Date: 2019-12-26 01:36:39 CET, cola version: 1.3.2
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All available functions which can be applied to this res_list object:
res_list
#> A 'ConsensusPartitionList' object with 24 methods.
#> On a matrix with 17524 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 = 4)
Dimension of the input matrix:
mat = get_matrix(res_list)
dim(mat)
#> [1] 17524 500
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)
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 | ||
|---|---|---|---|---|---|---|
| ATC:NMF | 2 | 1.000 | 0.962 | 0.985 | ** | |
| ATC:skmeans | 2 | 1.000 | 0.962 | 0.985 | ** | |
| ATC:kmeans | 3 | 0.924 | 0.907 | 0.961 | * | 2 |
| CV:skmeans | 2 | 0.852 | 0.900 | 0.960 | ||
| SD:skmeans | 2 | 0.844 | 0.906 | 0.961 | ||
| CV:NMF | 2 | 0.843 | 0.901 | 0.960 | ||
| MAD:skmeans | 2 | 0.834 | 0.907 | 0.962 | ||
| SD:NMF | 2 | 0.824 | 0.889 | 0.955 | ||
| ATC:pam | 3 | 0.805 | 0.902 | 0.954 | ||
| MAD:NMF | 2 | 0.802 | 0.887 | 0.953 | ||
| MAD:kmeans | 2 | 0.796 | 0.895 | 0.954 | ||
| CV:kmeans | 2 | 0.795 | 0.874 | 0.946 | ||
| SD:kmeans | 2 | 0.794 | 0.889 | 0.952 | ||
| MAD:mclust | 4 | 0.642 | 0.794 | 0.869 | ||
| CV:pam | 3 | 0.582 | 0.832 | 0.885 | ||
| SD:mclust | 3 | 0.576 | 0.750 | 0.866 | ||
| MAD:pam | 2 | 0.378 | 0.666 | 0.864 | ||
| ATC:mclust | 3 | 0.362 | 0.707 | 0.794 | ||
| ATC:hclust | 3 | 0.346 | 0.675 | 0.829 | ||
| SD:pam | 2 | 0.309 | 0.594 | 0.833 | ||
| MAD:hclust | 2 | 0.231 | 0.636 | 0.824 | ||
| SD:hclust | 2 | 0.207 | 0.633 | 0.818 | ||
| CV:hclust | 3 | 0.173 | 0.509 | 0.721 | ||
| CV:mclust | 3 | 0.170 | 0.461 | 0.667 |
**: 1-PAC > 0.95, *: 1-PAC > 0.9
Cumulative distribution function curves of consensus matrix for all methods.
collect_plots(res_list, fun = plot_ecdf)
Consensus heatmaps for all methods. (What is a consensus heatmap?)
collect_plots(res_list, k = 2, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = consensus_heatmap, mc.cores = 4)
Membership heatmaps for all methods. (What is a membership heatmap?)
collect_plots(res_list, k = 2, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = membership_heatmap, mc.cores = 4)
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)
collect_plots(res_list, k = 3, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 4, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 5, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 6, fun = get_signatures, mc.cores = 4)
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 0.824 0.889 0.955 0.501 0.499 0.499
#> CV:NMF 2 0.843 0.901 0.960 0.500 0.500 0.500
#> MAD:NMF 2 0.802 0.887 0.953 0.501 0.500 0.500
#> ATC:NMF 2 1.000 0.962 0.985 0.276 0.725 0.725
#> SD:skmeans 2 0.844 0.906 0.961 0.501 0.499 0.499
#> CV:skmeans 2 0.852 0.900 0.960 0.499 0.501 0.501
#> MAD:skmeans 2 0.834 0.907 0.962 0.501 0.499 0.499
#> ATC:skmeans 2 1.000 0.962 0.985 0.500 0.501 0.501
#> SD:mclust 2 0.565 0.855 0.901 0.404 0.616 0.616
#> CV:mclust 2 0.282 0.707 0.789 0.391 0.556 0.556
#> MAD:mclust 2 0.430 0.834 0.878 0.409 0.614 0.614
#> ATC:mclust 2 0.798 0.939 0.971 0.238 0.765 0.765
#> SD:kmeans 2 0.794 0.889 0.952 0.500 0.499 0.499
#> CV:kmeans 2 0.795 0.874 0.946 0.486 0.506 0.506
#> MAD:kmeans 2 0.796 0.895 0.954 0.500 0.499 0.499
#> ATC:kmeans 2 0.987 0.946 0.980 0.390 0.613 0.613
#> SD:pam 2 0.309 0.594 0.833 0.481 0.499 0.499
#> CV:pam 2 0.407 0.723 0.872 0.469 0.502 0.502
#> MAD:pam 2 0.378 0.666 0.864 0.488 0.507 0.507
#> ATC:pam 2 0.731 0.901 0.953 0.406 0.582 0.582
#> SD:hclust 2 0.207 0.633 0.818 0.451 0.509 0.509
#> CV:hclust 2 0.155 0.516 0.789 0.356 0.654 0.654
#> MAD:hclust 2 0.231 0.636 0.824 0.447 0.513 0.513
#> ATC:hclust 2 0.200 0.531 0.745 0.397 0.522 0.522
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.627 0.707 0.870 0.307 0.686 0.455
#> CV:NMF 3 0.517 0.599 0.803 0.307 0.783 0.592
#> MAD:NMF 3 0.622 0.764 0.882 0.306 0.683 0.452
#> ATC:NMF 3 0.748 0.868 0.942 1.048 0.678 0.564
#> SD:skmeans 3 0.748 0.774 0.905 0.310 0.754 0.547
#> CV:skmeans 3 0.668 0.729 0.830 0.314 0.782 0.592
#> MAD:skmeans 3 0.744 0.779 0.900 0.307 0.756 0.551
#> ATC:skmeans 3 0.845 0.832 0.932 0.294 0.794 0.610
#> SD:mclust 3 0.576 0.750 0.866 0.521 0.586 0.419
#> CV:mclust 3 0.170 0.461 0.667 0.439 0.815 0.681
#> MAD:mclust 3 0.499 0.730 0.852 0.484 0.578 0.409
#> ATC:mclust 3 0.362 0.707 0.794 1.112 0.646 0.547
#> SD:kmeans 3 0.493 0.613 0.769 0.294 0.748 0.543
#> CV:kmeans 3 0.588 0.783 0.848 0.327 0.741 0.535
#> MAD:kmeans 3 0.504 0.515 0.776 0.303 0.745 0.537
#> ATC:kmeans 3 0.924 0.907 0.961 0.546 0.608 0.442
#> SD:pam 3 0.423 0.606 0.810 0.351 0.690 0.456
#> CV:pam 3 0.582 0.832 0.885 0.319 0.719 0.506
#> MAD:pam 3 0.461 0.536 0.769 0.350 0.699 0.474
#> ATC:pam 3 0.805 0.902 0.954 0.434 0.579 0.410
#> SD:hclust 3 0.199 0.475 0.687 0.310 0.867 0.768
#> CV:hclust 3 0.173 0.509 0.721 0.456 0.753 0.645
#> MAD:hclust 3 0.180 0.415 0.658 0.325 0.727 0.543
#> ATC:hclust 3 0.346 0.675 0.829 0.458 0.584 0.393
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.580 0.664 0.801 0.133 0.799 0.499
#> CV:NMF 4 0.551 0.382 0.684 0.129 0.843 0.591
#> MAD:NMF 4 0.546 0.627 0.787 0.133 0.805 0.510
#> ATC:NMF 4 0.477 0.550 0.774 0.231 0.730 0.450
#> SD:skmeans 4 0.654 0.676 0.832 0.139 0.801 0.495
#> CV:skmeans 4 0.706 0.772 0.878 0.134 0.829 0.556
#> MAD:skmeans 4 0.661 0.726 0.855 0.143 0.805 0.504
#> ATC:skmeans 4 0.876 0.878 0.949 0.112 0.831 0.576
#> SD:mclust 4 0.631 0.773 0.859 0.158 0.809 0.563
#> CV:mclust 4 0.304 0.255 0.615 0.141 0.636 0.346
#> MAD:mclust 4 0.642 0.794 0.869 0.163 0.816 0.575
#> ATC:mclust 4 0.300 0.498 0.724 0.168 0.861 0.717
#> SD:kmeans 4 0.488 0.539 0.738 0.137 0.749 0.422
#> CV:kmeans 4 0.514 0.484 0.672 0.123 0.895 0.726
#> MAD:kmeans 4 0.475 0.528 0.739 0.130 0.720 0.368
#> ATC:kmeans 4 0.670 0.468 0.766 0.203 0.796 0.536
#> SD:pam 4 0.554 0.656 0.772 0.138 0.772 0.441
#> CV:pam 4 0.605 0.617 0.814 0.147 0.883 0.690
#> MAD:pam 4 0.543 0.617 0.790 0.123 0.759 0.418
#> ATC:pam 4 0.595 0.562 0.802 0.186 0.781 0.523
#> SD:hclust 4 0.253 0.410 0.649 0.136 0.720 0.506
#> CV:hclust 4 0.304 0.463 0.706 0.238 0.771 0.566
#> MAD:hclust 4 0.250 0.404 0.615 0.135 0.659 0.372
#> ATC:hclust 4 0.398 0.515 0.748 0.191 0.843 0.644
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.706 0.694 0.841 0.0726 0.852 0.519
#> CV:NMF 5 0.720 0.701 0.847 0.0741 0.825 0.461
#> MAD:NMF 5 0.761 0.750 0.871 0.0734 0.841 0.490
#> ATC:NMF 5 0.536 0.587 0.769 0.1011 0.852 0.547
#> SD:skmeans 5 0.692 0.621 0.791 0.0621 0.860 0.526
#> CV:skmeans 5 0.695 0.622 0.796 0.0615 0.908 0.669
#> MAD:skmeans 5 0.691 0.665 0.800 0.0599 0.892 0.613
#> ATC:skmeans 5 0.836 0.836 0.923 0.0825 0.859 0.560
#> SD:mclust 5 0.650 0.482 0.714 0.0818 0.882 0.636
#> CV:mclust 5 0.407 0.431 0.654 0.1347 0.732 0.390
#> MAD:mclust 5 0.668 0.656 0.798 0.0867 0.896 0.665
#> ATC:mclust 5 0.378 0.529 0.740 0.1649 0.808 0.571
#> SD:kmeans 5 0.521 0.400 0.622 0.0713 0.842 0.499
#> CV:kmeans 5 0.575 0.502 0.697 0.0755 0.819 0.483
#> MAD:kmeans 5 0.521 0.416 0.649 0.0686 0.853 0.517
#> ATC:kmeans 5 0.736 0.742 0.859 0.0843 0.813 0.444
#> SD:pam 5 0.591 0.552 0.764 0.0640 0.857 0.528
#> CV:pam 5 0.669 0.632 0.835 0.0742 0.888 0.643
#> MAD:pam 5 0.632 0.663 0.781 0.0632 0.853 0.520
#> ATC:pam 5 0.640 0.629 0.782 0.1037 0.781 0.407
#> SD:hclust 5 0.321 0.443 0.609 0.0727 0.900 0.731
#> CV:hclust 5 0.373 0.479 0.691 0.0893 0.904 0.737
#> MAD:hclust 5 0.312 0.446 0.583 0.0733 0.878 0.673
#> ATC:hclust 5 0.479 0.505 0.725 0.0726 0.895 0.677
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.725 0.705 0.835 0.0360 0.901 0.587
#> CV:NMF 6 0.755 0.722 0.836 0.0411 0.899 0.583
#> MAD:NMF 6 0.712 0.668 0.820 0.0380 0.907 0.607
#> ATC:NMF 6 0.604 0.519 0.726 0.0632 0.906 0.629
#> SD:skmeans 6 0.794 0.738 0.855 0.0431 0.912 0.616
#> CV:skmeans 6 0.730 0.654 0.809 0.0425 0.910 0.623
#> MAD:skmeans 6 0.799 0.754 0.866 0.0436 0.923 0.659
#> ATC:skmeans 6 0.779 0.678 0.826 0.0344 0.955 0.803
#> SD:mclust 6 0.658 0.569 0.738 0.0352 0.905 0.650
#> CV:mclust 6 0.477 0.301 0.636 0.0569 0.915 0.722
#> MAD:mclust 6 0.657 0.541 0.713 0.0397 0.906 0.643
#> ATC:mclust 6 0.484 0.423 0.681 0.0940 0.880 0.644
#> SD:kmeans 6 0.610 0.473 0.662 0.0430 0.848 0.429
#> CV:kmeans 6 0.620 0.489 0.670 0.0442 0.904 0.611
#> MAD:kmeans 6 0.606 0.453 0.642 0.0456 0.848 0.422
#> ATC:kmeans 6 0.681 0.511 0.708 0.0407 0.894 0.564
#> SD:pam 6 0.615 0.550 0.770 0.0144 0.984 0.924
#> CV:pam 6 0.661 0.542 0.781 0.0160 0.922 0.712
#> MAD:pam 6 0.643 0.602 0.767 0.0245 0.976 0.890
#> ATC:pam 6 0.677 0.610 0.806 0.0504 0.862 0.528
#> SD:hclust 6 0.363 0.398 0.513 0.0574 0.870 0.610
#> CV:hclust 6 0.397 0.371 0.621 0.0539 0.905 0.712
#> MAD:hclust 6 0.390 0.421 0.566 0.0572 0.844 0.516
#> ATC:hclust 6 0.513 0.482 0.701 0.0313 0.967 0.875
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)
collect_stats(res_list, k = 3)
collect_stats(res_list, k = 4)
collect_stats(res_list, k = 5)
collect_stats(res_list, k = 6)
Collect partitions from all methods:
collect_classes(res_list, k = 2)
collect_classes(res_list, k = 3)
collect_classes(res_list, k = 4)
collect_classes(res_list, k = 5)
collect_classes(res_list, k = 6)
Overlap of top rows from different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "euler")
top_rows_overlap(res_list, top_n = 2000, method = "euler")
top_rows_overlap(res_list, top_n = 3000, method = "euler")
top_rows_overlap(res_list, top_n = 4000, method = "euler")
top_rows_overlap(res_list, top_n = 5000, method = "euler")
Also visualize the correspondance of rankings between different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "correspondance")
top_rows_overlap(res_list, top_n = 2000, method = "correspondance")
top_rows_overlap(res_list, top_n = 3000, method = "correspondance")
top_rows_overlap(res_list, top_n = 4000, method = "correspondance")
top_rows_overlap(res_list, top_n = 5000, method = "correspondance")
Heatmaps of the top rows:
top_rows_heatmap(res_list, top_n = 1000)
top_rows_heatmap(res_list, top_n = 2000)
top_rows_heatmap(res_list, top_n = 3000)
top_rows_heatmap(res_list, top_n = 4000)
top_rows_heatmap(res_list, top_n = 5000)
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.207 0.633 0.818 0.4510 0.509 0.509
#> 3 3 0.199 0.475 0.687 0.3096 0.867 0.768
#> 4 4 0.253 0.410 0.649 0.1360 0.720 0.506
#> 5 5 0.321 0.443 0.609 0.0727 0.900 0.731
#> 6 6 0.363 0.398 0.513 0.0574 0.870 0.610
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2423 0.80168 0.040 0.960
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.73521 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.3584 0.80290 0.068 0.932
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1633 0.74421 0.976 0.024
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1184 0.79544 0.016 0.984
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2423 0.80168 0.040 0.960
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.6623 0.72824 0.828 0.172
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1633 0.74425 0.976 0.024
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.5178 0.74579 0.884 0.116
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.8661 0.64001 0.712 0.288
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4022 0.79333 0.080 0.920
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7219 0.73117 0.200 0.800
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.9460 0.47196 0.364 0.636
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.2423 0.80168 0.040 0.960
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.8144 0.67126 0.252 0.748
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.9983 0.09772 0.524 0.476
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.78716 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.9983 0.09772 0.524 0.476
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.78716 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.9881 0.19346 0.436 0.564
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2778 0.80296 0.048 0.952
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.6531 0.76375 0.168 0.832
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#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.8081 0.68963 0.248 0.752
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.9427 0.46629 0.360 0.640
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.73521 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0376 0.78954 0.004 0.996
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.7745 0.69515 0.772 0.228
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.9522 0.46089 0.628 0.372
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.1414 0.74311 0.980 0.020
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.5519 0.78873 0.128 0.872
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.9850 0.35725 0.572 0.428
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.9522 0.50062 0.628 0.372
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.9988 0.00369 0.480 0.520
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.73521 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.3879 0.80144 0.076 0.924
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.3114 0.79862 0.056 0.944
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0672 0.73924 0.992 0.008
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.4690 0.74648 0.900 0.100
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.9775 0.33188 0.412 0.588
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.4161 0.80038 0.084 0.916
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 1 0.9775 0.34636 0.588 0.412
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.8813 0.61886 0.300 0.700
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.9833 0.29164 0.424 0.576
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.2423 0.80168 0.040 0.960
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.5629 0.78743 0.132 0.868
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.8267 0.66927 0.260 0.740
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9983 0.16146 0.524 0.476
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.8267 0.66615 0.740 0.260
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.8016 0.69356 0.244 0.756
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.2778 0.74210 0.952 0.048
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.6247 0.76714 0.156 0.844
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.9754 0.30453 0.408 0.592
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0000 0.78716 0.000 1.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.8386 0.65964 0.732 0.268
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.6973 0.74881 0.188 0.812
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.5946 0.73845 0.856 0.144
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.8555 0.63668 0.280 0.720
#> A2007795-C728-4688-B199-AE89500011D2 2 0.3114 0.80475 0.056 0.944
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.2948 0.80475 0.052 0.948
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.9944 0.21787 0.544 0.456
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 1 0.9983 0.09772 0.524 0.476
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.9896 0.29107 0.560 0.440
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.9732 0.39618 0.596 0.404
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0376 0.78954 0.004 0.996
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.78716 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.73521 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.3733 0.80261 0.072 0.928
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.9983 0.09772 0.524 0.476
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.9754 0.41423 0.592 0.408
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.78716 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.7602 0.70078 0.780 0.220
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2948 0.80444 0.052 0.948
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.9248 0.49715 0.340 0.660
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.5519 0.74631 0.872 0.128
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.9988 0.04703 0.480 0.520
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.7376 0.72778 0.208 0.792
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.7299 0.74144 0.204 0.796
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.78716 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1184 0.74193 0.984 0.016
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3431 0.80571 0.064 0.936
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.78716 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.9963 0.18596 0.536 0.464
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6887 0.72159 0.816 0.184
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.73521 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8555 0.65408 0.280 0.720
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.3431 0.80339 0.064 0.936
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.7453 0.71976 0.212 0.788
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5408 0.79141 0.124 0.876
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.5178 0.79486 0.116 0.884
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.2778 0.79766 0.048 0.952
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.78716 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.73521 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.9795 0.25927 0.416 0.584
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8386 0.66724 0.268 0.732
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.9998 0.07252 0.508 0.492
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.73521 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.9248 0.50169 0.340 0.660
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2423 0.80168 0.040 0.960
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.5519 0.74631 0.872 0.128
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.8608 0.60446 0.716 0.284
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5629 0.74578 0.868 0.132
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9850 0.27904 0.428 0.572
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5946 0.73819 0.856 0.144
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.78716 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0376 0.73737 0.996 0.004
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.8267 0.67168 0.740 0.260
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.2236 0.80031 0.036 0.964
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.78716 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.9661 0.35961 0.392 0.608
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2236 0.80052 0.036 0.964
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5946 0.73819 0.856 0.144
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.9983 0.09772 0.524 0.476
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.9833 0.29420 0.576 0.424
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.9881 0.26146 0.436 0.564
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3879 0.80144 0.076 0.924
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.2423 0.80250 0.040 0.960
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.4815 0.73804 0.896 0.104
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2603 0.80375 0.044 0.956
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.7056 0.71934 0.808 0.192
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.73521 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4815 0.80048 0.104 0.896
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4815 0.74610 0.896 0.104
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.3584 0.80200 0.068 0.932
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.9933 0.25642 0.548 0.452
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.9954 0.25076 0.540 0.460
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9988 0.07836 0.520 0.480
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0376 0.73580 0.996 0.004
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.8443 0.66830 0.272 0.728
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9491 0.49821 0.632 0.368
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.1843 0.74217 0.972 0.028
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.458 0.55023 0.004 0.812 0.184
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.584 0.46832 0.732 0.016 0.252
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.165 0.58697 0.004 0.960 0.036
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.177 0.67177 0.960 0.024 0.016
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.579 0.43016 0.000 0.668 0.332
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.447 0.55307 0.004 0.820 0.176
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.662 0.67108 0.744 0.176 0.080
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.230 0.66439 0.944 0.020 0.036
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.466 0.69176 0.844 0.124 0.032
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.693 0.59951 0.664 0.296 0.040
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.620 0.41677 0.008 0.656 0.336
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.592 0.55668 0.080 0.792 0.128
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.819 0.45014 0.220 0.636 0.144
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.483 0.53961 0.004 0.792 0.204
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.679 0.52975 0.120 0.744 0.136
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.836 0.87075 0.160 0.216 0.624
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.599 0.36577 0.000 0.632 0.368
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.836 0.87075 0.160 0.216 0.624
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.599 0.36577 0.000 0.632 0.368
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.899 0.27622 0.340 0.516 0.144
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.429 0.56196 0.004 0.832 0.164
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.558 0.58110 0.100 0.812 0.088
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.870 0.42831 0.552 0.128 0.320
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.645 0.42125 0.672 0.020 0.308
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.849 0.19431 0.336 0.556 0.108
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.601 0.36024 0.000 0.628 0.372
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.715 0.61222 0.676 0.264 0.060
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.241 0.66121 0.940 0.020 0.040
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.212 0.65610 0.948 0.012 0.040
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.566 0.49337 0.008 0.728 0.264
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.279 0.67171 0.928 0.028 0.044
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.593 0.38604 0.000 0.644 0.356
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.930 0.06591 0.360 0.472 0.168
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.698 0.64584 0.704 0.228 0.068
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.543 0.47632 0.000 0.716 0.284
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.592 0.45740 0.724 0.016 0.260
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.953 0.40922 0.376 0.192 0.432
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.841 0.51459 0.580 0.308 0.112
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.803 0.57717 0.616 0.288 0.096
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.212 0.65610 0.948 0.012 0.040
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.640 0.52585 0.040 0.724 0.236
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.772 0.46308 0.208 0.672 0.120
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.599 0.36577 0.000 0.632 0.368
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.581 0.41839 0.000 0.664 0.336
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.781 0.49965 0.584 0.352 0.064
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.495 0.55499 0.016 0.808 0.176
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.509 0.65051 0.824 0.040 0.136
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.458 0.55023 0.004 0.812 0.184
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.546 0.48752 0.000 0.712 0.288
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.458 0.54923 0.004 0.812 0.184
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.798 0.75132 0.100 0.272 0.628
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.850 0.39711 0.516 0.388 0.096
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.414 0.68999 0.864 0.116 0.020
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.240 0.64479 0.932 0.004 0.064
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.406 0.69256 0.880 0.076 0.044
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.645 0.65944 0.736 0.212 0.052
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.688 0.52752 0.172 0.732 0.096
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.836 0.87075 0.160 0.216 0.624
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.606 0.56316 0.064 0.776 0.160
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.940 0.24650 0.216 0.504 0.280
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.758 0.61043 0.648 0.276 0.076
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.640 0.34744 0.008 0.620 0.372
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.889 0.18646 0.440 0.440 0.120
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.421 0.69501 0.872 0.088 0.040
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.567 0.64795 0.800 0.060 0.140
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.525 0.49721 0.000 0.736 0.264
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.531 0.52547 0.012 0.772 0.216
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.558 0.55539 0.024 0.772 0.204
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.654 0.65487 0.728 0.220 0.052
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.230 0.66439 0.944 0.020 0.036
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.865 0.34566 0.492 0.404 0.104
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.533 0.68943 0.812 0.144 0.044
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#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.683 0.52955 0.168 0.736 0.096
#> A2007795-C728-4688-B199-AE89500011D2 2 0.568 0.46008 0.000 0.684 0.316
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.541 0.53927 0.020 0.780 0.200
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.904 -0.01996 0.396 0.468 0.136
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.836 0.87075 0.160 0.216 0.624
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 2 0.923 -0.06160 0.416 0.432 0.152
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.972 0.18045 0.416 0.360 0.224
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.597 0.37241 0.000 0.636 0.364
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.610 0.33980 0.000 0.608 0.392
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.647 0.38016 0.668 0.020 0.312
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.199 0.58847 0.004 0.948 0.048
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.836 0.87075 0.160 0.216 0.624
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.869 0.23915 0.464 0.432 0.104
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.597 0.37204 0.000 0.636 0.364
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.741 0.63441 0.684 0.224 0.092
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.475 0.56277 0.012 0.816 0.172
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.782 0.45920 0.200 0.668 0.132
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.454 0.69584 0.848 0.124 0.028
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.904 0.19484 0.356 0.500 0.144
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.794 0.47373 0.116 0.648 0.236
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.718 0.54490 0.096 0.708 0.196
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.610 0.33980 0.000 0.608 0.392
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.292 0.67572 0.924 0.032 0.044
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.529 0.53214 0.008 0.764 0.228
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.610 0.33980 0.000 0.608 0.392
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.975 0.06210 0.320 0.436 0.244
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.746 0.61873 0.692 0.196 0.112
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.186 0.63919 0.948 0.000 0.052
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.808 0.49068 0.180 0.652 0.168
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.188 0.58761 0.004 0.952 0.044
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.565 0.55397 0.084 0.808 0.108
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.379 0.58992 0.048 0.892 0.060
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.620 0.57191 0.056 0.760 0.184
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.647 0.40418 0.012 0.632 0.356
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.610 0.33980 0.000 0.608 0.392
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.626 0.42064 0.696 0.020 0.284
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.798 0.75132 0.100 0.272 0.628
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.795 0.47419 0.148 0.660 0.192
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.942 0.16563 0.320 0.484 0.196
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.263 0.63946 0.916 0.000 0.084
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.770 0.46031 0.212 0.672 0.116
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.447 0.55307 0.004 0.820 0.176
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.454 0.69584 0.848 0.124 0.028
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.896 0.42929 0.540 0.304 0.156
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.576 0.68846 0.796 0.140 0.064
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.935 0.31650 0.252 0.516 0.232
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.627 0.68209 0.768 0.156 0.076
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.525 0.49721 0.000 0.736 0.264
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.165 0.65214 0.960 0.004 0.036
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.763 0.61009 0.652 0.264 0.084
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.583 0.46523 0.008 0.708 0.284
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.610 0.33980 0.000 0.608 0.392
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.865 0.36422 0.292 0.572 0.136
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.493 0.53275 0.004 0.784 0.212
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.635 0.68076 0.764 0.156 0.080
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.836 0.87075 0.160 0.216 0.624
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.991 -0.14577 0.272 0.380 0.348
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.887 0.30650 0.296 0.552 0.152
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.188 0.58789 0.004 0.952 0.044
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.580 0.49243 0.016 0.736 0.248
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.755 0.59893 0.684 0.112 0.204
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.250 0.58665 0.004 0.928 0.068
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.668 0.66152 0.728 0.208 0.064
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.647 0.38016 0.668 0.020 0.312
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.538 0.57168 0.024 0.788 0.188
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.369 0.68875 0.884 0.100 0.016
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.594 0.52099 0.024 0.740 0.236
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.945 -0.08717 0.388 0.432 0.180
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.876 -0.02671 0.404 0.484 0.112
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.885 0.79513 0.176 0.252 0.572
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.645 0.38321 0.672 0.020 0.308
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.798 0.50504 0.172 0.660 0.168
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.907 0.35663 0.500 0.352 0.148
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.693 0.35688 0.640 0.032 0.328
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.759 0.24991 0.000 0.404 0.196 0.400
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.519 0.42629 0.656 0.000 0.324 0.020
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.574 0.28443 0.000 0.300 0.052 0.648
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.266 0.71775 0.900 0.000 0.016 0.084
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.396 0.58820 0.000 0.820 0.028 0.152
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.761 -0.24562 0.000 0.396 0.200 0.404
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.592 0.51927 0.580 0.000 0.044 0.376
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.200 0.70981 0.936 0.000 0.020 0.044
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.487 0.65967 0.720 0.000 0.024 0.256
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.554 0.36707 0.540 0.004 0.012 0.444
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.608 0.53353 0.000 0.656 0.092 0.252
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.495 0.48906 0.012 0.160 0.048 0.780
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.607 0.56396 0.116 0.072 0.068 0.744
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.751 0.29559 0.000 0.432 0.184 0.384
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.494 0.53399 0.024 0.100 0.072 0.804
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.223 0.54200 0.000 0.928 0.036 0.036
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.223 0.54200 0.000 0.928 0.036 0.036
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.786 0.53313 0.208 0.092 0.104 0.596
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.754 -0.14974 0.000 0.352 0.196 0.452
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.650 0.42764 0.032 0.232 0.068 0.668
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.779 0.30524 0.424 0.000 0.280 0.296
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.631 0.36975 0.560 0.000 0.372 0.068
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.588 0.51259 0.192 0.052 0.032 0.724
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.308 0.56117 0.000 0.884 0.032 0.084
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.592 0.36245 0.516 0.000 0.036 0.448
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.185 0.70857 0.940 0.000 0.012 0.048
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.202 0.70377 0.936 0.000 0.024 0.040
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.554 0.54160 0.004 0.672 0.036 0.288
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.252 0.71638 0.908 0.000 0.016 0.076
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.300 0.55664 0.000 0.892 0.048 0.060
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.673 0.47167 0.212 0.028 0.100 0.660
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.608 0.48246 0.560 0.004 0.040 0.396
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.562 0.57581 0.000 0.720 0.108 0.172
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.527 0.40672 0.640 0.000 0.340 0.020
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.940 0.43656 0.272 0.160 0.412 0.156
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.666 -0.09408 0.428 0.020 0.044 0.508
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 4 0.627 -0.25258 0.468 0.012 0.032 0.488
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.202 0.70377 0.936 0.000 0.024 0.040
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.619 0.34935 0.000 0.144 0.184 0.672
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.505 0.55902 0.104 0.088 0.016 0.792
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.241 0.54901 0.000 0.920 0.036 0.044
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.355 0.58176 0.000 0.848 0.024 0.128
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.598 -0.08776 0.436 0.012 0.020 0.532
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.777 -0.23867 0.004 0.388 0.200 0.408
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.466 0.67477 0.796 0.000 0.116 0.088
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.759 0.24991 0.000 0.404 0.196 0.400
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.638 0.57327 0.000 0.628 0.108 0.264
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.759 0.25203 0.000 0.404 0.196 0.400
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.527 0.60509 0.000 0.452 0.540 0.008
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 4 0.554 0.11047 0.364 0.004 0.020 0.612
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.447 0.67979 0.760 0.000 0.020 0.220
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.172 0.68273 0.948 0.000 0.032 0.020
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.400 0.71475 0.812 0.000 0.024 0.164
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.569 0.52591 0.592 0.000 0.032 0.376
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.640 0.51834 0.080 0.156 0.052 0.712
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.807 -0.14704 0.024 0.372 0.168 0.436
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.904 0.28829 0.100 0.216 0.224 0.460
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.648 0.38184 0.508 0.008 0.052 0.432
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.217 0.51061 0.000 0.928 0.052 0.020
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.645 0.29771 0.268 0.012 0.080 0.640
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.441 0.69488 0.780 0.000 0.028 0.192
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.525 0.67197 0.752 0.000 0.100 0.148
