.888
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000      0.969 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.6531      0.819 0.168 0.832
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000      0.983 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000      0.969 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000      0.983 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000      0.969 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000      0.969 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000      0.983 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.0000      0.969 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.0000      0.969 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000      0.983 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000      0.983 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000      0.983 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000      0.983 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000      0.983 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000      0.983 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0000      0.969 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000      0.983 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000      0.983 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.0000      0.969 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000      0.983 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000      0.983 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.7453      0.738 0.212 0.788
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.8909      0.542 0.692 0.308
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.9286      0.458 0.656 0.344
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000      0.969 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.6887      0.799 0.184 0.816
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0000      0.983 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000      0.983 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000      0.983 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0000      0.983 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.0000      0.969 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000      0.969 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000      0.983 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000      0.969 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.6438      0.824 0.164 0.836
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.0000      0.969 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000      0.983 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000      0.969 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000      0.969 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000      0.983 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000      0.983 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000      0.983 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000      0.983 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000      0.983 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.6531      0.819 0.168 0.832
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000      0.969 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.8555      0.600 0.720 0.280
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000      0.969 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000      0.983 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000      0.983 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000      0.983 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000      0.983 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000    0.90978 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2356    0.86953 0.928 0.000 0.072
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000    0.90608 0.000 0.000 1.000
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#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0000    0.90608 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0000    0.90608 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.0000    0.90608 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3764     0.5561 0.784 0.000 0.000 0.216
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.4961     0.3556 0.552 0.000 0.448 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.2469     0.8194 0.000 0.108 0.892 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.3569     0.7022 0.196 0.000 0.804 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.5971     0.4081 0.584 0.000 0.368 0.048
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.3355     0.7300 0.160 0.000 0.004 0.836
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     3  0.7561     0.1481 0.000 0.348 0.452 0.200
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0188     0.8822 0.000 0.000 0.996 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.6626     0.5409 0.216 0.000 0.624 0.160
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.5990     0.4062 0.336 0.000 0.608 0.056
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.7581     0.1029 0.000 0.424 0.380 0.196
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0592     0.8111 0.984 0.000 0.016 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0376     0.8833 0.004 0.000 0.992 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.0376     0.8833 0.004 0.000 0.992 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.5159     0.0778 0.624 0.000 0.012 0.364
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.4985     0.2976 0.532 0.000 0.468 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.4193     0.5829 0.268 0.000 0.732 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.5744     0.6612 0.184 0.000 0.708 0.108
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.3325     0.8153 0.024 0.000 0.864 0.112
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0188     0.9147 0.000 0.996 0.004 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.4843     0.4461 0.604 0.000 0.396 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3444     0.6053 0.816 0.000 0.000 0.184
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0376     0.8833 0.004 0.000 0.992 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.2654     0.8251 0.004 0.000 0.888 0.108
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.7332     0.0856 0.448 0.000 0.396 0.156
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.2589     0.8428 0.884 0.000 0.116 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.3280     0.7613 0.860 0.000 0.016 0.124
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.2647     0.8100 0.000 0.120 0.880 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0707     0.8133 0.980 0.000 0.020 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.7572     0.3374 0.300 0.000 0.224 0.476
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.2714     0.8135 0.000 0.112 0.884 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3  0.3793     0.8047 0.044 0.000 0.844 0.112
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.4722     0.5503 0.300 0.000 0.008 0.692
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.5112     0.4929 0.436 0.000 0.004 0.560
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0188     0.7967 0.004 0.000 0.000 0.996
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     4  0.7367     0.1180 0.160 0.000 0.404 0.436
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4008     0.7143 0.756 0.000 0.244 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.3074     0.7731 0.000 0.152 0.848 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0921     0.8944 0.000 0.972 0.028 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.3074     0.7731 0.000 0.152 0.848 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.2814     0.8008 0.000 0.132 0.868 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.4661     0.6657 0.728 0.000 0.256 0.016
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.2704     0.8127 0.000 0.124 0.876 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3  0.1661     0.8598 0.000 0.004 0.944 0.052
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.5507     0.6935 0.156 0.000 0.732 0.112
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.3688     0.6698 0.208 0.000 0.792 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0921     0.8938 0.000 0.972 0.028 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0376     0.8833 0.004 0.004 0.992 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     4  0.0376     0.7953 0.004 0.000 0.004 0.992
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.4967     0.3441 0.548 0.000 0.452 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3  0.3706     0.8010 0.000 0.040 0.848 0.112
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.4978     0.4003 0.000 0.384 0.612 0.004
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.6911     0.2051 0.000 0.504 0.384 0.112
#> C44C898C-EEF9-4E03-911A-9D951312C380     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0376     0.9122 0.000 0.992 0.004 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     4  0.7503     0.3516 0.300 0.000 0.212 0.488
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.6953     0.1185 0.000 0.476 0.412 0.112
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     4  0.3355     0.7300 0.160 0.000 0.004 0.836
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.2814     0.7787 0.132 0.000 0.868 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     4  0.7098     0.3420 0.000 0.152 0.312 0.536
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.0188     0.7958 0.996 0.000 0.000 0.004
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3  0.2892     0.8337 0.000 0.036 0.896 0.068
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.2596     0.8027 0.908 0.000 0.024 0.068
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3  0.0336     0.8824 0.000 0.008 0.992 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3  0.0376     0.8833 0.004 0.000 0.992 0.004
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0921     0.7778 0.972 0.000 0.000 0.028
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.2281     0.8207 0.000 0.904 0.096 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.2988     0.8364 0.876 0.000 0.112 0.012
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3  0.0376     0.8833 0.004 0.004 0.992 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     3  0.0707     0.8776 0.020 0.000 0.980 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     3  0.4999    -0.1737 0.492 0.000 0.508 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.0000     0.9179 0.000 1.000 0.000 0.000
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#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.2469     0.8346 0.108 0.000 0.000 0.892
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.7581     0.1029 0.000 0.424 0.380 0.196
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0707     0.7859 0.980 0.000 0.000 0.020
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.2530     0.8354 0.112 0.000 0.000 0.888
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.4977     0.3225 0.540 0.000 0.460 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3  0.2530     0.8226 0.000 0.000 0.888 0.112
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.4522     0.3510 0.680 0.000 0.000 0.320
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.4746     0.5186 0.632 0.000 0.368 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.0188     0.8837 0.004 0.000 0.996 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0376     0.9122 0.000 0.992 0.004 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2480     0.8301 0.000 0.904 0.008 0.088
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.1211     0.8673 0.000 0.000 0.960 0.040
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     4  0.7648     0.2453 0.216 0.000 0.348 0.436
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0188     0.8821 0.000 0.000 0.996 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     4  0.7706     0.2357 0.348 0.000 0.228 0.424
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.7561     0.2702 0.348 0.000 0.200 0.452
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.7999 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0188     0.8030 0.996 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0336     0.8832 0.008 0.000 0.992 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.4277     0.5822 0.000 0.720 0.280 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3837     0.6430 0.224 0.000 0.776 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9179 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.7137     0.3719 0.304 0.000 0.536 0.160
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.4790     0.5186 0.620 0.000 0.380 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.2530     0.8455 0.888 0.000 0.112 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.0336     0.8810 0.000 0.000 0.992 0.008

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.3109    0.72668 0.000 0.000 0.000 0.800 0.200
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.2020    0.84906 0.000 0.000 0.900 0.100 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.0290    0.92778 0.008 0.000 0.992 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.3993    0.69096 0.028 0.000 0.756 0.216 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     4  0.6133    0.25471 0.300 0.000 0.160 0.540 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.3134    0.77655 0.848 0.000 0.000 0.120 0.032
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.1908    0.86586 0.092 0.000 0.908 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5213    0.36227 0.556 0.000 0.048 0.396 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0703    0.92060 0.024 0.000 0.976 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.3461    0.67534 0.224 0.000 0.000 0.772 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.2377    0.81875 0.000 0.000 0.872 0.128 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.5338    0.25933 0.056 0.000 0.544 0.400 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.2439    0.78914 0.876 0.000 0.004 0.120 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0566    0.93440 0.004 0.984 0.012 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.3266    0.70514 0.004 0.000 0.200 0.796 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.3109    0.72668 0.000 0.000 0.000 0.800 0.200
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0162    0.92887 0.004 0.000 0.996 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0290    0.92778 0.008 0.000 0.992 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.1965    0.76876 0.904 0.000 0.096 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.2127    0.83374 0.000 0.000 0.108 0.892 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3300    0.70879 0.792 0.000 0.004 0.204 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.2424    0.81137 0.132 0.000 0.000 0.000 0.868
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     4  0.1341    0.89804 0.056 0.000 0.000 0.944 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.4542    0.24068 0.536 0.000 0.008 0.456 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0162    0.92782 0.000 0.004 0.996 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0162    0.84983 0.996 0.000 0.000 0.000 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0703    0.83824 0.976 0.000 0.024 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.2068    0.80766 0.904 0.000 0.000 0.092 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.4238    0.46811 0.628 0.000 0.000 0.368 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.0880    0.93505 0.032 0.000 0.000 0.000 0.968
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0162    0.84983 0.996 0.000 0.000 0.000 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.3796    0.58276 0.000 0.000 0.700 0.300 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0290    0.92621 0.000 0.008 0.992 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.2732    0.74964 0.000 0.840 0.160 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0162    0.92782 0.000 0.004 0.996 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0404    0.92630 0.012 0.000 0.988 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     4  0.3109    0.71099 0.000 0.000 0.200 0.800 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.0162    0.92887 0.004 0.000 0.996 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.0162    0.92782 0.000 0.004 0.996 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3  0.4262    0.23532 0.440 0.000 0.560 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.0404    0.92630 0.012 0.000 0.988 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.1121    0.89846 0.000 0.956 0.044 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.4305    0.00814 0.512 0.000 0.000 0.000 0.488
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3  0.2074    0.84560 0.000 0.000 0.896 0.104 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
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#> C2C08680-E96B-468D-BBFA-E7D7E0034249     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.0162    0.92782 0.000 0.004 0.996 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     4  0.4704    0.68895 0.112 0.000 0.000 0.736 0.152
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     3  0.4974    0.08791 0.028 0.464 0.508 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     3  0.6184    0.16065 0.140 0.000 0.480 0.380 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     4  0.0290    0.93688 0.000 0.000 0.008 0.992 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.4182    0.36710 0.400 0.600 0.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.4150    0.39552 0.388 0.612 0.000 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     3  0.4714    0.48624 0.032 0.324 0.644 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.3098    0.75192 0.016 0.836 0.148 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.4287    0.23854 0.540 0.000 0.000 0.460 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.0290    0.92621 0.000 0.008 0.992 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.0703    0.91639 0.000 0.000 0.976 0.024 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     3  0.0290    0.92778 0.008 0.000 0.992 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     4  0.0404    0.93299 0.000 0.000 0.012 0.988 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.1851    0.87041 0.088 0.000 0.912 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.4392    0.44014 0.612 0.000 0.000 0.380 0.008
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.3305    0.69973 0.000 0.000 0.776 0.224 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.2068    0.80824 0.904 0.000 0.004 0.092 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0290    0.92621 0.000 0.008 0.992 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     4  0.1478    0.88356 0.000 0.000 0.064 0.936 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.4028    0.71268 0.040 0.000 0.768 0.192 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.4836    0.65063 0.188 0.716 0.096 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.4305    0.03332 0.488 0.000 0.512 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.94536 0.000 1.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     4  0.0566    0.93177 0.012 0.000 0.004 0.984 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.0000    0.85023 1.000 0.000 0.000 0.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0290    0.93673 0.000 0.000 0.000 0.992 0.008
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.0000    0.96505 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0880    0.91095 0.000 0.000 0.968 0.032 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.4182    0.32435 0.000 0.000 0.000 0.600 0.400
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.1121    0.90739 0.044 0.000 0.000 0.956 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3336    0.68792 0.000 0.000 0.772 0.228 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.2329    0.82835 0.124 0.876 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.3508    0.56372 0.748 0.252 0.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3837    0.51552 0.692 0.000 0.308 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0162    0.85114 0.996 0.000 0.004 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0794    0.91845 0.028 0.000 0.972 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2439    0.78914 0.876 0.000 0.004 0.120 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2439    0.78835 0.876 0.000 0.000 0.120 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.2813    0.77010 0.000 0.168 0.832 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000    0.92954 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0162    0.94534 0.004 0.996 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2439    0.78914 0.876 0.000 0.004 0.120 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.2605    0.80046 0.000 0.000 0.852 0.148 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.0000    0.94159 0.000 0.000 0.000 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.3612    0.56531 0.732 0.000 0.268 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000    0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.2431    0.74977 0.000 0.000 0.008 0.132 0.000 0.860
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3868    0.32506 0.496 0.000 0.504 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.5061    0.37520 0.428 0.000 0.496 0.000 0.000 0.076
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0865    0.87098 0.000 0.964 0.036 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.2165    0.57801 0.884 0.000 0.108 0.000 0.008 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.3175    0.48331 0.744 0.000 0.256 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.5139    0.35808 0.700 0.000 0.060 0.000 0.148 0.092
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6980   -0.06363 0.076 0.000 0.376 0.000 0.352 0.196
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.2732    0.77483 0.000 0.000 0.020 0.044 0.880 0.056
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.3200    0.73385 0.000 0.016 0.196 0.000 0.788 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.2230    0.56706 0.892 0.000 0.024 0.000 0.084 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0363    0.87643 0.000 0.988 0.012 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     5  0.0858    0.80411 0.028 0.000 0.004 0.000 0.968 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     5  0.5866    0.51534 0.180 0.000 0.036 0.000 0.596 0.188
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.2006    0.80211 0.004 0.000 0.104 0.000 0.000 0.892
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.3027    0.78451 0.000 0.824 0.148 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.3231    0.73175 0.000 0.016 0.200 0.000 0.784 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     6  0.2969    0.71631 0.000 0.000 0.224 0.000 0.000 0.776
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000    0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0000    0.83093 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0777    0.87444 0.004 0.972 0.024 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.2491    0.57737 0.868 0.000 0.112 0.000 0.020 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2728    0.57668 0.860 0.000 0.100 0.000 0.040 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     5  0.2624    0.76259 0.124 0.000 0.020 0.000 0.856 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     6  0.4645    0.41025 0.040 0.000 0.008 0.000 0.336 0.616
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.2697    0.50638 0.812 0.000 0.188 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.5175    0.38018 0.420 0.000 0.492 0.000 0.000 0.088
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.6208    0.20840 0.584 0.000 0.076 0.000 0.172 0.168
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     5  0.3161    0.75704 0.092 0.000 0.020 0.000 0.848 0.040
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     5  0.1461    0.80343 0.044 0.000 0.016 0.000 0.940 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.5408    0.54072 0.124 0.560 0.312 0.000 0.004 0.000
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#> 816CF68B-8476-4960-9F05-FB959A686323     1  0.3869   -0.35320 0.500 0.000 0.500 0.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     5  0.0891    0.80376 0.024 0.000 0.000 0.000 0.968 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.6665   -0.30905 0.120 0.372 0.424 0.000 0.084 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4537    0.34829 0.684 0.000 0.060 0.000 0.248 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.3596    0.71517 0.004 0.016 0.232 0.000 0.748 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1644    0.86413 0.004 0.920 0.076 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.1065    0.82723 0.020 0.000 0.008 0.000 0.008 0.964
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.1421    0.59187 0.944 0.000 0.028 0.000 0.028 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0692    0.58634 0.976 0.000 0.020 0.000 0.004 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.0891    0.82813 0.024 0.000 0.008 0.000 0.000 0.968
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     6  0.5404    0.66945 0.072 0.000 0.112 0.000 0.136 0.680
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0146    0.96381 0.000 0.000 0.004 0.996 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.0260    0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.0260    0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.0993    0.82789 0.024 0.000 0.012 0.000 0.000 0.964
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.3231    0.73175 0.000 0.016 0.200 0.000 0.784 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.0146    0.83087 0.000 0.000 0.004 0.000 0.000 0.996
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.0260    0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.2135    0.53289 0.872 0.000 0.128 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     6  0.0458    0.82937 0.000 0.000 0.016 0.000 0.000 0.984
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000    0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.1720    0.80599 0.032 0.000 0.040 0.000 0.928 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.4829    0.38956 0.424 0.000 0.520 0.000 0.000 0.056
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.1649    0.80618 0.032 0.000 0.036 0.000 0.932 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.3838   -0.20270 0.552 0.000 0.448 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.2003    0.51109 0.884 0.000 0.116 0.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6  0.3778    0.55207 0.000 0.000 0.016 0.288 0.000 0.696
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.0260    0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.3163    0.73435 0.024 0.000 0.008 0.000 0.144 0.824
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.5184    0.35341 0.432 0.000 0.480 0.000 0.000 0.088
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.2969    0.52116 0.776 0.000 0.224 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.5609    0.51362 0.024 0.500 0.396 0.000 0.080 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0260    0.83158 0.000 0.000 0.008 0.000 0.000 0.992
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.5354    0.57121 0.004 0.140 0.264 0.000 0.592 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.1327    0.56310 0.936 0.000 0.064 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.3606    0.39791 0.728 0.000 0.016 0.000 0.256 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.0951    0.80467 0.020 0.000 0.008 0.000 0.968 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.1856    0.59182 0.920 0.000 0.048 0.000 0.032 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.2034    0.78789 0.024 0.000 0.004 0.000 0.912 0.060
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.2094    0.78649 0.024 0.000 0.004 0.000 0.908 0.064
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.0291    0.83089 0.000 0.000 0.004 0.000 0.004 0.992
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.2344    0.79752 0.028 0.000 0.008 0.000 0.068 0.896
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.0363    0.83086 0.000 0.000 0.012 0.000 0.000 0.988
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.1285    0.56793 0.944 0.000 0.052 0.000 0.004 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.5334    0.23020 0.320 0.128 0.552 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.3864    0.34758 0.480 0.000 0.520 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     5  0.2461    0.77862 0.044 0.000 0.004 0.000 0.888 0.064
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.5242    0.05233 0.608 0.000 0.216 0.000 0.000 0.176
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.4273    0.67391 0.080 0.000 0.204 0.000 0.000 0.716
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5091    0.20601 0.564 0.000 0.068 0.000 0.360 0.008

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 17541 rows and 500 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 6.