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.762 0.42195 0.000 0.464 0.228 0.308
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.554 0.49800 0.008 0.656 0.024 0.312
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.620 0.37568 0.012 0.572 0.036 0.380
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.572 0.50471 0.580 0.000 0.032 0.388
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.200 0.70981 0.936 0.000 0.020 0.044
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.532 0.17787 0.336 0.004 0.016 0.644
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.527 0.63590 0.680 0.000 0.032 0.288
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.872 -0.11947 0.036 0.356 0.332 0.276
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.433 0.56795 0.124 0.040 0.012 0.824
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.871 0.14915 0.036 0.328 0.364 0.272
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.565 0.36178 0.000 0.580 0.028 0.392
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.574 0.28450 0.000 0.300 0.052 0.648
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.670 0.49894 0.160 0.028 0.136 0.676
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 4 0.641 0.41727 0.236 0.024 0.072 0.668
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.440 0.68194 0.768 0.000 0.020 0.212
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.528 0.64976 0.696 0.000 0.040 0.264
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.619 0.77857 0.004 0.288 0.636 0.072
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.548 0.27202 0.536 0.000 0.448 0.016
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.695 -0.12432 0.428 0.012 0.076 0.484
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.578 0.30779 0.560 0.000 0.408 0.032
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.626 0.41134 0.540 0.000 0.060 0.400
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.762 0.42195 0.000 0.464 0.228 0.308
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.723 0.54521 0.160 0.068 0.116 0.656
#> 7DA4280C-511E-493E-B187-88ECCA427C33 4 0.761 -0.24562 0.000 0.396 0.200 0.404
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.499 0.66109 0.728 0.000 0.036 0.236
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.619 0.34935 0.000 0.144 0.184 0.672
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.722 0.15071 0.004 0.264 0.172 0.560
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.735 0.32483 0.000 0.452 0.160 0.388
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 4 0.878 -0.03104 0.040 0.320 0.280 0.360
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#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.633 0.51779 0.080 0.156 0.048 0.716
#> A2007795-C728-4688-B199-AE89500011D2 2 0.621 0.57562 0.000 0.656 0.112 0.232
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.598 0.43633 0.012 0.616 0.032 0.340
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 4 0.693 0.42262 0.268 0.044 0.064 0.624
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 4 0.780 0.39966 0.292 0.060 0.096 0.552
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.886 0.31546 0.268 0.088 0.176 0.468
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.238 0.54773 0.000 0.920 0.028 0.052
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.158 0.49684 0.000 0.952 0.036 0.012
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.578 0.30779 0.560 0.000 0.408 0.032
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.572 0.30586 0.000 0.284 0.056 0.660
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.633 0.27625 0.296 0.016 0.056 0.632
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.266 0.56033 0.000 0.908 0.036 0.056
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.653 0.44153 0.556 0.004 0.072 0.368
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.761 -0.22271 0.004 0.400 0.172 0.424
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.526 0.55721 0.068 0.072 0.064 0.796
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.481 0.67525 0.728 0.000 0.024 0.248
#> DDC71530-38B7-483F-83DC-1BCC550719C3 4 0.751 0.52107 0.228 0.084 0.076 0.612
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.843 0.07845 0.068 0.384 0.120 0.428
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.785 0.21880 0.044 0.340 0.108 0.508
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.158 0.49987 0.000 0.952 0.036 0.012
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.388 0.71984 0.840 0.000 0.048 0.112
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.642 0.46427 0.004 0.588 0.072 0.336
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.158 0.49987 0.000 0.952 0.036 0.012
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.888 0.29049 0.184 0.088 0.260 0.468
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.643 0.51417 0.596 0.004 0.076 0.324
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.111 0.67708 0.968 0.000 0.028 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.813 0.39255 0.080 0.224 0.132 0.564
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.565 0.30642 0.000 0.284 0.052 0.664
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.505 0.49872 0.012 0.132 0.072 0.784
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.639 0.34643 0.020 0.276 0.060 0.644
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.824 -0.04294 0.040 0.360 0.152 0.448
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.525 0.57201 0.004 0.744 0.060 0.192
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.158 0.49684 0.000 0.952 0.036 0.012
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.570 0.35230 0.588 0.000 0.380 0.032
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.527 0.60509 0.000 0.452 0.540 0.008
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.800 0.35689 0.064 0.272 0.116 0.548
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.661 0.49717 0.160 0.024 0.136 0.680
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.248 0.68958 0.916 0.000 0.052 0.032
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.510 0.55919 0.104 0.084 0.020 0.792
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 4 0.761 -0.24562 0.000 0.396 0.200 0.404
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.481 0.67525 0.728 0.000 0.024 0.248
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.751 0.10384 0.456 0.028 0.092 0.424
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.543 0.60163 0.652 0.000 0.032 0.316
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.791 0.48478 0.120 0.104 0.172 0.604
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.588 0.57164 0.608 0.000 0.048 0.344
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.762 0.42195 0.000 0.464 0.228 0.308
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.152 0.69334 0.956 0.000 0.024 0.020
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.577 0.34772 0.508 0.000 0.028 0.464
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.526 0.57986 0.004 0.712 0.036 0.248
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.158 0.49987 0.000 0.952 0.036 0.012
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.713 0.56298 0.168 0.112 0.060 0.660
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.723 0.35320 0.000 0.480 0.148 0.372
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.584 0.56388 0.604 0.000 0.044 0.352
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.616 0.78216 0.004 0.284 0.640 0.072
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.880 0.07897 0.140 0.092 0.324 0.444
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.659 0.55821 0.172 0.060 0.072 0.696
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.562 0.30375 0.000 0.292 0.048 0.660
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.543 0.54992 0.012 0.700 0.028 0.260
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.642 0.55170 0.616 0.000 0.104 0.280
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.604 0.21709 0.000 0.332 0.060 0.608
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.612 0.51534 0.572 0.000 0.056 0.372
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.578 0.30779 0.560 0.000 0.408 0.032
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.680 0.15024 0.012 0.468 0.064 0.456
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.429 0.68652 0.772 0.000 0.016 0.212
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.671 0.36466 0.012 0.556 0.068 0.364
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.696 0.38215 0.248 0.024 0.104 0.624
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.678 0.40374 0.236 0.032 0.084 0.648
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.760 0.71492 0.036 0.264 0.572 0.128
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.587 0.29930 0.548 0.000 0.416 0.036
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.825 0.37187 0.076 0.232 0.144 0.548
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.712 0.21839 0.336 0.028 0.076 0.560
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.629 0.27588 0.528 0.000 0.412 0.060
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.6222 0.73785 0.236 0.548 0.000 0.216 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.5421 0.34772 0.012 0.052 0.324 0.000 0.612
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.6344 0.23145 0.608 0.200 0.028 0.164 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3456 0.68277 0.108 0.036 0.012 0.000 0.844
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4790 0.62156 0.160 0.044 0.040 0.756 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.6150 0.74085 0.236 0.560 0.000 0.204 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 5 0.6050 0.38362 0.420 0.056 0.028 0.000 0.496
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.2925 0.67954 0.064 0.036 0.016 0.000 0.884
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 5 0.5289 0.58278 0.280 0.040 0.024 0.000 0.656
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.5543 0.26251 0.448 0.036 0.016 0.000 0.500
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.7243 0.41973 0.252 0.088 0.132 0.528 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5013 0.45107 0.756 0.132 0.032 0.076 0.004
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5580 0.54659 0.744 0.108 0.060 0.028 0.060
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.6347 0.71730 0.228 0.524 0.000 0.248 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4557 0.49186 0.772 0.148 0.056 0.024 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.2787 0.65040 0.028 0.088 0.004 0.880 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.2787 0.65040 0.028 0.088 0.004 0.880 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6898 0.48522 0.600 0.188 0.024 0.032 0.156
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.6387 0.72182 0.276 0.544 0.008 0.172 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.6593 0.37193 0.636 0.184 0.048 0.116 0.016
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.7841 0.20455 0.328 0.068 0.248 0.000 0.356
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 5 0.6498 0.28695 0.068 0.052 0.364 0.000 0.516
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5464 0.56455 0.732 0.084 0.020 0.024 0.140
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.3386 0.66104 0.088 0.020 0.036 0.856 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.6308 0.24763 0.440 0.076 0.028 0.000 0.456
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.2103 0.67539 0.056 0.004 0.020 0.000 0.920
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 5 0.2829 0.67041 0.052 0.032 0.024 0.000 0.892
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.6761 0.39823 0.292 0.100 0.060 0.548 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.2729 0.68363 0.084 0.004 0.028 0.000 0.884
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.3523 0.62451 0.044 0.120 0.004 0.832 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.6008 0.54700 0.692 0.068 0.084 0.008 0.148
#> 72BCF7F5-3826-4289-B0C7-505678481099 5 0.5941 0.37151 0.424 0.048 0.028 0.000 0.500
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.5515 0.34639 0.112 0.260 0.000 0.628 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 5 0.5419 0.33343 0.012 0.048 0.340 0.000 0.600
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.8399 0.41713 0.144 0.068 0.476 0.076 0.236
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6460 0.06156 0.508 0.072 0.028 0.008 0.384
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5657 -0.13213 0.524 0.040 0.020 0.000 0.416
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.2829 0.67041 0.052 0.032 0.024 0.000 0.892
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.6005 0.28351 0.332 0.556 0.104 0.008 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5203 0.52685 0.752 0.132 0.016 0.028 0.072
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.2928 0.64840 0.032 0.092 0.004 0.872 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4017 0.64164 0.132 0.040 0.020 0.808 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.5723 0.05927 0.548 0.048 0.020 0.000 0.384
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.6461 0.73985 0.244 0.548 0.004 0.200 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.5403 0.62206 0.108 0.064 0.096 0.000 0.732
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.6222 0.73785 0.236 0.548 0.000 0.216 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.7197 0.07276 0.204 0.256 0.044 0.496 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.6245 0.73486 0.236 0.544 0.000 0.220 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4910 0.62178 0.004 0.048 0.672 0.276 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.5574 0.24738 0.616 0.048 0.024 0.000 0.312
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.4757 0.61082 0.248 0.036 0.012 0.000 0.704
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.2581 0.63350 0.020 0.048 0.028 0.000 0.904
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.4307 0.65903 0.180 0.040 0.012 0.000 0.768
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 5 0.5864 0.42417 0.396 0.056 0.020 0.000 0.528
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.6528 0.44428 0.660 0.172 0.032 0.080 0.056
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.7135 0.70276 0.272 0.500 0.008 0.196 0.024
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.8399 0.21463 0.444 0.128 0.284 0.096 0.048
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.6475 -0.23712 0.444 0.092 0.028 0.000 0.436
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 4 0.2228 0.63414 0.012 0.040 0.028 0.920 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.6144 0.40494 0.640 0.120 0.028 0.004 0.208
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.4909 0.63461 0.204 0.052 0.020 0.000 0.724
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 5 0.5598 0.61973 0.176 0.032 0.100 0.000 0.692
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.6801 0.43839 0.088 0.604 0.156 0.152 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.6384 0.36253 0.316 0.104 0.028 0.552 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.6816 0.25326 0.380 0.112 0.040 0.468 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 5 0.5883 0.40066 0.408 0.056 0.020 0.000 0.516
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.2925 0.67954 0.064 0.036 0.016 0.000 0.884
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.5545 0.30845 0.636 0.060 0.020 0.000 0.284
#> 95AFBE7A-9495-433D-8CF0-41D126110428 5 0.5527 0.55660 0.312 0.036 0.032 0.000 0.620
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.8607 0.21978 0.248 0.204 0.360 0.180 0.008
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.4782 0.54500 0.780 0.096 0.020 0.012 0.092
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.8481 0.26218 0.248 0.208 0.384 0.152 0.008
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.6704 0.18573 0.372 0.132 0.024 0.472 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 1 0.6344 0.23182 0.608 0.200 0.028 0.164 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.6265 0.54467 0.688 0.096 0.108 0.016 0.092
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.5781 0.48798 0.696 0.084 0.040 0.008 0.172
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 5 0.4874 0.61201 0.240 0.040 0.016 0.000 0.704
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.5784 0.56694 0.288 0.064 0.028 0.000 0.620
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4882 0.75953 0.036 0.096 0.764 0.104 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 5 0.5364 0.18575 0.008 0.036 0.460 0.000 0.496
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#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 4 0.3170 0.64223 0.036 0.104 0.004 0.856 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.6738 0.47542 0.656 0.120 0.084 0.112 0.028
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.5924 0.53015 0.696 0.144 0.108 0.012 0.040
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.1990 0.63029 0.004 0.040 0.028 0.000 0.928
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.3345 0.66445 0.052 0.060 0.024 0.864 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 5 0.5785 0.37769 0.420 0.048 0.020 0.000 0.512
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.6652 0.40540 0.592 0.084 0.068 0.004 0.252
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.3005 0.66142 0.048 0.028 0.040 0.000 0.884
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 1 0.6706 0.32304 0.612 0.188 0.040 0.148 0.012
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.6259 0.39520 0.628 0.116 0.032 0.004 0.220
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.5557 0.25570 0.620 0.048 0.024 0.000 0.308
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.5285 0.55644 0.740 0.088 0.040 0.004 0.128
#> C653CC8E-7598-4332-A053-D72CFBC380DF 5 0.3911 0.53968 0.000 0.060 0.144 0.000 0.796
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.6344 0.23891 0.608 0.200 0.028 0.164 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 4 0.6388 0.51882 0.224 0.068 0.088 0.620 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.2338 0.66135 0.032 0.036 0.016 0.000 0.916
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 5 0.4939 0.61827 0.236 0.040 0.020 0.000 0.704
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.7038 0.48798 0.648 0.104 0.092 0.068 0.088
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 1 0.6249 0.25607 0.620 0.196 0.028 0.156 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 1 0.9177 0.12463 0.384 0.112 0.232 0.088 0.184
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.7260 0.42811 0.608 0.104 0.128 0.132 0.028
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.7089 0.49115 0.644 0.100 0.096 0.068 0.092
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.6150 0.74085 0.236 0.560 0.000 0.204 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.6644 0.27329 0.596 0.144 0.032 0.220 0.008
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 1 0.8063 0.29324 0.520 0.140 0.080 0.208 0.052
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.8111 0.45096 0.532 0.084 0.132 0.068 0.184
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.6343 0.28442 0.420 0.080 0.028 0.000 0.472
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.8247 0.17690 0.460 0.172 0.172 0.184 0.012
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 5 0.6929 0.17673 0.088 0.052 0.408 0.004 0.448
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.7154 0.38268 0.408 0.424 0.008 0.120 0.040
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.5808 0.53923 0.704 0.152 0.040 0.012 0.092
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.6801 0.43839 0.088 0.604 0.156 0.152 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.6308 0.24763 0.440 0.076 0.028 0.000 0.456
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.7161 0.34142 0.596 0.160 0.068 0.156 0.020
#> 93E69515-4C47-4E68-8842-818DE0E369E2 5 0.5626 0.51177 0.348 0.048 0.020 0.000 0.584
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6494 0.44726 0.664 0.168 0.032 0.080 0.056
#> A2007795-C728-4688-B199-AE89500011D2 4 0.7089 0.16570 0.176 0.244 0.052 0.528 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.6455 0.29869 0.352 0.108 0.024 0.516 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.6744 0.49996 0.620 0.080 0.052 0.028 0.220
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.7129 0.49245 0.588 0.076 0.080 0.028 0.228
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.8000 0.40362 0.516 0.100 0.128 0.036 0.220
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3345 0.66445 0.052 0.060 0.024 0.864 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.0671 0.62368 0.004 0.000 0.016 0.980 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 5 0.5707 0.20446 0.016 0.048 0.424 0.000 0.512
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 1 0.6280 0.23195 0.608 0.212 0.024 0.156 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.5455 0.39260 0.688 0.064 0.024 0.004 0.220
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.3273 0.63990 0.036 0.112 0.004 0.848 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.6305 0.30543 0.404 0.072 0.032 0.000 0.492
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.6438 0.71329 0.280 0.500 0.000 0.220 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.5166 0.52343 0.768 0.112 0.036 0.032 0.052
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 5 0.5422 0.60191 0.268 0.052 0.024 0.000 0.656
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.6680 0.54797 0.652 0.084 0.060 0.036 0.168
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 1 0.8278 0.18398 0.432 0.112 0.128 0.300 0.028
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.7523 0.25713 0.540 0.120 0.104 0.224 0.012
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.0867 0.63433 0.008 0.008 0.008 0.976 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 5 0.4342 0.68706 0.128 0.024 0.056 0.000 0.792
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.7164 0.22932 0.332 0.160 0.044 0.464 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0867 0.63433 0.008 0.008 0.008 0.976 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.8442 0.33728 0.496 0.124 0.196 0.068 0.116
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 5 0.6350 0.42699 0.352 0.044 0.068 0.000 0.536
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.1990 0.63029 0.004 0.040 0.028 0.000 0.928
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.7777 0.29246 0.552 0.196 0.100 0.112 0.040
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.6226 0.25390 0.616 0.204 0.024 0.156 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.5162 0.44964 0.732 0.176 0.040 0.048 0.004
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.6953 0.28575 0.592 0.188 0.036 0.164 0.020
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.7625 0.52685 0.360 0.404 0.024 0.188 0.024
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.6018 0.54293 0.208 0.064 0.072 0.656 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.0671 0.62368 0.004 0.000 0.016 0.980 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 5 0.5740 0.25747 0.020 0.048 0.392 0.000 0.540
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4910 0.62178 0.004 0.048 0.672 0.276 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.7424 0.36980 0.576 0.108 0.116 0.180 0.020
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.6218 0.54467 0.692 0.096 0.104 0.016 0.092
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.2966 0.65531 0.040 0.020 0.056 0.000 0.884
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.5118 0.52501 0.756 0.128 0.012 0.028 0.076
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.6150 0.74085 0.236 0.560 0.000 0.204 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 5 0.5422 0.60191 0.268 0.052 0.024 0.000 0.656
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.7336 0.04439 0.420 0.076 0.072 0.016 0.416
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.5866 0.50843 0.332 0.052 0.032 0.000 0.584
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.6880 0.48649 0.608 0.124 0.200 0.020 0.048
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.6084 0.45477 0.384 0.052 0.028 0.004 0.532
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.6801 0.43839 0.088 0.604 0.156 0.152 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.2591 0.65790 0.032 0.044 0.020 0.000 0.904
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.5902 -0.24646 0.476 0.044 0.028 0.000 0.452
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.6404 0.48057 0.256 0.088 0.056 0.600 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.0867 0.63433 0.008 0.008 0.008 0.976 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6087 0.54138 0.700 0.120 0.024 0.048 0.108
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6677 0.64739 0.224 0.468 0.004 0.304 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 5 0.6025 0.44479 0.392 0.052 0.024 0.004 0.528
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4830 0.76181 0.036 0.092 0.768 0.104 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.7484 0.06825 0.444 0.104 0.364 0.008 0.080
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.6124 0.55692 0.700 0.096 0.068 0.020 0.116
#> F17B682D-A902-4730-A300-5C163209F7CD 1 0.6339 0.23520 0.608 0.204 0.028 0.160 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.6326 0.45547 0.272 0.096 0.040 0.592 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.6629 0.46101 0.304 0.060 0.084 0.000 0.552
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.6651 0.15377 0.556 0.224 0.024 0.196 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 5 0.5999 0.38787 0.424 0.052 0.028 0.000 0.496
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.5707 0.20446 0.016 0.048 0.424 0.000 0.512
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.7211 0.00161 0.460 0.132 0.060 0.348 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.4847 0.61794 0.236 0.040 0.016 0.000 0.708
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.7540 0.21271 0.368 0.108 0.108 0.416 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6611 0.47374 0.628 0.100 0.084 0.004 0.184
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5950 0.49212 0.688 0.092 0.048 0.008 0.164
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.6456 0.71224 0.112 0.100 0.672 0.100 0.016
#> AB642383-1611-4355-B03C-08D42FF4676C 5 0.5798 0.20049 0.020 0.048 0.432 0.000 0.500
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.7717 0.21922 0.536 0.236 0.080 0.112 0.036
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6479 0.34646 0.592 0.088 0.032 0.012 0.276
#> EE118E80-F125-4655-8845-56A9CBBA0680 5 0.6199 0.18597 0.044 0.048 0.420 0.000 0.488
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5176 0.71408 0.004 0.600 0.000 0.288 0.000 0.108
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.6045 0.66160 0.224 0.008 0.248 0.004 0.516 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4157 0.43338 0.008 0.068 0.024 0.796 0.004 0.100
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3636 0.03953 0.676 0.000 0.000 0.004 0.320 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.4319 0.64605 0.000 0.016 0.028 0.224 0.008 0.724
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5057 0.71654 0.004 0.612 0.000 0.288 0.000 0.096
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4480 0.53006 0.744 0.004 0.016 0.152 0.084 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4039 -0.21118 0.568 0.000 0.000 0.008 0.424 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3039 0.46269 0.848 0.004 0.000 0.060 0.088 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.5170 0.50754 0.636 0.016 0.000 0.252 0.096 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.7015 0.45014 0.000 0.048 0.132 0.284 0.044 0.492
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.4349 0.55329 0.076 0.024 0.012 0.804 0.048 0.036
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.5745 0.56956 0.212 0.016 0.040 0.656 0.064 0.012
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5272 0.69687 0.000 0.584 0.000 0.276 0.000 0.140
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.5718 0.57107 0.116 0.052 0.048 0.704 0.072 0.008
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.3891 0.75773 0.000 0.064 0.816 0.028 0.012 0.080
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.2994 0.69038 0.000 0.080 0.000 0.064 0.004 0.852
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3891 0.75773 0.000 0.064 0.816 0.028 0.012 0.080
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.2994 0.69038 0.000 0.080 0.000 0.064 0.004 0.852
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.7235 0.44150 0.296 0.120 0.016 0.476 0.076 0.016
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.5228 0.68173 0.000 0.564 0.008 0.344 0.000 0.084
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5885 0.51545 0.076 0.072 0.048 0.708 0.024 0.072
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.7882 0.00544 0.308 0.016 0.188 0.176 0.312 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 5 0.6745 0.59959 0.244 0.008 0.300 0.028 0.420 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.5803 0.39401 0.348 0.016 0.008 0.552 0.056 0.020
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.3333 0.67693 0.000 0.012 0.040 0.100 0.008 0.840
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5931 0.47695 0.592 0.024 0.012 0.240 0.132 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.3823 -0.22851 0.564 0.000 0.000 0.000 0.436 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.3907 -0.21329 0.588 0.004 0.000 0.000 0.408 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.6455 0.39906 0.000 0.052 0.064 0.360 0.032 0.492
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4329 -0.16651 0.576 0.000 0.008 0.012 0.404 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.3649 0.67168 0.000 0.112 0.000 0.084 0.004 0.800
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6701 0.40364 0.316 0.016 0.056 0.488 0.124 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4720 0.52750 0.700 0.004 0.004 0.184 0.108 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.5497 0.34974 0.000 0.256 0.000 0.184 0.000 0.560
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 5 0.6088 0.66177 0.220 0.008 0.264 0.004 0.504 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.8093 0.25602 0.108 0.020 0.424 0.104 0.280 0.064
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6301 0.30976 0.544 0.036 0.020 0.292 0.108 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4731 0.43741 0.636 0.004 0.004 0.304 0.052 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3907 -0.21329 0.588 0.004 0.000 0.000 0.408 0.000
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#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.4668 0.49573 0.688 0.012 0.004 0.240 0.056 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.6274 0.50186 0.000 0.048 0.064 0.308 0.032 0.548
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.0717 0.66679 0.000 0.008 0.000 0.016 0.000 0.976
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6700 0.52183 0.256 0.068 0.020 0.564 0.072 0.020
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.5801 0.62585 0.000 0.520 0.004 0.276 0.000 0.200
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4124 0.52510 0.776 0.004 0.012 0.124 0.084 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3891 0.75773 0.000 0.064 0.816 0.028 0.012 0.080
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.7941 0.01684 0.152 0.040 0.336 0.332 0.140 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.5798 0.50269 0.280 0.008 0.052 0.600 0.056 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.4163 0.43387 0.008 0.076 0.016 0.796 0.008 0.096
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.6526 0.43595 0.016 0.056 0.048 0.336 0.024 0.520
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.6626 0.14758 0.444 0.012 0.036 0.152 0.356 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.4736 0.39737 0.008 0.088 0.016 0.744 0.008 0.136
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4329 0.53034 0.728 0.000 0.004 0.180 0.088 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.5941 0.59958 0.168 0.004 0.348 0.004 0.476 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.6714 0.20096 0.016 0.044 0.060 0.540 0.044 0.296
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3473 0.41591 0.804 0.004 0.000 0.048 0.144 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.6995 -0.14431 0.016 0.040 0.116 0.432 0.020 0.376
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.6964 0.27301 0.348 0.024 0.052 0.436 0.140 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.6328 0.27970 0.392 0.020 0.012 0.452 0.120 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.6045 0.71147 0.024 0.064 0.696 0.080 0.056 0.080
#> AB642383-1611-4355-B03C-08D42FF4676C 5 0.6063 0.58776 0.168 0.008 0.364 0.004 0.456 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.8266 0.28267 0.128 0.232 0.064 0.452 0.056 0.068
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6943 -0.04888 0.428 0.044 0.020 0.364 0.140 0.004
#> EE118E80-F125-4655-8845-56A9CBBA0680 5 0.6355 0.56643 0.156 0.004 0.360 0.028 0.452 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.794 0.889 0.952 0.5004 0.499 0.499
#> 3 3 0.493 0.613 0.769 0.2938 0.748 0.543
#> 4 4 0.488 0.539 0.738 0.1370 0.749 0.422
#> 5 5 0.521 0.400 0.622 0.0713 0.842 0.499
#> 6 6 0.610 0.473 0.662 0.0430 0.848 0.429
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9477 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9473 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9477 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9473 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9477 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9477 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2423 0.9254 0.960 0.040
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9473 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9473 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9473 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9477 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7453 0.7077 0.212 0.788
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.9491 0.4688 0.632 0.368
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9477 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0672 0.9416 0.008 0.992
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.9710 0.3810 0.400 0.600
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9477 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.9087 0.5511 0.324 0.676
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9477 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.1633 0.9296 0.024 0.976
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9477 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9477 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9473 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9473 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4815 0.8605 0.896 0.104
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9477 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9473 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9473 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9473 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9477 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9473 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9477 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9473 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9473 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9477 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9473 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0376 0.9452 0.996 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9473 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9473 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9473 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9477 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.2603 0.9225 0.956 0.044
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9477 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9477 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.9473 1.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9477 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9473 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9477 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9477 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9477 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.7376 0.7385 0.208 0.792
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9473 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9473 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9473 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9473 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2423 0.9254 0.960 0.040
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.9477 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.9710 0.3810 0.400 0.600
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4022 0.8798 0.080 0.920
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.6247 0.8004 0.156 0.844
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.2423 0.9254 0.960 0.040
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9477 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9473 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9473 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9473 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9477 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9477 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.9477 0.000 1.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.2423 0.9254 0.960 0.040
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.9473 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.7815 0.7096 0.768 0.232
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9473 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.7139 0.7545 0.196 0.804
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9710 0.3742 0.600 0.400
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.7139 0.7545 0.196 0.804
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.9477 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9477 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9710 0.3810 0.400 0.600
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9473 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9473 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.9473 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.9710 0.3810 0.400 0.600
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.9473 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.9473 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.9473 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9473 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9477 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.9473 1.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9477 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.9473 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.7056 0.7657 0.808 0.192
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9477 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.9477 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.9710 0.3810 0.400 0.600
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.9477 0.000 1.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.9473 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.2423 0.9254 0.960 0.040
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.9473 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.2236 0.9193 0.036 0.964
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.7528 0.7330 0.784 0.216
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.4815 0.8603 0.896 0.104
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.9473 1.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.9477 0.000 1.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.9473 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.0000 0.9477 0.000 1.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.0000 0.9473 1.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.0000 0.9477 0.000 1.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.9710 0.3810 0.400 0.600
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.2603 0.9225 0.956 0.044
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#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9473 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9473 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9477 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9473 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9477 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9473 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9473 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9393 0.4316 0.644 0.356
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9473 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9477 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9170 0.4905 0.668 0.332
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9473 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0237 0.82547 0.000 0.996 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.6192 0.53916 0.420 0.000 0.580
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6887 0.72057 0.060 0.704 0.236
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4062 0.57450 0.836 0.000 0.164
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.4399 0.79079 0.000 0.812 0.188
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0237 0.82547 0.000 0.996 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0424 0.65615 0.992 0.000 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4002 0.57852 0.840 0.000 0.160
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2066 0.62510 0.940 0.000 0.060
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2356 0.61890 0.928 0.000 0.072
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.3038 0.81440 0.000 0.896 0.104
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.6714 0.59340 0.672 0.032 0.296
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6482 0.60003 0.680 0.024 0.296
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0237 0.82547 0.000 0.996 0.004
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.9125 0.47828 0.164 0.516 0.320
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6295 0.23019 0.000 0.472 0.528
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.82521 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6168 0.26624 0.000 0.412 0.588
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0237 0.82547 0.000 0.996 0.004
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.9738 0.30217 0.444 0.252 0.304
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.9686 0.33185 0.460 0.276 0.264
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7424 0.66119 0.060 0.640 0.300
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4887 0.58113 0.228 0.000 0.772
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.6180 0.54189 0.416 0.000 0.584
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5722 0.61356 0.704 0.004 0.292
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0892 0.82048 0.000 0.980 0.020
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4702 0.58058 0.788 0.000 0.212
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4605 0.53864 0.796 0.000 0.204
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2066 0.62510 0.940 0.000 0.060
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.4002 0.80161 0.000 0.840 0.160
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4974 0.54374 0.764 0.000 0.236
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0237 0.82547 0.000 0.996 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5465 0.61674 0.712 0.000 0.288
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2066 0.62914 0.940 0.000 0.060
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0237 0.82547 0.000 0.996 0.004
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.6180 0.54146 0.416 0.000 0.584
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1267 0.55169 0.024 0.004 0.972
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.5291 0.61733 0.732 0.000 0.268
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0592 0.65677 0.988 0.000 0.012
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.2165 0.62216 0.936 0.000 0.064
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.1529 0.82590 0.000 0.960 0.040
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6224 0.60559 0.688 0.016 0.296
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0237 0.82547 0.000 0.996 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.1860 0.82375 0.000 0.948 0.052
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3482 0.66181 0.872 0.000 0.128
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1860 0.82177 0.000 0.948 0.052
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.5621 0.57159 0.308 0.000 0.692
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0237 0.82547 0.000 0.996 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.82521 0.000 1.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0747 0.82168 0.000 0.984 0.016
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6302 0.21086 0.000 0.480 0.520
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2796 0.64729 0.908 0.000 0.092
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.2066 0.62510 0.940 0.000 0.060
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.5785 0.56323 0.332 0.000 0.668
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4062 0.57874 0.836 0.000 0.164
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0592 0.65677 0.988 0.000 0.012
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.7562 0.64699 0.064 0.628 0.308
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4346 0.47581 0.000 0.184 0.816
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.6970 0.69249 0.048 0.676 0.276
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.6404 0.67782 0.012 0.644 0.344
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0592 0.65677 0.988 0.000 0.012
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0892 0.82048 0.000 0.980 0.020
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3941 0.58265 0.844 0.000 0.156
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4702 0.56830 0.788 0.000 0.212
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.6225 0.53011 0.432 0.000 0.568
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1289 0.81565 0.000 0.968 0.032
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.2356 0.82125 0.000 0.928 0.072
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.4978 0.76993 0.004 0.780 0.216
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0592 0.65677 0.988 0.000 0.012
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3941 0.58265 0.844 0.000 0.156
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.6129 0.61379 0.700 0.016 0.284
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.2066 0.62510 0.940 0.000 0.060
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.6307 0.17488 0.000 0.488 0.512
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.6357 0.60319 0.684 0.020 0.296
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.6308 -0.14423 0.000 0.508 0.492
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4293 0.79493 0.004 0.832 0.164
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.4345 0.80205 0.016 0.848 0.136
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.8460 0.14189 0.244 0.148 0.608
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4702 0.64449 0.788 0.000 0.212
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2066 0.62510 0.940 0.000 0.060
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.4235 0.57143 0.824 0.000 0.176
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.6286 0.23748 0.000 0.464 0.536
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.6126 0.55041 0.400 0.000 0.600
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.6192 0.54488 0.580 0.000 0.420
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.5254 0.58316 0.264 0.000 0.736
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4605 0.53864 0.796 0.000 0.204
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1289 0.81565 0.000 0.968 0.032
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.5929 0.59384 0.676 0.004 0.320
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.82521 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.5016 0.54505 0.760 0.000 0.240
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.1525 0.65673 0.964 0.004 0.032
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.6398 0.74253 0.060 0.748 0.192
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0892 0.82048 0.000 0.980 0.020
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4555 0.44909 0.000 0.200 0.800
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.7562 0.64683 0.064 0.628 0.308
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.5431 0.61959 0.716 0.000 0.284
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0424 0.65615 0.992 0.000 0.008
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.3941 0.61860 0.844 0.000 0.156
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.9712 0.30997 0.436 0.232 0.332
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.5269 0.64884 0.784 0.016 0.200
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.1877 0.54860 0.032 0.012 0.956
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0747 0.65777 0.984 0.000 0.016
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0892 0.82048 0.000 0.980 0.020
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.6062 0.55838 0.384 0.000 0.616
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.5397 0.73871 0.000 0.720 0.280
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.5431 0.57690 0.284 0.000 0.716
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.3038 0.81440 0.000 0.896 0.104
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.5706 0.39284 0.000 0.320 0.680
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.5404 0.63042 0.740 0.004 0.256
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 3 0.8628 -0.28734 0.428 0.100 0.472
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.6303 0.34587 0.032 0.248 0.720
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0892 0.82048 0.000 0.980 0.020
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.2066 0.62510 0.940 0.000 0.060
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0237 0.82547 0.000 0.996 0.004
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.6204 0.54871 0.576 0.000 0.424
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.5882 0.56168 0.348 0.000 0.652
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.82521 0.000 1.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.6244 0.52199 0.440 0.000 0.560
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0237 0.82547 0.000 0.996 0.004
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.4326 0.79494 0.012 0.844 0.144
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.6215 0.53268 0.428 0.000 0.572
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.4605 0.53864 0.796 0.000 0.204
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 1 0.8514 0.48669 0.528 0.100 0.372
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.6215 0.53764 0.572 0.000 0.428
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.5178 0.62912 0.744 0.000 0.256
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0892 0.82048 0.000 0.980 0.020
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.8148 0.52951 0.604 0.100 0.296
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.6527 0.56333 0.588 0.008 0.404
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.7040 0.70813 0.060 0.688 0.252
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.2448 0.82111 0.000 0.924 0.076
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.5882 0.56168 0.348 0.000 0.652
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.6192 0.53916 0.420 0.000 0.580
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.5334 0.78590 0.060 0.820 0.120
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.2448 0.81934 0.000 0.924 0.076
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0237 0.82547 0.000 0.996 0.004
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0747 0.82168 0.000 0.984 0.016
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.2448 0.81934 0.000 0.924 0.076
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.2066 0.62510 0.940 0.000 0.060
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.3879 0.80365 0.000 0.848 0.152
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 3 0.6295 -0.33674 0.000 0.472 0.528
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0592 0.82277 0.000 0.988 0.012
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 3 0.6126 0.30975 0.400 0.000 0.600
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.4887 0.50220 0.772 0.000 0.228
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.4605 0.53864 0.796 0.000 0.204
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.6495 0.51001 0.536 0.004 0.460
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.2066 0.62510 0.940 0.000 0.060
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.6193 0.60833 0.692 0.016 0.292
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.5254 0.62809 0.736 0.000 0.264
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 1 0.6927 0.58537 0.664 0.040 0.296
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.1411 0.66059 0.964 0.000 0.036
#> 5206C997-CCAE-463E-9902-C60ADA86E632 3 0.5363 0.39890 0.000 0.276 0.724
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0237 0.82547 0.000 0.996 0.004
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 1 0.6247 0.58172 0.620 0.004 0.376
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.3192 0.81414 0.000 0.888 0.112
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 3 0.1905 0.54030 0.028 0.016 0.956
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.6313 0.60505 0.676 0.016 0.308
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 2 0.0747 0.82168 0.000 0.984 0.016
#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.0237 0.82547 0.000 0.996 0.004
#> EF3D2659-7C4A-4003-A1B1-9A47A5388034 3 0.6045 0.46406 0.380 0.000 0.620
#> 09A7BAD6-4AB2-428A-B96C-BC3C298C4496 3 0.9535 -0.00198 0.248 0.264 0.488
#> 02D46E43-75BB-4A0A-8A02-403C7FBFB112 2 0.7860 0.64685 0.088 0.628 0.284
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#> E2625C62-2ABA-4670-A186-A7C03D69DD58 1 0.6126 0.56516 0.600 0.000 0.400
#> FCA5BADD-A6B2-4602-9B8F-0CD760E0AC2A 2 0.6836 0.71896 0.056 0.704 0.240
#> 36A4A073-CB26-4A65-8E47-A61F29929BDC 3 0.4887 0.27440 0.228 0.000 0.772
#> BB6D222E-585A-4C3E-ADD2-1B2BD5281F50 2 0.0892 0.82048 0.000 0.980 0.020
#> 55CFCA9F-0704-4948-BFB3-9027DE73E4BC 3 0.5926 0.55650 0.356 0.000 0.644
#> 3A052FCB-69B1-4699-BE22-19A835E6D102 2 0.0892 0.82048 0.000 0.980 0.020
#> 90AAB588-049D-4C56-B024-97831990F7CB 2 0.4750 0.77790 0.000 0.784 0.216
#> 75858032-A88A-4851-BCE5-66831D649D57 2 0.7396 0.66365 0.060 0.644 0.296
#> EA5B09C5-A45D-44BC-8477-DAF6B0DD79C7 2 0.6083 0.76774 0.060 0.772 0.168
#> 8026EF80-8CFB-4A62-9C72-BB5B50BDECFE 3 0.5810 0.56093 0.336 0.000 0.664
#> C1D05156-9AA7-48FD-9C3C-8894F9025D29 2 0.5016 0.76620 0.000 0.760 0.240
#> D3AEFD54-52E3-4761-898B-F05A5B6BA198 2 0.7308 0.67572 0.060 0.656 0.284
#> 33FAC29F-D146-454C-AE5D-07DF7C191DFC 2 0.7425 0.65663 0.052 0.620 0.328
#> E3E13B94-9335-4B34-9975-ECA99EB1BCBE 1 0.5497 0.61455 0.708 0.000 0.292
#> 2E1AC099-CE43-4605-BDFD-FA71DE8EAE44 2 0.0000 0.82521 0.000 1.000 0.000
#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.0000 0.82521 0.000 1.000 0.000
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.0237 0.82547 0.000 0.996 0.004
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.2173 0.81521 0.048 0.944 0.008
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.0237 0.82547 0.000 0.996 0.004
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.2537 0.61278 0.920 0.000 0.080
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.7300 0.68231 0.064 0.664 0.272
#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.6541 0.60011 0.672 0.024 0.304
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0892 0.82048 0.000 0.980 0.020
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0892 0.82048 0.000 0.980 0.020
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.0892 0.82048 0.000 0.980 0.020
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 3 0.6192 0.53921 0.420 0.000 0.580
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 1 0.5327 0.56739 0.728 0.000 0.272
#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.1643 0.54726 0.044 0.000 0.956
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 3 0.4702 0.58112 0.212 0.000 0.788
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0592 0.65677 0.988 0.000 0.012
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.2537 0.61530 0.920 0.000 0.080
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 3 0.5760 0.56522 0.328 0.000 0.672
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.5926 0.55650 0.356 0.000 0.644
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.6887 0.71173 0.060 0.704 0.236
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.5408 0.77751 0.052 0.812 0.136
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 1 0.9948 0.20398 0.364 0.284 0.352
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.6482 0.60003 0.680 0.024 0.296
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.5760 0.56522 0.328 0.000 0.672
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.6927 0.58537 0.664 0.040 0.296
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.5529 0.61327 0.704 0.000 0.296
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.1163 0.82013 0.000 0.972 0.028
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.7338 0.67237 0.060 0.652 0.288
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.5461 0.64020 0.768 0.016 0.216
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.2165 0.62492 0.936 0.000 0.064
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.4291 0.55673 0.820 0.000 0.180
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.4796 0.42710 0.000 0.220 0.780
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.4555 0.78607 0.000 0.800 0.200
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.9746 -0.20850 0.240 0.432 0.328
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.3879 0.80020 0.000 0.848 0.152
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.6204 0.53644 0.424 0.000 0.576
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.5926 0.55650 0.356 0.000 0.644
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.4002 0.58078 0.840 0.000 0.160
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.1031 0.82093 0.000 0.976 0.024
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.6357 0.60319 0.684 0.020 0.296
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.82521 0.000 1.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0237 0.82547 0.000 0.996 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0237 0.82547 0.000 0.996 0.004
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.6823 0.58975 0.668 0.036 0.296
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.5919 0.61805 0.712 0.012 0.276
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.5810 0.56093 0.336 0.000 0.664
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.2066 0.82196 0.000 0.940 0.060
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0424 0.65615 0.992 0.000 0.008
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.6225 -0.36767 0.432 0.000 0.568
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.5859 0.55549 0.344 0.000 0.656
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.7180 0.69017 0.060 0.672 0.268
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.1411 0.64092 0.964 0.000 0.036
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.3816 0.65953 0.852 0.000 0.148
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.6193 0.60833 0.692 0.016 0.292
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.6235 0.52607 0.436 0.000 0.564
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.7277 0.67932 0.060 0.660 0.280
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0892 0.82048 0.000 0.980 0.020
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.4062 0.57450 0.836 0.000 0.164
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.2356 0.61890 0.928 0.000 0.072
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.6082 0.11599 0.296 0.012 0.692
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.7003 0.70686 0.060 0.692 0.248
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.3879 0.52053 0.000 0.152 0.848
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.5012 0.43271 0.204 0.008 0.788
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.3083 0.50559 0.060 0.024 0.916
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0237 0.82547 0.000 0.996 0.004
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.7396 0.66471 0.060 0.644 0.296
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0892 0.82048 0.000 0.980 0.020
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.5420 0.27213 0.240 0.008 0.752
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.5919 0.61757 0.724 0.016 0.260
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.6140 0.60327 0.000 0.596 0.404
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2066 0.54540 0.060 0.000 0.940
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.7015 0.70467 0.064 0.696 0.240
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.5639 0.63496 0.752 0.016 0.232
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.3947 0.75906 0.076 0.884 0.040
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.4002 0.62018 0.840 0.000 0.160
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.5958 0.71823 0.008 0.692 0.300
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0747 0.64976 0.984 0.000 0.016
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6836 0.55243 0.572 0.016 0.412
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0892 0.82048 0.000 0.980 0.020
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.4750 0.77170 0.000 0.784 0.216
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.6235 0.53509 0.564 0.000 0.436
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.6252 0.24254 0.000 0.444 0.556
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.3686 0.51583 0.140 0.000 0.860
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.5178 0.26003 0.256 0.000 0.744
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.1753 0.82406 0.000 0.952 0.048
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1163 0.81751 0.000 0.972 0.028
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.6126 0.54929 0.400 0.000 0.600
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4189 0.80392 0.056 0.876 0.068
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4887 0.43168 0.000 0.228 0.772
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.2066 0.66272 0.940 0.000 0.060
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0237 0.82547 0.000 0.996 0.004
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.5859 0.56389 0.656 0.000 0.344
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0424 0.82590 0.000 0.992 0.008
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.9558 0.34894 0.444 0.200 0.356
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.2066 0.62510 0.940 0.000 0.060
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5497 0.61455 0.708 0.000 0.292
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5678 0.71048 0.000 0.684 0.316
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.7442 0.66612 0.056 0.628 0.316
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0592 0.82277 0.000 0.988 0.012
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.2165 0.62678 0.936 0.000 0.064
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0592 0.82277 0.000 0.988 0.012
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0237 0.82547 0.000 0.996 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.1989 0.54354 0.048 0.004 0.948
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6302 -0.37023 0.520 0.000 0.480
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.4062 0.57450 0.836 0.000 0.164
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.7504 0.66569 0.060 0.628 0.312
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.6398 0.75364 0.060 0.748 0.192
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.9527 0.40515 0.220 0.480 0.300
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5884 0.72307 0.012 0.716 0.272
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.5891 0.75645 0.036 0.764 0.200
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.1860 0.82205 0.000 0.948 0.052
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1031 0.81940 0.000 0.976 0.024
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.6192 0.53921 0.420 0.000 0.580
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6299 0.21440 0.000 0.476 0.524
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8246 0.62000 0.100 0.588 0.312
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.6505 0.50134 0.528 0.004 0.468
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.5785 0.56323 0.332 0.000 0.668
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.7295 0.55490 0.584 0.036 0.380
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0747 0.82168 0.000 0.984 0.016
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0424 0.65615 0.992 0.000 0.008
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.1964 0.54382 0.056 0.000 0.944
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3941 0.58265 0.844 0.000 0.156
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6189 0.10517 0.364 0.004 0.632
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2066 0.62510 0.940 0.000 0.060
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1289 0.81565 0.000 0.968 0.032
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.3941 0.56469 0.844 0.000 0.156
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0747 0.65787 0.984 0.000 0.016
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1964 0.82246 0.000 0.944 0.056
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0592 0.82277 0.000 0.988 0.012
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6798 0.55988 0.584 0.016 0.400
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.82521 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.65325 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6291 0.23364 0.000 0.468 0.532
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.5291 0.56275 0.268 0.000 0.732
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5497 0.61455 0.708 0.000 0.292
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0237 0.82547 0.000 0.996 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.4291 0.79410 0.000 0.820 0.180
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.6126 0.39607 0.400 0.000 0.600
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0237 0.82547 0.000 0.996 0.004
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2066 0.62510 0.940 0.000 0.060
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.5760 0.56522 0.328 0.000 0.672
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.3941 0.79902 0.000 0.844 0.156
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.2066 0.62510 0.940 0.000 0.060
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.5465 0.73327 0.000 0.712 0.288
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5098 0.53747 0.752 0.000 0.248
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3192 0.66226 0.888 0.000 0.112
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2955 0.54590 0.008 0.080 0.912
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5988 0.56180 0.368 0.000 0.632
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4555 0.77505 0.000 0.800 0.200
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.6016 0.25158 0.256 0.020 0.724
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.3340 0.52124 0.120 0.000 0.880
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2730 0.8366 0.000 0.896 0.016 0.088
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5678 0.2455 0.452 0.000 0.524 0.024
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4933 0.4593 0.000 0.296 0.016 0.688
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2334 0.6263 0.908 0.000 0.088 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5716 0.1737 0.000 0.552 0.028 0.420
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#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3583 0.6422 0.004 0.040 0.864 0.092
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5448 0.5243 0.244 0.000 0.700 0.056
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.6991 0.3404 0.000 0.348 0.128 0.524
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.6965 -0.1540 0.096 0.004 0.460 0.440
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4793 0.5955 0.040 0.000 0.756 0.204
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5765 0.52094 0.000 0.612 0.048 0.304 0.036
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4302 0.49010 0.248 0.000 0.720 0.000 0.032
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2771 0.52140 0.012 0.128 0.000 0.860 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.6754 -0.05831 0.404 0.000 0.284 0.000 0.312
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.7220 0.17440 0.000 0.464 0.040 0.308 0.188
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5702 0.54969 0.000 0.636 0.048 0.276 0.040
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2983 0.65813 0.864 0.000 0.040 0.096 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.6549 0.09807 0.476 0.000 0.244 0.000 0.280
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2830 0.62092 0.876 0.000 0.080 0.000 0.044
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3898 0.56252 0.804 0.000 0.116 0.000 0.080
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.7191 0.25569 0.000 0.496 0.044 0.260 0.200
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.6086 0.27362 0.348 0.004 0.024 0.560 0.064
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.5990 0.10702 0.436 0.000 0.024 0.484 0.056
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5537 0.56195 0.000 0.648 0.048 0.272 0.032
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.7205 0.39374 0.100 0.040 0.040 0.564 0.256
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6439 0.46326 0.000 0.116 0.636 0.076 0.172
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0880 0.72779 0.000 0.968 0.000 0.032 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6597 0.46355 0.000 0.092 0.624 0.112 0.172
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0880 0.72779 0.000 0.968 0.000 0.032 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.5734 0.33230 0.012 0.008 0.048 0.576 0.356
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.6505 0.39378 0.012 0.096 0.048 0.628 0.216
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5131 0.35828 0.000 0.024 0.016 0.608 0.352
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4425 0.01431 0.004 0.000 0.452 0.000 0.544
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3789 0.52412 0.212 0.000 0.768 0.000 0.020
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.6880 0.37876 0.260 0.000 0.016 0.488 0.236
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.1525 0.71884 0.000 0.948 0.012 0.036 0.004
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.6323 0.41697 0.280 0.000 0.112 0.028 0.580
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.6581 0.30261 0.280 0.000 0.252 0.000 0.468
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.3019 0.61345 0.864 0.000 0.088 0.000 0.048
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.7400 0.07974 0.008 0.432 0.040 0.360 0.160
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.6435 0.39840 0.240 0.000 0.176 0.016 0.568
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3090 0.70846 0.000 0.860 0.032 0.104 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.6453 0.17297 0.556 0.000 0.016 0.268 0.160
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1124 0.65119 0.960 0.000 0.036 0.000 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4961 0.62768 0.000 0.720 0.048 0.208 0.024
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4210 0.50063 0.224 0.000 0.740 0.000 0.036
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4997 0.38053 0.000 0.008 0.568 0.020 0.404
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.6318 0.44959 0.248 0.000 0.032 0.120 0.600
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1197 0.66270 0.952 0.000 0.000 0.048 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4179 0.53116 0.776 0.000 0.152 0.000 0.072
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.2856 0.71171 0.000 0.872 0.008 0.104 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.5083 0.16484 0.428 0.000 0.004 0.540 0.028
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.3693 0.68158 0.000 0.808 0.032 0.156 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3900 0.61284 0.000 0.788 0.012 0.180 0.020
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2286 0.65565 0.888 0.000 0.000 0.108 0.004
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.7564 0.08883 0.000 0.284 0.048 0.412 0.256
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.5177 0.08110 0.040 0.000 0.472 0.000 0.488
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.6049 0.41635 0.000 0.544 0.048 0.368 0.040
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.7455 0.18506 0.000 0.260 0.048 0.448 0.244
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.5591 0.56498 0.000 0.656 0.048 0.256 0.040
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6682 0.45254 0.000 0.204 0.588 0.048 0.160
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1216 0.65957 0.960 0.000 0.000 0.020 0.020
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4179 0.53116 0.776 0.000 0.152 0.000 0.072
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.6517 -0.12660 0.192 0.000 0.416 0.000 0.392
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.6618 0.14926 0.384 0.000 0.216 0.000 0.400
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2020 0.65750 0.900 0.000 0.000 0.100 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.4845 0.42547 0.008 0.012 0.024 0.700 0.256
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.5519 0.43450 0.000 0.020 0.624 0.052 0.304
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.6635 0.19654 0.000 0.064 0.060 0.444 0.432
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.7212 -0.09015 0.000 0.108 0.080 0.332 0.480
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.1965 0.65754 0.904 0.000 0.000 0.096 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0960 0.72899 0.000 0.972 0.004 0.016 0.008
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.6053 0.28686 0.576 0.000 0.196 0.000 0.228
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.6491 0.40175 0.284 0.000 0.136 0.024 0.556
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4562 0.45208 0.292 0.000 0.676 0.000 0.032
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2758 0.70797 0.000 0.896 0.048 0.024 0.032
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.4407 0.55085 0.000 0.724 0.020 0.244 0.012
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.7054 0.20974 0.016 0.340 0.028 0.496 0.120