#> 
#> 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 0.918           0.918       0.968         0.5009 0.500   0.500
#> 3 3 0.798           0.849       0.921         0.3046 0.737   0.527
#> 4 4 0.925           0.911       0.962         0.1370 0.850   0.602
#> 5 5 0.930           0.879       0.946         0.0524 0.908   0.674
#> 6 6 0.914           0.855       0.940         0.0423 0.938   0.730

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

suggest_best_k(res)
#> [1] 6
#> attr(,"optional")
#> [1] 2 4 5

There is also optional best \(k\) = 2 4 5 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000     0.9828 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000     0.9828 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000     0.9511 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.7139     0.7366 0.804 0.196
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9511 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000     0.9511 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000     0.9511 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9828 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0000     0.9828 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.9828 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.6438     0.7847 0.164 0.836
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000     0.9511 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9511 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9511 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000     0.9828 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9828 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000     0.9828 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9511 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.0376     0.9480 0.004 0.996
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9511 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000     0.9828 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9511 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9828 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9511 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9828 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9511 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0000     0.9511 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9511 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.3114     0.9243 0.944 0.056
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9828 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.0000     0.9511 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9511 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.9833     0.3098 0.424 0.576
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9828 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000     0.9828 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000     0.9828 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9511 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.9828 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9828 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0000     0.9828 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.0000     0.9511 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9828 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9511 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9828 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.9732     0.3617 0.404 0.596
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.9828 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.0000     0.9828 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000     0.9828 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000     0.9828 1.000 0.000
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#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.0000     0.9511 0.000 1.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.0000     0.9828 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9511 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.0376     0.9480 0.004 0.996
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     2  0.9977     0.1666 0.472 0.528
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.0000     0.9511 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0000     0.9511 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     2  0.9993     0.1259 0.484 0.516
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000     0.9511 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.9828 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0000     0.9511 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.0000     0.9828 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9511 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.9511 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     2  0.6438     0.7877 0.164 0.836
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.0000     0.9828 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.0000     0.9511 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.9988     0.1396 0.480 0.520
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9828 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9511 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.0000     0.9828 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0000     0.9828 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0000     0.9828 1.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.9511 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000     0.9511 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9828 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0000     0.9828 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000     0.9828 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9828 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9511 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9511 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.0000     0.9828 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.0000     0.9828 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0000     0.9828 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9828 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.5842     0.8165 0.140 0.860
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9828 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0000     0.9828 1.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9511 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0000     0.9828 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0000     0.9828 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.7376     0.7294 0.208 0.792
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000     0.9511 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.9988     0.1397 0.480 0.520
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000     0.9828 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000     0.9511 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9828 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9511 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9511 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9828 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.0000     0.9511 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.0000     0.9511 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9828 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9828 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000     0.9828 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9828 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.9828 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9828 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.0376     0.9480 0.004 0.996
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9828 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9828 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.0000     0.9511 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000     0.9828 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9828 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.9922     0.2097 0.448 0.552
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.0000     0.9828 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.1414     0.9629 0.980 0.020
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9511 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.9828 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0000     0.9828 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.9828 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9828 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0000     0.9828 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.0000     0.9511 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9511 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9828 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9511 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.9661     0.3910 0.392 0.608
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.0376     0.9480 0.004 0.996
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.9828 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000     0.9511 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9511 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9828 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.9828 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.9828 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9828 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000     0.9828 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.9993     0.1265 0.484 0.516
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9511 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.0000     0.9828 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9511 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9828 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9828 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.9828 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9828 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000     0.9426 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.6244    -0.1570 0.560 0.000 0.440
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2165     0.7782 0.000 0.064 0.936
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0000     0.8228 0.000 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9573 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000     0.9573 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000     0.9573 0.000 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.4452     0.7759 0.192 0.000 0.808
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0000     0.9426 1.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.9426 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.4452     0.7106 0.808 0.192 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000     0.9573 0.000 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9573 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9573 0.000 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.0000     0.9426 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9426 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.2959     0.8053 0.100 0.000 0.900
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9573 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.5650     0.5097 0.688 0.312 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9573 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.5650     0.7237 0.312 0.000 0.688
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9573 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9426 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9573 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.5650     0.7237 0.312 0.000 0.688
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9573 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0000     0.9573 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9573 0.000 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.9426 1.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0000     0.9426 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.2878     0.7491 0.000 0.096 0.904
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9573 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.0000     0.8228 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.5650     0.7237 0.312 0.000 0.688
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0000     0.9426 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000     0.9426 1.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9573 0.000 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.5650     0.7237 0.312 0.000 0.688
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.5650     0.7237 0.312 0.000 0.688
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.5650     0.7237 0.312 0.000 0.688
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.0424     0.9516 0.000 0.992 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0000     0.8228 0.000 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9573 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9426 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0237     0.8208 0.000 0.004 0.996
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.9426 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.6295     0.4248 0.472 0.000 0.528
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.0000     0.9426 1.000 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000     0.9426 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9573 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3  0.5650     0.7237 0.312 0.000 0.688
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.5650     0.7237 0.312 0.000 0.688
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.0000     0.9426 1.000 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.0000     0.9573 0.000 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.5650     0.7237 0.312 0.000 0.688
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0000     0.9426 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9573 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9573 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0000     0.9573 0.000 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9573 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.3619     0.8197 0.136 0.864 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9573 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.0000     0.9573 0.000 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0000     0.9426 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.0000     0.9426 1.000 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0000     0.9426 1.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0000     0.9426 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0000     0.9426 1.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.0000     0.8228 0.000 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.5650     0.7237 0.312 0.000 0.688
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9573 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000     0.9426 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9573 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.5591     0.6348 0.000 0.696 0.304
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#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9573 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.6225     0.3887 0.000 0.568 0.432
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0000     0.8228 0.000 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.0000     0.9573 0.000 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0000     0.9573 0.000 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.0000     0.8228 0.000 0.000 1.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000     0.9573 0.000 1.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     3  0.5785     0.6992 0.332 0.000 0.668
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.6244     0.2231 0.440 0.560 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.0000     0.9426 1.000 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9573 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.3816     0.6982 0.000 0.148 0.852
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.1643     0.7990 0.000 0.044 0.956
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.0000     0.8228 0.000 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.0000     0.9573 0.000 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8228 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.0000     0.9426 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9573 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     3  0.5650     0.7237 0.312 0.000 0.688
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.0000     0.8228 0.000 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.0000     0.9426 1.000 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.9573 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000     0.9573 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.5650     0.7237 0.312 0.000 0.688
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.5650     0.7237 0.312 0.000 0.688
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0000     0.9426 1.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3  0.3752     0.7926 0.144 0.000 0.856
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9573 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9573 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3  0.5650     0.7237 0.312 0.000 0.688
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000     0.8228 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.0000     0.8228 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0000     0.9426 1.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8228 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0000     0.9426 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0000     0.9426 1.000 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9573 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.0000     0.8228 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.5926     0.6649 0.356 0.000 0.644
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0000     0.8228 0.000 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.4605     0.7282 0.204 0.796 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0000     0.8228 0.000 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0000     0.9426 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000     0.9573 0.000 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0000     0.9426 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.6126     0.3033 0.600 0.400 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9573 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     3  0.5785     0.6992 0.332 0.000 0.668
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.0424     0.9516 0.000 0.992 0.008
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.2165     0.7783 0.000 0.064 0.936
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     3  0.5650     0.7237 0.312 0.000 0.688
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.5785     0.6995 0.332 0.000 0.668
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000     0.9426 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     3  0.5650     0.7237 0.312 0.000 0.688
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     3  0.5650     0.7237 0.312 0.000 0.688
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.5650     0.7237 0.312 0.000 0.688
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.5650     0.5097 0.688 0.312 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     3  0.5882     0.6768 0.348 0.000 0.652
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.5650     0.7237 0.312 0.000 0.688
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000     0.8228 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     3  0.5650     0.7237 0.312 0.000 0.688
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9426 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0000     0.9426 1.000 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0000     0.8228 0.000 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.0000     0.9426 1.000 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000     0.8228 0.000 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.0000     0.8228 0.000 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.6244    -0.1568 0.560 0.000 0.440
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.5678     0.7192 0.316 0.000 0.684
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0000     0.9426 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.8228 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.0237     0.9545 0.000 0.996 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9573 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.4974     0.7586 0.236 0.000 0.764
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9573 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.8228 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.6244     0.2234 0.440 0.560 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0000     0.9426 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000     0.9573 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9573 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0000     0.9426 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0000     0.9426 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.6299     0.4177 0.476 0.000 0.524
#> E6446572-BFA9-4018-89B3-7E4519EBE072     3  0.5810     0.6938 0.336 0.000 0.664
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.5650     0.7237 0.312 0.000 0.688
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0000     0.8228 0.000 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9573 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8228 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9573 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0000     0.9426 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0000     0.8228 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0000     0.8228 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9426 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.3726     0.7273 0.788 0.000 0.212 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0336     0.9070 0.000 0.008 0.992 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4356     0.5662 0.708 0.000 0.292 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.3726     0.7281 0.000 0.212 0.788 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.3764     0.7218 0.784 0.000 0.216 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.1118     0.8909 0.000 0.036 0.964 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.3172     0.7779 0.160 0.000 0.840 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.3486     0.7307 0.188 0.000 0.812 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.0188     0.9560 0.996 0.000 0.000 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.1302     0.9438 0.044 0.000 0.000 0.956
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0336     0.9070 0.000 0.008 0.992 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0188     0.9670 0.000 0.996 0.004 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.3444     0.7679 0.000 0.816 0.000 0.184
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     4  0.0000     0.9852 0.000 0.000 0.000 1.000
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#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0188     0.9670 0.000 0.996 0.004 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     3  0.3486     0.7307 0.188 0.000 0.812 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     4  0.3610     0.7462 0.200 0.000 0.000 0.800
#> B57C849C-28B1-4315-885C-330B9C9482B3     3  0.0188     0.9087 0.000 0.004 0.996 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     3  0.3873     0.6984 0.000 0.228 0.772 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     3  0.2345     0.8386 0.100 0.000 0.900 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.3726     0.7150 0.000 0.788 0.212 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.5292     0.6791 0.088 0.744 0.168 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.3649     0.7384 0.000 0.204 0.796 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.0188     0.9085 0.004 0.000 0.996 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.4916     0.3134 0.000 0.424 0.576 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.0188     0.9829 0.004 0.000 0.000 0.996
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0188     0.9562 0.996 0.000 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     4  0.0921     0.9599 0.028 0.000 0.000 0.972
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0469     0.9042 0.012 0.000 0.988 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.0188     0.9561 0.996 0.000 0.004 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.0336     0.9536 0.992 0.000 0.008 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.3105     0.8170 0.856 0.000 0.004 0.140
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.4790     0.3977 0.000 0.620 0.000 0.380
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0592     0.9028 0.000 0.016 0.984 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.1302     0.9225 0.956 0.000 0.044 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4661     0.4826 0.652 0.000 0.348 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0188     0.9560 0.996 0.000 0.000 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.4406     0.5736 0.300 0.000 0.000 0.700
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.4972     0.1210 0.544 0.000 0.456 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.0817     0.8983 0.000 0.024 0.976 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.5784     0.6633 0.000 0.100 0.700 0.200
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.1792     0.8684 0.000 0.068 0.932 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3172     0.7985 0.840 0.000 0.000 0.160
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0000     0.9102 0.000 0.000 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.3172     0.7832 0.000 0.160 0.840 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.4866     0.3594 0.596 0.000 0.404 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9706 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     4  0.0000     0.9852 0.000 0.000 0.000 1.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0336     0.9536 0.992 0.000 0.008 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000     0.9590 1.000 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     4  0.0188     0.9829 0.004 0.000 0.000 0.996

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0510     0.9287 0.000 0.000 0.000 0.984 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0609     0.8444 0.020 0.000 0.980 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0671     0.8444 0.016 0.000 0.980 0.004 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.9129 1.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.3983     0.4452 0.340 0.660 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.3837     0.5565 0.692 0.000 0.000 0.308 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     5  0.4644     0.1303 0.000 0.000 0.460 0.012 0.528
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.0162     0.9598 0.000 0.000 0.000 0.004 0.996
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.3300     0.7209 0.792 0.204 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     5  0.0510     0.9583 0.000 0.000 0.000 0.016 0.984
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0404     0.9325 0.000 0.000 0.012 0.988 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4287     0.3218 0.000 0.000 0.540 0.460 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.0703     0.9536 0.000 0.000 0.000 0.024 0.976