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.1965 0.65754 0.904 0.000 0.000 0.096 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.6514 0.10969 0.484 0.000 0.236 0.000 0.280
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.4182 0.34491 0.644 0.000 0.000 0.352 0.004
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.2830 0.62092 0.876 0.000 0.080 0.000 0.044
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.6636 0.37670 0.000 0.064 0.552 0.080 0.304
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4630 0.23091 0.396 0.000 0.000 0.588 0.016
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.7495 0.33831 0.000 0.144 0.484 0.092 0.280
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3246 0.44553 0.000 0.184 0.008 0.808 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.5369 0.40289 0.000 0.196 0.040 0.704 0.060
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.6631 0.05482 0.004 0.052 0.084 0.296 0.564
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4743 0.47995 0.732 0.000 0.000 0.112 0.156
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2889 0.61857 0.872 0.000 0.084 0.000 0.044
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.6678 0.36813 0.304 0.000 0.160 0.020 0.516
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.6040 0.46307 0.000 0.060 0.644 0.068 0.228
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.3745 0.52613 0.196 0.000 0.780 0.000 0.024
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.4478 0.44557 0.044 0.000 0.028 0.152 0.776
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3790 0.42573 0.000 0.000 0.724 0.004 0.272
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.6725 0.24777 0.312 0.000 0.272 0.000 0.416
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2430 0.71295 0.000 0.912 0.040 0.020 0.028
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.7597 0.20358 0.348 0.008 0.028 0.360 0.256
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.5614 0.56636 0.000 0.652 0.048 0.260 0.040
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.6668 0.44083 0.228 0.000 0.116 0.064 0.592
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.6087 0.57761 0.672 0.000 0.120 0.140 0.068
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.5985 0.41867 0.000 0.144 0.048 0.672 0.136
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.4058 0.69988 0.000 0.820 0.048 0.096 0.036
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.7517 0.36457 0.012 0.060 0.516 0.176 0.236
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.4620 0.29714 0.008 0.008 0.000 0.616 0.368
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.3734 0.60270 0.812 0.000 0.000 0.128 0.060
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.2740 0.66062 0.876 0.000 0.028 0.096 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.6746 0.42627 0.268 0.000 0.120 0.052 0.560
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.5945 0.30742 0.020 0.016 0.032 0.532 0.400
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.7158 0.10001 0.456 0.000 0.100 0.368 0.076
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.4915 0.36562 0.024 0.000 0.172 0.064 0.740
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.1908 0.65927 0.908 0.000 0.000 0.092 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.1299 0.72057 0.000 0.960 0.012 0.020 0.008
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.4070 0.52961 0.164 0.000 0.784 0.004 0.048
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.6865 0.33471 0.000 0.164 0.036 0.532 0.268
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.4151 0.32548 0.000 0.000 0.652 0.004 0.344
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.7207 0.24885 0.000 0.492 0.044 0.264 0.200
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.6297 0.45362 0.000 0.076 0.604 0.056 0.264
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.6311 -0.02026 0.476 0.000 0.024 0.416 0.084
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.6790 0.21664 0.064 0.004 0.076 0.320 0.536
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.8828 0.07947 0.016 0.176 0.208 0.304 0.296
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.4730 0.68433 0.000 0.776 0.048 0.116 0.060
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.3090 0.61027 0.860 0.000 0.088 0.000 0.052
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.2769 0.71347 0.000 0.876 0.032 0.092 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.4462 0.42818 0.044 0.000 0.020 0.168 0.768
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.4805 0.39901 0.144 0.000 0.728 0.000 0.128
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.6174 0.39818 0.000 0.536 0.048 0.368 0.048
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.5527 0.26139 0.388 0.000 0.540 0.000 0.072
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.1628 0.72537 0.000 0.936 0.008 0.056 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 4 0.7069 0.33406 0.000 0.152 0.048 0.504 0.296
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.5329 0.34290 0.336 0.000 0.596 0.000 0.068
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.6748 0.23638 0.308 0.000 0.284 0.000 0.408
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.4792 0.46447 0.044 0.000 0.012 0.712 0.232
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 5 0.3943 0.43049 0.028 0.000 0.016 0.156 0.800
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.4995 0.44840 0.704 0.000 0.004 0.208 0.084
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.1686 0.71650 0.000 0.944 0.008 0.028 0.020
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 4 0.6061 0.41522 0.072 0.004 0.048 0.648 0.228
#> FE330797-5A40-45A8-98DF-43A33369E90F 5 0.5250 0.05025 0.040 0.000 0.004 0.404 0.552
#> DAD951A3-C22E-42F0-BB02-854413DDC351 4 0.5345 0.48920 0.000 0.084 0.048 0.728 0.140
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.6602 0.35738 0.000 0.560 0.024 0.176 0.240
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.3291 0.47724 0.088 0.000 0.848 0.000 0.064
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.4276 0.49405 0.244 0.000 0.724 0.000 0.032
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.4350 0.49695 0.028 0.128 0.036 0.800 0.008
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.6873 0.33521 0.000 0.544 0.036 0.216 0.204
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.1877 0.72383 0.000 0.924 0.012 0.064 0.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.4245 0.68820 0.000 0.800 0.048 0.124 0.028
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.6560 0.40965 0.000 0.592 0.036 0.184 0.188
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.2889 0.61857 0.872 0.000 0.084 0.000 0.044
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.7550 0.05750 0.000 0.396 0.044 0.304 0.256
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.8683 0.12253 0.032 0.096 0.220 0.348 0.304
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.1026 0.73017 0.000 0.968 0.004 0.024 0.004
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 5 0.6227 0.43576 0.188 0.000 0.136 0.040 0.636
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 5 0.6569 0.30297 0.272 0.000 0.256 0.000 0.472
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 5 0.6425 0.36447 0.252 0.000 0.212 0.004 0.532
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 5 0.3770 0.41411 0.016 0.004 0.012 0.160 0.808
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.3019 0.61345 0.864 0.000 0.088 0.000 0.048
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 4 0.6229 0.12704 0.424 0.000 0.024 0.476 0.076
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.4106 0.49278 0.724 0.000 0.000 0.256 0.020
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#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.5299 0.48173 0.208 0.016 0.024 0.712 0.040
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.6326 0.32056 0.000 0.060 0.048 0.532 0.360
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.6910 0.37934 0.000 0.152 0.048 0.544 0.256
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6699 0.39066 0.000 0.576 0.040 0.172 0.212
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1483 0.72654 0.000 0.952 0.008 0.028 0.012
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3789 0.52520 0.212 0.000 0.768 0.000 0.020
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6609 0.45777 0.000 0.180 0.600 0.048 0.172
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.8242 0.34184 0.192 0.064 0.036 0.440 0.268
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.6154 0.11408 0.040 0.012 0.052 0.280 0.616
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.6150 -0.06765 0.132 0.000 0.464 0.000 0.404
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.4832 0.46333 0.088 0.000 0.000 0.712 0.200
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.5937 0.52113 0.000 0.616 0.048 0.284 0.052
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2712 0.66021 0.880 0.000 0.032 0.088 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.4833 0.39743 0.036 0.000 0.128 0.072 0.764
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.6722 0.22588 0.364 0.000 0.188 0.008 0.440
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.8993 -0.15516 0.176 0.024 0.224 0.284 0.292
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3844 0.58894 0.804 0.000 0.132 0.000 0.064
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2430 0.71295 0.000 0.912 0.040 0.020 0.028
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.6398 0.18193 0.500 0.000 0.300 0.000 0.200
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2280 0.64964 0.880 0.000 0.000 0.120 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.5358 0.51814 0.000 0.692 0.040 0.220 0.048
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0794 0.72779 0.000 0.972 0.000 0.028 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.5783 0.31497 0.052 0.000 0.020 0.544 0.384
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3141 0.70951 0.000 0.860 0.040 0.096 0.004
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1310 0.66144 0.956 0.000 0.020 0.024 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6448 0.46396 0.000 0.112 0.636 0.080 0.172
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6337 0.44485 0.088 0.000 0.612 0.056 0.244
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.6119 -0.02909 0.476 0.000 0.016 0.428 0.080
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4848 0.53302 0.000 0.644 0.032 0.320 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.7427 -0.01815 0.000 0.380 0.040 0.364 0.216
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.5769 0.39757 0.156 0.000 0.208 0.004 0.632
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4134 0.63651 0.000 0.744 0.032 0.224 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2843 0.62050 0.876 0.000 0.076 0.000 0.048
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2824 0.46545 0.020 0.000 0.864 0.000 0.116
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4937 0.25350 0.000 0.292 0.012 0.664 0.032
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3828 0.56659 0.808 0.000 0.120 0.000 0.072
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.7820 0.18833 0.016 0.288 0.040 0.420 0.236
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.6369 0.36252 0.236 0.000 0.216 0.004 0.544
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5368 0.57646 0.736 0.000 0.080 0.108 0.076
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.6211 0.44807 0.000 0.044 0.608 0.084 0.264
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4271 0.52884 0.180 0.000 0.768 0.008 0.044
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.7086 0.35023 0.000 0.160 0.048 0.508 0.284
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.4572 0.39527 0.016 0.000 0.056 0.168 0.760
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.6393 0.46020 0.060 0.000 0.636 0.144 0.160
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3961 0.01367 0.000 0.556 0.004 0.000 0.000 0.440
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4676 0.57301 0.216 0.004 0.684 0.000 0.096 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.5480 0.20504 0.028 0.492 0.004 0.436 0.008 0.032
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4700 0.48720 0.180 0.008 0.112 0.000 0.700 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4542 0.51530 0.000 0.012 0.028 0.688 0.012 0.260
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.3989 -0.07319 0.000 0.528 0.004 0.000 0.000 0.468
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1675 0.68939 0.936 0.032 0.024 0.000 0.008 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.5331 0.31029 0.312 0.008 0.104 0.000 0.576 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3887 0.60013 0.780 0.004 0.112 0.000 0.104 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4533 0.56584 0.728 0.012 0.112 0.000 0.148 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.4512 0.47528 0.000 0.004 0.028 0.676 0.016 0.276
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5929 0.22266 0.320 0.176 0.004 0.496 0.004 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5277 0.08217 0.476 0.084 0.000 0.436 0.004 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4111 -0.03849 0.000 0.536 0.004 0.000 0.004 0.456
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2885 0.59565 0.068 0.044 0.008 0.872 0.008 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.5382 0.57690 0.000 0.080 0.652 0.232 0.016 0.020
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.0692 0.79487 0.000 0.020 0.000 0.000 0.004 0.976
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.5029 0.56313 0.000 0.052 0.656 0.264 0.016 0.012
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.0777 0.79434 0.000 0.024 0.000 0.000 0.004 0.972
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3462 0.53238 0.000 0.828 0.016 0.076 0.080 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2586 0.54408 0.000 0.880 0.008 0.000 0.032 0.080
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5534 0.19752 0.000 0.328 0.064 0.568 0.040 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.5014 0.47993 0.004 0.016 0.164 0.124 0.692 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3755 0.65123 0.136 0.000 0.796 0.016 0.052 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.5737 0.48070 0.200 0.128 0.004 0.628 0.040 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.1983 0.77140 0.000 0.012 0.012 0.060 0.000 0.916
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.5187 0.67016 0.072 0.132 0.040 0.032 0.724 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.2767 0.64471 0.080 0.016 0.024 0.004 0.876 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4018 0.58983 0.768 0.004 0.116 0.000 0.112 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.3925 0.60232 0.000 0.028 0.016 0.784 0.012 0.160
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.5067 0.67228 0.072 0.096 0.052 0.036 0.744 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.2700 0.71244 0.000 0.156 0.004 0.000 0.004 0.836
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5273 0.30902 0.576 0.044 0.004 0.348 0.028 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1789 0.67266 0.924 0.000 0.032 0.000 0.044 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.4117 0.22642 0.000 0.464 0.004 0.000 0.004 0.528
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4326 0.60825 0.168 0.004 0.732 0.000 0.096 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.5641 0.52379 0.000 0.076 0.656 0.128 0.140 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.6012 0.65265 0.076 0.160 0.068 0.040 0.656 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1962 0.68629 0.924 0.028 0.020 0.000 0.028 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4263 0.56564 0.744 0.004 0.132 0.000 0.120 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 6 0.3490 0.73439 0.000 0.080 0.008 0.060 0.016 0.836
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6313 0.10164 0.436 0.252 0.008 0.300 0.004 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 6 0.3192 0.64653 0.000 0.216 0.004 0.000 0.004 0.776
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.4423 0.34766 0.000 0.020 0.016 0.320 0.000 0.644
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2143 0.68972 0.916 0.048 0.016 0.008 0.012 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4379 0.46341 0.000 0.752 0.008 0.020 0.052 0.168
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.3159 0.58235 0.000 0.020 0.152 0.008 0.820 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3769 0.22493 0.000 0.640 0.004 0.000 0.000 0.356
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6391 0.43229 0.000 0.588 0.056 0.200 0.020 0.136
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3993 -0.09444 0.000 0.520 0.004 0.000 0.000 0.476
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.5402 0.56759 0.000 0.020 0.656 0.220 0.016 0.088
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2554 0.67591 0.892 0.024 0.040 0.000 0.044 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4184 0.57410 0.752 0.004 0.124 0.000 0.120 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.3353 0.53698 0.032 0.004 0.160 0.000 0.804 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.3334 0.60456 0.132 0.008 0.040 0.000 0.820 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.1408 0.68912 0.944 0.036 0.020 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.5391 0.48722 0.020 0.700 0.068 0.152 0.060 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4516 0.57279 0.000 0.040 0.700 0.240 0.016 0.004
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4706 0.47521 0.000 0.740 0.012 0.140 0.088 0.020
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.4278 0.54194 0.000 0.056 0.096 0.788 0.052 0.008
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.1088 0.68933 0.960 0.024 0.016 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 6 0.0653 0.79634 0.000 0.012 0.004 0.004 0.000 0.980
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 5 0.5376 -0.01341 0.440 0.008 0.084 0.000 0.468 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.4972 0.67267 0.076 0.100 0.044 0.032 0.748 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4880 0.53652 0.256 0.008 0.652 0.000 0.084 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.3234 0.75376 0.004 0.012 0.084 0.032 0.012 0.856
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.5294 0.11945 0.000 0.056 0.012 0.480 0.004 0.448
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.3860 0.56270 0.008 0.096 0.000 0.788 0.000 0.108
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.1313 0.68951 0.952 0.028 0.016 0.000 0.004 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.5416 0.24949 0.340 0.008 0.104 0.000 0.548 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.4879 0.50938 0.684 0.184 0.004 0.124 0.004 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.3887 0.60013 0.780 0.004 0.112 0.000 0.104 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.5858 0.49848 0.000 0.080 0.592 0.276 0.040 0.012
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.6340 -0.00305 0.380 0.292 0.004 0.320 0.004 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 4 0.6492 -0.11372 0.000 0.084 0.400 0.448 0.040 0.028
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.5238 0.27909 0.012 0.536 0.000 0.396 0.008 0.048
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.4918 0.47917 0.016 0.684 0.004 0.236 0.008 0.052
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.5055 0.50126 0.000 0.072 0.104 0.724 0.096 0.004
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3589 0.61379 0.808 0.012 0.008 0.144 0.028 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.3842 0.60343 0.784 0.004 0.112 0.000 0.100 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.3385 0.66722 0.076 0.064 0.004 0.016 0.840 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4862 0.59901 0.000 0.076 0.692 0.212 0.008 0.012
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.3633 0.65410 0.124 0.000 0.808 0.016 0.052 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.5716 0.60703 0.000 0.156 0.084 0.112 0.648 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3811 0.58989 0.000 0.036 0.796 0.032 0.136 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.3220 0.61893 0.088 0.016 0.052 0.000 0.844 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 6 0.2739 0.76918 0.004 0.008 0.056 0.032 0.012 0.888
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.5035 0.52289 0.224 0.032 0.024 0.688 0.032 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.3993 -0.09037 0.000 0.520 0.004 0.000 0.000 0.476
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.5388 0.66772 0.068 0.132 0.052 0.036 0.712 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.6122 0.51366 0.616 0.132 0.028 0.024 0.196 0.004
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.2520 0.54086 0.000 0.872 0.000 0.012 0.008 0.108
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 6 0.3795 0.44066 0.000 0.364 0.004 0.000 0.000 0.632
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4942 0.24989 0.000 0.008 0.504 0.448 0.036 0.004
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.6717 0.36154 0.020 0.564 0.084 0.148 0.184 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.3798 0.66866 0.812 0.040 0.000 0.088 0.060 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.1218 0.68973 0.956 0.028 0.012 0.004 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.5200 0.67055 0.076 0.128 0.040 0.032 0.724 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.5562 0.36776 0.004 0.248 0.068 0.628 0.052 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.7340 0.13198 0.424 0.148 0.016 0.304 0.108 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.5463 0.61882 0.000 0.156 0.088 0.084 0.672 0.000
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#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 6 0.2624 0.71985 0.000 0.148 0.004 0.000 0.004 0.844
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.5600 0.25984 0.332 0.124 0.004 0.536 0.004 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.4925 0.32990 0.332 0.048 0.016 0.604 0.000 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.3894 0.53890 0.064 0.008 0.152 0.000 0.776 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 6 0.4594 0.07984 0.000 0.008 0.016 0.436 0.004 0.536
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.1693 0.68899 0.932 0.044 0.020 0.000 0.004 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.5590 0.61293 0.000 0.156 0.080 0.104 0.660 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.2465 0.63869 0.052 0.008 0.040 0.004 0.896 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.3449 0.52411 0.000 0.780 0.008 0.196 0.000 0.016
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.4170 0.63130 0.776 0.016 0.036 0.020 0.152 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.1686 0.68825 0.932 0.052 0.008 0.004 0.004 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.5291 0.01208 0.460 0.072 0.004 0.460 0.004 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.5356 0.44759 0.288 0.004 0.580 0.000 0.128 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.5937 0.35129 0.036 0.552 0.056 0.336 0.016 0.004
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 6 0.4858 0.06193 0.000 0.000 0.024 0.440 0.020 0.516
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.5369 0.33245 0.292 0.008 0.116 0.000 0.584 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.4520 0.53956 0.716 0.004 0.124 0.000 0.156 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.6405 0.55002 0.000 0.168 0.100 0.164 0.568 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.5831 0.50223 0.020 0.680 0.072 0.164 0.040 0.024
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.6109 0.48629 0.000 0.104 0.588 0.220 0.088 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.3797 0.59805 0.036 0.032 0.060 0.832 0.040 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.6948 0.46185 0.000 0.172 0.128 0.212 0.488 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.3961 0.01142 0.000 0.556 0.004 0.000 0.000 0.440
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.3758 0.52764 0.068 0.132 0.000 0.792 0.000 0.008
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 6 0.5720 0.56792 0.000 0.148 0.036 0.112 0.032 0.672
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.5910 0.59375 0.000 0.156 0.088 0.128 0.628 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.6804 -0.21124 0.068 0.420 0.060 0.044 0.408 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.4245 0.54451 0.000 0.056 0.104 0.788 0.044 0.008
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.5024 0.60815 0.000 0.076 0.716 0.128 0.080 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.2103 0.56940 0.000 0.916 0.000 0.020 0.024 0.040
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.5660 0.33749 0.576 0.112 0.012 0.292 0.008 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 6 0.4943 0.60830 0.012 0.016 0.212 0.044 0.012 0.704
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.6744 0.49263 0.144 0.280 0.040 0.028 0.508 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.3807 0.57803 0.000 0.068 0.060 0.820 0.048 0.004
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.1434 0.68859 0.948 0.024 0.020 0.000 0.008 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.6961 0.01536 0.000 0.400 0.072 0.208 0.320 0.000
#> A2007795-C728-4688-B199-AE89500011D2 6 0.1219 0.78502 0.000 0.048 0.004 0.000 0.000 0.948
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.4134 0.52979 0.004 0.136 0.000 0.764 0.004 0.092
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.6404 0.52998 0.000 0.168 0.080 0.196 0.556 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.5191 0.57768 0.000 0.076 0.660 0.236 0.016 0.012
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5029 0.62106 0.032 0.052 0.728 0.152 0.036 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.5742 0.60235 0.000 0.176 0.080 0.104 0.640 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 6 0.3589 0.60452 0.000 0.008 0.012 0.208 0.004 0.768
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.1167 0.78827 0.000 0.008 0.012 0.020 0.000 0.960
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.3858 0.64999 0.104 0.000 0.796 0.016 0.084 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4725 0.52140 0.016 0.728 0.004 0.068 0.008 0.176
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.5142 0.57793 0.000 0.072 0.664 0.236 0.016 0.012
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.2046 0.68043 0.916 0.032 0.008 0.044 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.4126 -0.10452 0.000 0.512 0.004 0.000 0.004 0.480
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.5630 0.65796 0.044 0.132 0.064 0.064 0.696 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.3698 0.40390 0.000 0.740 0.012 0.004 0.004 0.240
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.6570 0.38202 0.028 0.592 0.080 0.124 0.176 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.3843 0.60111 0.784 0.004 0.108 0.000 0.104 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5052 0.45263 0.640 0.064 0.000 0.272 0.024 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.6291 0.46725 0.000 0.124 0.104 0.644 0.076 0.052
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.2594 0.61768 0.004 0.008 0.028 0.900 0.036 0.024
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.0260 0.79556 0.000 0.008 0.000 0.000 0.000 0.992
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3272 0.63750 0.836 0.008 0.080 0.000 0.076 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.5011 0.61012 0.000 0.132 0.004 0.192 0.004 0.668
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.0777 0.79434 0.000 0.024 0.000 0.000 0.004 0.972
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.4917 0.30711 0.020 0.004 0.304 0.632 0.040 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4757 0.26378 0.620 0.024 0.332 0.004 0.020 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.5211 0.40491 0.256 0.008 0.116 0.000 0.620 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.3762 0.59372 0.028 0.108 0.008 0.820 0.032 0.004
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.6823 0.00631 0.108 0.360 0.000 0.436 0.008 0.088
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.6297 -0.01176 0.220 0.368 0.004 0.400 0.008 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.5964 0.17904 0.000 0.356 0.072 0.512 0.060 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.4445 0.52026 0.000 0.756 0.004 0.136 0.024 0.080
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.5019 0.37442 0.000 0.008 0.028 0.604 0.024 0.336
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.0665 0.79363 0.000 0.008 0.008 0.004 0.000 0.980
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3633 0.65410 0.124 0.000 0.808 0.016 0.052 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.5459 0.56813 0.000 0.028 0.652 0.228 0.016 0.076
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.3229 0.60707 0.088 0.024 0.008 0.852 0.028 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.6001 0.41145 0.008 0.084 0.096 0.628 0.184 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.2912 0.53643 0.012 0.000 0.172 0.000 0.816 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7114 0.30369 0.120 0.512 0.060 0.252 0.056 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.4222 -0.07366 0.000 0.516 0.004 0.008 0.000 0.472
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1003 0.68894 0.964 0.020 0.016 0.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.5532 0.61796 0.000 0.148 0.096 0.088 0.668 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.3510 0.64692 0.108 0.032 0.028 0.004 0.828 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4355 0.53473 0.052 0.000 0.152 0.756 0.040 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4330 0.55565 0.708 0.008 0.052 0.000 0.232 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.2974 0.76133 0.004 0.008 0.072 0.032 0.012 0.872
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.6003 0.04731 0.368 0.008 0.180 0.000 0.444 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.1461 0.68853 0.940 0.044 0.016 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.4150 0.34440 0.000 0.004 0.012 0.612 0.000 0.372
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.0260 0.79556 0.000 0.008 0.000 0.000 0.000 0.992
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.7875 0.15730 0.068 0.380 0.076 0.304 0.172 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.2979 0.68112 0.000 0.188 0.004 0.000 0.004 0.804
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1478 0.68848 0.944 0.020 0.004 0.000 0.032 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.5254 0.57943 0.000 0.076 0.660 0.232 0.016 0.016
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6470 0.26933 0.040 0.008 0.440 0.384 0.128 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5134 0.20656 0.524 0.088 0.000 0.388 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4450 0.09386 0.000 0.528 0.000 0.020 0.004 0.448
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.3310 0.61053 0.000 0.000 0.020 0.816 0.016 0.148
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.2776 0.66028 0.020 0.032 0.008 0.056 0.884 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 6 0.4198 0.40619 0.000 0.344 0.004 0.012 0.004 0.636
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.3860 0.60385 0.788 0.008 0.096 0.000 0.108 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3320 0.59210 0.000 0.000 0.772 0.016 0.212 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4895 0.21362 0.000 0.328 0.000 0.600 0.004 0.068
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4102 0.58228 0.760 0.004 0.116 0.000 0.120 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3420 0.61936 0.004 0.016 0.020 0.844 0.020 0.096
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3623 0.65661 0.068 0.028 0.028 0.036 0.840 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5311 0.56692 0.680 0.020 0.012 0.144 0.144 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4277 0.55814 0.000 0.020 0.700 0.260 0.016 0.004
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4174 0.66160 0.108 0.020 0.796 0.032 0.044 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4398 0.51276 0.000 0.764 0.008 0.136 0.024 0.068
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.6377 0.53661 0.000 0.196 0.080 0.164 0.560 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4450 0.55967 0.004 0.028 0.688 0.264 0.016 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.844 0.906 0.961 0.5014 0.499 0.499
#> 3 3 0.748 0.774 0.905 0.3096 0.754 0.547
#> 4 4 0.654 0.676 0.832 0.1386 0.801 0.495
#> 5 5 0.692 0.621 0.791 0.0621 0.860 0.526
#> 6 6 0.794 0.738 0.855 0.0431 0.912 0.616
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9569 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9591 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9569 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9591 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9569 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9569 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9591 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9591 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9591 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9591 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9569 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.8081 0.6607 0.248 0.752
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.8813 0.5925 0.700 0.300
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9569 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.2423 0.9232 0.040 0.960
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.9491 0.4397 0.368 0.632
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9569 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7299 0.7388 0.204 0.796
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9569 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.9569 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9569 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9569 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9591 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9591 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1184 0.9463 0.984 0.016
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9569 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9591 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9591 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9591 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9569 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9591 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9569 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9591 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9591 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9569 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9591 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.9591 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9591 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9591 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9591 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9569 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.9591 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9569 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9569 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.9591 1.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9569 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9591 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9569 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9569 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9569 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.7219 0.7443 0.200 0.800
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9591 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9591 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9591 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9591 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9591 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.9569 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.9710 0.3607 0.400 0.600
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9569 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.0376 0.9538 0.004 0.996
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9591 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9569 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9591 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9591 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9591 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9569 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9569 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.9569 0.000 1.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.9591 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.9591 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.7299 0.7380 0.796 0.204
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9591 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0672 0.9507 0.008 0.992
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9710 0.3516 0.600 0.400
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.1184 0.9442 0.016 0.984
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.9569 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9569 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9775 0.3304 0.412 0.588
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9591 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9591 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.9591 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.9710 0.3607 0.400 0.600
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.9591 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.9591 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.9591 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9591 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9569 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.9591 1.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9569 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.9591 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.3879 0.8914 0.924 0.076
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9569 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.9569 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.9710 0.3607 0.400 0.600
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.9569 0.000 1.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.9591 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.9591 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.9591 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.0000 0.9569 0.000 1.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.7219 0.7436 0.800 0.200
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.3114 0.9106 0.944 0.056
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.9591 1.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.9569 0.000 1.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.9591 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.0000 0.9569 0.000 1.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.0000 0.9591 1.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.0000 0.9569 0.000 1.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.9710 0.3607 0.400 0.600
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0000 0.9591 1.000 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.7139 0.7445 0.804 0.196
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.1184 0.9449 0.016 0.984
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.9569 0.000 1.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.9591 1.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.9569 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0000 0.9591 1.000 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.9591 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.9569 0.000 1.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.9591 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.9569 0.000 1.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.9569 0.000 1.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.9591 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.9591 1.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.7299 0.7306 0.204 0.796
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0000 0.9591 1.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.9591 1.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.9569 0.000 1.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.9881 0.2627 0.564 0.436
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.0000 0.9591 1.000 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0000 0.9569 0.000 1.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.0000 0.9569 0.000 1.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.0000 0.9591 1.000 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0000 0.9591 1.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0000 0.9569 0.000 1.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.0000 0.9569 0.000 1.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0000 0.9569 0.000 1.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0000 0.9569 0.000 1.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.0000 0.9569 0.000 1.000
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.9591 1.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.0000 0.9569 0.000 1.000
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.0000 0.9569 0.000 1.000
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0000 0.9569 0.000 1.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0000 0.9591 1.000 0.000
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0000 0.9591 1.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.0000 0.9591 1.000 0.000
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.0000 0.9591 1.000 0.000
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0000 0.9591 1.000 0.000
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.7219 0.7436 0.800 0.200
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.0000 0.9591 1.000 0.000
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 2 0.0672 0.9506 0.008 0.992
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.0000 0.9591 1.000 0.000
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.7299 0.7388 0.204 0.796
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0000 0.9569 0.000 1.000
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 1 0.0000 0.9591 1.000 0.000
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.0000 0.9569 0.000 1.000
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 1 0.5629 0.8295 0.868 0.132
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.7299 0.7380 0.796 0.204
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 2 0.0000 0.9569 0.000 1.000
#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.0000 0.9569 0.000 1.000
#> EF3D2659-7C4A-4003-A1B1-9A47A5388034 1 0.0000 0.9591 1.000 0.000
#> 09A7BAD6-4AB2-428A-B96C-BC3C298C4496 2 0.3584 0.8973 0.068 0.932
#> 02D46E43-75BB-4A0A-8A02-403C7FBFB112 2 0.0000 0.9569 0.000 1.000
#> 450A8523-03F4-4EF5-BA7A-E8E5329BE218 1 0.0000 0.9591 1.000 0.000
#> 6EA613FC-FDDD-4D89-B73E-FB2357D12651 2 0.0000 0.9569 0.000 1.000
#> 9B979DBE-6BAE-4631-A37D-3F57CD81D98E 2 0.0000 0.9569 0.000 1.000
#> 467BF85C-E6B2-4EE0-98E1-84341089B13F 1 0.0000 0.9591 1.000 0.000
#> BDCEEABA-4D55-4FDD-A180-C6FDF6EEF46F 2 0.0000 0.9569 0.000 1.000
#> 692D9E91-B8E7-421B-8165-B4797FB63EBF 1 0.9710 0.3516 0.600 0.400
#> BEE00B8C-02E2-4730-B3D3-28B1921BC61C 2 0.0000 0.9569 0.000 1.000
#> E2DD2578-89C1-4450-A2E9-081B97C3D9E1 2 0.0000 0.9569 0.000 1.000
#> 1D8EDBA0-FE22-4B74-941B-379636CEB488 1 1.0000 0.0429 0.500 0.500
#> 7C64AB4D-F135-42E8-B90C-B17382D7DEF2 2 0.0000 0.9569 0.000 1.000
#> 64FFE05F-5B89-4037-B39F-4D3F2632A763 2 0.0000 0.9569 0.000 1.000
#> FAB10659-FFDB-4D2F-BA6E-5DDFB9E62B30 1 0.0000 0.9591 1.000 0.000
#> F0CE637A-2087-4A54-9FAA-D30808D4D4DE 1 0.0000 0.9591 1.000 0.000
#> 8890CB3F-8F04-4F16-BDD9-F02558619CDF 2 0.0000 0.9569 0.000 1.000
#> 517E939F-D96F-4567-93EB-5F12AEF517B7 1 0.0000 0.9591 1.000 0.000
#> 9A30B1BE-CF22-42F4-8503-6FDB9FF6D7ED 2 0.0000 0.9569 0.000 1.000
#> 197C2AC3-7698-44D7-B4A9-18788AC6EF7E 1 0.0000 0.9591 1.000 0.000
#> 5A3A95CC-E103-4D0F-9EDC-212B5654C507 2 0.0000 0.9569 0.000 1.000
#> B225302F-E758-4056-B882-D965F01C22E0 2 0.0938 0.9474 0.012 0.988
#> 0079EF9C-5452-4C3C-9901-D19FA47ECCFA 1 0.0000 0.9591 1.000 0.000
#> 9691B578-C121-438B-8107-4C9584FC10C0 1 0.0000 0.9591 1.000 0.000
#> F0A740B2-74AD-4350-A09F-C215479D124C 2 0.2236 0.9267 0.036 0.964
#> F0A4A2A9-61EB-4D59-8738-0CF7F15738A5 2 0.0000 0.9569 0.000 1.000
#> BFF9A571-CEC4-4228-A32B-EB8A873FFA06 1 0.0000 0.9591 1.000 0.000
#> FFCCB1B7-6425-4550-8ED5-2FC22F1E64F1 2 0.0000 0.9569 0.000 1.000
#> 7163AF9E-6EF7-4FAC-AABC-B70E44DB71A7 1 0.9710 0.3192 0.600 0.400
#> FECFA772-F3C9-4588-9D5A-518419F193B5 2 0.0000 0.9569 0.000 1.000
#> B1D5CEFC-62AE-4906-85E7-6D41AF4F11E0 2 0.0000 0.9569 0.000 1.000
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#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.9591 1.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.7299 0.7388 0.204 0.796
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0000 0.9569 0.000 1.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 1 0.6247 0.8001 0.844 0.156
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.9569 0.000 1.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0000 0.9591 1.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.9591 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.9591 1.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0000 0.9569 0.000 1.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.9635 0.3831 0.612 0.388
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.9569 0.000 1.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.9569 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.9569 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.7139 0.7421 0.196 0.804
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.9775 0.3190 0.588 0.412
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.9591 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.9569 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.9591 1.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.0000 0.9591 1.000 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.9591 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.9569 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.9591 1.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.9591 1.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.2043 0.9328 0.968 0.032
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.9591 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.9569 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0000 0.9569 0.000 1.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.9591 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.9591 1.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.6048 0.8095 0.852 0.148
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.9569 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.9710 0.3607 0.400 0.600
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.7219 0.7388 0.800 0.200
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.9754 0.3400 0.408 0.592
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.9569 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.9569 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.9569 0.000 1.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.0376 0.9560 0.996 0.004
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.6801 0.7707 0.820 0.180
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.0000 0.9569 0.000 1.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.9591 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0000 0.9569 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.7299 0.7380 0.796 0.204
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.7219 0.7370 0.200 0.800
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.9591 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.9569 0.000 1.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.9591 1.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6973 0.7561 0.812 0.188
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.9569 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.9569 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.0000 0.9591 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.7299 0.7388 0.204 0.796
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.0000 0.9591 1.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.0000 0.9591 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.9569 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.9569 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.9591 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.9569 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9710 0.3607 0.400 0.600
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.9591 1.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9569 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.9591 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9569 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.9569 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.9591 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.9591 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.9569 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.9569 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.9569 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.9591 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.9569 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9569 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.9591 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.9591 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.9591 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.9569 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.9569 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.4562 0.8674 0.096 0.904
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9569 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.9569 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.9569 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.9569 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9591 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.7299 0.7388 0.204 0.796
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0000 0.9569 0.000 1.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.0000 0.9591 1.000 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.9591 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.8081 0.6608 0.248 0.752
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9569 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9591 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.9591 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.9591 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.9591 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9591 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9569 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9591 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9591 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9569 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9569 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9591 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9569 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9591 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.9286 0.4939 0.344 0.656
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9591 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1184 0.9463 0.984 0.016
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9569 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9569 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9591 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9569 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9591 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9591 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9569 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9591 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9569 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9591 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9591 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.8763 0.5732 0.704 0.296
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9591 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9569 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.8608 0.5970 0.716 0.284
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9591 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.95801 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5327 0.60607 0.272 0.000 0.728
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.95801 0.000 1.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.6045 0.46778 0.620 0.000 0.380
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.95801 0.000 1.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.95801 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.87650 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.6045 0.46778 0.620 0.000 0.380
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.87650 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1753 0.84094 0.952 0.000 0.048
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.95801 0.000 1.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0000 0.87650 1.000 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.87650 1.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.95801 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.4277 0.80660 0.016 0.852 0.132
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6111 0.38766 0.000 0.396 0.604
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.95801 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6111 0.38766 0.000 0.396 0.604
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.95801 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0237 0.95477 0.000 0.996 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3752 0.80266 0.000 0.856 0.144
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.95801 0.000 1.000 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.77746 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5291 0.61028 0.268 0.000 0.732
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6026 0.19720 0.624 0.000 0.376
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.95801 0.000 1.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6111 0.44348 0.604 0.000 0.396
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6204 0.08310 0.424 0.000 0.576
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.87650 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.95801 0.000 1.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.5835 0.31038 0.340 0.000 0.660
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.95801 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.87650 1.000 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.87650 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.95801 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.5291 0.61028 0.268 0.000 0.732
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.77746 0.000 0.000 1.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6111 0.44348 0.604 0.000 0.396
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.87650 1.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.87650 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.95801 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.87650 1.000 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.95801 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.95801 0.000 1.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.87650 1.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.95801 0.000 1.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.77746 0.000 0.000 1.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.95801 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.95801 0.000 1.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.95801 0.000 1.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6111 0.38766 0.000 0.396 0.604
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.87650 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.87650 1.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0000 0.77746 0.000 0.000 1.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.6062 0.46174 0.616 0.000 0.384
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.87650 1.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0592 0.94817 0.000 0.988 0.012
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3879 0.70777 0.000 0.152 0.848
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4887 0.67181 0.000 0.772 0.228
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.5678 0.52329 0.000 0.316 0.684
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.87650 1.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.95801 0.000 1.000 0.000
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#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.95801 0.000 1.000 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.77746 0.000 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.6111 0.44348 0.604 0.000 0.396
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.6267 0.21961 0.000 0.452 0.548
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0237 0.77681 0.004 0.000 0.996
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0000 0.95801 0.000 1.000 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0000 0.87650 1.000 0.000 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.6613 0.65004 0.188 0.740 0.072
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.6111 0.44348 0.604 0.000 0.396
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.95801 0.000 1.000 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.87650 1.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.0424 0.77407 0.008 0.000 0.992
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.95801 0.000 1.000 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.95801 0.000 1.000 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.77746 0.000 0.000 1.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.6111 0.38766 0.000 0.396 0.604
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5621 0.56150 0.308 0.000 0.692
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.77746 0.000 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.95801 0.000 1.000 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.95801 0.000 1.000 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4504 0.67422 0.196 0.000 0.804
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.95801 0.000 1.000 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.5948 0.45940 0.000 0.360 0.640
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.87650 1.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.95801 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0000 0.77746 0.000 0.000 1.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.95801 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.5216 0.62835 0.000 0.740 0.260
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.87650 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.87650 1.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.3551 0.82524 0.000 0.868 0.132
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0892 0.94103 0.000 0.980 0.020
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.95801 0.000 1.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.87650 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.95801 0.000 1.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.95801 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0237 0.77698 0.004 0.000 0.996
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6168 0.08523 0.588 0.000 0.412
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.6045 0.46778 0.620 0.000 0.380
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.5591 0.51257 0.000 0.696 0.304
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.95801 0.000 1.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.6019 0.57930 0.288 0.700 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.95801 0.000 1.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.95801 0.000 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.95801 0.000 1.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.95801 0.000 1.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5327 0.60607 0.272 0.000 0.728
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6111 0.38766 0.000 0.396 0.604
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8834 0.37349 0.224 0.580 0.196
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0000 0.77746 0.000 0.000 1.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.77746 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.5919 0.61304 0.724 0.016 0.260
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.95801 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.87650 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.77746 0.000 0.000 1.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.6045 0.46778 0.620 0.000 0.380
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6111 0.42875 0.396 0.000 0.604
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.87650 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.95801 0.000 1.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.6235 0.18241 0.564 0.000 0.436
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.87650 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.95801 0.000 1.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.95801 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6126 0.43667 0.600 0.000 0.400
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.95801 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.87650 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6111 0.38766 0.000 0.396 0.604
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4750 0.65769 0.216 0.000 0.784
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.87650 1.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.95801 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.95801 0.000 1.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.77746 0.000 0.000 1.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.95801 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.87650 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.77746 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.95801 0.000 1.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.87650 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.95801 0.000 1.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.0237 0.77673 0.004 0.000 0.996
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0424 0.87220 0.992 0.000 0.008
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3686 0.71525 0.000 0.140 0.860
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5216 0.61831 0.260 0.000 0.740
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.95801 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.77746 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5254 0.61435 0.264 0.000 0.736
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.6113 0.53755 0.284 0.080 0.636 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.1867 0.75838 0.000 0.072 0.000 0.928
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 3 0.4830 0.45399 0.392 0.000 0.608 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 3 0.4830 0.45399 0.392 0.000 0.608 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3764 0.60143 0.784 0.000 0.216 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5008 0.69292 0.732 0.040 0.000 0.228
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.1929 0.85916 0.940 0.036 0.000 0.024
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.4722 0.54030 0.008 0.692 0.000 0.300
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5793 0.41610 0.000 0.600 0.360 0.040
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4941 0.08370 0.000 0.564 0.000 0.436
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5026 0.48657 0.000 0.672 0.312 0.016
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4967 -0.00159 0.000 0.548 0.000 0.452
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.1637 0.74681 0.000 0.000 0.060 0.940
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.1637 0.74671 0.000 0.000 0.060 0.940
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.2125 0.76169 0.000 0.076 0.004 0.920
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2011 0.73293 0.000 0.080 0.920 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.6113 0.53755 0.284 0.080 0.636 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5628 0.53974 0.704 0.080 0.216 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2408 0.76182 0.000 0.896 0.000 0.104
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 3 0.4713 0.48880 0.360 0.000 0.640 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.3873 0.65610 0.228 0.000 0.772 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.3649 0.67547 0.204 0.000 0.796 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.6113 0.53755 0.284 0.080 0.636 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2011 0.73293 0.000 0.080 0.920 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 3 0.4713 0.48880 0.360 0.000 0.640 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.4134 0.53068 0.000 0.260 0.000 0.740
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0921 0.87467 0.972 0.000 0.000 0.028
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 36B2E208-FF01-4249-92C3-BE77D426691B 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.5137 0.57917 0.000 0.716 0.244 0.040
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0336 0.75551 0.008 0.000 0.992 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.4830 0.45399 0.392 0.000 0.608 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.0469 0.77671 0.000 0.000 0.012 0.988
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.5244 0.37586 0.000 0.600 0.388 0.012
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.4194 0.73621 0.000 0.228 0.008 0.764
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.4072 0.57170 0.000 0.748 0.252 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3172 0.72653 0.000 0.840 0.000 0.160
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4972 -0.07334 0.544 0.000 0.456 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.4679 0.50208 0.352 0.000 0.648 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.6334 0.46401 0.328 0.080 0.592 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2704 0.75597 0.000 0.876 0.000 0.124
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.2081 0.76301 0.000 0.916 0.000 0.084
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> 40424A8F-CE23-436B-8F65-4919F90F6691 3 0.4925 0.38036 0.428 0.000 0.572 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.3873 0.71830 0.772 0.000 0.000 0.228
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.5137 0.57917 0.000 0.716 0.244 0.040
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.4542 0.70749 0.752 0.020 0.000 0.228
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.4831 0.61677 0.000 0.752 0.208 0.040
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.1211 0.76888 0.000 0.040 0.000 0.960
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.0336 0.77821 0.000 0.008 0.000 0.992
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.4193 0.55865 0.000 0.732 0.268 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.4713 0.48880 0.360 0.000 0.640 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.5793 0.41610 0.000 0.600 0.360 0.040
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.5486 0.63613 0.200 0.080 0.720 0.000
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#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.7852 -0.10620 0.268 0.372 0.360 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0921 0.74849 0.000 0.028 0.972 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.2081 0.76301 0.000 0.916 0.000 0.084
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.2704 0.75597 0.000 0.876 0.000 0.124
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 3 0.4999 0.05996 0.000 0.000 0.508 0.492
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.4103 0.56906 0.000 0.744 0.256 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2197 0.73299 0.004 0.080 0.916 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.0000 0.77840 0.000 0.000 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.3539 0.76351 0.820 0.004 0.000 0.176
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.1837 0.73985 0.028 0.944 0.000 0.028
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 3 0.6489 0.33796 0.372 0.000 0.548 0.080
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.3172 0.70017 0.000 0.840 0.000 0.160
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.3545 0.68352 0.008 0.000 0.828 0.164
#> A2007795-C728-4688-B199-AE89500011D2 2 0.4564 0.46283 0.000 0.672 0.000 0.328
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.5619 0.48176 0.000 0.640 0.320 0.040
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.6299 0.47834 0.320 0.080 0.600 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.2530 0.75983 0.000 0.888 0.000 0.112
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.5371 0.64745 0.188 0.080 0.732 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0188 0.77851 0.000 0.004 0.000 0.996
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.5793 0.41610 0.000 0.600 0.360 0.040
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0336 0.75551 0.008 0.000 0.992 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.4250 0.52400 0.000 0.000 0.276 0.724
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0469 0.87993 0.988 0.012 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.3013 0.75869 0.000 0.888 0.032 0.080
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.2647 0.75691 0.000 0.880 0.000 0.120
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3528 0.68330 0.000 0.808 0.000 0.192
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4998 -0.14228 0.000 0.512 0.000 0.488
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.5126 0.10557 0.004 0.444 0.552 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6453 0.15528 0.560 0.080 0.360 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 3 0.4830 0.45399 0.392 0.000 0.608 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.6351 0.31185 0.000 0.588 0.080 0.332
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.4543 0.40762 0.000 0.324 0.000 0.676
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.7044 0.29885 0.164 0.276 0.000 0.560
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.4072 0.72192 0.000 0.252 0.000 0.748
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.2469 0.76107 0.000 0.892 0.000 0.108
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2647 0.75691 0.000 0.880 0.000 0.120
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.6158 0.52543 0.292 0.080 0.628 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.5366 0.54209 0.000 0.684 0.276 0.040
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0804 0.74244 0.000 0.980 0.008 0.012
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.4866 0.15402 0.000 0.404 0.596 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5723 0.48060 0.052 0.004 0.268 0.676
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.4830 0.45399 0.392 0.000 0.608 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.4606 0.53887 0.012 0.724 0.264 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2704 0.75597 0.000 0.876 0.000 0.124
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.4985 0.32942 0.468 0.000 0.532 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0336 0.88260 0.992 0.000 0.000 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2647 0.75691 0.000 0.880 0.000 0.120
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.6482 0.51660 0.152 0.000 0.640 0.208
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5793 0.41610 0.000 0.600 0.360 0.040
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6100 0.55136 0.272 0.084 0.644 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1109 0.87094 0.968 0.028 0.000 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0592 0.78016 0.000 0.016 0.000 0.984
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.75428 0.000 0.000 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0336 0.77821 0.000 0.008 0.000 0.992
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2011 0.73293 0.000 0.080 0.920 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4661 0.61636 0.000 0.348 0.000 0.652
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.88365 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.2011 0.76425 0.000 0.920 0.000 0.080
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.1867 0.74963 0.072 0.000 0.928 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0336 0.87938 0.992 0.000 0.008 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.4817 0.37434 0.000 0.612 0.388 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.6113 0.53755 0.284 0.080 0.636 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.3873 0.74245 0.000 0.228 0.000 0.772
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0336 0.75291 0.000 0.000 0.992 0.008
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.6298 0.53838 0.268 0.100 0.632 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3242 0.7215 0.216 0.000 0.784 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5620 -0.0946 0.000 0.316 0.068 0.604 0.012
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3724 0.7136 0.184 0.000 0.028 0.000 0.788
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.3582 0.6481 0.000 0.224 0.008 0.768 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0162 0.7176 0.000 0.996 0.000 0.004 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0510 0.8543 0.984 0.000 0.016 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4221 0.6561 0.236 0.000 0.032 0.000 0.732
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0693 0.8538 0.980 0.000 0.012 0.000 0.008
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2124 0.8128 0.916 0.000 0.028 0.000 0.056
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.3728 0.6506 0.000 0.244 0.008 0.748 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.6688 0.4753 0.488 0.000 0.180 0.320 0.012
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4696 0.7402 0.748 0.000 0.172 0.068 0.012
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3412 0.3741 0.008 0.000 0.172 0.812 0.008
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.3421 0.7043 0.000 0.008 0.788 0.204 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.4009 0.6377 0.000 0.312 0.004 0.684 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3210 0.7005 0.000 0.000 0.788 0.212 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.4009 0.6387 0.000 0.312 0.004 0.684 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.4087 0.6345 0.000 0.756 0.000 0.208 0.036
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3690 0.6381 0.000 0.764 0.000 0.224 0.012
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5454 -0.1253 0.000 0.332 0.036 0.608 0.024
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4114 0.4448 0.000 0.000 0.624 0.000 0.376