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0000     0.9405 0.000 0.000 0.000 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0162     0.9681 0.000 0.996 0.004 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0510     0.9072 0.984 0.016 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.3143     0.7232 0.796 0.204 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0404     0.9089 0.988 0.000 0.012 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
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#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000     0.9405 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0671     0.8410 0.004 0.000 0.980 0.016 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.0609     0.9536 0.000 0.000 0.020 0.000 0.980
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0609     0.8444 0.020 0.000 0.980 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.3055     0.7818 0.016 0.000 0.144 0.840 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0510     0.9287 0.000 0.000 0.000 0.984 0.016
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.0000     0.9405 0.000 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.3109     0.6879 0.000 0.000 0.000 0.800 0.200
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3715     0.6623 0.004 0.000 0.736 0.260 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0162     0.9124 0.996 0.004 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0000     0.9405 0.000 0.000 0.000 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0609     0.9564 0.000 0.980 0.020 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.9129 1.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0609     0.9055 0.980 0.000 0.020 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.0000     0.9590 0.000 0.000 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0510     0.9103 0.984 0.000 0.016 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.2516     0.7698 0.000 0.000 0.000 0.860 0.140
#> E6446572-BFA9-4018-89B3-7E4519EBE072     4  0.0162     0.9382 0.000 0.000 0.000 0.996 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000     0.9405 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9129 1.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.1117     0.8340 0.016 0.020 0.964 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0671     0.8444 0.016 0.000 0.980 0.004 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9705 0.000 1.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     5  0.0404     0.9602 0.000 0.000 0.000 0.012 0.988
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.0963     0.9149 0.000 0.000 0.036 0.964 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.1121     0.9084 0.000 0.000 0.044 0.956 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     5  0.0833     0.9575 0.004 0.000 0.004 0.016 0.976

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#>                                      class entropy silhouette    p1    p2    p3    p4    p5    p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.2562     0.7507 0.000 0.000 0.000 0.172 0.000 0.828
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0713     0.9399 0.028 0.972 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2762     0.7056 0.804 0.000 0.000 0.000 0.000 0.196
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     4  0.3482     0.5278 0.000 0.000 0.316 0.684 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     5  0.5005     0.5170 0.248 0.124 0.000 0.000 0.628 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.3797     0.2558 0.000 0.000 0.000 0.580 0.420 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0713     0.9421 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.3797     0.4286 0.000 0.000 0.580 0.000 0.000 0.420
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.2912     0.6862 0.784 0.216 0.000 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     5  0.0260     0.8645 0.000 0.000 0.000 0.008 0.992 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0146     0.8940 0.996 0.000 0.004 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1267     0.8503 0.940 0.000 0.000 0.000 0.000 0.060
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0363     0.8885 0.988 0.000 0.000 0.000 0.000 0.012
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.3823     0.1932 0.000 0.564 0.000 0.000 0.436 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.1714     0.8750 0.000 0.000 0.092 0.908 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.1327     0.8481 0.936 0.064 0.000 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 311D089C-33F1-4722-9118-F56427C5C128     4  0.2260     0.8182 0.000 0.000 0.000 0.860 0.140 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.3847     0.2183 0.544 0.456 0.000 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     5  0.0865     0.8433 0.036 0.000 0.000 0.000 0.964 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.3371     0.5868 0.708 0.292 0.000 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     5  0.3620     0.4479 0.000 0.000 0.000 0.352 0.648 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0146     0.9612 0.000 0.000 0.000 0.996 0.004 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     5  0.0146     0.8674 0.000 0.000 0.000 0.004 0.996 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     6  0.0405     0.9330 0.004 0.000 0.008 0.000 0.000 0.988
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0363     0.8413 0.000 0.012 0.988 0.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     4  0.3851     0.1516 0.000 0.000 0.460 0.540 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.1267     0.9108 0.000 0.940 0.060 0.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     5  0.3405     0.6122 0.004 0.272 0.000 0.000 0.724 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0146     0.8934 0.996 0.000 0.000 0.000 0.000 0.004
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0632     0.8831 0.976 0.000 0.024 0.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0146     0.8940 0.996 0.000 0.004 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.3592     0.4557 0.000 0.656 0.000 0.000 0.344 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     6  0.3647     0.4309 0.360 0.000 0.000 0.000 0.000 0.640
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     6  0.0146     0.9378 0.000 0.000 0.004 0.000 0.000 0.996
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     6  0.5548     0.2570 0.356 0.000 0.000 0.088 0.020 0.536
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.3240     0.6466 0.752 0.244 0.004 0.000 0.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     6  0.1387     0.8791 0.000 0.000 0.000 0.068 0.000 0.932
#> 241F589C-D559-43D7-8340-31EBCEB36E14     5  0.3464     0.5511 0.000 0.312 0.000 0.000 0.688 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     5  0.5417     0.4623 0.164 0.000 0.000 0.268 0.568 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 40467950-A95C-4731-AD93-0A128442C837     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     6  0.0363     0.9315 0.000 0.000 0.000 0.012 0.000 0.988
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.3737     0.4908 0.000 0.000 0.608 0.000 0.000 0.392
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     5  0.3607     0.4798 0.000 0.348 0.000 0.000 0.652 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.7465    -0.1663 0.060 0.368 0.336 0.000 0.032 0.204
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.0260     0.8922 0.992 0.000 0.008 0.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.1075     0.8617 0.952 0.048 0.000 0.000 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0865     0.9344 0.000 0.964 0.000 0.000 0.036 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.0146     0.8938 0.996 0.000 0.004 0.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     6  0.1204     0.8911 0.000 0.000 0.000 0.056 0.000 0.944
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.2378     0.8056 0.000 0.848 0.152 0.000 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.0146     0.8477 0.000 0.004 0.996 0.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.2454     0.7656 0.000 0.000 0.840 0.000 0.000 0.160
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.2053     0.8053 0.888 0.108 0.000 0.000 0.004 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     4  0.0146     0.9602 0.000 0.000 0.000 0.996 0.000 0.004
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4210     0.6284 0.040 0.000 0.672 0.000 0.000 0.288
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     6  0.0260     0.9350 0.000 0.000 0.008 0.000 0.000 0.992
#> EE40EE80-4520-4643-B906-48246BA616A7     5  0.3515     0.5055 0.000 0.000 0.000 0.324 0.676 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     5  0.3647     0.4301 0.000 0.000 0.000 0.360 0.640 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     6  0.0260     0.9350 0.000 0.000 0.008 0.000 0.000 0.992
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.5983     0.1438 0.412 0.000 0.000 0.232 0.000 0.356
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.2491     0.7615 0.836 0.000 0.164 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.1267     0.9113 0.000 0.940 0.000 0.000 0.060 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     4  0.0858     0.9389 0.004 0.000 0.000 0.968 0.028 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.0865     0.9104 0.000 0.000 0.000 0.036 0.000 0.964
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     6  0.3428     0.5678 0.000 0.000 0.000 0.304 0.000 0.696
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.1714     0.8524 0.000 0.000 0.000 0.092 0.000 0.908
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0146     0.8940 0.996 0.000 0.004 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.1719     0.8805 0.016 0.000 0.060 0.000 0.000 0.924
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6  0.3659     0.4398 0.000 0.000 0.000 0.364 0.000 0.636
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.0790     0.9141 0.000 0.000 0.000 0.032 0.000 0.968
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.1863     0.8382 0.000 0.000 0.000 0.896 0.000 0.104
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3266     0.6664 0.000 0.000 0.728 0.000 0.000 0.272
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     5  0.3706     0.4054 0.000 0.380 0.000 0.000 0.620 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.0000     0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0260     0.8909 0.992 0.000 0.000 0.000 0.008 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     4  0.1007     0.9271 0.000 0.000 0.000 0.956 0.044 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0777     0.8819 0.972 0.004 0.000 0.000 0.024 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.2793     0.7119 0.000 0.000 0.000 0.200 0.000 0.800
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.1444     0.8749 0.000 0.000 0.000 0.072 0.000 0.928
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.0363     0.8413 0.000 0.012 0.988 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     4  0.0000     0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.0000     0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.0260     0.9350 0.000 0.000 0.008 0.000 0.000 0.992
#> 2785594A-571A-46B4-A901-CB9C62DC6174     4  0.1858     0.8735 0.004 0.000 0.000 0.904 0.092 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 17541 rows and 500 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 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 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 0.960           0.932       0.961         0.3176 0.684   0.684
#> 3 3 0.909           0.911       0.962         0.6821 0.777   0.675
#> 4 4 0.884           0.879       0.954         0.1621 0.795   0.608
#> 5 5 0.906           0.889       0.957         0.1245 0.900   0.743
#> 6 6 0.810           0.822       0.924         0.0939 0.910   0.710

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 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.2423     0.9418 0.960 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3431     0.9408 0.936 0.064
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000     0.9716 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000     0.9716 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.2423     0.9509 0.040 0.960
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000     0.9716 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000     0.9716 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.0000     0.9716 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.0000     0.9716 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.2423     0.9418 0.960 0.040
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.7528     0.8036 0.784 0.216
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000     0.9716 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2423     0.9509 0.040 0.960
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.2423     0.9509 0.040 0.960
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.8608     0.7044 0.716 0.284
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.6247     0.7916 0.156 0.844
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0000     0.9716 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.2423     0.9509 0.040 0.960
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.7950     0.7715 0.760 0.240
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2423     0.9509 0.040 0.960
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     2  0.9954     0.0217 0.460 0.540
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2423     0.9509 0.040 0.960
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.2423     0.9418 0.960 0.040
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2423     0.9509 0.040 0.960
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     2  0.6438     0.7859 0.164 0.836
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.2423     0.9509 0.040 0.960
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0000     0.9716 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9716 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.0000     0.9716 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.3879     0.9391 0.924 0.076
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.0000     0.9716 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.2423     0.9509 0.040 0.960
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.0000     0.9716 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.0000     0.9716 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.0000     0.9716 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0000     0.9716 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9716 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.0000     0.9716 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3431     0.9408 0.936 0.064
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.2778     0.9336 0.048 0.952
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.0000     0.9716 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.0000     0.9716 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.2423     0.9509 0.040 0.960
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.2423     0.9418 0.960 0.040
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.0000     0.9716 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.0000     0.9716 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     2  0.0000     0.9716 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.3879     0.9391 0.924 0.076
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.2423     0.9418 0.960 0.040
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.2423     0.9509 0.040 0.960
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.0000     0.9716 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B     2  0.2423     0.9410 0.040 0.960
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.2778     0.9336 0.048 0.952
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.0000     0.9716 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     2  0.2778     0.9336 0.048 0.952
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.3879     0.9391 0.924 0.076
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.2423     0.9509 0.040 0.960
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.2423     0.9509 0.040 0.960
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0000     0.9716 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.2423     0.9509 0.040 0.960
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.0000     0.9716 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.2423     0.9509 0.040 0.960
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.0000     0.9716 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.9833     0.1308 0.424 0.576
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.3879     0.9391 0.924 0.076
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.3879     0.9391 0.924 0.076
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.2423     0.9418 0.960 0.040
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5408     0.9042 0.876 0.124
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     2  0.0000     0.9716 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     2  0.2778     0.9336 0.048 0.952
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.0000     0.9716 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.2423     0.9418 0.960 0.040
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9716 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     2  0.0000     0.9716 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.0000     0.9716 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     2  0.1843     0.9514 0.028 0.972
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     2  0.0000     0.9716 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0000     0.9716 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.0000     0.9716 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000     0.9716 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.0000     0.9716 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     2  0.0000     0.9716 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.0000     0.9716 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     2  0.0000     0.9716 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     2  0.0000     0.9716 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.2423     0.9509 0.040 0.960
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     2  0.2423     0.9410 0.040 0.960
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     2  0.0000     0.9716 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     2  0.0000     0.9716 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000     0.9716 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     2  0.0000     0.9716 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     2  0.0000     0.9716 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.0000     0.9716 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.2423     0.9509 0.040 0.960
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     2  0.0000     0.9716 0.000 1.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.2423     0.9418 0.960 0.040
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.2423     0.9509 0.040 0.960
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.2423     0.9509 0.040 0.960
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     2  0.4562     0.8803 0.096 0.904
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.2236     0.9532 0.036 0.964
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     2  0.0000     0.9716 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.4815     0.9184 0.896 0.104
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0000     0.9716 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.0000     0.9716 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     2  0.0000     0.9716 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.2423     0.9418 0.960 0.040
#> D09064DF-70AE-4A49-9F70-2A8093C96724     2  0.0000     0.9716 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     2  0.0000     0.9716 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     2  0.0000     0.9716 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.2423     0.9418 0.960 0.040
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.2423     0.9509 0.040 0.960
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0000     0.9716 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0376     0.9697 0.004 0.996
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.3879     0.9391 0.924 0.076
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0000     0.9716 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.2423     0.9509 0.040 0.960
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.2423     0.9418 0.960 0.040
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.2423     0.9509 0.040 0.960
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     2  0.0000     0.9716 0.000 1.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.2423     0.9418 0.960 0.040
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     2  0.9996    -0.0964 0.488 0.512
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     2  0.0000     0.9716 0.000 1.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.2423     0.9509 0.040 0.960
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.2423     0.9418 0.960 0.040
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     1  0.7883     0.7770 0.764 0.236
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.3879     0.9391 0.924 0.076
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.0000     0.9716 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     2  0.0000     0.9716 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     2  0.2778     0.9336 0.048 0.952
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     2  0.2778     0.9336 0.048 0.952
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     2  0.0000     0.9716 0.000 1.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.2423     0.9509 0.040 0.960
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     2  0.0000     0.9716 0.000 1.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     2  0.0000     0.9716 0.000 1.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.3879     0.9391 0.924 0.076
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     2  0.0000     0.9716 0.000 1.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     2  0.0000     0.9716 0.000 1.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     2  0.0376     0.9697 0.004 0.996
#> CBEFE77E-A0EB-457D-A145-763654236EBB     2  0.2778     0.9336 0.048 0.952
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.2423     0.9509 0.040 0.960
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     2  0.0000     0.9716 0.000 1.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     2  0.0000     0.9716 0.000 1.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.2423     0.9509 0.040 0.960
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.2423     0.9509 0.040 0.960
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     2  0.0000     0.9716 0.000 1.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.2423     0.9509 0.040 0.960
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.2423     0.9509 0.040 0.960
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#> 1469D134-06E6-42EF-9C5A-C30DC2B34C01     2  0.2423     0.9509 0.040 0.960
#> F3F32D39-7ACE-4462-8866-FDCD35DA4599     2  0.0000     0.9716 0.000 1.000
#> E56486B8-FAAE-42BF-B67E-D253783B1043     1  0.2423     0.9418 0.960 0.040
#> F8E9F501-DECA-4A6A-8CF1-1A54915E6FA6     1  0.2778     0.9416 0.952 0.048
#> B3AFCDBB-95EF-4028-84F7-9DBC39B25E70     2  0.2423     0.9509 0.040 0.960
#> 864ACE9F-29B4-4BB2-A966-E6F601637A79     2  0.0000     0.9716 0.000 1.000
#> 932BAFF1-A2A8-404F-A9E9-44DCAA8CFF83     2  0.2778     0.9336 0.048 0.952
#> 1C82688E-01A7-4723-8266-F614FB7EABE5     1  0.5408     0.9042 0.876 0.124
#> 8FED16FD-AFBF-475D-A19F-1BC84D0AA571     2  0.0000     0.9716 0.000 1.000
#> 9EF7685F-CA09-4869-94EA-12A1129093B1     2  0.2423     0.9509 0.040 0.960
#> 18AB08E8-6C1A-49E4-9DF0-79D80D9BEC78     2  0.0000     0.9716 0.000 1.000
#> 97FB3176-395F-475B-8EAE-332C5BEE8155     1  0.2423     0.9418 0.960 0.040
#> E1876307-DFD9-4688-876F-D71B37466068     2  0.2423     0.9509 0.040 0.960
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04     2  0.0000     0.9716 0.000 1.000
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00     2  0.2778     0.9336 0.048 0.952
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79     2  0.0000     0.9716 0.000 1.000
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A     2  0.0000     0.9716 0.000 1.000
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18     2  0.0000     0.9716 0.000 1.000
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D     2  0.0000     0.9716 0.000 1.000
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854     2  0.0000     0.9716 0.000 1.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90     1  0.9983     0.2203 0.524 0.476
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C     2  0.0000     0.9716 0.000 1.000
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046     2  0.0000     0.9716 0.000 1.000
#> 919AED7C-37E6-4F90-8BBC-C0975A291946     2  0.0000     0.9716 0.000 1.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9     2  0.0000     0.9716 0.000 1.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351     2  0.2423     0.9509 0.040 0.960
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63     2  0.2423     0.9509 0.040 0.960
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE     2  0.2423     0.9509 0.040 0.960
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886     2  0.2778     0.9336 0.048 0.952
#> 4326E7CF-426E-4352-9903-27BF06E76626     2  0.2423     0.9509 0.040 0.960
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D     1  0.3879     0.9391 0.924 0.076
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF     2  0.0000     0.9716 0.000 1.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900     2  0.0000     0.9716 0.000 1.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291     2  0.0000     0.9716 0.000 1.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E     2  0.0000     0.9716 0.000 1.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513     2  0.2423     0.9509 0.040 0.960
#> E71AD72B-D55B-4654-89F7-C31CA32624F4     2  0.2423     0.9509 0.040 0.960
#> 7B86D69D-7C51-499A-A603-12D5541EEE96     2  0.0000     0.9716 0.000 1.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB     1  0.5519     0.9007 0.872 0.128
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765     2  0.0000     0.9716 0.000 1.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400     2  0.0000     0.9716 0.000 1.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9     2  0.2423     0.9509 0.040 0.960
#> 457090A2-AE7F-4E68-85EA-032DE8411110     1  0.3879     0.9391 0.924 0.076
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99     2  0.0000     0.9716 0.000 1.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F     2  0.0000     0.9716 0.000 1.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B     2  0.2423     0.9509 0.040 0.960
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B     2  0.0000     0.9716 0.000 1.000
#> 34ED910C-7470-4552-8561-D01D59190521     1  0.2423     0.9418 0.960 0.040
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982     2  0.0000     0.9716 0.000 1.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A     2  0.0000     0.9716 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195     1  0.2423     0.9418 0.960 0.040
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02     2  0.2423     0.9509 0.040 0.960
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69     2  0.0000     0.9716 0.000 1.000
#> A9195281-8CAE-45A8-8493-744E577907FA     2  0.0000     0.9716 0.000 1.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818     2  0.2423     0.9509 0.040 0.960
#> E789661A-C027-405D-9F76-E6D52CE3018B     2  0.0000     0.9716 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3     2  0.0000     0.9716 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11     2  0.0000     0.9716 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345     2  0.2778     0.9336 0.048 0.952
#> CCABB592-8ED5-4879-9918-5C1CCF196A18     1  0.2423     0.9418 0.960 0.040
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4     2  0.0000     0.9716 0.000 1.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     2  0.0000     0.9716 0.000 1.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     2  0.0000     0.9716 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     2  0.0000     0.9716 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     1  0.2423     0.9418 0.960 0.040
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.2423     0.9509 0.040 0.960
#> 80936433-AA91-4219-98F1-706C36298060     2  0.2423     0.9509 0.040 0.960
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     1  0.3879     0.9391 0.924 0.076
#> 241F589C-D559-43D7-8340-31EBCEB36E14     2  0.0000     0.9716 0.000 1.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     2  0.0000     0.9716 0.000 1.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     1  0.2423     0.9418 0.960 0.040
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     2  0.0000     0.9716 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     2  0.0000     0.9716 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     2  0.0000     0.9716 0.000 1.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.2423     0.9418 0.960 0.040
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     2  0.0000     0.9716 0.000 1.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     2  0.0000     0.9716 0.000 1.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     2  0.0000     0.9716 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     2  0.0000     0.9716 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     2  0.3584     0.9131 0.068 0.932
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     2  0.2236     0.9532 0.036 0.964
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     1  0.2423     0.9418 0.960 0.040
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000     0.9716 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     2  0.0000     0.9716 0.000 1.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     2  0.0000     0.9716 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     2  0.0000     0.9716 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     2  0.0000     0.9716 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     2  0.0000     0.9716 0.000 1.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     2  0.0000     0.9716 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     2  0.9248     0.4283 0.340 0.660
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.0000     0.9716 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     2  0.0000     0.9716 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     2  0.0000     0.9716 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.0000     0.9716 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     2  0.0000     0.9716 0.000 1.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     2  0.0000     0.9716 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     2  0.0000     0.9716 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     2  0.0000     0.9716 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     1  0.2423     0.9418 0.960 0.040
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.0000     0.9716 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     2  0.2778     0.9336 0.048 0.952
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     2  0.0000     0.9716 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.0000     0.9716 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.2423     0.9509 0.040 0.960
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.2423     0.9509 0.040 0.960
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     2  0.0938     0.9637 0.012 0.988
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     2  0.2778     0.9336 0.048 0.952
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.3879     0.9391 0.924 0.076
#> 887E7408-C7D7-420F-A763-0EE70A316D17     2  0.0000     0.9716 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.2423     0.9509 0.040 0.960
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.2423     0.9509 0.040 0.960
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.2778     0.9336 0.048 0.952
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.0000     0.9716 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     2  0.0000     0.9716 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.5408     0.9042 0.876 0.124
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.0000     0.9716 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.9000     0.6482 0.684 0.316
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.0000     0.9716 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9716 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     2  0.0000     0.9716 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     2  0.0000     0.9716 0.000 1.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.0000     0.9716 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.7453     0.6941 0.212 0.788
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.0000     0.9716 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.5842     0.8894 0.860 0.140
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000     0.9716 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     2  0.0000     0.9716 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.0000     0.9716 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.2423     0.9509 0.040 0.960
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     2  0.9754     0.2224 0.408 0.592
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.0000     0.9716 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.0000     0.9716 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     2  0.2778     0.9336 0.048 0.952
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     2  0.0000     0.9716 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.2423     0.9418 0.960 0.040
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.9922     0.3119 0.552 0.448
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.9710     0.2495 0.400 0.600
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     2  0.0000     0.9716 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.9866     0.3839 0.568 0.432
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.3879     0.9391 0.924 0.076
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.7815     0.7716 0.768 0.232
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.0000     0.9716 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.3879     0.9391 0.924 0.076
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.2423     0.9418 0.960 0.040
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  1.0000    -0.1610 0.496 0.504
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.0000     0.9716 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9716 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9716 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.0000     0.9716 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.2423     0.9418 0.960 0.040
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.3879     0.9391 0.924 0.076
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3879     0.9391 0.924 0.076
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.0000     0.9716 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.0000     0.9716 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0000     0.9716 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     2  0.0000     0.9716 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0376     0.9697 0.004 0.996
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.0000     0.9716 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.0000     0.9716 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.5408     0.9042 0.876 0.124
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000     0.9716 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2423     0.9509 0.040 0.960
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4298     0.9318 0.912 0.088
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.3879     0.9391 0.924 0.076
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.8608     0.6902 0.716 0.284
#> E6446572-BFA9-4018-89B3-7E4519EBE072     2  0.9393     0.3844 0.356 0.644
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.2778     0.9336 0.048 0.952
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.0000     0.9716 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0000     0.9716 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.0000     0.9716 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2423     0.9509 0.040 0.960
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3879     0.9391 0.924 0.076
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.0000     0.9716 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     2  0.0000     0.9716 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.0000     0.9716 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000     0.8741 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.2448     0.8743 0.924 0.000 0.076
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.9661 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0000     0.9661 0.000 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9820 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000     0.9661 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.0000     0.9661 0.000 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.0000     0.9661 0.000 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0000     0.9661 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.8741 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.5291     0.6903 0.732 0.000 0.268
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0000     0.9661 0.000 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9820 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9820 0.000 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.5835     0.5935 0.660 0.000 0.340
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.3686     0.8119 0.140 0.000 0.860
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.0000     0.9661 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9820 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.5529     0.6555 0.704 0.000 0.296
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9820 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.6309    -0.1026 0.500 0.000 0.500
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9820 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.8741 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9820 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.4555     0.7347 0.200 0.000 0.800
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9820 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.9661 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.0000     0.9661 0.000 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.0000     0.9661 0.000 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2796     0.8722 0.908 0.000 0.092
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000     0.9661 0.000 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9820 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.0000     0.9661 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.0000     0.9661 0.000 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.0000     0.9661 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.0000     0.9661 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.0000     0.9661 0.000 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000     0.9661 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.2356     0.8746 0.928 0.000 0.072
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.2356     0.9034 0.072 0.000 0.928
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0000     0.9661 0.000 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0000     0.9661 0.000 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9820 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.8741 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0000     0.9661 0.000 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.9661 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0000     0.9661 0.000 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.2796     0.8722 0.908 0.000 0.092
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0000     0.8741 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9820 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     3  0.0000     0.9661 0.000 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.2066     0.9149 0.060 0.000 0.940
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.2356     0.9034 0.072 0.000 0.928
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0000     0.9661 0.000 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.2356     0.9034 0.072 0.000 0.928
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.2796     0.8722 0.908 0.000 0.092
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9820 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9820 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0000     0.9661 0.000 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9820 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.0000     0.9661 0.000 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9820 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.0000     0.9661 0.000 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3  0.6008     0.3138 0.372 0.000 0.628
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.2796     0.8722 0.908 0.000 0.092
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.2796     0.8722 0.908 0.000 0.092
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0000     0.8741 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.4062     0.8111 0.836 0.000 0.164
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.0000     0.9661 0.000 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.2356     0.9034 0.072 0.000 0.928
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0000     0.9661 0.000 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000     0.8741 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3  0.0000     0.9661 0.000 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0000     0.9661 0.000 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000     0.9661 0.000 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.1289     0.9400 0.032 0.000 0.968
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.9661 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3  0.0000     0.9661 0.000 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.9661 0.000 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.9661 0.000 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.0000     0.9661 0.000 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.0000     0.9661 0.000 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3  0.0000     0.9661 0.000 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0000     0.9661 0.000 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.0000     0.9661 0.000 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9820 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     3  0.2165     0.9111 0.064 0.000 0.936
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.9661 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.0000     0.9661 0.000 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3  0.0000     0.9661 0.000 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3  0.0000     0.9661 0.000 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0000     0.9661 0.000 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     3  0.0000     0.9661 0.000 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9820 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.0000     0.9661 0.000 0.000 1.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.0000     0.8741 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9820 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9820 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.3412     0.8442 0.124 0.000 0.876
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3  0.4702     0.7282 0.000 0.212 0.788
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3  0.0000     0.9661 0.000 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.3192     0.8556 0.888 0.000 0.112
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3  0.0000     0.9661 0.000 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.0000     0.9661 0.000 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.0000     0.9661 0.000 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     1  0.0000     0.8741 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.0000     0.9661 0.000 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.0000     0.9661 0.000 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     3  0.0000     0.9661 0.000 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     1  0.0000     0.8741 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3  0.6235     0.2632 0.000 0.436 0.564
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     3  0.0000     0.9661 0.000 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.4842     0.6453 0.000 0.776 0.224
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.2796     0.8722 0.908 0.000 0.092
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     3  0.0000     0.9661 0.000 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.9820 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     1  0.0000     0.8741 1.000 0.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.1411     0.9329 0.000 0.964 0.036
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0000     0.9661 0.000 0.000 1.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     1  0.0000     0.8741 1.000 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.6295     0.1968 0.528 0.000 0.472
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     3  0.0000     0.9661 0.000 0.000 1.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000     0.9820 0.000 1.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     1  0.0000     0.8741 1.000 0.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     1  0.5497     0.6605 0.708 0.000 0.292
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.2796     0.8722 0.908 0.000 0.092
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3  0.0000     0.9661 0.000 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3  0.0000     0.9661 0.000 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     3  0.2356     0.9034 0.072 0.000 0.928
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.2356     0.9034 0.072 0.000 0.928
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3  0.0000     0.9661 0.000 0.000 1.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0000     0.9820 0.000 1.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3  0.0000     0.9661 0.000 0.000 1.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3  0.0000     0.9661 0.000 0.000 1.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.2796     0.8722 0.908 0.000 0.092
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3  0.0000     0.9661 0.000 0.000 1.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     3  0.0000     0.9661 0.000 0.000 1.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     3  0.1163     0.9431 0.000 0.028 0.972
#> CBEFE77E-A0EB-457D-A145-763654236EBB     3  0.2356     0.9034 0.072 0.000 0.928
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.0000     0.9820 0.000 1.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3  0.0000     0.9661 0.000 0.000 1.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     3  0.0000     0.9661 0.000 0.000 1.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0000     0.9820 0.000 1.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.0000     0.9820 0.000 1.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     3  0.0000     0.9661 0.000 0.000 1.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.0000     0.9820 0.000 1.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.0000     0.9820 0.000 1.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     1  0.0000     0.8741 1.000 0.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3  0.0000     0.9661 0.000 0.000 1.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     3  0.6111     0.2942 0.396 0.000 0.604
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0     2  0.0000     0.9820 0.000 1.000 0.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3     3  0.0000     0.9661 0.000 0.000 1.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406     3  0.0000     0.9661 0.000 0.000 1.000
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA     1  0.0000     0.8741 1.000 0.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE     1  0.3752     0.8305 0.856 0.000 0.144
#> 70F9FC41-6202-4B58-9C7C-9946E103E319     1  0.0000     0.8741 1.000 0.000 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F     1  0.2796     0.8722 0.908 0.000 0.092
#> DAB49A2E-BBFD-459B-B156-726D8D91D598     1  0.2796     0.8722 0.908 0.000 0.092
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F     3  0.0000     0.9661 0.000 0.000 1.000
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0     2  0.0000     0.9820 0.000 1.000 0.000
#> D149276E-A961-49D6-8BDA-004E8264A0A1     3  0.0000     0.9661 0.000 0.000 1.000
#> D17803A2-4BF2-4382-A544-76E28695214F     3  0.2537     0.8954 0.080 0.000 0.920
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6     3  0.0000     0.9661 0.000 0.000 1.000
#> 16F5BF94-5103-4973-9432-34FDCC82B6A2     1  0.0000     0.8741 1.000 0.000 0.000
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#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0000     0.9661 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0000     0.9661 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.0000     0.9661 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.0921     0.8016 0.972 0.000 0.000 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.0921     0.9384 0.028 0.000 0.972 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.4543     0.5687 0.324 0.000 0.000 0.676
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     3  0.1389     0.9214 0.048 0.000 0.952 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0921     0.9384 0.028 0.000 0.972 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.1118     0.8034 0.964 0.000 0.036 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.0188     0.8187 0.996 0.000 0.004 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.0921     0.9384 0.028 0.000 0.972 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     3  0.0707     0.9451 0.020 0.000 0.980 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.3528     0.6228 0.808 0.000 0.000 0.192
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     1  0.0921     0.8067 0.972 0.000 0.028 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4804     0.3034 0.384 0.000 0.616 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     3  0.4898     0.2285 0.416 0.000 0.584 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.3356     0.7993 0.176 0.000 0.000 0.824
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.3649     0.6446 0.796 0.000 0.204 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0921     0.8066 0.972 0.000 0.028 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.0921     0.8067 0.972 0.000 0.028 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.4164     0.5738 0.736 0.000 0.264 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     3  0.0921     0.9384 0.028 0.000 0.972 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.4855     0.4074 0.600 0.000 0.400 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.4746     0.4534 0.632 0.000 0.368 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0707     0.9236 0.020 0.000 0.000 0.980
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     3  0.0921     0.9384 0.028 0.000 0.972 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.1118     0.8034 0.964 0.000 0.036 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3  0.2973     0.8087 0.144 0.000 0.856 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     4  0.3486     0.7872 0.188 0.000 0.000 0.812
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3  0.3726     0.7239 0.000 0.212 0.788 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.4477     0.5121 0.312 0.000 0.688 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.1118     0.8034 0.964 0.000 0.036 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3  0.4941     0.2753 0.000 0.436 0.564 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.3837     0.6091 0.000 0.776 0.224 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     1  0.3610     0.6465 0.800 0.000 0.200 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     4  0.3764     0.7537 0.216 0.000 0.000 0.784
#> 9980293D-AF0A-4215-9688-C576B1F8B519     2  0.1118     0.9242 0.000 0.964 0.036 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0336     0.8176 0.992 0.000 0.008 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     1  0.0921     0.8067 0.972 0.000 0.028 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     1  0.4746     0.4654 0.632 0.000 0.368 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.1118     0.8034 0.964 0.000 0.036 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     3  0.0921     0.9379 0.000 0.028 0.972 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.3528     0.6553 0.808 0.000 0.192 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913     1  0.0000     0.8197 1.000 0.000 0.000 0.000
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#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000     0.9342 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.3528     0.6228 0.808 0.000 0.000 0.192
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.3764     0.6288 0.784 0.000 0.216 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3  0.1557     0.9097 0.000 0.056 0.944 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0336     0.8176 0.992 0.000 0.008 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3569     0.6599 0.000 0.804 0.196 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     3  0.1792     0.9008 0.068 0.000 0.932 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     3  0.3610     0.7259 0.200 0.000 0.800 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     3  0.4830     0.3051 0.392 0.000 0.608 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.3942     0.6063 0.764 0.000 0.236 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.0000     0.8197 1.000 0.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9799 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     3  0.3444     0.7512 0.184 0.000 0.816 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0000     0.9608 0.000 0.000 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.4925     0.3449 0.572 0.000 0.428 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.0000     0.9608 0.000 0.000 1.000 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.0162      0.859 0.000 0.000 0.000 0.996 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.0162      0.963 0.000 0.000 0.996 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0404      0.957 0.012 0.000 0.988 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.0404      0.892 0.988 0.000 0.012 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.2286      0.782 0.888 0.000 0.108 0.004 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     3  0.0162      0.963 0.000 0.000 0.996 0.004 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0162      0.859 0.000 0.000 0.004 0.996 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0162      0.978 0.004 0.996 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.0404      0.892 0.988 0.000 0.012 0.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.3949      0.452 0.332 0.000 0.000 0.668 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     3  0.0162      0.963 0.000 0.000 0.996 0.004 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.0609      0.887 0.980 0.000 0.020 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.3109      0.659 0.000 0.000 0.000 0.800 0.200