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3039 0.7367 0.192 0.000 0.808 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.4564 0.2005 0.388 0.000 0.600 0.004 0.008
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.4025 0.6459 0.000 0.292 0.008 0.700 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0404 0.8552 0.012 0.000 0.000 0.000 0.988
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0912 0.8535 0.012 0.000 0.016 0.000 0.972
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0898 0.8507 0.972 0.000 0.020 0.000 0.008
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4221 0.6424 0.000 0.236 0.032 0.732 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0404 0.8552 0.012 0.000 0.000 0.000 0.988
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2280 0.6179 0.000 0.880 0.000 0.120 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.2648 0.8035 0.848 0.000 0.152 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0404 0.8550 0.988 0.000 0.012 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1792 0.6595 0.000 0.916 0.000 0.084 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.3177 0.7271 0.208 0.000 0.792 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3395 0.6514 0.000 0.000 0.764 0.000 0.236
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0404 0.8552 0.012 0.000 0.000 0.000 0.988
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1270 0.8476 0.948 0.000 0.052 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1168 0.8440 0.960 0.000 0.032 0.000 0.008
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.3166 0.3703 0.000 0.112 0.020 0.856 0.012
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3523 0.8068 0.836 0.000 0.116 0.040 0.008
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2280 0.6176 0.000 0.880 0.000 0.120 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.3700 0.6504 0.000 0.240 0.008 0.752 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0290 0.8562 0.992 0.000 0.000 0.000 0.008
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.0794 0.8525 0.000 0.000 0.028 0.000 0.972
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.3752 0.2600 0.000 0.708 0.000 0.292 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0609 0.7051 0.000 0.980 0.000 0.020 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.3210 0.7005 0.000 0.000 0.788 0.212 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0693 0.8565 0.980 0.000 0.012 0.000 0.008
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1082 0.8467 0.964 0.000 0.028 0.000 0.008
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1041 0.8505 0.004 0.000 0.032 0.000 0.964
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.3412 0.7458 0.152 0.000 0.028 0.000 0.820
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0404 0.8564 0.988 0.000 0.012 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4523 0.6119 0.000 0.712 0.008 0.252 0.028
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3724 0.7134 0.000 0.000 0.788 0.184 0.028
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0162 0.7176 0.000 0.996 0.000 0.004 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.4059 0.3464 0.000 0.004 0.292 0.700 0.004
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0404 0.8564 0.988 0.000 0.012 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.4562 -0.3723 0.000 0.500 0.008 0.492 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.5048 -0.1433 0.492 0.000 0.032 0.000 0.476
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0404 0.8552 0.012 0.000 0.000 0.000 0.988
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.3816 0.6450 0.304 0.000 0.696 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 4 0.5888 0.5362 0.000 0.316 0.124 0.560 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.3878 0.6461 0.000 0.236 0.016 0.748 0.000
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#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.3544 0.7871 0.812 0.000 0.164 0.016 0.008
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 4 0.4435 0.6113 0.000 0.336 0.016 0.648 0.000
#> 93429F04-8404-4E8C-B654-9D2216BA432C 4 0.4660 0.1175 0.000 0.228 0.024 0.724 0.024
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.2763 0.8040 0.848 0.000 0.148 0.000 0.004
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.1082 0.8464 0.964 0.000 0.028 0.000 0.008
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 5 0.3910 0.6980 0.196 0.000 0.032 0.000 0.772
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.4138 0.4643 0.000 0.000 0.616 0.384 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.4025 0.6459 0.000 0.292 0.008 0.700 0.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.5831 0.6815 0.116 0.096 0.700 0.088 0.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.3970 0.6419 0.000 0.236 0.020 0.744 0.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.3242 0.7215 0.216 0.000 0.784 0.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 5 0.4031 0.7005 0.184 0.000 0.044 0.000 0.772
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 5 0.4687 0.5376 0.336 0.000 0.028 0.000 0.636
#> 6D711561-D549-44C7-885F-F3B846DB130C 4 0.4025 0.6459 0.000 0.292 0.008 0.700 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.6415 0.5546 0.556 0.000 0.172 0.260 0.012
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0162 0.7176 0.000 0.996 0.000 0.004 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0963 0.7123 0.000 0.964 0.000 0.036 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0880 0.7019 0.000 0.968 0.000 0.032 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.6472 0.5475 0.548 0.000 0.180 0.260 0.012
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.2664 0.8405 0.892 0.000 0.064 0.040 0.004
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.3413 0.7571 0.124 0.000 0.044 0.000 0.832
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.3671 0.6499 0.000 0.236 0.008 0.756 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.8565 1.000 0.000 0.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.0404 0.8547 0.000 0.000 0.012 0.000 0.988
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.0794 0.8525 0.000 0.000 0.028 0.000 0.972
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.3480 0.6360 0.000 0.752 0.000 0.248 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0794 0.8499 0.972 0.000 0.028 0.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0609 0.8555 0.980 0.000 0.020 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.4528 0.7462 0.756 0.000 0.172 0.064 0.008
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.4446 0.4833 0.400 0.000 0.592 0.000 0.008
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.5695 -0.2559 0.000 0.392 0.040 0.544 0.024
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 4 0.4108 0.6380 0.000 0.308 0.008 0.684 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.4404 0.6254 0.264 0.000 0.032 0.000 0.704
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.1300 0.8430 0.956 0.000 0.028 0.000 0.016
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.0609 0.8513 0.000 0.000 0.020 0.000 0.980
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.5285 0.4878 0.000 0.548 0.016 0.412 0.024
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.3922 0.6820 0.000 0.040 0.780 0.000 0.180
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.1522 0.7160 0.044 0.000 0.944 0.012 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.4060 0.3125 0.000 0.000 0.360 0.000 0.640
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.5690 0.5609 0.000 0.224 0.152 0.624 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.4816 -0.3615 0.000 0.500 0.008 0.484 0.008
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.0609 0.8513 0.000 0.000 0.020 0.000 0.980
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.3967 0.6803 0.008 0.020 0.000 0.200 0.772
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.4815 0.3205 0.000 0.008 0.304 0.660 0.028
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.3231 0.6781 0.004 0.000 0.800 0.000 0.196
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.3305 0.6436 0.000 0.776 0.000 0.224 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.2917 0.8195 0.868 0.000 0.108 0.012 0.012
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.7982 -0.1760 0.080 0.264 0.336 0.320 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.3280 0.7249 0.012 0.000 0.000 0.176 0.812
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.4536 0.6394 0.000 0.240 0.048 0.712 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0510 0.8561 0.984 0.000 0.016 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0771 0.8490 0.000 0.020 0.004 0.000 0.976
#> A2007795-C728-4688-B199-AE89500011D2 2 0.4452 -0.3624 0.000 0.500 0.004 0.496 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.5543 0.5742 0.000 0.224 0.136 0.640 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.0404 0.8547 0.000 0.000 0.012 0.000 0.988
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.3210 0.7005 0.000 0.000 0.788 0.212 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.2806 0.7485 0.152 0.004 0.844 0.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.0510 0.8532 0.000 0.000 0.016 0.000 0.984
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3878 0.6480 0.000 0.236 0.016 0.748 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.4088 0.6411 0.000 0.304 0.008 0.688 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.3280 0.7415 0.176 0.000 0.812 0.000 0.012
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4710 0.5550 0.000 0.616 0.008 0.364 0.012
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.3421 0.7043 0.000 0.008 0.788 0.204 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0404 0.8550 0.988 0.000 0.012 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0404 0.8547 0.000 0.000 0.012 0.000 0.988
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.7189 0.000 1.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.6750 0.1102 0.000 0.280 0.008 0.232 0.480
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0693 0.8538 0.980 0.000 0.012 0.000 0.008
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.2648 0.8038 0.848 0.000 0.152 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.4589 0.6417 0.000 0.292 0.008 0.680 0.020
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.4210 0.6375 0.000 0.224 0.036 0.740 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.4108 0.6396 0.000 0.308 0.008 0.684 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0798 0.8529 0.976 0.000 0.016 0.000 0.008
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.4009 0.6380 0.000 0.312 0.004 0.684 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.4101 0.6231 0.000 0.332 0.004 0.664 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.3803 0.7529 0.040 0.000 0.836 0.088 0.036
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.4196 0.4538 0.356 0.000 0.640 0.000 0.004
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.4104 0.6719 0.220 0.000 0.032 0.000 0.748
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.6327 0.3395 0.000 0.280 0.520 0.200 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5624 0.2349 0.016 0.096 0.180 0.696 0.012
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.7124 0.0498 0.052 0.184 0.180 0.572 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4574 -0.0511 0.000 0.576 0.000 0.412 0.012
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0510 0.7093 0.000 0.984 0.016 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.4046 0.6444 0.000 0.296 0.008 0.696 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.4108 0.6396 0.000 0.308 0.008 0.684 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3003 0.7387 0.188 0.000 0.812 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.3210 0.7005 0.000 0.000 0.788 0.212 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.4965 0.3310 0.016 0.012 0.384 0.588 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.6102 0.2936 0.000 0.000 0.200 0.232 0.568
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0794 0.8525 0.000 0.000 0.028 0.000 0.972
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.7609 -0.0204 0.008 0.264 0.032 0.288 0.408
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0290 0.7150 0.000 0.992 0.000 0.008 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0404 0.8550 0.988 0.000 0.012 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0404 0.8547 0.000 0.000 0.012 0.000 0.988
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.3535 0.7336 0.164 0.000 0.028 0.000 0.808
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.2953 0.7258 0.012 0.000 0.844 0.144 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1082 0.8464 0.964 0.000 0.028 0.000 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 4 0.4348 0.6288 0.000 0.316 0.016 0.668 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4909 0.2263 0.588 0.000 0.032 0.000 0.380
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0794 0.8541 0.972 0.000 0.028 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.4026 0.6498 0.000 0.244 0.020 0.736 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.4108 0.6396 0.000 0.308 0.008 0.684 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.2929 0.7353 0.008 0.000 0.000 0.152 0.840
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2648 0.5761 0.000 0.848 0.000 0.152 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0404 0.8550 0.988 0.000 0.012 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3421 0.7043 0.000 0.008 0.788 0.204 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3003 0.7387 0.188 0.000 0.812 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.3013 0.7948 0.832 0.000 0.160 0.008 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4675 0.4621 0.000 0.544 0.008 0.444 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.4210 0.6396 0.000 0.224 0.036 0.740 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0510 0.8547 0.000 0.000 0.016 0.000 0.984
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.5092 0.4183 0.000 0.508 0.016 0.464 0.012
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0798 0.8525 0.976 0.000 0.016 0.000 0.008
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3209 0.6885 0.008 0.000 0.812 0.000 0.180
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.5213 0.5857 0.000 0.284 0.076 0.640 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0992 0.8487 0.968 0.000 0.024 0.000 0.008
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.4795 0.6225 0.000 0.224 0.072 0.704 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.1522 0.8439 0.012 0.000 0.044 0.000 0.944
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1168 0.8484 0.960 0.000 0.032 0.000 0.008
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3210 0.7005 0.000 0.000 0.788 0.212 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3003 0.7387 0.188 0.000 0.812 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0162 0.7176 0.000 0.996 0.000 0.004 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0880 0.8467 0.000 0.000 0.032 0.000 0.968
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.1270 0.7364 0.052 0.000 0.948 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3634 0.56295 0.356 0.000 0.644 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3703 0.60512 0.000 0.004 0.004 0.688 0.000 0.304
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4222 0.67153 0.248 0.000 0.028 0.016 0.708 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0405 0.89120 0.000 0.000 0.004 0.008 0.000 0.988
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0914 0.84940 0.968 0.000 0.016 0.016 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4611 0.61496 0.280 0.000 0.036 0.020 0.664 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0146 0.85574 0.996 0.000 0.004 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0146 0.85574 0.996 0.000 0.004 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.0260 0.89101 0.000 0.000 0.008 0.000 0.000 0.992
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.0935 0.70090 0.032 0.000 0.004 0.964 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3817 0.48980 0.568 0.000 0.000 0.432 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2554 0.68567 0.000 0.000 0.048 0.876 0.000 0.076
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0935 0.80303 0.000 0.004 0.964 0.000 0.000 0.032
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.0692 0.88915 0.000 0.020 0.000 0.004 0.000 0.976
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0865 0.80232 0.000 0.000 0.964 0.000 0.000 0.036
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.0692 0.88915 0.000 0.020 0.000 0.004 0.000 0.976
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0146 0.91844 0.000 0.996 0.000 0.004 0.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0458 0.91084 0.000 0.984 0.000 0.016 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5048 0.55536 0.000 0.012 0.036 0.612 0.016 0.324
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4241 0.46111 0.004 0.000 0.628 0.020 0.348 0.000
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#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 6 0.3088 0.84071 0.000 0.064 0.020 0.032 0.016 0.868
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.0146 0.89113 0.000 0.000 0.004 0.000 0.000 0.996
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.0692 0.88906 0.000 0.020 0.004 0.000 0.000 0.976
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.1556 0.79854 0.080 0.000 0.920 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0937 0.80206 0.000 0.000 0.960 0.000 0.000 0.040
#> 4F501635-545A-479A-A95E-12C4AC30BA50 6 0.3528 0.59155 0.000 0.000 0.004 0.296 0.000 0.700
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.4499 0.44175 0.000 0.000 0.028 0.012 0.636 0.324
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.1059 0.86581 0.004 0.000 0.016 0.016 0.964 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.3011 0.64222 0.004 0.004 0.000 0.800 0.192 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0458 0.85403 0.984 0.000 0.016 0.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0260 0.86676 0.000 0.000 0.000 0.008 0.992 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2981 0.79719 0.116 0.000 0.020 0.016 0.848 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.2074 0.79494 0.004 0.000 0.912 0.048 0.000 0.036
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1959 0.82684 0.924 0.000 0.032 0.024 0.020 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.1686 0.86547 0.000 0.064 0.012 0.000 0.000 0.924
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.3499 0.72843 0.816 0.000 0.036 0.020 0.128 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0865 0.85027 0.964 0.000 0.000 0.036 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.0692 0.88719 0.000 0.000 0.004 0.020 0.000 0.976
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.0837 0.88938 0.000 0.020 0.004 0.004 0.000 0.972
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.4191 0.49315 0.000 0.000 0.040 0.284 0.676 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3868 0.00235 0.000 0.508 0.000 0.000 0.000 0.492
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0603 0.85285 0.980 0.000 0.016 0.004 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0935 0.80303 0.000 0.004 0.964 0.000 0.000 0.032
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.1675 0.79623 0.032 0.000 0.936 0.024 0.008 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.3464 0.65021 0.688 0.000 0.000 0.312 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.5117 0.49026 0.000 0.092 0.000 0.548 0.000 0.360
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.1958 0.84869 0.000 0.000 0.004 0.100 0.000 0.896
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0914 0.86622 0.000 0.000 0.016 0.016 0.968 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.4631 0.52924 0.000 0.052 0.000 0.596 0.000 0.352
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0547 0.85355 0.980 0.000 0.020 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0777 0.80253 0.000 0.000 0.972 0.004 0.024 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.2455 0.83796 0.000 0.012 0.004 0.112 0.000 0.872
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0146 0.85574 0.996 0.000 0.004 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 6 0.2431 0.81968 0.000 0.000 0.008 0.132 0.000 0.860
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.1806 0.85473 0.008 0.000 0.044 0.020 0.928 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2411 0.81997 0.900 0.000 0.032 0.044 0.024 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0865 0.80232 0.000 0.000 0.964 0.000 0.000 0.036
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.1007 0.80420 0.044 0.000 0.956 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0146 0.92286 0.000 0.996 0.000 0.000 0.000 0.004
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.2146 0.80586 0.000 0.000 0.116 0.004 0.880 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0972 0.80400 0.028 0.000 0.964 0.008 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.309 0.594 0.833 0.4807 0.499 0.499
#> 3 3 0.423 0.606 0.810 0.3510 0.690 0.456
#> 4 4 0.554 0.656 0.772 0.1382 0.772 0.441
#> 5 5 0.591 0.552 0.764 0.0640 0.857 0.528
#> 6 6 0.615 0.550 0.770 0.0144 0.984 0.924
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.81252 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0376 0.72869 0.996 0.004
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.81252 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.72829 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.81252 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.81252 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.9358 0.44000 0.648 0.352
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.72829 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.6623 0.64273 0.828 0.172
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.72829 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.81252 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.9983 0.18582 0.524 0.476
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.9977 0.20170 0.528 0.472
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.81252 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.9661 0.30370 0.392 0.608
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.9775 0.29665 0.588 0.412
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.81252 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.9866 0.24330 0.568 0.432
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.81252 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.8327 0.51830 0.264 0.736
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.9933 0.06090 0.452 0.548
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.8016 0.56258 0.244 0.756
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.8713 0.50915 0.708 0.292
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0376 0.72869 0.996 0.004
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.9922 0.15764 0.552 0.448
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.81252 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0938 0.72570 0.988 0.012
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.72829 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.72829 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.3431 0.75984 0.064 0.936
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.6247 0.64529 0.844 0.156
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.81252 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0376 0.72869 0.996 0.004
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0376 0.72869 0.996 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.81252 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0376 0.72869 0.996 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.9087 0.45968 0.676 0.324
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.8327 0.54153 0.736 0.264
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.6973 0.63123 0.812 0.188
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.72829 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.81252 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.8813 0.48580 0.700 0.300
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.81252 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.81252 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.9833 0.30998 0.576 0.424
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.7219 0.61786 0.200 0.800
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.6623 0.63422 0.828 0.172
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.81252 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0376 0.81065 0.004 0.996
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.81252 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.9460 0.29836 0.364 0.636
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.5294 0.68003 0.880 0.120
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.72829 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.72829 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.72829 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.6973 0.63123 0.812 0.188
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.7883 0.57175 0.236 0.764
#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.9286 0.42888 0.656 0.344
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.9775 0.27255 0.412 0.588
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.9754 0.28205 0.408 0.592
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.9427 0.42983 0.640 0.360
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.81252 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.72829 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.8207 0.54945 0.744 0.256
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0376 0.72869 0.996 0.004
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.4939 0.72395 0.108 0.892
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.81252 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0376 0.81017 0.004 0.996
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.9427 0.42983 0.640 0.360
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.72829 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.9833 0.30998 0.576 0.424
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.6973 0.63123 0.812 0.188
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.8813 0.49474 0.300 0.700
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9963 0.22014 0.536 0.464
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.9087 0.45543 0.324 0.676
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.81252 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.81252 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9754 0.28205 0.408 0.592
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.5842 0.66813 0.860 0.140
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2778 0.71529 0.952 0.048
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.8207 0.54945 0.744 0.256
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.9460 0.39488 0.636 0.364
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#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.7745 0.57854 0.228 0.772
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.2043 0.79111 0.032 0.968
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.81252 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0672 0.72791 0.992 0.008
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.9970 0.04123 0.468 0.532
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8763 0.41632 0.296 0.704
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.9909 0.19151 0.444 0.556
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.72829 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.8327 0.53215 0.264 0.736
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.81252 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.9393 0.43348 0.644 0.356
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.8909 0.48593 0.692 0.308
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.72829 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.8861 0.53352 0.696 0.304
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.72829 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.81252 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.72829 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.9815 0.31813 0.580 0.420
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.81252 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.81252 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.9944 0.14862 0.456 0.544
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.81252 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.72829 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.9460 0.39477 0.636 0.364
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.1414 0.72495 0.980 0.020
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.8713 0.53245 0.708 0.292
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.81252 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.81252 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.8713 0.50915 0.708 0.292
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.81252 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0376 0.72869 0.996 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.6623 0.63337 0.828 0.172
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.81252 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.72829 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.81252 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.1184 0.72523 0.984 0.016
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2423 0.71784 0.960 0.040
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9460 0.39600 0.636 0.364
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0376 0.72869 0.996 0.004
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.7528 0.55611 0.216 0.784
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.8813 0.49779 0.700 0.300
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0376 0.72869 0.996 0.004
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.8686 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.2356 0.6738 0.928 0.000 0.072
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6062 0.6532 0.016 0.708 0.276
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.6244 -0.1239 0.560 0.000 0.440
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.2356 0.8462 0.000 0.928 0.072
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.8686 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.3851 0.6707 0.860 0.136 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3192 0.6304 0.888 0.000 0.112
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.7042 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0747 0.6991 0.984 0.000 0.016
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.2356 0.8486 0.000 0.928 0.072
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.8556 0.4411 0.604 0.164 0.232
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.8556 0.4411 0.604 0.164 0.232
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.8686 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.6181 0.6464 0.072 0.156 0.772
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.5024 0.4997 0.004 0.220 0.776
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.8686 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.2772 0.6625 0.004 0.080 0.916
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.8686 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 3 0.6511 0.6324 0.072 0.180 0.748
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 3 0.7308 0.5811 0.056 0.296 0.648
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.6119 0.6424 0.064 0.164 0.772
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2165 0.7003 0.064 0.000 0.936
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3879 0.6457 0.848 0.000 0.152
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.6252 0.6534 0.084 0.144 0.772
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2066 0.8524 0.000 0.940 0.060
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6307 -0.2328 0.512 0.000 0.488
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6299 0.3091 0.476 0.000 0.524
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.7042 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.1337 0.8603 0.016 0.972 0.012
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.6225 0.3942 0.432 0.000 0.568
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0237 0.8685 0.000 0.996 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.1289 0.7022 0.968 0.000 0.032
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0237 0.7043 0.996 0.000 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.8686 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.2356 0.6738 0.928 0.000 0.072
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0592 0.6807 0.012 0.000 0.988
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 3 0.6008 0.4887 0.372 0.000 0.628
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0424 0.7044 0.992 0.000 0.008
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0747 0.6991 0.984 0.000 0.016
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.8686 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 3 0.7339 0.6079 0.148 0.144 0.708
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.8686 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.8686 0.000 1.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4634 0.6516 0.824 0.164 0.012
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4629 0.6952 0.004 0.808 0.188
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.5497 0.5224 0.292 0.000 0.708
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.8686 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1031 0.8636 0.000 0.976 0.024
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0237 0.8671 0.000 0.996 0.004
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6154 -0.0755 0.000 0.408 0.592
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.7042 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0747 0.6991 0.984 0.000 0.016
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.6235 0.2945 0.436 0.000 0.564
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.3192 0.6397 0.888 0.000 0.112
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.7042 1.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 3 0.6295 0.6367 0.072 0.164 0.764
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0475 0.6812 0.004 0.004 0.992
#> F043185A-D4D2-4503-93FA-A7B7DA684290 3 0.7218 0.5189 0.052 0.296 0.652
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.2846 0.7009 0.056 0.020 0.924
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.3851 0.6702 0.860 0.136 0.004
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3412 0.7599 0.000 0.876 0.124
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.6244 -0.1007 0.560 0.000 0.440
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.6225 0.3942 0.432 0.000 0.568
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.2356 0.6738 0.928 0.000 0.072
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0892 0.8635 0.000 0.980 0.020
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.5216 0.6776 0.000 0.740 0.260
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.2846 0.8501 0.020 0.924 0.056
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3573 0.6763 0.876 0.120 0.004
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.6291 -0.1961 0.532 0.000 0.468
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.4634 0.6516 0.824 0.164 0.012
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.7042 1.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.6140 0.0515 0.000 0.404 0.596
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.8689 0.4207 0.588 0.164 0.248
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.5733 0.3171 0.000 0.324 0.676
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.1411 0.8609 0.000 0.964 0.036
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.2703 0.8514 0.016 0.928 0.056
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.2879 0.7007 0.052 0.024 0.924
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1620 0.7038 0.964 0.012 0.024
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.7042 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.6168 0.4279 0.412 0.000 0.588
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4834 0.5742 0.004 0.204 0.792
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.5882 0.4375 0.652 0.000 0.348
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.5237 0.6736 0.056 0.120 0.824
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.4931 0.5212 0.232 0.000 0.768
#> E435C03F-0277-49C1-83EF-19452082723E 3 0.6299 0.3091 0.476 0.000 0.524
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.8686 0.000 1.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.8556 0.4411 0.604 0.164 0.232
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.8686 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 3 0.4702 0.6480 0.212 0.000 0.788
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.8914 0.2794 0.556 0.164 0.280
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0237 0.8680 0.000 0.996 0.004
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.3752 0.7371 0.000 0.856 0.144
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.1585 0.6781 0.028 0.008 0.964
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.5757 0.6618 0.056 0.152 0.792
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.4235 0.5611 0.824 0.000 0.176
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.4634 0.6516 0.824 0.164 0.012
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 3 0.4702 0.6480 0.212 0.000 0.788