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.0162      0.859 0.000 0.000 0.004 0.996 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4192      0.266 0.000 0.000 0.596 0.404 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.6486      0.254 0.472 0.000 0.324 0.204 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     4  0.3074      0.656 0.000 0.000 0.196 0.804 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     4  0.0794      0.839 0.000 0.000 0.028 0.972 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.0162      0.859 0.000 0.000 0.004 0.996 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0290      0.976 0.008 0.992 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0404      0.974 0.012 0.988 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0671      0.890 0.980 0.000 0.016 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0451      0.888 0.988 0.000 0.000 0.004 0.008
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.0451      0.892 0.988 0.000 0.008 0.004 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.0162      0.859 0.000 0.000 0.004 0.996 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.0404      0.892 0.988 0.000 0.012 0.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.4126      0.375 0.380 0.000 0.620 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0290      0.976 0.008 0.992 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3  0.2516      0.817 0.000 0.000 0.860 0.140 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.2377      0.770 0.872 0.000 0.128 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0162      0.978 0.004 0.996 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3  0.3496      0.732 0.012 0.200 0.788 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.4273      0.279 0.552 0.000 0.448 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     3  0.3895      0.500 0.000 0.000 0.680 0.320 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     4  0.0162      0.859 0.000 0.000 0.004 0.996 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     1  0.3039      0.681 0.808 0.000 0.192 0.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     3  0.4597      0.277 0.012 0.424 0.564 0.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
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#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.4171      0.387 0.604 0.000 0.396 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     3  0.4101      0.370 0.000 0.000 0.628 0.372 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.0162      0.963 0.000 0.000 0.996 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     4  0.2690      0.705 0.000 0.000 0.156 0.844 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0451      0.892 0.988 0.000 0.008 0.004 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.0451      0.892 0.988 0.000 0.008 0.004 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.0703      0.884 0.976 0.000 0.024 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.0162      0.963 0.004 0.000 0.996 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     3  0.0162      0.963 0.000 0.000 0.996 0.004 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.2424      0.762 0.868 0.000 0.132 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.0451      0.892 0.988 0.000 0.008 0.004 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.1043      0.938 0.040 0.000 0.960 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.0510      0.888 0.984 0.000 0.016 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0290      0.976 0.008 0.992 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.2377      0.736 0.000 0.000 0.128 0.872 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.2280      0.841 0.000 0.000 0.880 0.120 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     5  0.1197      0.951 0.048 0.000 0.000 0.000 0.952
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.3452      0.654 0.000 0.000 0.756 0.244 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.0404      0.892 0.988 0.000 0.012 0.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.0000      0.998 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0609      0.887 0.980 0.000 0.020 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     3  0.0609      0.950 0.020 0.000 0.980 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.3876      0.465 0.000 0.000 0.000 0.684 0.316
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.3398      0.630 0.004 0.000 0.216 0.780 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     3  0.0290      0.961 0.008 0.000 0.992 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3  0.1740      0.910 0.012 0.056 0.932 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     1  0.5575      0.556 0.644 0.168 0.188 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     3  0.2516      0.810 0.140 0.000 0.860 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.0451      0.892 0.988 0.000 0.008 0.004 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.0404      0.854 0.012 0.000 0.000 0.988 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     4  0.3395      0.605 0.000 0.000 0.236 0.764 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.0000      0.861 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.0404      0.960 0.012 0.000 0.988 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000      0.980 0.000 1.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0404      0.891 0.988 0.000 0.000 0.012 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0000      0.965 0.000 0.000 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.4242      0.324 0.000 0.000 0.428 0.572 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.0000      0.965 0.000 0.000 1.000 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000     0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     1  0.2260     0.8005 0.860 0.000 0.140 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.1714     0.8609 0.908 0.000 0.092 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.3482     0.4955 0.684 0.000 0.316 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.0363     0.9370 0.988 0.000 0.000 0.000 0.012 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0146     0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0146     0.9532 0.004 0.996 0.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     5  0.1267     0.8351 0.060 0.000 0.000 0.000 0.940 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0260     0.9521 0.000 0.992 0.008 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.1700     0.8368 0.000 0.004 0.080 0.000 0.916 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000     0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0146     0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.3351     0.5728 0.000 0.288 0.712 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     6  0.3804     0.2682 0.000 0.000 0.000 0.000 0.424 0.576
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0260     0.9399 0.992 0.000 0.008 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     1  0.0260     0.9396 0.992 0.000 0.008 0.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     5  0.1957     0.7686 0.112 0.000 0.000 0.000 0.888 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.3592     0.4309 0.656 0.000 0.344 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     6  0.2793     0.6666 0.000 0.000 0.000 0.200 0.000 0.800
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.1814     0.8840 0.000 0.900 0.100 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0000     0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.4184     0.2385 0.576 0.000 0.016 0.000 0.000 0.408
#> 066B10C1-777F-4863-ACCA-6684310B913E     5  0.5484     0.4014 0.228 0.000 0.000 0.000 0.568 0.204
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     6  0.2762     0.6718 0.196 0.000 0.000 0.000 0.000 0.804
#> 4379559E-E467-49BD-9673-40A486146A3B     6  0.0713     0.8463 0.028 0.000 0.000 0.000 0.000 0.972
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
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#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000     0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.0260     0.8891 0.008 0.000 0.000 0.000 0.992 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.0547     0.9302 0.980 0.000 0.000 0.000 0.020 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     6  0.3482     0.4712 0.000 0.000 0.000 0.316 0.000 0.684
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.3918     0.6871 0.124 0.000 0.000 0.000 0.108 0.768
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0458     0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.3428     0.5191 0.696 0.000 0.304 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     3  0.4264     0.4366 0.352 0.028 0.620 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.6409     0.5117 0.184 0.140 0.108 0.000 0.568 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.2260     0.7986 0.860 0.000 0.000 0.000 0.140 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.0363     0.8603 0.000 0.000 0.000 0.000 0.012 0.988
#> E6446572-BFA9-4018-89B3-7E4519EBE072     6  0.3050     0.6228 0.236 0.000 0.000 0.000 0.000 0.764
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.0000     0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.1814     0.7688 0.100 0.000 0.900 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.0458     0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     5  0.0000     0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000     0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.3810     0.3085 0.428 0.000 0.000 0.000 0.000 0.572
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0000     0.9443 1.000 0.000 0.000 0.000 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-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 17541 rows and 500 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 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-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 0.834           0.913       0.963         0.2971 0.709   0.709
#> 3 3 0.433           0.455       0.667         0.7237 0.665   0.549
#> 4 4 0.696           0.646       0.843         0.2761 0.753   0.498
#> 5 5 0.734           0.822       0.905         0.0414 0.865   0.643
#> 6 6 0.788           0.823       0.904         0.0940 0.862   0.610

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

suggest_best_k(res)
#> [1] 4

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000     0.9065 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.5629     0.8438 0.868 0.132
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0672     0.9639 0.008 0.992
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.7376     0.7122 0.208 0.792
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000     0.9701 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000     0.9701 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000     0.9701 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.0000     0.9701 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     1  0.6343     0.8242 0.840 0.160
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000     0.9065 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.8909     0.6423 0.692 0.308
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0000     0.9701 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000     0.9701 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000     0.9701 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.0938     0.9607 0.012 0.988
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.0000     0.9701 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     2  0.0376     0.9671 0.004 0.996
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000     0.9701 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.7950     0.7393 0.760 0.240
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000     0.9701 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     1  0.1184     0.9050 0.984 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000     0.9701 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000     0.9065 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000     0.9701 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     2  0.0000     0.9701 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000     0.9701 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.0000     0.9701 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0000     0.9701 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.0376     0.9671 0.004 0.996
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     2  0.0938     0.9607 0.012 0.988
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.0000     0.9701 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000     0.9701 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     2  0.2236     0.9372 0.036 0.964
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.0000     0.9701 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.0000     0.9701 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0376     0.9671 0.004 0.996
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000     0.9701 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     2  0.0000     0.9701 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     2  0.9491     0.3689 0.368 0.632
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     2  0.9323     0.4225 0.348 0.652
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.0000     0.9701 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.0000     0.9701 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000     0.9701 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000     0.9065 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.0000     0.9701 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.0000     0.9701 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     1  0.1184     0.9050 0.984 0.016
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.0672     0.9640 0.008 0.992
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.5946     0.8332 0.856 0.144
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0938     0.9607 0.012 0.988
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.0000     0.9701 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B     2  0.0000     0.9701 0.000 1.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.0938     0.9053 0.988 0.012
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.0000     0.9701 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     2  0.0000     0.9701 0.000 1.000
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.7745     0.6756 0.228 0.772
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000     0.9701 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0000     0.9701 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0000     0.9701 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000     0.9701 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.0000     0.9701 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000     0.9701 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.0000     0.9701 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.0938     0.9607 0.012 0.988
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.8386     0.7018 0.732 0.268
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.6801     0.8038 0.820 0.180
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0000     0.9065 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.7219     0.7241 0.200 0.800
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     2  0.0000     0.9701 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     2  0.0000     0.9701 0.000 1.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     1  0.1184     0.9050 0.984 0.016
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000     0.9065 1.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000     0.9701 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     1  0.1184     0.9050 0.984 0.016
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.0000     0.9701 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     2  0.7674     0.6854 0.224 0.776
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     1  0.6801     0.8072 0.820 0.180
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.1184     0.9576 0.016 0.984
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     2  0.0000     0.9701 0.000 1.000
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.8081     0.7278 0.752 0.248
#> 887E7408-C7D7-420F-A763-0EE70A316D17     2  0.0000     0.9701 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000     0.9701 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000     0.9701 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     2  0.0000     0.9701 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     2  0.0000     0.9701 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     2  0.0000     0.9701 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.0938     0.9607 0.012 0.988
#> C075F09E-623C-46ED-B927-889B48F450B3     2  0.0000     0.9701 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.0938     0.9607 0.012 0.988
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.0000     0.9701 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0000     0.9701 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     2  0.0000     0.9701 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     2  0.0000     0.9701 0.000 1.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.0000     0.9701 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.0938     0.9607 0.012 0.988
#> 816CF68B-8476-4960-9F05-FB959A686323     2  0.7056     0.7380 0.192 0.808
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.8016     0.6458 0.244 0.756
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0376     0.9671 0.004 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789     2  0.0000     0.9701 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.9661     0.4691 0.608 0.392
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000     0.9701 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     2  0.0000     0.9701 0.000 1.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.0000     0.9701 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.0000     0.9701 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     2  0.0000     0.9701 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     2  0.0000     0.9701 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000     0.9065 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     2  0.4939     0.8556 0.108 0.892
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     2  0.7056     0.7381 0.192 0.808
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     2  0.0000     0.9701 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.8813     0.6553 0.700 0.300
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     2  0.0000     0.9701 0.000 1.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     2  0.0000     0.9701 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.0000     0.9701 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512     1  0.1184     0.9050 0.984 0.016
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000     0.9065 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.0672     0.9640 0.008 0.992
#> C56C7ED7-A684-40CC-B426-B108E2248467     1  0.1184     0.9050 0.984 0.016
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0000     0.9701 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     2  0.0000     0.9701 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.0000     0.9701 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     1  0.0938     0.9053 0.988 0.012
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     2  0.0376     0.9670 0.004 0.996
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     2  0.0000     0.9701 0.000 1.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     2  0.0000     0.9701 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.0000     0.9701 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0376     0.9671 0.004 0.996
#> 1B73CE27-B464-41E6-BE27-90FA13683331     2  0.0000     0.9701 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.4815     0.8625 0.104 0.896
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.0000     0.9701 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.0000     0.9701 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.9988    -0.0768 0.480 0.520
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0000     0.9701 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000     0.9701 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     2  0.0938     0.9607 0.012 0.988
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     2  0.1184     0.9576 0.016 0.984
#> EB7883EB-0079-4548-9132-169E94A698BA     2  0.0000     0.9701 0.000 1.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     2  0.0000     0.9701 0.000 1.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     2  0.0000     0.9701 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.0000     0.9701 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     2  0.0938     0.9606 0.012 0.988
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     1  0.2043     0.8985 0.968 0.032
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000     0.9701 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.0938     0.9607 0.012 0.988
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     2  0.0000     0.9701 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     2  0.0000     0.9701 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.0000     0.9701 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000    0.79853 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.6676   -0.29094 0.476 0.008 0.516
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3116    0.48767 0.108 0.000 0.892
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.2537    0.52648 0.080 0.000 0.920
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.6295    0.64372 0.000 0.528 0.472
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.6305    0.63924 0.000 0.516 0.484
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.6302    0.64202 0.000 0.520 0.480
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.6307    0.63270 0.000 0.512 0.488
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.6944   -0.28860 0.468 0.016 0.516
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000    0.79853 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.5785    0.51101 0.668 0.332 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.6299    0.64329 0.000 0.524 0.476
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0237    0.45732 0.004 0.996 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.6295    0.64372 0.000 0.528 0.472
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.6941    0.63751 0.016 0.520 0.464
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     2  0.6299    0.64329 0.000 0.524 0.476
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.0237    0.55028 0.000 0.004 0.996
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0237    0.45732 0.004 0.996 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     1  0.5465    0.56111 0.712 0.288 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0237    0.45732 0.004 0.996 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.6944   -0.28860 0.468 0.016 0.516
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0237    0.45732 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     1  0.0000    0.79853 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0237    0.45732 0.004 0.996 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.5016    0.27331 0.000 0.240 0.760
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0475    0.45318 0.004 0.992 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.6305    0.63924 0.000 0.516 0.484
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.6299    0.64329 0.000 0.524 0.476
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.6295    0.64372 0.000 0.528 0.472
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     2  0.6813    0.64023 0.012 0.520 0.468
#> 97C34F1F-2002-4771-8D99-511EA08591CD     2  0.6307    0.63279 0.000 0.512 0.488
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0237    0.45732 0.004 0.996 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.2537    0.52652 0.080 0.000 0.920
#> C06D8112-0FA0-4607-988D-589D8694743F     2  0.6305    0.63924 0.000 0.516 0.484
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.6295    0.64372 0.000 0.528 0.472
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.6509    0.64350 0.004 0.524 0.472
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.6295    0.64372 0.000 0.528 0.472
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.5722    0.09521 0.004 0.292 0.704
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.6252   -0.23260 0.444 0.000 0.556
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.6026   -0.09376 0.376 0.000 0.624
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.6309   -0.60310 0.000 0.496 0.504
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     2  0.6305    0.63924 0.000 0.516 0.484
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0237    0.45732 0.004 0.996 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     1  0.0000    0.79853 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     2  0.6305    0.63924 0.000 0.516 0.484
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.6509    0.64278 0.004 0.524 0.472
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.6944   -0.28860 0.468 0.016 0.516
#> 066B10C1-777F-4863-ACCA-6684310B913E     2  0.6509    0.64350 0.004 0.524 0.472
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     1  0.4291    0.66696 0.820 0.180 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0747    0.45427 0.016 0.984 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     2  0.6305    0.63924 0.000 0.516 0.484
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4346    0.39829 0.000 0.184 0.816
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     1  0.6905    0.38585 0.544 0.016 0.440
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.6305    0.63924 0.000 0.516 0.484
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.4002    0.43249 0.000 0.160 0.840
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.9199    0.48306 0.168 0.504 0.328
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0237    0.45732 0.004 0.996 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.6291    0.64319 0.000 0.532 0.468
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.6295    0.64372 0.000 0.528 0.472
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0475    0.45866 0.004 0.992 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.6299    0.64329 0.000 0.524 0.476
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0829    0.46090 0.004 0.984 0.012
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.6302    0.64202 0.000 0.520 0.480
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.6672    0.64214 0.008 0.520 0.472
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     1  0.6192    0.34009 0.580 0.420 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     1  0.6235    0.28423 0.564 0.436 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     1  0.0000    0.79853 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.9338    0.45438 0.196 0.504 0.300
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     3  0.5591    0.04927 0.000 0.304 0.696
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.4291    0.40673 0.000 0.180 0.820
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.6944   -0.28860 0.468 0.016 0.516
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     1  0.0000    0.79853 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.3851    0.49035 0.004 0.860 0.136
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.6944   -0.28860 0.468 0.016 0.516
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.6299    0.64345 0.000 0.524 0.476
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.2261    0.54041 0.068 0.000 0.932
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.6944   -0.28860 0.468 0.016 0.516
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.7278    0.62992 0.028 0.516 0.456
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.5882   -0.14867 0.000 0.348 0.652
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0237    0.45732 0.004 0.996 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     2  0.6305    0.63924 0.000 0.516 0.484
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.6126   -0.23069 0.000 0.400 0.600
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.6295    0.64372 0.000 0.528 0.472
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     1  0.9386    0.30476 0.500 0.296 0.204
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     2  0.6305    0.63924 0.000 0.516 0.484
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.1411    0.46741 0.000 0.964 0.036
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     3  0.6204   -0.41135 0.000 0.424 0.576
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.4094    0.51382 0.028 0.100 0.872
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     3  0.6305   -0.57544 0.000 0.484 0.516
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.6260    0.63359 0.000 0.552 0.448
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     3  0.4974    0.28316 0.000 0.236 0.764
#> 4D361EA8-1F79-4B89-841B-87F83215D805     2  0.6305    0.63924 0.000 0.516 0.484
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.6669    0.64226 0.008 0.524 0.468
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0237    0.45732 0.004 0.996 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     2  0.6305    0.63924 0.000 0.516 0.484
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     1  0.0000    0.79853 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.6460    0.62681 0.004 0.556 0.440
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#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     3  0.1163    0.54207 0.000 0.028 0.972
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     3  0.6026   -0.24883 0.000 0.376 0.624
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     2  0.6509    0.64278 0.004 0.524 0.472
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0237    0.45732 0.004 0.996 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0829    0.46090 0.004 0.984 0.012
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     3  0.5431    0.13094 0.000 0.284 0.716
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.2356    0.51452 0.000 0.072 0.928
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.6897    0.25342 0.548 0.436 0.016
#> 887E7408-C7D7-420F-A763-0EE70A316D17     3  0.6299   -0.55532 0.000 0.476 0.524
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0237    0.45732 0.004 0.996 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0237    0.45732 0.004 0.996 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3  0.4291    0.40436 0.000 0.180 0.820
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.4346    0.39829 0.000 0.184 0.816
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.4555    0.37021 0.000 0.200 0.800
#> EE40EE80-4520-4643-B906-48246BA616A7     2  0.6672    0.64214 0.008 0.520 0.472
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0747    0.54758 0.000 0.016 0.984
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     2  0.6941    0.63751 0.016 0.520 0.464
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     2  0.6509    0.64278 0.004 0.524 0.472
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.1129    0.46286 0.004 0.976 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.4062    0.42573 0.000 0.164 0.836
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     2  0.6305    0.63924 0.000 0.516 0.484
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     2  0.6307    0.63627 0.000 0.512 0.488
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.9243    0.46422 0.192 0.520 0.288
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.2448    0.53144 0.076 0.000 0.924
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     2  0.9387    0.43538 0.220 0.508 0.272
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0237    0.45732 0.004 0.996 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     2  0.6302    0.64202 0.000 0.520 0.480
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     1  0.6308    0.11875 0.508 0.492 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0475    0.45866 0.004 0.992 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     2  0.6305    0.63924 0.000 0.516 0.484
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.6305    0.63924 0.000 0.516 0.484
#> 5E03E52F-957D-455B-A007-19714FAA818A     2  0.6305    0.63924 0.000 0.516 0.484
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     3  0.6295   -0.54513 0.000 0.472 0.528
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.5722    0.09473 0.004 0.292 0.704
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     1  0.0000    0.79853 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     3  0.1860    0.55219 0.052 0.000 0.948
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     3  0.1860    0.55219 0.052 0.000 0.948
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     3  0.6244   -0.45863 0.000 0.440 0.560
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     1  0.5650    0.53379 0.688 0.312 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     2  0.6305    0.63924 0.000 0.516 0.484
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.0237    0.55028 0.000 0.004 0.996
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     2  0.6305    0.63924 0.000 0.516 0.484
#> 1122039D-5785-4F70-9916-17C585453512     3  0.6813   -0.28419 0.468 0.012 0.520
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     1  0.0000    0.79853 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.6509    0.64350 0.004 0.524 0.472
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.6944   -0.28860 0.468 0.016 0.516
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.6669    0.64048 0.008 0.524 0.468
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.4178    0.41554 0.000 0.172 0.828
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     2  0.6305    0.63924 0.000 0.516 0.484
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.6944   -0.28860 0.468 0.016 0.516
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.0892    0.54632 0.000 0.020 0.980
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     2  0.6305    0.63924 0.000 0.516 0.484
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0237    0.55028 0.000 0.004 0.996
#> 79BA86D9-466F-48D7-B64B-F933B6995716     2  0.6305    0.63924 0.000 0.516 0.484
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3644    0.49153 0.004 0.872 0.124
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.4452    0.38657 0.000 0.192 0.808
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5678    0.21741 0.316 0.684 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     2  0.6305    0.63924 0.000 0.516 0.484
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.6305    0.63924 0.000 0.516 0.484
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     2  0.8427    0.19189 0.412 0.500 0.088
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.6295    0.64372 0.000 0.528 0.472
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0237    0.45732 0.004 0.996 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     2  0.6813    0.64023 0.012 0.520 0.468
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     2  0.6941    0.63751 0.016 0.520 0.464
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.5621    0.04583 0.000 0.308 0.692
#> E6446572-BFA9-4018-89B3-7E4519EBE072     2  0.6307    0.63270 0.000 0.512 0.488
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.4750    0.33772 0.000 0.216 0.784
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     2  0.6305    0.63924 0.000 0.516 0.484
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.7517   -0.24367 0.420 0.040 0.540
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.6944   -0.28860 0.468 0.016 0.516
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0237    0.45732 0.004 0.996 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.6672    0.64214 0.008 0.520 0.472
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.5138    0.23241 0.000 0.252 0.748
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0424    0.54962 0.000 0.008 0.992
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.6302    0.64202 0.000 0.520 0.480

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.0336    0.51963 0.000 0.000 0.992 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.4994    0.40296 0.480 0.000 0.520 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.4994    0.40296 0.480 0.000 0.520 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.6894    0.75904 0.512 0.112 0.376 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.5165    0.87733 0.512 0.004 0.484 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     4  0.4996    0.00946 0.000 0.484 0.000 0.516
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.5404    0.87349 0.512 0.012 0.476 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.5292    0.87579 0.512 0.008 0.480 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6521    0.80519 0.512 0.076 0.412 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.5165    0.87725 0.512 0.004 0.484 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.1389    0.54031 0.048 0.000 0.952 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.4500    0.48679 0.000 0.316 0.000 0.684
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     3  0.4998   -0.84666 0.488 0.000 0.512 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.5165    0.87733 0.512 0.004 0.484 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.5404    0.87360 0.512 0.012 0.476 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.5332    0.87594 0.512 0.004 0.480 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.4994    0.40296 0.480 0.000 0.520 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.5506    0.87058 0.512 0.016 0.472 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.5688    0.86418 0.512 0.024 0.464 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.5771    0.86061 0.512 0.028 0.460 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.0707    0.52938 0.020 0.000 0.980 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4994    0.40296 0.480 0.000 0.520 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     3  0.5000   -0.85893 0.496 0.000 0.504 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     1  0.7063    0.73016 0.508 0.132 0.360 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     1  0.5292    0.87581 0.512 0.008 0.480 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.1637    0.42092 0.060 0.000 0.940 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     3  0.1118    0.46522 0.036 0.000 0.964 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.8367    0.64508 0.512 0.072 0.280 0.136
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.7380    0.63739 0.512 0.200 0.288 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.5404    0.87360 0.512 0.012 0.476 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.5165    0.87733 0.512 0.004 0.484 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.5165    0.87733 0.512 0.004 0.484 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.5600    0.86739 0.512 0.020 0.468 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.7467   -0.15201 0.372 0.004 0.156 0.468
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.6698    0.34395 0.156 0.004 0.208 0.632
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.7133    0.44509 0.512 0.344 0.144 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.0817    0.48550 0.024 0.000 0.976 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.7053    0.73131 0.512 0.132 0.356 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.4972    0.41689 0.456 0.000 0.544 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.4996    0.39920 0.484 0.000 0.516 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.6366    0.22743 0.512 0.424 0.064 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.1302    0.53860 0.044 0.000 0.956 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.4992   -0.16597 0.000 0.476 0.524 0.000
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#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.5850    0.85604 0.512 0.032 0.456 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.5292    0.87581 0.512 0.008 0.480 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     1  0.7211    0.72261 0.512 0.004 0.352 0.132
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.5506    0.87065 0.512 0.016 0.472 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.3172    0.56417 0.160 0.000 0.840 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     3  0.2647    0.55819 0.120 0.000 0.880 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.5165    0.00958 0.512 0.484 0.004 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.5506    0.87104 0.512 0.016 0.472 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.5688    0.86386 0.512 0.024 0.464 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.5771    0.86008 0.512 0.028 0.460 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     1  0.4998   -0.00686 0.512 0.488 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     1  0.5292    0.87581 0.512 0.008 0.480 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.7053    0.06379 0.132 0.356 0.512 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.5404    0.87349 0.512 0.012 0.476 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.4989    0.40758 0.472 0.000 0.528 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     1  0.6330    0.15513 0.492 0.448 0.060 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     1  0.5407    0.86963 0.504 0.012 0.484 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     1  0.7536    0.50710 0.488 0.000 0.228 0.284
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.1792    0.40397 0.068 0.000 0.932 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     3  0.3764   -0.09120 0.216 0.000 0.784 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.5600    0.86753 0.512 0.020 0.468 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.4955    0.42287 0.444 0.000 0.556 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.6252    0.82923 0.512 0.056 0.432 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.5506    0.87058 0.512 0.016 0.472 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.0469    0.88594 0.000 0.988 0.012 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     3  0.2408    0.31915 0.104 0.000 0.896 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     3  0.4999   -0.85312 0.492 0.000 0.508 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.4998   -0.00686 0.512 0.488 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.4994    0.40296 0.480 0.000 0.520 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     1  0.7861    0.52736 0.508 0.268 0.208 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.5292    0.87581 0.512 0.008 0.480 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     4  0.4998   -0.00604 0.000 0.488 0.000 0.512
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.1211    0.45867 0.040 0.000 0.960 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     4  0.4855    0.28421 0.000 0.400 0.000 0.600
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 1122039D-5785-4F70-9916-17C585453512     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000    0.90667 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.5771    0.86008 0.512 0.028 0.460 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     1  0.6822    0.34587 0.512 0.384 0.104 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0188    0.52166 0.004 0.000 0.996 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1940    0.54883 0.076 0.000 0.924 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.4998   -0.00686 0.512 0.488 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     3  0.4996   -0.84001 0.484 0.000 0.516 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.5600    0.12459 0.468 0.512 0.000 0.020
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.5165    0.87733 0.512 0.004 0.484 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.8640    0.39334 0.512 0.232 0.092 0.164
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5850    0.85636 0.512 0.032 0.456 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.5600    0.86739 0.512 0.020 0.468 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.5766    0.86507 0.512 0.020 0.464 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.4776   -0.61950 0.376 0.000 0.624 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.0188    0.51397 0.004 0.000 0.996 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4998    0.87825 0.512 0.000 0.488 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4996    0.39928 0.484 0.000 0.516 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.4998    0.39603 0.488 0.000 0.512 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.89542 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5292    0.87581 0.512 0.008 0.480 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.4981   -0.80709 0.464 0.000 0.536 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0000    0.51925 0.000 0.000 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.5292    0.87581 0.512 0.008 0.480 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0162     0.9393 0.000 0.000 0.000 0.004 0.996
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.4221     0.7252 0.108 0.000 0.780 0.000 0.112
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.3346     0.7594 0.036 0.008 0.848 0.108 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.3216     0.7705 0.044 0.000 0.848 0.108 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.1661     0.8830 0.940 0.036 0.024 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.2690     0.6850 0.000 0.000 0.844 0.156 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.1638     0.9101 0.000 0.000 0.064 0.004 0.932
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.3768     0.7623 0.020 0.808 0.156 0.000 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0324     0.9049 0.992 0.004 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0609     0.8999 0.980 0.020 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.3123     0.8072 0.828 0.012 0.160 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.0912     0.8983 0.972 0.012 0.016 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.2648     0.8426 0.152 0.000 0.848 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0162     0.8915 0.000 0.996 0.004 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.4214     0.7382 0.000 0.780 0.152 0.004 0.064
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.0000     0.9408 0.000 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.0880     0.9358 0.000 0.000 0.032 0.000 0.968
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0510     0.9017 0.984 0.000 0.016 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0566     0.8983 0.012 0.984 0.004 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0162     0.9056 0.996 0.004 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.1197     0.8896 0.952 0.000 0.048 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.2470     0.8500 0.884 0.012 0.104 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0162     0.9052 0.996 0.000 0.004 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.3216     0.7705 0.044 0.000 0.848 0.108 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.1670     0.8825 0.936 0.012 0.052 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.1732     0.8734 0.920 0.000 0.080 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.0955     0.8948 0.968 0.028 0.004 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.2605     0.8424 0.148 0.000 0.852 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.2690     0.8418 0.156 0.000 0.844 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.3267     0.7685 0.044 0.000 0.844 0.112 0.000
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#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0290     0.9049 0.992 0.000 0.008 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000     0.9408 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.4015     0.3384 0.652 0.000 0.348 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.0693     0.9002 0.980 0.012 0.008 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.2648     0.8426 0.152 0.000 0.848 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     1  0.6031     0.2712 0.520 0.352 0.128 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0162     0.9052 0.996 0.000 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.2690     0.7913 0.000 0.844 0.156 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     1  0.3264     0.8021 0.820 0.016 0.164 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.0912     0.9005 0.972 0.016 0.012 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.2864     0.8270 0.852 0.012 0.136 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     1  0.2864     0.8270 0.852 0.012 0.136 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.3395     0.6170 0.764 0.000 0.236 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0290     0.9043 0.992 0.000 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.2690     0.8420 0.156 0.000 0.844 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0000     0.9062 1.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.4901     0.5398 0.000 0.096 0.708 0.196 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     4  0.0000     0.9408 0.000 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0404     0.8998 0.012 0.988 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2723     0.8362 0.864 0.012 0.124 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0794     0.8924 0.972 0.000 0.028 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.2648     0.8426 0.152 0.000 0.848 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0162     0.9055 0.996 0.000 0.004 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     6  0.1075    0.93428 0.000 0.000 0.000 0.000 0.048 0.952
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.2532    0.81546 0.012 0.000 0.884 0.000 0.024 0.080
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.1088    0.85223 0.000 0.000 0.960 0.016 0.024 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.1176    0.84880 0.000 0.000 0.956 0.020 0.024 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.0508    0.91434 0.984 0.000 0.012 0.000 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.2176    0.81083 0.000 0.000 0.896 0.080 0.024 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     6  0.1663    0.92518 0.000 0.000 0.000 0.000 0.088 0.912
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.1461    0.64185 0.000 0.044 0.000 0.000 0.940 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     5  0.4150    0.65878 0.320 0.000 0.028 0.000 0.652 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     3  0.0405    0.86312 0.004 0.000 0.988 0.000 0.008 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0713    0.88715 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     5  0.1498    0.63355 0.000 0.032 0.000 0.000 0.940 0.028
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.1633    0.90030 0.932 0.000 0.044 0.000 0.024 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0937    0.89408 0.960 0.000 0.000 0.000 0.040 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     5  0.2941    0.80719 0.220 0.000 0.000 0.000 0.780 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.1528    0.90187 0.936 0.000 0.048 0.000 0.016 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.1341    0.84212 0.000 0.000 0.948 0.028 0.024 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0713    0.91312 0.972 0.000 0.028 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     5  0.3360    0.76346 0.264 0.000 0.004 0.000 0.732 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.2300    0.77784 0.856 0.000 0.000 0.000 0.144 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     3  0.0909    0.86139 0.012 0.000 0.968 0.000 0.020 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     3  0.0914    0.86160 0.016 0.000 0.968 0.000 0.016 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.0993    0.85531 0.000 0.000 0.964 0.012 0.024 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.0458    0.91426 0.984 0.000 0.016 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.0547    0.91397 0.980 0.000 0.020 0.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     5  0.4459    0.74499 0.204 0.004 0.084 0.000 0.708 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     5  0.2969    0.80674 0.224 0.000 0.000 0.000 0.776 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.3746    0.67356 0.048 0.000 0.000 0.000 0.760 0.192
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     5  0.3076    0.61475 0.000 0.240 0.000 0.000 0.760 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0891    0.91274 0.968 0.000 0.024 0.000 0.008 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.2826    0.75370 0.128 0.000 0.844 0.000 0.028 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.0865    0.91166 0.964 0.000 0.036 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.1829    0.89315 0.920 0.000 0.056 0.000 0.024 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.0622    0.90946 0.980 0.012 0.000 0.000 0.008 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.3531    0.43067 0.328 0.672 0.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.1141    0.88449 0.948 0.000 0.000 0.000 0.052 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     5  0.3695    0.79175 0.164 0.000 0.000 0.000 0.776 0.060
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     5  0.4267    0.75478 0.120 0.000 0.016 0.000 0.760 0.104
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     6  0.2597    0.89111 0.000 0.000 0.000 0.000 0.176 0.824
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     5  0.2996    0.80601 0.228 0.000 0.000 0.000 0.772 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.1461    0.90390 0.940 0.000 0.044 0.000 0.016 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     3  0.3658    0.63235 0.216 0.000 0.752 0.000 0.032 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     2  0.0547    0.88773 0.020 0.980 0.000 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.0405    0.91188 0.988 0.004 0.000 0.000 0.008 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     3  0.0632    0.86143 0.000 0.000 0.976 0.000 0.024 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.1341    0.84089 0.000 0.000 0.948 0.028 0.024 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.4249    0.43320 0.328 0.000 0.640 0.000 0.032 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.4012    0.42081 0.000 0.344 0.640 0.000 0.016 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.4236    0.68012 0.000 0.088 0.772 0.000 0.112 0.028
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.0405    0.91271 0.988 0.000 0.004 0.000 0.008 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.3371    0.58860 0.708 0.292 0.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.1151    0.90989 0.956 0.000 0.032 0.000 0.012 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0777    0.86020 0.000 0.004 0.972 0.000 0.024 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.1594    0.89996 0.932 0.000 0.052 0.000 0.016 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.3499    0.54910 0.680 0.320 0.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.1528    0.90187 0.936 0.000 0.048 0.000 0.016 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.1461    0.90374 0.940 0.000 0.044 0.000 0.016 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     5  0.3151    0.78708 0.252 0.000 0.000 0.000 0.748 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.0547    0.91397 0.980 0.000 0.020 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     6  0.2491    0.89799 0.000 0.000 0.000 0.000 0.164 0.836