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.1964 0.7000 0.056 0.000 0.944
#> 60A51C36-7423-4C84-8034-325DE57046BE 3 0.7126 0.6169 0.116 0.164 0.720
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.2261 0.7001 0.068 0.000 0.932
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.7042 1.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.8686 0.000 1.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.6192 0.1998 0.420 0.000 0.580
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.7559 0.4547 0.056 0.608 0.336
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.4931 0.5212 0.232 0.000 0.768
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.2356 0.8462 0.000 0.928 0.072
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0829 0.6806 0.004 0.012 0.984
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.8206 0.4871 0.640 0.164 0.196
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 3 0.8454 0.3309 0.432 0.088 0.480
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.4179 0.6898 0.072 0.052 0.876
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.3941 0.7319 0.000 0.844 0.156
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0747 0.6991 0.984 0.000 0.016
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.8686 0.000 1.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 3 0.5634 0.6607 0.056 0.144 0.800
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.6291 0.2257 0.468 0.000 0.532
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.7417 0.4744 0.056 0.632 0.312
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.2356 0.6738 0.928 0.000 0.072
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.8686 0.000 1.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 3 0.7831 0.2460 0.056 0.404 0.540
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.2356 0.6738 0.928 0.000 0.072
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.6309 -0.2508 0.504 0.000 0.496
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 3 0.6295 0.6367 0.072 0.164 0.764
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 3 0.1964 0.7000 0.056 0.000 0.944
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.2651 0.6970 0.928 0.060 0.012
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.3752 0.7371 0.000 0.856 0.144
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.7515 0.5394 0.680 0.220 0.100
#> FE330797-5A40-45A8-98DF-43A33369E90F 3 0.5823 0.6600 0.064 0.144 0.792
#> DAD951A3-C22E-42F0-BB02-854413DDC351 3 0.7565 0.5822 0.084 0.256 0.660
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.5291 0.6688 0.000 0.732 0.268
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.6180 0.2411 0.416 0.000 0.584
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.2356 0.6738 0.928 0.000 0.072
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.1337 0.8603 0.016 0.972 0.012
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#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3030 0.6619 0.004 0.092 0.904
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.5327 0.4731 0.272 0.000 0.728
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4925 0.6640 0.844 0.076 0.080
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1529 0.8595 0.000 0.960 0.040
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.4702 0.7390 0.000 0.788 0.212
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.2261 0.7001 0.068 0.000 0.932
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.8686 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.7042 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4974 0.5174 0.236 0.000 0.764
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2703 0.8473 0.016 0.928 0.056
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0747 0.6991 0.984 0.000 0.016
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.6284 0.6215 0.016 0.680 0.304
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.5363 0.5829 0.276 0.000 0.724
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.5098 0.6181 0.248 0.000 0.752
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2845 0.6643 0.012 0.068 0.920
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.4504 0.6170 0.804 0.000 0.196
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2486 0.8307 0.060 0.932 0.008
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.2261 0.7001 0.068 0.000 0.932
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.6180 0.2028 0.416 0.000 0.584
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.1940 0.80412 0.924 0.000 0.076 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.1890 0.73528 0.000 0.056 0.008 0.936
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3610 0.66291 0.800 0.000 0.200 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.3583 0.82018 0.000 0.816 0.004 0.180
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4989 0.36141 0.472 0.000 0.000 0.528
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5535 0.41365 0.656 0.000 0.304 0.040
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0707 0.82118 0.980 0.000 0.020 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.3751 0.81255 0.000 0.800 0.004 0.196
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.3311 0.75586 0.172 0.000 0.000 0.828
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.3801 0.74195 0.220 0.000 0.000 0.780
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.1302 0.71968 0.000 0.000 0.044 0.956
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.5610 0.56526 0.000 0.176 0.720 0.104
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0469 0.88516 0.000 0.988 0.000 0.012
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4095 0.64461 0.000 0.024 0.804 0.172
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0469 0.88516 0.000 0.988 0.000 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.5936 0.13063 0.004 0.040 0.352 0.604
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7707 -0.14635 0.004 0.188 0.396 0.412
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4994 -0.24241 0.000 0.000 0.480 0.520
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.1867 0.69578 0.000 0.000 0.928 0.072
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3933 0.70064 0.792 0.000 0.200 0.008
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.6332 -0.15463 0.060 0.000 0.452 0.488
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3208 0.83767 0.000 0.848 0.004 0.148
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 3 0.6028 0.43423 0.364 0.000 0.584 0.052
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6028 0.43423 0.364 0.000 0.584 0.052
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.3266 0.71891 0.000 0.168 0.000 0.832
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.6136 0.44482 0.356 0.000 0.584 0.060
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0188 0.88547 0.000 0.996 0.000 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.4720 0.67611 0.264 0.000 0.016 0.720
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3486 0.59163 0.812 0.000 0.000 0.188
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1211 0.87438 0.000 0.960 0.000 0.040
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.1940 0.80412 0.924 0.000 0.076 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2469 0.68818 0.000 0.000 0.892 0.108
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 3 0.7058 0.48710 0.344 0.000 0.520 0.136
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 4 0.5000 0.14981 0.496 0.000 0.000 0.504
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.2011 0.86554 0.000 0.920 0.000 0.080
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.4724 0.74391 0.112 0.000 0.096 0.792
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0469 0.88516 0.000 0.988 0.000 0.012
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2345 0.85764 0.000 0.900 0.000 0.100
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.6522 0.66914 0.224 0.000 0.144 0.632
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0895 0.87684 0.000 0.976 0.020 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.2670 0.68487 0.040 0.000 0.908 0.052
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0469 0.88421 0.000 0.988 0.000 0.012
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.7193 0.06109 0.000 0.340 0.508 0.152
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1489 0.80682 0.952 0.000 0.004 0.044
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.4898 0.25196 0.416 0.000 0.584 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.6155 0.35211 0.412 0.000 0.536 0.052
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0592 0.81829 0.984 0.000 0.000 0.016
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.4697 0.21102 0.000 0.000 0.356 0.644
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.2408 0.68410 0.000 0.000 0.896 0.104
#> F043185A-D4D2-4503-93FA-A7B7DA684290 3 0.5590 0.59331 0.000 0.244 0.692 0.064
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.4485 0.66219 0.000 0.012 0.740 0.248
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4992 -0.28921 0.524 0.000 0.000 0.476
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0336 0.88527 0.000 0.992 0.000 0.008
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.7659 0.33049 0.296 0.000 0.460 0.244
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.6028 0.43870 0.364 0.000 0.584 0.052
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1807 0.81245 0.940 0.000 0.052 0.008
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2988 0.85532 0.000 0.876 0.012 0.112
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.4728 0.78109 0.000 0.752 0.032 0.216
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.2408 0.73784 0.000 0.104 0.000 0.896
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4454 0.30525 0.692 0.000 0.000 0.308
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4328 0.59825 0.748 0.000 0.244 0.008
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4103 0.72336 0.256 0.000 0.000 0.744
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.5735 0.19715 0.000 0.392 0.576 0.032
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4018 0.74208 0.224 0.000 0.004 0.772
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.5947 0.36614 0.000 0.312 0.628 0.060
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4188 0.77530 0.000 0.752 0.004 0.244
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.2530 0.73601 0.000 0.112 0.000 0.888
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.4589 0.69402 0.000 0.048 0.784 0.168
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 4 0.4989 0.22838 0.472 0.000 0.000 0.528
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.6234 0.45440 0.348 0.000 0.584 0.068
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4245 0.59403 0.000 0.196 0.784 0.020
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.5161 0.34852 0.592 0.000 0.400 0.008
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.4564 0.49369 0.000 0.000 0.672 0.328
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3215 0.68344 0.032 0.000 0.876 0.092
#> E435C03F-0277-49C1-83EF-19452082723E 3 0.6148 0.35420 0.408 0.000 0.540 0.052
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2011 0.86501 0.000 0.920 0.000 0.080
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.2704 0.76565 0.124 0.000 0.000 0.876
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 3 0.5744 0.55974 0.256 0.000 0.676 0.068
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.5380 0.73144 0.136 0.000 0.120 0.744
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.3219 0.75907 0.000 0.836 0.000 0.164
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.2101 0.86201 0.000 0.928 0.060 0.012
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.3801 0.64206 0.000 0.000 0.780 0.220
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.6458 0.42610 0.000 0.072 0.520 0.408
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.6213 -0.27870 0.484 0.000 0.464 0.052
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.4103 0.72336 0.256 0.000 0.000 0.744
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 3 0.6098 0.49246 0.316 0.000 0.616 0.068
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.4830 0.49355 0.000 0.000 0.608 0.392
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.4535 0.76206 0.112 0.000 0.084 0.804
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.3450 0.70091 0.008 0.000 0.836 0.156
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0336 0.82399 0.992 0.000 0.000 0.008
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.2345 0.85764 0.000 0.900 0.000 0.100
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.3710 0.57528 0.192 0.000 0.804 0.004
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.6714 0.52646 0.000 0.540 0.100 0.360
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.1022 0.66630 0.032 0.000 0.968 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.3569 0.81631 0.000 0.804 0.000 0.196
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.2647 0.68642 0.000 0.000 0.880 0.120
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.3444 0.75628 0.184 0.000 0.000 0.816
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 3 0.8893 0.35322 0.356 0.180 0.392 0.072
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.3801 0.51886 0.000 0.000 0.220 0.780
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.2704 0.80928 0.000 0.876 0.124 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.1211 0.80733 0.960 0.000 0.000 0.040
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 4 0.5000 -0.28397 0.000 0.000 0.496 0.504
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.4103 0.64566 0.744 0.000 0.256 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.6341 0.54446 0.000 0.652 0.212 0.136
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.1557 0.81262 0.944 0.000 0.056 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 3 0.7199 0.51454 0.000 0.216 0.552 0.232
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.1940 0.80412 0.924 0.000 0.076 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 3 0.6028 0.43423 0.364 0.000 0.584 0.052
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.4891 0.35832 0.012 0.000 0.308 0.680
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 3 0.3266 0.69906 0.000 0.000 0.832 0.168
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 4 0.4356 0.68808 0.292 0.000 0.000 0.708
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.8521 -0.04211 0.404 0.028 0.284 0.284
#> FE330797-5A40-45A8-98DF-43A33369E90F 3 0.5353 0.35125 0.012 0.000 0.556 0.432
#> DAD951A3-C22E-42F0-BB02-854413DDC351 4 0.2408 0.74245 0.000 0.104 0.000 0.896
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.3907 0.82018 0.000 0.828 0.032 0.140
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.4522 0.46249 0.320 0.000 0.680 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.2271 0.80180 0.916 0.000 0.076 0.008
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.3266 0.71960 0.000 0.168 0.000 0.832
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3668 0.81671 0.000 0.808 0.004 0.188
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0188 0.88525 0.000 0.996 0.000 0.004
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0707 0.88448 0.000 0.980 0.000 0.020
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.4995 0.74363 0.000 0.720 0.032 0.248
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.4833 0.77374 0.000 0.740 0.032 0.228
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.3356 0.59025 0.000 0.000 0.176 0.824
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.1940 0.86691 0.000 0.924 0.000 0.076
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 3 0.2892 0.68920 0.036 0.000 0.896 0.068
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 3 0.6028 0.43423 0.364 0.000 0.584 0.052
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 3 0.6028 0.43423 0.364 0.000 0.584 0.052
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#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.3217 0.73045 0.128 0.000 0.012 0.860
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5526 0.10956 0.564 0.000 0.020 0.416
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2081 0.86464 0.000 0.916 0.000 0.084
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0524 0.82407 0.988 0.000 0.008 0.004
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.4500 0.67634 0.316 0.000 0.000 0.684
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4977 0.23341 0.000 0.540 0.000 0.460
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.4992 0.33875 0.000 0.000 0.524 0.476
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.88506 0.000 1.000 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.6457 0.24687 0.604 0.000 0.296 0.100
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4379 0.60312 0.000 0.172 0.792 0.036
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3160 0.64666 0.108 0.000 0.872 0.020
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.3837 0.72677 0.224 0.000 0.000 0.776
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1867 0.86404 0.000 0.928 0.000 0.072
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.4993 0.74527 0.000 0.712 0.028 0.260
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.2124 0.69475 0.008 0.000 0.924 0.068
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.1940 0.85815 0.000 0.924 0.000 0.076
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0188 0.82470 0.996 0.000 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2411 0.67962 0.040 0.000 0.920 0.040
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.3172 0.72335 0.000 0.160 0.000 0.840
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.82526 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2814 0.69584 0.000 0.132 0.000 0.868
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.5220 0.65363 0.156 0.000 0.752 0.092
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.7414 0.30466 0.180 0.000 0.480 0.340
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4121 0.65097 0.000 0.020 0.796 0.184
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.4295 0.63797 0.752 0.000 0.240 0.008
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4916 0.22691 0.000 0.576 0.000 0.424
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.3498 0.70003 0.008 0.000 0.832 0.160
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.3852 0.58395 0.180 0.000 0.808 0.012
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4278 0.14695 0.452 0.000 0.548 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4313 0.46073 0.000 0.000 0.008 0.636 0.356
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3940 0.49939 0.768 0.000 0.208 0.016 0.008
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.3885 0.78157 0.000 0.784 0.000 0.176 0.040
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4354 0.14805 0.624 0.000 0.008 0.368 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4957 0.35451 0.636 0.000 0.328 0.016 0.020
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0566 0.67386 0.984 0.000 0.012 0.004 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4289 0.76555 0.000 0.760 0.000 0.176 0.064
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.4177 0.75230 0.164 0.000 0.000 0.772 0.064
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.2929 0.75553 0.180 0.000 0.000 0.820 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.3210 0.54556 0.000 0.000 0.000 0.212 0.788
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.5456 0.21200 0.000 0.028 0.592 0.028 0.352
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0404 0.88553 0.000 0.988 0.000 0.012 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6066 0.28713 0.000 0.004 0.592 0.180 0.224
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0510 0.88536 0.000 0.984 0.000 0.016 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.3289 0.58769 0.000 0.008 0.004 0.172 0.816
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.8131 0.15471 0.000 0.216 0.180 0.428 0.176
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.1851 0.62218 0.000 0.000 0.000 0.088 0.912
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4074 0.39864 0.000 0.000 0.364 0.000 0.636
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4722 0.23614 0.368 0.000 0.608 0.024 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.6099 0.46374 0.016 0.000 0.168 0.196 0.620
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3958 0.74888 0.000 0.780 0.000 0.044 0.176
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 3 0.7163 0.17675 0.324 0.000 0.388 0.016 0.272
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.7163 0.17675 0.324 0.000 0.388 0.016 0.272
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.0794 0.76119 0.000 0.028 0.000 0.972 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.7163 0.17675 0.324 0.000 0.388 0.016 0.272
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0162 0.88633 0.000 0.996 0.000 0.000 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.5052 0.70152 0.200 0.000 0.008 0.708 0.084
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3109 0.49682 0.800 0.000 0.000 0.200 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0963 0.87532 0.000 0.964 0.000 0.036 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4268 0.15903 0.444 0.000 0.556 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.3561 0.51611 0.000 0.000 0.260 0.000 0.740
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.6154 0.29747 0.144 0.000 0.236 0.016 0.604
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5406 -0.15773 0.480 0.000 0.000 0.464 0.056
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.3421 0.80525 0.016 0.816 0.004 0.164 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.5070 0.72495 0.156 0.000 0.020 0.732 0.092
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0290 0.88562 0.000 0.992 0.000 0.008 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3242 0.77768 0.000 0.784 0.000 0.216 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.5209 0.69739 0.172 0.000 0.116 0.704 0.008
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0671 0.87833 0.000 0.980 0.016 0.000 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.6200 0.30321 0.180 0.000 0.540 0.000 0.280
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0510 0.88357 0.000 0.984 0.000 0.000 0.016
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6769 0.30841 0.000 0.192 0.592 0.152 0.064
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0992 0.66502 0.968 0.000 0.008 0.024 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.6641 0.13474 0.352 0.000 0.448 0.004 0.196
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.7155 0.14256 0.348 0.000 0.376 0.016 0.260
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0510 0.67070 0.984 0.000 0.000 0.016 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.2732 0.58434 0.000 0.000 0.000 0.160 0.840
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4341 0.17344 0.000 0.000 0.592 0.004 0.404
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.6712 0.13796 0.000 0.532 0.168 0.024 0.276
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.0162 0.63162 0.000 0.000 0.000 0.004 0.996
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.3966 0.17581 0.664 0.000 0.000 0.336 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.8573 -0.00705 0.296 0.000 0.232 0.252 0.220
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.6685 0.01269 0.448 0.000 0.388 0.016 0.148
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.3909 0.47957 0.760 0.000 0.216 0.024 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.4180 0.77946 0.000 0.768 0.028 0.192 0.012
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 5 0.4275 0.44584 0.000 0.284 0.000 0.020 0.696
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.0771 0.76201 0.000 0.020 0.000 0.976 0.004
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3366 0.47535 0.784 0.000 0.004 0.212 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4301 0.48261 0.740 0.000 0.228 0.016 0.016
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4367 0.49810 0.416 0.000 0.004 0.580 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 5 0.5327 0.46016 0.000 0.216 0.120 0.000 0.664
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.2389 0.77589 0.116 0.000 0.004 0.880 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 5 0.6071 0.40717 0.000 0.180 0.192 0.012 0.616
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4766 0.70978 0.000 0.708 0.000 0.220 0.072
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.3216 0.75092 0.000 0.044 0.004 0.856 0.096
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.0451 0.63255 0.000 0.008 0.000 0.004 0.988
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 4 0.5546 0.24075 0.436 0.000 0.000 0.496 0.068
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.6937 -0.07163 0.192 0.000 0.388 0.016 0.404
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.6754 0.30955 0.000 0.132 0.596 0.072 0.200
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.6054 0.26305 0.328 0.000 0.564 0.092 0.016
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.4367 0.39784 0.000 0.000 0.372 0.008 0.620
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3274 0.34866 0.000 0.000 0.780 0.000 0.220
#> E435C03F-0277-49C1-83EF-19452082723E 3 0.7120 0.12974 0.364 0.000 0.376 0.016 0.244
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.3141 0.81463 0.000 0.832 0.016 0.152 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.3631 0.76463 0.104 0.000 0.000 0.824 0.072
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.4610 0.36475 0.000 0.000 0.388 0.016 0.596
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.6139 0.41339 0.260 0.000 0.184 0.556 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.3274 0.68641 0.000 0.780 0.000 0.220 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0404 0.88525 0.000 0.988 0.000 0.012 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 5 0.6368 0.17146 0.000 0.000 0.332 0.180 0.488
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.0740 0.63361 0.000 0.008 0.008 0.004 0.980
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.7517 0.15426 0.508 0.000 0.188 0.096 0.208
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.3752 0.68018 0.292 0.000 0.000 0.708 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.4610 0.36475 0.000 0.000 0.388 0.016 0.596
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 5 0.5791 0.39610 0.000 0.000 0.188 0.196 0.616
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.2244 0.77039 0.040 0.000 0.016 0.920 0.024
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0290 0.63079 0.000 0.000 0.008 0.000 0.992
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0865 0.66594 0.972 0.000 0.004 0.024 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.2966 0.79811 0.000 0.816 0.000 0.184 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.5131 0.41657 0.148 0.000 0.740 0.044 0.068
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 5 0.4450 0.56320 0.000 0.132 0.000 0.108 0.760
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.1671 0.44320 0.000 0.000 0.924 0.000 0.076
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.3596 0.76900 0.000 0.776 0.000 0.212 0.012
#> 5D663B98-8416-4305-A891-111B7A4DC40B 5 0.2179 0.58108 0.000 0.000 0.112 0.000 0.888
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.1608 0.77195 0.072 0.000 0.000 0.928 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.8706 -0.10709 0.328 0.204 0.168 0.012 0.288
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.4114 0.24458 0.000 0.000 0.000 0.624 0.376
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0671 0.88368 0.000 0.980 0.000 0.016 0.004
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.1124 0.63279 0.000 0.000 0.004 0.036 0.960
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.3934 0.29495 0.276 0.000 0.716 0.000 0.008
#> 810FC459-F77D-462D-90B7-E77C1FD43981 5 0.4425 0.24339 0.000 0.452 0.000 0.004 0.544
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.2852 0.54654 0.828 0.000 0.172 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0290 0.88568 0.000 0.992 0.000 0.008 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 5 0.1668 0.63061 0.000 0.032 0.000 0.028 0.940
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.4273 0.15410 0.448 0.000 0.552 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 3 0.7163 0.17675 0.324 0.000 0.388 0.016 0.272
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.5954 0.45061 0.000 0.000 0.192 0.592 0.216
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 5 0.3003 0.55287 0.000 0.000 0.188 0.000 0.812
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 4 0.3366 0.73298 0.232 0.000 0.000 0.768 0.000
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#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.4382 0.71547 0.000 0.700 0.004 0.276 0.020
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1892 0.86002 0.000 0.916 0.004 0.080 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4326 0.41681 0.160 0.000 0.780 0.024 0.036
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.5403 0.58920 0.000 0.644 0.000 0.108 0.248
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4026 0.33688 0.000 0.000 0.736 0.020 0.244
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.4305 0.73715 0.200 0.000 0.000 0.748 0.052
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.4599 0.36665 0.000 0.000 0.384 0.016 0.600
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.4743 0.54596 0.000 0.004 0.212 0.064 0.720
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.6385 0.26432 0.504 0.000 0.000 0.200 0.296
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 5 0.3274 0.53932 0.000 0.220 0.000 0.000 0.780
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 5 0.3366 0.53241 0.000 0.000 0.000 0.232 0.768
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0404 0.88589 0.000 0.988 0.000 0.012 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1197 0.65978 0.952 0.000 0.000 0.048 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3262 0.80259 0.000 0.840 0.000 0.124 0.036
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0290 0.88568 0.000 0.992 0.000 0.008 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.5905 0.44703 0.008 0.000 0.172 0.192 0.628
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4056 0.49972 0.768 0.000 0.008 0.024 0.200
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.3752 0.51373 0.780 0.000 0.200 0.016 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.2074 0.77548 0.104 0.000 0.000 0.896 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0932 0.76205 0.000 0.020 0.004 0.972 0.004
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3300 0.69577 0.000 0.000 0.004 0.792 0.204
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.1386 0.63086 0.000 0.032 0.000 0.016 0.952
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.5941 0.46587 0.000 0.196 0.004 0.188 0.612
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5954 0.43908 0.000 0.576 0.000 0.152 0.272
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0794 0.88197 0.000 0.972 0.000 0.028 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4620 0.21388 0.392 0.000 0.592 0.016 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6912 0.30613 0.000 0.176 0.592 0.096 0.136
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.0963 0.76921 0.036 0.000 0.000 0.964 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.0404 0.63321 0.000 0.000 0.000 0.012 0.988
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.5493 0.36170 0.124 0.000 0.660 0.004 0.212
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.6156 0.45035 0.000 0.000 0.216 0.224 0.560
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2966 0.50938 0.816 0.000 0.000 0.184 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3039 0.55323 0.000 0.000 0.192 0.000 0.808
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.7153 0.16733 0.332 0.000 0.388 0.016 0.264
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.3616 0.71844 0.052 0.000 0.004 0.828 0.116
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4347 0.48699 0.732 0.000 0.032 0.232 0.004
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3151 0.81475 0.000 0.836 0.020 0.144 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0451 0.67580 0.988 0.000 0.004 0.000 0.008
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.4278 0.43432 0.452 0.000 0.000 0.548 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.4235 -0.02686 0.000 0.424 0.000 0.576 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0290 0.88568 0.000 0.992 0.000 0.008 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.5975 0.36656 0.000 0.000 0.188 0.224 0.588
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.88608 0.000 1.000 0.000 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4778 0.46378 0.744 0.000 0.184 0.028 0.044
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6861 0.30794 0.000 0.128 0.592 0.088 0.192
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6659 0.34907 0.048 0.000 0.588 0.148 0.216
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.4595 0.73325 0.172 0.000 0.000 0.740 0.088
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2561 0.79575 0.000 0.856 0.000 0.000 0.144
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6418 0.25210 0.000 0.472 0.000 0.184 0.344
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.4588 0.37165 0.000 0.000 0.380 0.016 0.604
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2286 0.82873 0.000 0.888 0.004 0.108 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2674 0.41500 0.004 0.000 0.856 0.000 0.140
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.0794 0.76238 0.000 0.028 0.000 0.972 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.67880 1.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3003 0.71687 0.000 0.092 0.000 0.864 0.044
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.7479 0.16109 0.144 0.000 0.288 0.088 0.480
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.8231 0.14525 0.152 0.000 0.188 0.380 0.280
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.3838 0.41586 0.000 0.000 0.280 0.004 0.716
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5222 0.24647 0.356 0.000 0.600 0.028 0.016
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4651 0.17559 0.000 0.560 0.004 0.428 0.008
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0000 0.63098 0.000 0.000 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4573 0.41502 0.140 0.000 0.776 0.052 0.032
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3810 0.1768 0.428 0.000 0.572 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3883 0.4755 0.000 0.000 0.012 0.656 0.332 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3858 0.4930 0.740 0.000 0.216 0.000 0.000 0.044
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.3856 0.7274 0.000 0.784 0.000 0.156 0.032 0.028
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4052 0.1689 0.628 0.000 0.016 0.356 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4783 0.3311 0.612 0.000 0.332 0.000 0.012 0.044
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0291 0.6960 0.992 0.000 0.004 0.004 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.3860 0.7025 0.000 0.764 0.000 0.164 0.072 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.3566 0.7471 0.156 0.000 0.000 0.788 0.056 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.2597 0.7514 0.176 0.000 0.000 0.824 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0146 0.8476 0.000 0.996 0.000 0.004 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.2664 0.5740 0.000 0.000 0.000 0.184 0.816 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4621 0.1050 0.000 0.016 0.604 0.024 0.356 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1387 0.8405 0.000 0.932 0.000 0.000 0.000 0.068
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.5360 0.0638 0.000 0.004 0.608 0.184 0.204 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1387 0.8405 0.000 0.932 0.000 0.000 0.000 0.068
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.3852 0.5926 0.000 0.024 0.000 0.192 0.764 0.020
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7837 0.1465 0.000 0.196 0.180 0.428 0.160 0.036
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.1204 0.6667 0.000 0.000 0.000 0.056 0.944 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.3795 0.4258 0.000 0.000 0.364 0.000 0.632 0.004
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4458 0.2520 0.352 0.000 0.608 0.040 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.5227 0.4811 0.000 0.000 0.148 0.252 0.600 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3508 0.7383 0.000 0.800 0.000 0.000 0.132 0.068
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 3 0.6999 0.1649 0.336 0.000 0.384 0.000 0.204 0.076
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6999 0.1649 0.336 0.000 0.384 0.000 0.204 0.076
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.0146 0.7433 0.000 0.004 0.000 0.996 0.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.6999 0.1649 0.336 0.000 0.384 0.000 0.204 0.076
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0777 0.8472 0.000 0.972 0.000 0.004 0.024 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.3683 0.7309 0.192 0.000 0.000 0.764 0.044 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2912 0.4793 0.784 0.000 0.000 0.216 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0858 0.8431 0.000 0.968 0.000 0.028 0.004 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.3804 0.1822 0.424 0.000 0.576 0.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.3109 0.5751 0.000 0.000 0.224 0.000 0.772 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.6078 0.3039 0.132 0.000 0.228 0.000 0.580 0.060
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 4 0.4534 0.1845 0.472 0.000 0.000 0.496 0.032 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.4122 0.7504 0.024 0.792 0.012 0.116 0.000 0.056