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     1  0.3175    0.64345 0.744 0.256 0.000 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     5  0.2912    0.63156 0.000 0.216 0.000 0.000 0.784 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     3  0.0508    0.86340 0.004 0.000 0.984 0.000 0.012 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.1528    0.90187 0.936 0.000 0.048 0.000 0.016 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.2046    0.88952 0.908 0.000 0.060 0.000 0.032 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     1  0.3833   -0.08918 0.556 0.000 0.000 0.000 0.444 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     2  0.4091    0.08474 0.000 0.520 0.472 0.000 0.008 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.1168    0.90991 0.956 0.000 0.028 0.000 0.016 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     3  0.0891    0.85780 0.000 0.000 0.968 0.008 0.024 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.0632    0.91357 0.976 0.000 0.024 0.000 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     5  0.2883    0.63325 0.000 0.212 0.000 0.000 0.788 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     1  0.0717    0.90897 0.976 0.016 0.000 0.000 0.008 0.000
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3     1  0.2803    0.85627 0.872 0.052 0.064 0.000 0.012 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7     1  0.3794    0.77732 0.796 0.060 0.128 0.000 0.016 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17     6  0.2260    0.90829 0.000 0.000 0.000 0.000 0.140 0.860
#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     3  0.1575    0.85203 0.032 0.000 0.936 0.000 0.032 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.0713    0.90171 0.972 0.000 0.000 0.000 0.028 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     1  0.0458    0.91426 0.984 0.000 0.016 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     5  0.3023    0.80540 0.212 0.000 0.000 0.000 0.784 0.004
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     1  0.0146    0.91359 0.996 0.000 0.000 0.000 0.004 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.1092    0.85947 0.020 0.000 0.960 0.000 0.020 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.0632    0.86143 0.000 0.000 0.976 0.000 0.024 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     3  0.0363    0.86245 0.000 0.000 0.988 0.000 0.012 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     5  0.3043    0.80632 0.200 0.008 0.000 0.000 0.792 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     5  0.3076    0.61735 0.000 0.240 0.000 0.000 0.760 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     1  0.0777    0.91324 0.972 0.000 0.024 0.000 0.004 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     1  0.1528    0.90187 0.936 0.000 0.048 0.000 0.016 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.0146    0.91257 0.996 0.000 0.000 0.000 0.004 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     1  0.1391    0.90550 0.944 0.000 0.040 0.000 0.016 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     1  0.1176    0.91171 0.956 0.000 0.024 0.000 0.020 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     5  0.3487    0.79426 0.168 0.044 0.000 0.000 0.788 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     5  0.3259    0.79235 0.216 0.000 0.012 0.000 0.772 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.3502    0.68101 0.000 0.160 0.800 0.024 0.016 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     3  0.2911    0.73678 0.144 0.000 0.832 0.000 0.024 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.0508    0.86416 0.012 0.000 0.984 0.000 0.004 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.0632    0.86143 0.000 0.000 0.976 0.000 0.024 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     2  0.4615    0.27512 0.396 0.568 0.028 0.000 0.008 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     3  0.1176    0.85856 0.024 0.000 0.956 0.000 0.020 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     1  0.0858    0.91263 0.968 0.000 0.028 0.000 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.3679    0.64571 0.200 0.000 0.760 0.000 0.040 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     1  0.3833    0.24277 0.556 0.444 0.000 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     1  0.1320    0.90689 0.948 0.000 0.036 0.000 0.016 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     3  0.1341    0.85573 0.028 0.000 0.948 0.000 0.024 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     5  0.3915    0.76977 0.128 0.000 0.004 0.000 0.776 0.092
#> 887E7408-C7D7-420F-A763-0EE70A316D17     1  0.1461    0.90374 0.940 0.000 0.044 0.000 0.016 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     3  0.1418    0.85417 0.032 0.000 0.944 0.000 0.024 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     1  0.3770    0.67360 0.728 0.000 0.244 0.000 0.028 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     1  0.1829    0.89336 0.920 0.000 0.056 0.000 0.024 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     5  0.3866    0.37847 0.484 0.000 0.000 0.000 0.516 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0632    0.86143 0.000 0.000 0.976 0.000 0.024 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     5  0.3259    0.78803 0.216 0.000 0.012 0.000 0.772 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     2  0.2178    0.77649 0.000 0.868 0.132 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     1  0.3062    0.79323 0.816 0.000 0.160 0.000 0.024 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.0291    0.91340 0.992 0.000 0.004 0.000 0.004 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     1  0.2263    0.86678 0.884 0.000 0.100 0.000 0.016 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     5  0.3012    0.80572 0.196 0.008 0.000 0.000 0.796 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.1341    0.84212 0.000 0.000 0.948 0.028 0.024 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     5  0.3290    0.80739 0.208 0.000 0.000 0.000 0.776 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     2  0.2730    0.70939 0.000 0.808 0.000 0.000 0.192 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.0547    0.90957 0.980 0.000 0.000 0.000 0.020 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.2664    0.64166 0.000 0.184 0.000 0.000 0.816 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.1501    0.81742 0.076 0.924 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.0622    0.91385 0.980 0.000 0.008 0.000 0.012 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0547    0.91397 0.980 0.000 0.020 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0993    0.91204 0.964 0.000 0.024 0.000 0.012 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.1564    0.84900 0.040 0.000 0.936 0.000 0.024 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     6  0.1663    0.92512 0.000 0.000 0.000 0.000 0.088 0.912
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     3  0.1092    0.85947 0.020 0.000 0.960 0.000 0.020 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     3  0.1092    0.85947 0.020 0.000 0.960 0.000 0.020 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.1633    0.90030 0.932 0.000 0.044 0.000 0.024 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.1480    0.63642 0.000 0.040 0.000 0.000 0.940 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0935    0.90857 0.964 0.000 0.004 0.000 0.032 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     3  0.1780    0.84247 0.048 0.000 0.924 0.000 0.028 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.1297    0.90690 0.948 0.000 0.040 0.000 0.012 0.000
#> 1122039D-5785-4F70-9916-17C585453512     4  0.0547    0.95821 0.000 0.000 0.020 0.980 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     6  0.0000    0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.1814    0.83364 0.900 0.000 0.000 0.000 0.100 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     5  0.3133    0.80918 0.212 0.008 0.000 0.000 0.780 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.0603    0.86397 0.004 0.000 0.980 0.000 0.016 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.1633    0.90034 0.932 0.000 0.044 0.000 0.024 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     3  0.2901    0.74932 0.128 0.000 0.840 0.000 0.032 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.1010    0.90678 0.960 0.000 0.004 0.000 0.036 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.0000    0.86316 0.000 0.000 1.000 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.0291    0.91349 0.992 0.000 0.004 0.000 0.004 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     5  0.4996    0.66029 0.200 0.156 0.000 0.000 0.644 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.1391    0.90563 0.944 0.000 0.040 0.000 0.016 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.2823    0.63632 0.000 0.204 0.000 0.000 0.796 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.1124    0.90964 0.956 0.000 0.036 0.000 0.008 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0260    0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.3081    0.80786 0.220 0.000 0.000 0.000 0.776 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.1168    0.91089 0.956 0.000 0.016 0.000 0.028 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.3023    0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     3  0.3960    0.64769 0.176 0.000 0.752 0.000 0.072 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.1418    0.90805 0.944 0.000 0.024 0.000 0.032 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     3  0.1341    0.85573 0.028 0.000 0.948 0.000 0.024 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0713    0.91304 0.972 0.000 0.028 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.2401    0.81333 0.000 0.028 0.900 0.048 0.024 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     4  0.0000    0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.0000    0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.3371    0.46972 0.708 0.000 0.000 0.000 0.292 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.1950    0.88878 0.912 0.000 0.064 0.000 0.024 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0508    0.86272 0.004 0.000 0.984 0.000 0.012 0.000
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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-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 17541 rows and 500 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 0.939           0.951       0.979         0.3497 0.663   0.663
#> 3 3 0.678           0.817       0.903         0.7815 0.634   0.478
#> 4 4 0.712           0.776       0.897         0.1375 0.751   0.452
#> 5 5 0.694           0.703       0.854         0.0944 0.777   0.390
#> 6 6 0.643           0.558       0.755         0.0545 0.895   0.587

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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000      0.976 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     2  0.0000      0.978 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.0000      0.978 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.0000      0.978 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.3114      0.928 0.056 0.944
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.0000      0.978 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.0000      0.978 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     2  0.0000      0.978 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     2  0.0000      0.978 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     1  0.0000      0.976 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     1  0.0000      0.976 1.000 0.000
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#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0376      0.975 0.004 0.996
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show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#>                                      class entropy silhouette    p1    p2    p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     1  0.0000    0.91115 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     3  0.2625    0.88053 0.000 0.084 0.916
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     2  0.2448    0.80722 0.000 0.924 0.076
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     2  0.3879    0.75112 0.000 0.848 0.152
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.7202    0.70833 0.160 0.716 0.124
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     3  0.1964    0.91199 0.000 0.056 0.944
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     3  0.3116    0.86633 0.000 0.108 0.892
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     3  0.1163    0.92565 0.000 0.028 0.972
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#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     2  0.1753    0.81526 0.000 0.952 0.048
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2680    0.81746 0.068 0.924 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.5285    0.77305 0.812 0.040 0.148
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     3  0.0237    0.92990 0.000 0.004 0.996
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     3  0.0747    0.92566 0.000 0.016 0.984
#> 2785594A-571A-46B4-A901-CB9C62DC6174     3  0.1753    0.91609 0.000 0.048 0.952

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#>                                      class entropy silhouette    p1    p2    p3    p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     1  0.3354    0.81138 0.880 0.020 0.016 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.2868    0.76106 0.136 0.000 0.864 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     3  0.4040    0.64358 0.248 0.000 0.752 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     2  0.3311    0.77106 0.172 0.828 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     2  0.1389    0.86088 0.048 0.952 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4040    0.65195 0.752 0.248 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0336    0.82861 0.008 0.000 0.992 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.4053    0.64636 0.000 0.768 0.004 0.228
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     2  0.0817    0.87026 0.024 0.976 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.0376    0.87231 0.000 0.992 0.004 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     2  0.2530    0.80338 0.000 0.888 0.000 0.112
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.6568    0.14700 0.512 0.408 0.000 0.080
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4781    0.39345 0.000 0.660 0.336 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     4  0.5085    0.57815 0.000 0.304 0.020 0.676
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.3837    0.64485 0.000 0.776 0.224 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.0469    0.82879 0.012 0.000 0.988 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.0376    0.87231 0.000 0.992 0.004 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     3  0.2973    0.78424 0.000 0.144 0.856 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.0000    0.82853 0.000 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     2  0.3444    0.75753 0.184 0.816 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     2  0.0921    0.87057 0.028 0.972 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     2  0.1305    0.86651 0.036 0.960 0.000 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     4  0.2586    0.85913 0.048 0.040 0.000 0.912
#> 97C34F1F-2002-4771-8D99-511EA08591CD     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     3  0.4905    0.53261 0.000 0.364 0.632 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     3  0.3123    0.74256 0.156 0.000 0.844 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     1  0.0592    0.88778 0.984 0.016 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     2  0.5384    0.69470 0.196 0.728 0.000 0.076
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     2  0.0188    0.87315 0.000 0.996 0.000 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     1  0.2589    0.80136 0.884 0.000 0.116 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     3  0.4431    0.55050 0.304 0.000 0.696 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     2  0.2973    0.79532 0.144 0.856 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.1792    0.85644 0.932 0.068 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     3  0.4804    0.48203 0.000 0.384 0.616 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     1  0.4250    0.60655 0.724 0.276 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     2  0.5574    0.38469 0.004 0.604 0.372 0.020
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.0336    0.82861 0.008 0.000 0.992 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     4  0.3984    0.76197 0.132 0.040 0.000 0.828
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.0524    0.87089 0.000 0.988 0.008 0.004
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     1  0.0336    0.89014 0.992 0.008 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     1  0.0188    0.88976 0.996 0.004 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     3  0.0000    0.82853 0.000 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     2  0.3649    0.73862 0.204 0.796 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     2  0.0707    0.86883 0.000 0.980 0.000 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.0592    0.86979 0.000 0.984 0.016 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     2  0.0188    0.87315 0.000 0.996 0.000 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     2  0.0592    0.87213 0.016 0.984 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.3668    0.69167 0.004 0.808 0.188 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     2  0.1118    0.86580 0.036 0.964 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.4564    0.44964 0.000 0.672 0.328 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     2  0.2868    0.80097 0.136 0.864 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     2  0.2578    0.84614 0.036 0.912 0.000 0.052
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     4  0.0336    0.91492 0.000 0.008 0.000 0.992
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     4  0.0188    0.91747 0.000 0.000 0.004 0.996
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     2  0.0817    0.86931 0.000 0.976 0.000 0.024
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     1  0.0469    0.88966 0.988 0.012 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     3  0.0000    0.82853 0.000 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     3  0.4790    0.51090 0.000 0.380 0.620 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.0469    0.82879 0.012 0.000 0.988 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     2  0.0817    0.87018 0.024 0.976 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     1  0.4632    0.53562 0.688 0.004 0.308 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.1637    0.81321 0.060 0.000 0.940 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     2  0.0817    0.86924 0.000 0.976 0.000 0.024
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     1  0.3172    0.75513 0.840 0.000 0.160 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.1022    0.82823 0.000 0.032 0.968 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.4790    0.37813 0.620 0.380 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.1706    0.82578 0.036 0.016 0.948 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0188    0.82882 0.004 0.000 0.996 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     1  0.4989    0.06675 0.528 0.472 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     1  0.0336    0.89014 0.992 0.008 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.2281    0.79247 0.096 0.000 0.904 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.0921    0.88390 0.972 0.028 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     2  0.0188    0.87315 0.000 0.996 0.000 0.004
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     3  0.4961    0.32837 0.000 0.448 0.552 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.3907    0.67844 0.768 0.232 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     4  0.0188    0.91747 0.000 0.000 0.004 0.996
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.0524    0.87265 0.004 0.988 0.008 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.0779    0.86781 0.000 0.980 0.016 0.004
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     1  0.0469    0.88459 0.988 0.000 0.012 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     3  0.1867    0.81795 0.000 0.072 0.928 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571     2  0.0188    0.87351 0.000 0.996 0.000 0.004
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1     3  0.0336    0.82938 0.000 0.008 0.992 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B     1  0.0469    0.88926 0.988 0.012 0.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724     1  0.2589    0.80483 0.884 0.000 0.116 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2     1  0.4304    0.59013 0.716 0.284 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1     3  0.4313    0.69654 0.000 0.260 0.736 0.004
#> C44C898C-EEF9-4E03-911A-9D951312C380     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1     2  0.0336    0.87392 0.008 0.992 0.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F     2  0.0524    0.87089 0.000 0.988 0.008 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E     2  0.1792    0.84690 0.000 0.932 0.000 0.068
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1     2  0.0188    0.87315 0.000 0.996 0.000 0.004
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4     2  0.0376    0.87231 0.000 0.992 0.004 0.004
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B     4  0.0524    0.91441 0.004 0.000 0.008 0.988
#> 9980293D-AF0A-4215-9688-C576B1F8B519     3  0.2197    0.81607 0.004 0.080 0.916 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159     1  0.1389    0.86352 0.952 0.000 0.048 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9     4  0.3479    0.78953 0.000 0.012 0.148 0.840
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70     2  0.0000    0.87320 0.000 1.000 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E     2  0.4382    0.60546 0.296 0.704 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6     3  0.0188    0.82874 0.004 0.000 0.996 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0     1  0.4866    0.30347 0.596 0.404 0.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97     2  0.0657    0.86960 0.000 0.984 0.012 0.004
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636     1  0.0592    0.88881 0.984 0.016 0.000 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB     2  0.1557    0.85646 0.056 0.944 0.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB     4  0.5929    0.38327 0.356 0.048 0.000 0.596
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716     3  0.2973    0.75381 0.144 0.000 0.856 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF     1  0.0376    0.89008 0.992 0.004 0.004 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86     3  0.1297    0.83127 0.020 0.016 0.964 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB     1  0.0376    0.89019 0.992 0.004 0.000 0.004
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8     3  0.2921    0.78671 0.000 0.140 0.860 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63     1  0.0592    0.88735 0.984 0.016 0.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5     2  0.0188    0.87283 0.000 0.996 0.004 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843     2  0.0707    0.86898 0.000 0.980 0.020 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3     3  0.4134    0.70296 0.000 0.260 0.740 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747     3  0.0817    0.82924 0.000 0.024 0.976 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF     4  0.0000    0.91935 0.000 0.000 0.000 1.000
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#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     1  0.1557    0.86277 0.944 0.056 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     2  0.4193    0.65120 0.268 0.732 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.0921    0.88258 0.972 0.028 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     1  0.0336    0.89014 0.992 0.008 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     1  0.0336    0.88753 0.992 0.000 0.008 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.4955    0.39225 0.000 0.648 0.008 0.344
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     1  0.0707    0.88591 0.980 0.020 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.0336    0.89014 0.992 0.008 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512     3  0.2281    0.79255 0.096 0.000 0.904 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000    0.91935 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     2  0.0657    0.87327 0.012 0.984 0.000 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467     3  0.0469    0.82879 0.012 0.000 0.988 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.0524    0.87183 0.000 0.988 0.004 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.4992    0.06391 0.524 0.000 0.476 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     3  0.0469    0.82879 0.012 0.000 0.988 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     1  0.2542    0.83463 0.904 0.012 0.000 0.084
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     1  0.0592    0.88363 0.984 0.000 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.4996    0.03269 0.516 0.484 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.0188    0.87315 0.000 0.996 0.000 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.0672    0.87010 0.000 0.984 0.008 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.0592    0.88847 0.984 0.016 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     2  0.3024    0.79041 0.148 0.852 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     4  0.4661    0.46963 0.000 0.348 0.000 0.652
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     2  0.0817    0.87197 0.024 0.976 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.0376    0.87231 0.000 0.992 0.004 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     4  0.5696    0.06220 0.024 0.480 0.000 0.496
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.4238    0.74186 0.028 0.176 0.000 0.796
#> EB7883EB-0079-4548-9132-169E94A698BA     1  0.0188    0.89064 0.996 0.004 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.0817    0.88491 0.976 0.024 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     1  0.1297    0.87686 0.964 0.016 0.020 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.0592    0.88788 0.984 0.016 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.1940    0.80478 0.076 0.000 0.924 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0921    0.82571 0.028 0.000 0.972 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.4981   -0.06074 0.000 0.536 0.464 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     2  0.2844    0.84433 0.052 0.900 0.000 0.048
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     1  0.0000    0.88957 1.000 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     2  0.3074    0.78602 0.152 0.848 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     4  0.1502     0.8717 0.004 0.056 0.000 0.940 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0693     0.8337 0.012 0.000 0.980 0.008 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     4  0.3075     0.8034 0.000 0.048 0.092 0.860 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615     1  0.4262     0.1351 0.560 0.440 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.2006     0.7491 0.916 0.000 0.072 0.012 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.0740     0.7677 0.980 0.008 0.004 0.008 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.2629     0.7157 0.860 0.000 0.004 0.136 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.0510     0.8247 0.000 0.016 0.984 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     5  0.0162     0.9434 0.000 0.000 0.004 0.000 0.996
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     2  0.6555     0.3515 0.320 0.460 0.000 0.000 0.220
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.1026     0.7653 0.968 0.024 0.004 0.004 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     2  0.2329     0.7734 0.124 0.876 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     1  0.2179     0.7167 0.888 0.112 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     1  0.6554     0.0679 0.404 0.200 0.000 0.000 0.396
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.3953     0.6677 0.804 0.000 0.144 0.012 0.040
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     4  0.0671     0.9043 0.004 0.016 0.000 0.980 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.0771     0.7820 0.020 0.976 0.004 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.2378     0.7754 0.048 0.904 0.000 0.000 0.048
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.2017     0.7884 0.080 0.912 0.008 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.2068     0.7838 0.000 0.092 0.904 0.004 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.2561     0.7627 0.144 0.856 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     5  0.0162     0.9445 0.000 0.000 0.000 0.004 0.996
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.0609     0.7696 0.000 0.980 0.020 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.2280     0.7657 0.000 0.120 0.880 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.0613     0.7669 0.984 0.004 0.008 0.004 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB     1  0.1851     0.7329 0.912 0.088 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     1  0.0693     0.7663 0.980 0.012 0.000 0.008 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.4700     0.0512 0.516 0.000 0.004 0.008 0.472
#> 97C34F1F-2002-4771-8D99-511EA08591CD     4  0.4552     0.6327 0.264 0.000 0.040 0.696 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.0290     0.7742 0.000 0.992 0.008 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277     4  0.3304     0.7511 0.000 0.168 0.016 0.816 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F     4  0.4302     0.1492 0.480 0.000 0.000 0.520 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B     1  0.3080     0.7079 0.852 0.000 0.124 0.020 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5     1  0.4350     0.2357 0.588 0.408 0.000 0.004 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6     1  0.3816     0.4656 0.696 0.304 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3     4  0.1153     0.8942 0.004 0.008 0.024 0.964 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64     4  0.2124     0.8564 0.000 0.056 0.028 0.916 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220     1  0.0693     0.7671 0.980 0.012 0.000 0.008 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC     1  0.2971     0.7017 0.836 0.000 0.008 0.156 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4     2  0.0566     0.7727 0.004 0.984 0.012 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293     5  0.0162     0.9445 0.000 0.000 0.000 0.004 0.996
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0     4  0.3647     0.7138 0.228 0.004 0.004 0.764 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0     3  0.3844     0.6747 0.256 0.004 0.736 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70     3  0.2179     0.7671 0.000 0.112 0.888 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E     5  0.2554     0.8690 0.072 0.000 0.000 0.036 0.892
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53     2  0.2280     0.7740 0.120 0.880 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43     4  0.1965     0.8555 0.096 0.000 0.000 0.904 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B     3  0.4794     0.5097 0.344 0.000 0.624 0.032 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15     2  0.4297    -0.0156 0.000 0.528 0.472 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E     1  0.3318     0.6487 0.808 0.000 0.180 0.012 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540     4  0.0290     0.9101 0.008 0.000 0.000 0.992 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128     1  0.5455     0.4818 0.636 0.088 0.000 0.004 0.272
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0     2  0.3684     0.6452 0.280 0.720 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A     1  0.4249     0.1651 0.568 0.432 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8     1  0.0162     0.7665 0.996 0.004 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643     2  0.2536     0.7728 0.128 0.868 0.004 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406     1  0.0451     0.7658 0.988 0.008 0.000 0.004 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62     2  0.4917     0.2633 0.416 0.556 0.028 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01     1  0.2871     0.7379 0.872 0.088 0.000 0.040 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52     1  0.0451     0.7657 0.988 0.008 0.000 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD     5  0.0613     0.9382 0.004 0.008 0.000 0.004 0.984
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7     5  0.0451     0.9414 0.008 0.000 0.000 0.004 0.988
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7     1  0.5164     0.5113 0.660 0.084 0.000 0.000 0.256
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD     4  0.4484     0.5767 0.308 0.000 0.024 0.668 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD     4  0.0290     0.9102 0.008 0.000 0.000 0.992 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80     2  0.3305     0.5793 0.000 0.776 0.224 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6     1  0.5456     0.2878 0.592 0.328 0.080 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E     3  0.1478     0.8032 0.000 0.064 0.936 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F     1  0.2806     0.6834 0.844 0.000 0.152 0.004 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3     4  0.1243     0.8921 0.004 0.028 0.008 0.960 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090     3  0.0579     0.8305 0.008 0.008 0.984 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B     1  0.4088     0.6260 0.776 0.168 0.000 0.000 0.056
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A     3  0.1670     0.8300 0.012 0.000 0.936 0.052 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98     3  0.4247     0.6908 0.132 0.092 0.776 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320     1  0.1626     0.7622 0.940 0.000 0.016 0.044 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A     3  0.1756     0.8219 0.008 0.036 0.940 0.016 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114     1  0.1851     0.7352 0.912 0.088 0.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D     3  0.0671     0.8237 0.000 0.016 0.980 0.000 0.004
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A     4  0.1399     0.8914 0.020 0.028 0.000 0.952 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771     1  0.3521     0.5831 0.764 0.232 0.004 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA     4  0.0290     0.9102 0.008 0.000 0.000 0.992 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B     3  0.0566     0.8334 0.012 0.000 0.984 0.004 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3     4  0.0404     0.9100 0.012 0.000 0.000 0.988 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89     1  0.3521     0.5864 0.764 0.232 0.004 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2     4  0.0609     0.9086 0.020 0.000 0.000 0.980 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805     1  0.5421     0.3899 0.628 0.000 0.276 0.096 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3     1  0.3814     0.5261 0.720 0.276 0.000 0.004 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A     2  0.0290     0.7742 0.000 0.992 0.008 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2     1  0.2017     0.7495 0.912 0.000 0.008 0.080 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322     2  0.3452     0.6681 0.244 0.756 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D     2  0.3274     0.7076 0.220 0.780 0.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D     4  0.0451     0.9079 0.004 0.008 0.000 0.988 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4     2  0.1197     0.7572 0.000 0.952 0.048 0.000 0.000
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#> 14B4BE11-4576-4511-946E-28EB079ABA3E     2  0.1915     0.7855 0.040 0.928 0.032 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060     2  0.0579     0.7774 0.008 0.984 0.008 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9     4  0.0613     0.9068 0.004 0.008 0.000 0.984 0.004
#> 241F589C-D559-43D7-8340-31EBCEB36E14     1  0.2648     0.6804 0.848 0.152 0.000 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7     1  0.2719     0.7096 0.852 0.000 0.004 0.144 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249     5  0.0162     0.9445 0.000 0.000 0.000 0.004 0.996
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE     3  0.2020     0.7780 0.000 0.100 0.900 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9     1  0.0693     0.7671 0.980 0.008 0.000 0.012 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2     4  0.1478     0.8828 0.064 0.000 0.000 0.936 0.000
#> 40467950-A95C-4731-AD93-0A128442C837     5  0.0451     0.9401 0.008 0.000 0.000 0.004 0.988
#> FE7B013B-9204-40BC-B644-7B3A5F170A96     1  0.1908     0.7341 0.908 0.092 0.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1     4  0.3724     0.7398 0.184 0.028 0.000 0.788 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65     3  0.3307     0.7952 0.104 0.000 0.844 0.052 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D     3  0.2054     0.8275 0.028 0.000 0.920 0.052 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13     1  0.4219     0.2172 0.584 0.416 0.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA     5  0.0162     0.9445 0.000 0.000 0.000 0.004 0.996
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141     2  0.4907     0.1315 0.484 0.492 0.024 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B     4  0.1211     0.8992 0.016 0.024 0.000 0.960 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F     4  0.4777     0.6117 0.268 0.000 0.052 0.680 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681     1  0.1717     0.7580 0.936 0.004 0.052 0.008 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A     1  0.4235     0.2039 0.576 0.424 0.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6     4  0.3177     0.7386 0.208 0.000 0.000 0.792 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001     1  0.1908     0.7327 0.908 0.092 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA     4  0.1792     0.8673 0.084 0.000 0.000 0.916 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291     2  0.3366     0.6990 0.232 0.768 0.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC     4  0.2396     0.8515 0.004 0.024 0.000 0.904 0.068
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E     3  0.0404     0.8264 0.000 0.012 0.988 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20     2  0.6719     0.4723 0.064 0.576 0.252 0.108 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B     1  0.1502     0.7624 0.940 0.004 0.000 0.056 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F     3  0.1836     0.8329 0.016 0.008 0.936 0.040 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C     1  0.1243     0.7652 0.960 0.004 0.028 0.008 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201     3  0.1364     0.8333 0.012 0.000 0.952 0.036 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1     5  0.0162     0.9445 0.000 0.000 0.000 0.004 0.996
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E     1  0.4845     0.6309 0.724 0.148 0.128 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9     4  0.3586     0.6739 0.264 0.000 0.000 0.736 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E     3  0.4781     0.3204 0.428 0.000 0.552 0.020 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C     2  0.1117     0.7830 0.020 0.964 0.016 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27     2  0.3586     0.6548 0.264 0.736 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784     4  0.2127     0.8462 0.108 0.000 0.000 0.892 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32     4  0.0566     0.9098 0.012 0.000 0.004 0.984 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A     5  0.0324     0.9430 0.004 0.000 0.000 0.004 0.992
#> 887E7408-C7D7-420F-A763-0EE70A316D17     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7     2  0.1648     0.7893 0.040 0.940 0.020 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D     2  0.4808     0.3355 0.400 0.576 0.024 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD     4  0.0865     0.8995 0.004 0.024 0.000 0.972 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5     3  0.5754     0.5597 0.260 0.000 0.604 0.136 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8     4  0.1557     0.8865 0.052 0.000 0.008 0.940 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7     1  0.0324     0.7662 0.992 0.004 0.000 0.000 0.004
#> C075F09E-623C-46ED-B927-889B48F450B3     3  0.0693     0.8339 0.012 0.000 0.980 0.008 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59     1  0.1484     0.7574 0.944 0.008 0.000 0.000 0.048
#> 580C059F-1B04-4229-8047-DCB3BC29FB01     1  0.4425    -0.0353 0.544 0.004 0.452 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A     3  0.3790     0.5961 0.000 0.272 0.724 0.004 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364     4  0.4587     0.6890 0.096 0.000 0.160 0.744 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24     1  0.1522     0.7600 0.944 0.000 0.044 0.012 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E     4  0.4885     0.5914 0.276 0.000 0.056 0.668 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     1  0.4227     0.1942 0.580 0.420 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323     3  0.1281     0.8296 0.000 0.012 0.956 0.032 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     5  0.1041     0.9258 0.032 0.000 0.000 0.004 0.964
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.4798    -0.0406 0.472 0.012 0.512 0.000 0.004
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.1267     0.7662 0.960 0.004 0.024 0.012 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     2  0.1410     0.7872 0.060 0.940 0.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     1  0.4557    -0.0132 0.516 0.476 0.008 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     4  0.0671     0.9081 0.016 0.004 0.000 0.980 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.0693     0.7667 0.980 0.000 0.008 0.012 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.2873     0.7206 0.860 0.000 0.020 0.120 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     4  0.0794     0.9052 0.028 0.000 0.000 0.972 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.3336     0.7971 0.096 0.000 0.844 0.060 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     4  0.0162     0.9098 0.004 0.000 0.000 0.996 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     4  0.0290     0.9102 0.008 0.000 0.000 0.992 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     2  0.4818     0.6334 0.080 0.708 0.000 0.000 0.212
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     4  0.0510     0.9095 0.016 0.000 0.000 0.984 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     4  0.0609     0.9088 0.020 0.000 0.000 0.980 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     1  0.6618     0.1072 0.452 0.000 0.244 0.304 0.000
#> 1122039D-5785-4F70-9916-17C585453512     3  0.6175     0.3221 0.000 0.152 0.516 0.332 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     5  0.0000     0.9447 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     1  0.0566     0.7655 0.984 0.012 0.000 0.004 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.4003     0.4670 0.000 0.704 0.288 0.008 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.2179     0.7787 0.112 0.888 0.000 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     3  0.1579     0.8341 0.032 0.000 0.944 0.024 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     4  0.0404     0.9100 0.012 0.000 0.000 0.988 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.4562    -0.1141 0.000 0.496 0.496 0.008 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     4  0.0290     0.9096 0.008 0.000 0.000 0.992 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     4  0.6161     0.4346 0.196 0.000 0.000 0.556 0.248
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.1981     0.8254 0.064 0.000 0.920 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.1764     0.7581 0.928 0.000 0.008 0.064 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.4306     0.1157 0.492 0.508 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     4  0.0290     0.9101 0.008 0.000 0.000 0.992 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     2  0.3796     0.6046 0.300 0.700 0.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.4237     0.6533 0.772 0.000 0.076 0.152 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     1  0.0451     0.7664 0.988 0.008 0.000 0.004 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.2575     0.8455 0.100 0.012 0.000 0.004 0.884
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.3706     0.5682 0.756 0.004 0.236 0.004 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2806     0.7588 0.152 0.844 0.004 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     1  0.4551     0.3997 0.636 0.008 0.000 0.008 0.348
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     5  0.3611     0.7309 0.208 0.004 0.000 0.008 0.780
#> EB7883EB-0079-4548-9132-169E94A698BA     4  0.0162     0.9091 0.004 0.000 0.000 0.996 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4443     0.0130 0.524 0.000 0.004 0.472 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     4  0.1892     0.8570 0.004 0.080 0.000 0.916 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4313     0.3743 0.636 0.000 0.008 0.356 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.1211     0.8243 0.000 0.024 0.960 0.016 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0510     0.8247 0.000 0.016 0.984 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.2077     0.7881 0.084 0.908 0.008 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.0486     0.7665 0.988 0.004 0.004 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     4  0.0880     0.9031 0.032 0.000 0.000 0.968 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     4  0.0566     0.9079 0.004 0.000 0.012 0.984 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174     1  0.0854     0.7669 0.976 0.004 0.012 0.008 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
#> 922B74CF-AED1-4E9E-9650-4843F0A18820     4  0.0000    0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824     6  0.2672    0.81403 0.000 0.080 0.000 0.000 0.052 0.868
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33     3  0.0692    0.77631 0.020 0.000 0.976 0.000 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38     6  0.3766    0.75606 0.000 0.068 0.100 0.000 0.024 0.808
#> BE685EF3-953B-483C-A99C-75FBF81D6615     5  0.5005    0.45605 0.164 0.192 0.000 0.000 0.644 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412     1  0.3462    0.55331 0.816 0.000 0.100 0.000 0.080 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7     1  0.2264    0.57289 0.888 0.096 0.000 0.000 0.012 0.004
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D     1  0.4723    0.41460 0.664 0.000 0.000 0.000 0.232 0.104
#> 8414BA78-A8A9-4424-9C5A-9683128B1551     3  0.1333    0.76952 0.008 0.000 0.944 0.000 0.048 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F     4  0.0363    0.87686 0.000 0.000 0.000 0.988 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9     5  0.4805    0.47920 0.056 0.128 0.000 0.084 0.732 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7     1  0.4109    0.25069 0.576 0.012 0.000 0.000 0.412 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F     5  0.4933    0.08229 0.068 0.396 0.000 0.000 0.536 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9     5  0.3424    0.56702 0.204 0.024 0.000 0.000 0.772 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD     4  0.6524    0.32790 0.172 0.172 0.000 0.552 0.104 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2     1  0.6354    0.38977 0.600 0.000 0.156 0.128 0.108 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79     6  0.0405    0.88125 0.000 0.008 0.000 0.000 0.004 0.988
#> F4D81754-F220-405F-9DDC-AA27EA1C529B     2  0.4098    0.23906 0.004 0.548 0.004 0.000 0.444 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783     2  0.4865    0.44715 0.004 0.652 0.000 0.096 0.248 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6     2  0.4034    0.48794 0.024 0.692 0.004 0.000 0.280 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8     3  0.1970    0.73060 0.000 0.060 0.912 0.000 0.028 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA     2  0.3873    0.59368 0.124 0.772 0.000 0.000 0.104 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6     4  0.0000    0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD     2  0.2203    0.60955 0.004 0.896 0.016 0.000 0.084 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0     6  0.0000    0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782     3  0.2998    0.70064 0.024 0.096 0.856 0.000 0.024 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB     1  0.3201    0.47502 0.780 0.000 0.000 0.000 0.208 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB     5  0.4453    0.35779 0.400 0.032 0.000 0.000 0.568 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784     5  0.3997   -0.03914 0.488 0.004 0.000 0.000 0.508 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5     1  0.4366    0.22041 0.540 0.000 0.000 0.440 0.016 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD     6  0.4232    0.70448 0.152 0.000 0.040 0.000 0.044 0.764
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2     2  0.4293    0.31983 0.004 0.584 0.016 0.000 0.396 0.000
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#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294     2  0.5756    0.08491 0.388 0.440 0.000 0.000 0.172 0.000
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#> EBA9865F-E212-4BCD-9816-7C001E7DFF99     4  0.1858    0.82701 0.004 0.000 0.000 0.904 0.092 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740     3  0.5283    0.49193 0.320 0.056 0.592 0.000 0.032 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789     1  0.4085    0.52407 0.748 0.052 0.004 0.000 0.192 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903     5  0.3883    0.25199 0.012 0.332 0.000 0.000 0.656 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C     2  0.4227    0.07944 0.492 0.496 0.008 0.000 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE     6  0.2856    0.80737 0.068 0.000 0.000 0.000 0.076 0.856
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48     1  0.3200    0.48376 0.788 0.000 0.000 0.000 0.196 0.016
#> 5E03E52F-957D-455B-A007-19714FAA818A     1  0.4637    0.49689 0.732 0.000 0.028 0.000 0.148 0.092
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A     6  0.0777    0.87991 0.024 0.000 0.000 0.000 0.004 0.972
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF     3  0.4915    0.60058 0.272 0.000 0.652 0.000 0.044 0.032
#> AF331A84-397D-4E85-81FA-D4DD2D40E949     4  0.0000    0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13     6  0.0000    0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5     6  0.0000    0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0     6  0.0260    0.88425 0.000 0.000 0.000 0.000 0.008 0.992
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E     5  0.5832   -0.02783 0.012 0.400 0.000 0.132 0.456 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344     6  0.0000    0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> C33059A9-A313-4806-B43B-0031365F3BE4     6  0.1245    0.87515 0.032 0.000 0.000 0.000 0.016 0.952
#> D9C02B51-F92B-4F5F-89AC-BD526832C915     6  0.7316   -0.12438 0.332 0.000 0.176 0.000 0.136 0.356
#> 1122039D-5785-4F70-9916-17C585453512     3  0.6219    0.30857 0.000 0.180 0.516 0.000 0.032 0.272
#> F7849C4C-5733-40C6-A826-EF610E7CB14E     4  0.0000    0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058     5  0.3081    0.49914 0.220 0.004 0.000 0.000 0.776 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467     2  0.3934    0.49979 0.000 0.708 0.260 0.000 0.032 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD     2  0.4122    0.24128 0.004 0.520 0.000 0.000 0.472 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED     1  0.5032    0.40615 0.612 0.092 0.292 0.000 0.000 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17     6  0.0000    0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0     2  0.4712    0.11774 0.000 0.512 0.448 0.000 0.036 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4     6  0.0405    0.88421 0.004 0.000 0.000 0.000 0.008 0.988
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E     6  0.5016    0.67389 0.088 0.000 0.000 0.108 0.084 0.720
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0     3  0.3384    0.68527 0.228 0.000 0.760 0.000 0.008 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716     1  0.2789    0.58652 0.880 0.064 0.008 0.000 0.012 0.036
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12     2  0.3608    0.54165 0.272 0.716 0.000 0.000 0.012 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331     6  0.0146    0.88446 0.004 0.000 0.000 0.000 0.000 0.996
#> B4CD2742-8985-436A-B185-76D37DC4EFF3     5  0.4291    0.36761 0.052 0.268 0.000 0.000 0.680 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1     1  0.5649    0.46781 0.656 0.000 0.080 0.000 0.120 0.144
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435     5  0.3515    0.43816 0.324 0.000 0.000 0.000 0.676 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C     5  0.4151    0.35047 0.040 0.000 0.000 0.276 0.684 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F     1  0.5899    0.21912 0.472 0.000 0.276 0.000 0.252 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC     2  0.2009    0.63676 0.068 0.908 0.000 0.000 0.024 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348     5  0.5183    0.31585 0.116 0.004 0.000 0.272 0.608 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938     4  0.4944    0.20453 0.064 0.000 0.000 0.488 0.448 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA     6  0.2838    0.75811 0.004 0.000 0.000 0.000 0.188 0.808
#> E6446572-BFA9-4018-89B3-7E4519EBE072     1  0.4947    0.44851 0.636 0.000 0.000 0.000 0.120 0.244
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43     6  0.1829    0.84297 0.000 0.056 0.000 0.000 0.024 0.920
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073     1  0.4717    0.41925 0.632 0.000 0.008 0.000 0.052 0.308
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E     3  0.0260    0.76769 0.000 0.008 0.992 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F     3  0.0520    0.76613 0.000 0.008 0.984 0.000 0.008 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F     2  0.4158    0.28012 0.004 0.572 0.008 0.000 0.416 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493     1  0.2402    0.54347 0.868 0.000 0.000 0.012 0.120 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC     6  0.1908    0.83325 0.096 0.000 0.004 0.000 0.000 0.900
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B     6  0.0458    0.88293 0.000 0.000 0.016 0.000 0.000 0.984
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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