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.3930 0.7448 0.148 0.000 0.016 0.780 0.056 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0692 0.8473 0.000 0.976 0.000 0.004 0.000 0.020
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3377 0.7127 0.000 0.784 0.000 0.188 0.000 0.028
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.4451 0.7125 0.164 0.000 0.092 0.732 0.012 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1168 0.8347 0.000 0.956 0.028 0.000 0.000 0.016
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.5552 0.3106 0.200 0.000 0.576 0.000 0.220 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0820 0.8418 0.000 0.972 0.012 0.000 0.000 0.016
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6648 -0.0421 0.000 0.168 0.604 0.072 0.084 0.072
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0937 0.6765 0.960 0.000 0.000 0.040 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.6381 0.1143 0.372 0.000 0.432 0.000 0.160 0.036
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.6983 0.1436 0.348 0.000 0.372 0.000 0.208 0.072
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0632 0.6838 0.976 0.000 0.000 0.024 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.2320 0.6176 0.000 0.000 0.004 0.132 0.864 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4047 0.1035 0.000 0.000 0.604 0.012 0.384 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.6359 0.2054 0.000 0.580 0.168 0.040 0.192 0.020
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.0000 0.6684 0.000 0.000 0.000 0.000 1.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.3563 0.1762 0.664 0.000 0.000 0.336 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0632 0.8467 0.000 0.976 0.000 0.000 0.000 0.024
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.8140 -0.0513 0.272 0.000 0.232 0.304 0.160 0.032
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.6540 -0.0173 0.428 0.000 0.384 0.000 0.112 0.076
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.3755 0.4786 0.744 0.000 0.220 0.036 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.3171 0.9017 0.000 0.092 0.004 0.056 0.004 0.844
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 5 0.3376 0.5157 0.000 0.220 0.000 0.016 0.764 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.0000 0.7437 0.000 0.000 0.000 1.000 0.000 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3189 0.4423 0.760 0.000 0.004 0.236 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4152 0.4673 0.712 0.000 0.240 0.000 0.004 0.044
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4123 0.4839 0.420 0.000 0.012 0.568 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 5 0.4700 0.5104 0.000 0.204 0.080 0.000 0.700 0.016
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.2402 0.7630 0.120 0.000 0.012 0.868 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 5 0.5095 0.4820 0.000 0.160 0.152 0.016 0.672 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4212 0.6111 0.000 0.688 0.000 0.264 0.048 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.2215 0.7407 0.000 0.012 0.012 0.900 0.076 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.0146 0.6692 0.000 0.004 0.000 0.000 0.996 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 4 0.4636 0.2507 0.444 0.000 0.000 0.516 0.040 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
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#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3774 0.1991 0.408 0.000 0.592 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6060 0.0167 0.000 0.176 0.604 0.036 0.172 0.012
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.0790 0.7530 0.032 0.000 0.000 0.968 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.0363 0.6706 0.000 0.000 0.000 0.012 0.988 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.5386 0.3717 0.116 0.000 0.664 0.000 0.176 0.044
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.6165 0.4716 0.000 0.000 0.224 0.176 0.556 0.044
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2854 0.4861 0.792 0.000 0.000 0.208 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3710 0.5766 0.000 0.020 0.184 0.000 0.776 0.020
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.6977 0.1638 0.336 0.000 0.384 0.000 0.208 0.072
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.3123 0.6918 0.056 0.000 0.000 0.832 0.112 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4230 0.5213 0.752 0.000 0.032 0.188 0.012 0.016
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.3030 0.9032 0.000 0.092 0.000 0.056 0.004 0.848
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0405 0.6950 0.988 0.000 0.004 0.000 0.008 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.4086 0.4022 0.464 0.000 0.008 0.528 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.3828 -0.0793 0.000 0.440 0.000 0.560 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1387 0.8405 0.000 0.932 0.000 0.000 0.000 0.068
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.5461 0.3511 0.000 0.000 0.184 0.248 0.568 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0458 0.8454 0.000 0.984 0.000 0.000 0.000 0.016
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4206 0.5054 0.764 0.000 0.172 0.024 0.024 0.016
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6061 0.0233 0.000 0.148 0.604 0.076 0.172 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.5819 0.2921 0.044 0.000 0.612 0.160 0.184 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.3806 0.7382 0.164 0.000 0.000 0.768 0.068 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2482 0.7549 0.000 0.848 0.000 0.004 0.148 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5826 0.1401 0.000 0.436 0.000 0.188 0.376 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.4593 0.3678 0.000 0.000 0.380 0.000 0.576 0.044
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2575 0.8064 0.000 0.880 0.004 0.072 0.000 0.044
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2531 0.3307 0.012 0.000 0.856 0.000 0.132 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.0000 0.7437 0.000 0.000 0.000 1.000 0.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.6981 1.000 0.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2258 0.7103 0.000 0.060 0.000 0.896 0.044 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.7554 0.1070 0.140 0.000 0.300 0.084 0.428 0.048
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.7184 0.2665 0.144 0.000 0.180 0.444 0.232 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.2941 0.5194 0.000 0.000 0.220 0.000 0.780 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4883 0.2543 0.320 0.000 0.616 0.048 0.016 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4774 0.1696 0.000 0.536 0.012 0.428 0.008 0.016
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0146 0.6686 0.000 0.000 0.004 0.000 0.996 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.3930 0.3357 0.136 0.000 0.784 0.064 0.016 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.565 0.855 0.901 0.4041 0.616 0.616
#> 3 3 0.576 0.750 0.866 0.5211 0.586 0.419
#> 4 4 0.631 0.773 0.859 0.1582 0.809 0.563
#> 5 5 0.650 0.482 0.714 0.0818 0.882 0.636
#> 6 6 0.658 0.569 0.738 0.0352 0.905 0.650
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3431 0.8969 0.064 0.936
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 2 0.7602 0.8047 0.220 0.780
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.9732 0.5228 0.404 0.596
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.0376 0.8902 0.004 0.996
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.7950 0.7913 0.240 0.760
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2423 0.8931 0.040 0.960
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0672 0.9365 0.992 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.9661 0.4100 0.608 0.392
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0672 0.9365 0.992 0.008
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.2423 0.8974 0.040 0.960
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.7674 0.8066 0.224 0.776
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0672 0.9365 0.992 0.008
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0672 0.9365 0.992 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3431 0.8969 0.064 0.936
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.5178 0.8538 0.884 0.116
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.2948 0.8963 0.052 0.948
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4022 0.8973 0.080 0.920
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.4022 0.8904 0.080 0.920
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.5059 0.8883 0.112 0.888
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3431 0.8969 0.064 0.936
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2423 0.8918 0.040 0.960
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.2778 0.9007 0.048 0.952
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.2423 0.8934 0.040 0.960
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 2 0.7376 0.8072 0.208 0.792
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.8144 0.7950 0.252 0.748
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.7139 0.8258 0.196 0.804
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0376 0.8902 0.004 0.996
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.0376 0.8902 0.004 0.996
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0672 0.9365 0.992 0.008
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.8443 0.7752 0.272 0.728
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.0376 0.8902 0.004 0.996
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3431 0.8969 0.064 0.936
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0672 0.9365 0.992 0.008
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0672 0.9365 0.992 0.008
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.3431 0.8969 0.064 0.936
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 2 0.7376 0.8072 0.208 0.792
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.2423 0.8934 0.040 0.960
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.1633 0.8965 0.024 0.976
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0672 0.9365 0.992 0.008
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0672 0.9365 0.992 0.008
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.8955 0.7064 0.312 0.688
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1843 0.9262 0.972 0.028
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.3431 0.8969 0.064 0.936
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.8081 0.7891 0.248 0.752
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.8016 0.7998 0.244 0.756
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2236 0.8917 0.036 0.964
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 2 0.0672 0.8929 0.008 0.992
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3431 0.8969 0.064 0.936
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1843 0.8972 0.028 0.972
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3431 0.8969 0.064 0.936
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.2423 0.8934 0.040 0.960
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.8016 0.7998 0.244 0.756
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.8327 0.6144 0.736 0.264
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 2 0.0672 0.8921 0.008 0.992
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 0.5294 0.8731 0.120 0.880
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0672 0.9365 0.992 0.008
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.3114 0.8985 0.056 0.944
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.2423 0.8934 0.040 0.960
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.2236 0.8948 0.036 0.964
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.4022 0.8953 0.080 0.920
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0672 0.9365 0.992 0.008
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3879 0.8977 0.076 0.924
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.2603 0.9163 0.956 0.044
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.0376 0.8902 0.004 0.996
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 2 0.7815 0.7988 0.232 0.768
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.7528 0.8158 0.216 0.784
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.7883 0.8048 0.236 0.764
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.5294 0.8267 0.880 0.120
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0672 0.9365 0.992 0.008
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.2778 0.9141 0.952 0.048
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.1843 0.9262 0.972 0.028
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0672 0.9365 0.992 0.008
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.2423 0.8934 0.040 0.960
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.1184 0.9332 0.984 0.016
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.2948 0.8963 0.052 0.948
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.7815 0.8085 0.232 0.768
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.3879 0.8984 0.076 0.924
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.4431 0.8924 0.092 0.908
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0672 0.9365 0.992 0.008
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0672 0.9365 0.992 0.008
#> F4F647DC-C630-429C-AD49-ADA43B652781 2 0.0376 0.8902 0.004 0.996
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.2423 0.8934 0.040 0.960
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 2 0.7056 0.8250 0.192 0.808
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 2 0.2043 0.8972 0.032 0.968
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 2 0.2423 0.8934 0.040 0.960
#> E435C03F-0277-49C1-83EF-19452082723E 2 0.0672 0.8921 0.008 0.992
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.7674 0.8126 0.224 0.776
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.9922 -0.0507 0.552 0.448
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.2423 0.8931 0.040 0.960
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.0376 0.8902 0.004 0.996
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.2236 0.9246 0.964 0.036
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.3584 0.8964 0.068 0.932
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.3431 0.8998 0.064 0.936
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.8081 0.7964 0.248 0.752
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.2043 0.8972 0.032 0.968
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 2 0.8081 0.7955 0.248 0.752
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0672 0.9365 0.992 0.008
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 2 0.0376 0.8902 0.004 0.996
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.3584 0.8997 0.068 0.932
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.2423 0.9179 0.960 0.040
#> E3A5FB64-EB24-4A24-9B79-539012C57711 2 0.0000 0.8897 0.000 1.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.1843 0.9262 0.972 0.028
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.8016 0.8020 0.244 0.756
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 2 0.6343 0.8414 0.160 0.840
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.8207 0.7923 0.256 0.744
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 2 0.0376 0.8914 0.004 0.996
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.8016 0.7866 0.244 0.756
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.2423 0.8934 0.040 0.960
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0672 0.9365 0.992 0.008
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.2236 0.8917 0.036 0.964
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.8016 0.7866 0.244 0.756
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.2423 0.9012 0.040 0.960
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0672 0.9365 0.992 0.008
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.3431 0.8969 0.064 0.936
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 2 0.3879 0.8950 0.076 0.924
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 2 0.2603 0.8933 0.044 0.956
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.2423 0.8931 0.040 0.960
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 2 0.7883 0.7946 0.236 0.764
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.3274 0.8977 0.060 0.940
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.2423 0.8931 0.040 0.960
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 2 0.7674 0.8014 0.224 0.776
#> 55788408-50CF-4518-8A82-1D94AEA7444E 2 0.0376 0.8902 0.004 0.996
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.8016 0.7341 0.244 0.756
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 2 0.1843 0.8972 0.028 0.972
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0672 0.9365 0.992 0.008
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.7056 0.8351 0.192 0.808
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.3274 0.8966 0.060 0.940
#> FE330797-5A40-45A8-98DF-43A33369E90F 2 0.2778 0.8990 0.048 0.952
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.4562 0.8969 0.096 0.904
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.2423 0.8993 0.040 0.960
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 2 0.2948 0.8927 0.052 0.948
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 2 0.7453 0.8066 0.212 0.788
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 1 0.6623 0.7674 0.828 0.172
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.7602 0.8105 0.220 0.780
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.4022 0.8981 0.080 0.920
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.5059 0.8884 0.112 0.888
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.7376 0.8193 0.208 0.792
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0672 0.9365 0.992 0.008
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.7815 0.8024 0.232 0.768
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.8386 0.7773 0.268 0.732
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.5294 0.8849 0.120 0.880
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 2 0.0000 0.8897 0.000 1.000
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 2 0.0376 0.8902 0.004 0.996
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 2 0.0376 0.8902 0.004 0.996
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 2 0.2236 0.8990 0.036 0.964
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0672 0.9365 0.992 0.008
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.0672 0.9365 0.992 0.008
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.0672 0.9365 0.992 0.008
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 1 0.0672 0.9365 0.992 0.008
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.0672 0.9365 0.992 0.008
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.2043 0.8917 0.032 0.968
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.4022 0.8981 0.080 0.920
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 2 0.2043 0.8972 0.032 0.968
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.8443 0.7752 0.272 0.728
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 2 0.1184 0.8948 0.016 0.984
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.2236 0.9248 0.964 0.036
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 2 0.3879 0.8977 0.076 0.924
#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.2236 0.8989 0.036 0.964
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#> 8026EF80-8CFB-4A62-9C72-BB5B50BDECFE 2 0.0000 0.8897 0.000 1.000
#> C1D05156-9AA7-48FD-9C3C-8894F9025D29 2 0.8267 0.7880 0.260 0.740
#> D3AEFD54-52E3-4761-898B-F05A5B6BA198 2 0.3274 0.8977 0.060 0.940
#> 33FAC29F-D146-454C-AE5D-07DF7C191DFC 2 0.2778 0.8992 0.048 0.952
#> E3E13B94-9335-4B34-9975-ECA99EB1BCBE 1 0.6712 0.7470 0.824 0.176
#> 2E1AC099-CE43-4605-BDFD-FA71DE8EAE44 2 0.2423 0.8931 0.040 0.960
#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.3431 0.8969 0.064 0.936
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.3431 0.8969 0.064 0.936
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.3584 0.8964 0.068 0.932
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.7056 0.8419 0.192 0.808
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 2 0.8016 0.7923 0.244 0.756
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.3584 0.8964 0.068 0.932
#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.2423 0.9179 0.960 0.040
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.7674 0.8126 0.224 0.776
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.7139 0.8296 0.196 0.804
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.6887 0.8355 0.184 0.816
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 2 0.7674 0.8036 0.224 0.776
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 2 0.0376 0.8902 0.004 0.996
#> 976924B0-5799-4AC9-804F-78C8568037CA 2 0.0376 0.8914 0.004 0.996
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 2 0.0000 0.8897 0.000 1.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0938 0.9350 0.988 0.012
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.2236 0.9183 0.964 0.036
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 2 0.0000 0.8897 0.000 1.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 2 0.3431 0.8908 0.064 0.936
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0672 0.8931 0.008 0.992
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.2948 0.8954 0.052 0.948
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.2778 0.8991 0.048 0.952
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.9970 -0.0954 0.532 0.468
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 2 0.2423 0.8934 0.040 0.960
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0672 0.9365 0.992 0.008
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.3879 0.8855 0.924 0.076
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.2603 0.8948 0.044 0.956
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.4690 0.8894 0.100 0.900
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0672 0.9365 0.992 0.008
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.2423 0.9179 0.960 0.040
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 2 0.0376 0.8902 0.004 0.996
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.7815 0.7987 0.232 0.768
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.8443 0.7752 0.272 0.728
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.7139 0.8220 0.196 0.804
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.7139 0.8414 0.196 0.804
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 2 0.7139 0.8315 0.196 0.804
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 2 0.2778 0.8930 0.048 0.952
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 2 0.9896 0.1312 0.440 0.560
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.8207 0.7923 0.256 0.744
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.1843 0.9262 0.972 0.028
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.2423 0.8931 0.040 0.960
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.3584 0.8964 0.068 0.932
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.3431 0.8969 0.064 0.936
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.0672 0.9365 0.992 0.008
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.0938 0.9348 0.988 0.012
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 2 0.2423 0.8935 0.040 0.960
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.8081 0.7856 0.248 0.752
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.1843 0.9262 0.972 0.028
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 2 0.1633 0.8969 0.024 0.976
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 2 0.0000 0.8897 0.000 1.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.3114 0.8981 0.056 0.944
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.2423 0.9179 0.960 0.040
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.4161 0.8800 0.916 0.084
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0672 0.9365 0.992 0.008
#> C653CC8E-7598-4332-A053-D72CFBC380DF 2 0.7883 0.7946 0.236 0.764
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.5059 0.8897 0.112 0.888
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.8081 0.8009 0.248 0.752
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.9000 0.5232 0.684 0.316
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 2 0.7219 0.8190 0.200 0.800
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.2043 0.8982 0.032 0.968
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.2236 0.8979 0.036 0.964
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.0672 0.8928 0.008 0.992
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.8443 0.7752 0.272 0.728
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.0000 0.8897 0.000 1.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.3431 0.8969 0.064 0.936
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.9460 0.6276 0.364 0.636
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0376 0.8915 0.004 0.996
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 2 0.0000 0.8897 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.0672 0.8915 0.008 0.992
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.3584 0.8968 0.068 0.932
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 2 0.2603 0.8946 0.044 0.956
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.3584 0.8964 0.068 0.932
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0672 0.9365 0.992 0.008
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.7883 0.8048 0.236 0.764
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.1843 0.8962 0.028 0.972
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.4690 0.8951 0.100 0.900
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0672 0.9365 0.992 0.008
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.3114 0.8987 0.056 0.944
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1843 0.8972 0.028 0.972
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 1.0000 0.2710 0.496 0.504
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.2043 0.8982 0.032 0.968
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.2778 0.8956 0.048 0.952
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 2 0.7815 0.8018 0.232 0.768
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 2 0.0000 0.8897 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.8443 0.7752 0.272 0.728
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.7139 0.8258 0.196 0.804
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 2 0.6247 0.8444 0.156 0.844
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.3431 0.8973 0.064 0.936
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.2603 0.8946 0.044 0.956
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0672 0.9365 0.992 0.008
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.3431 0.8969 0.064 0.936
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 2 0.0376 0.8902 0.004 0.996
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.3431 0.8969 0.064 0.936
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.2043 0.8972 0.032 0.968
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0672 0.9365 0.992 0.008
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.9922 0.4263 0.448 0.552
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.2423 0.8993 0.040 0.960
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.8016 0.7866 0.244 0.756
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4939 0.8900 0.108 0.892
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.6973 0.7248 0.812 0.188
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6973 0.8448 0.188 0.812
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4562 0.8939 0.096 0.904
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.7745 0.8032 0.228 0.772
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 2 0.9881 0.4477 0.436 0.564
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.0938 0.8928 0.012 0.988
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8267 0.7880 0.260 0.740
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.1414 0.9302 0.980 0.020
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.2236 0.9242 0.964 0.036
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.2236 0.8987 0.036 0.964
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.2423 0.8931 0.040 0.960
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5737 0.8724 0.136 0.864
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4022 0.8955 0.080 0.920
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 2 0.7674 0.8036 0.224 0.776
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.2423 0.8934 0.040 0.960
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.9635 0.5777 0.388 0.612
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.4562 0.8908 0.096 0.904
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 2 0.0000 0.8897 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.2778 0.9004 0.048 0.952
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2423 0.8931 0.040 0.960
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0672 0.9365 0.992 0.008
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.0000 0.8897 0.000 1.000
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.0672 0.8919 0.008 0.992
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.8386 0.7723 0.268 0.732
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0672 0.9365 0.992 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.7528 0.8158 0.216 0.784
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.9552 0.3251 0.624 0.376
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0672 0.9365 0.992 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.8443 0.7752 0.272 0.728
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.4161 0.8972 0.084 0.916
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.3274 0.8988 0.060 0.940
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3431 0.8969 0.064 0.936
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1633 0.9287 0.976 0.024
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.2778 0.8956 0.048 0.952
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.8016 0.7866 0.244 0.756
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.9129 0.4083 0.672 0.328
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3274 0.8977 0.060 0.940
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.8443 0.7752 0.272 0.728
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.0938 0.8939 0.012 0.988
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.7376 0.8299 0.208 0.792
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0672 0.9365 0.992 0.008
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 2 0.2423 0.8934 0.040 0.960
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.7950 0.8008 0.240 0.760
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.6623 0.7700 0.828 0.172
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.8499 0.7511 0.276 0.724
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.6148 0.8650 0.152 0.848
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2423 0.9179 0.960 0.040
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.3584 0.8903 0.068 0.932
#> AB642383-1611-4355-B03C-08D42FF4676C 2 0.5178 0.8813 0.116 0.884
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3431 0.8969 0.064 0.936
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.0000 0.8897 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 2 0.7674 0.8036 0.224 0.776
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0237 0.8142 0.000 0.996 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5331 0.7454 0.184 0.024 0.792
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.0475 0.8842 0.992 0.004 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.6158 0.7651 0.052 0.760 0.188
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.4087 0.8403 0.880 0.068 0.052
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0237 0.8142 0.000 0.996 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.8853 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.7970 0.4957 0.660 0.156 0.184
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8853 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.4261 0.7739 0.140 0.848 0.012
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.4569 0.8278 0.860 0.068 0.072
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0000 0.8853 1.000 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.8853 1.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0424 0.8132 0.000 0.992 0.008
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.1647 0.8774 0.960 0.004 0.036
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4399 0.7470 0.000 0.188 0.812
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.5778 0.6024 0.200 0.768 0.032
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4409 0.7559 0.004 0.172 0.824
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.6056 0.5708 0.224 0.744 0.032
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.1989 0.8139 0.048 0.948 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3134 0.8140 0.052 0.916 0.032
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.4196 0.7752 0.112 0.864 0.024
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2066 0.7920 0.000 0.060 0.940
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5223 0.7508 0.176 0.024 0.800
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3045 0.8572 0.916 0.064 0.020
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#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.1015 0.8830 0.980 0.008 0.012
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.5465 0.5406 0.000 0.712 0.288
#> 93429F04-8404-4E8C-B654-9D2216BA432C 1 0.7741 0.4222 0.608 0.324 0.068
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.8853 1.000 0.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.1129 0.8811 0.976 0.004 0.020
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 2 0.5947 0.7747 0.052 0.776 0.172
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 1 0.7384 0.5530 0.660 0.068 0.272
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 1 0.3530 0.8502 0.900 0.068 0.032
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.9317 -0.0764 0.164 0.448 0.388
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 1 0.6168 0.6898 0.740 0.224 0.036
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.6634 0.7654 0.144 0.104 0.752
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.5247 0.6203 0.008 0.224 0.768
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.8926 0.3170 0.568 0.240 0.192
#> 6D711561-D549-44C7-885F-F3B846DB130C 1 0.6935 0.5102 0.652 0.312 0.036
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0000 0.8853 1.000 0.000 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0237 0.8142 0.000 0.996 0.004
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.2173 0.8121 0.048 0.944 0.008
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0424 0.8132 0.000 0.992 0.008
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.0475 0.8845 0.992 0.004 0.004
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.0829 0.8831 0.984 0.004 0.012
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.5656 0.5149 0.004 0.284 0.712
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 1 0.4087 0.8397 0.880 0.068 0.052
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.8853 1.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 2 0.7245 0.6945 0.120 0.712 0.168
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 2 0.5595 0.7393 0.016 0.756 0.228
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.2773 0.8164 0.048 0.928 0.024
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.1129 0.8811 0.976 0.004 0.020
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.8853 1.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0000 0.8853 1.000 0.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.6541 0.5833 0.304 0.024 0.672
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.6570 0.5232 0.308 0.668 0.024
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.8354 0.3373 0.320 0.576 0.104
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.4195 0.7875 0.852 0.012 0.136
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.6521 -0.1033 0.500 0.496 0.004
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.4521 0.7742 0.004 0.816 0.180
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.3694 0.8161 0.052 0.896 0.052
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.6140 0.4389 0.000 0.596 0.404
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.3234 0.8507 0.908 0.072 0.020
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.4235 0.7765 0.000 0.824 0.176
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0237 0.8142 0.000 0.996 0.004
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.1878 0.8723 0.952 0.044 0.004
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.4121 0.7799 0.000 0.832 0.168
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 2 0.4351 0.7800 0.004 0.828 0.168
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.5835 0.7764 0.052 0.784 0.164
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.9961 -0.1227 0.372 0.296 0.332
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.3752 0.7776 0.000 0.144 0.856
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.2280 0.8116 0.052 0.940 0.008
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0475 0.8845 0.992 0.004 0.004
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.9417 0.1776 0.224 0.504 0.272
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.5835 0.7781 0.052 0.784 0.164
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.6998 0.5781 0.664 0.292 0.044
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.8853 1.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.2550 0.8205 0.040 0.936 0.024
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1031 0.8147 0.000 0.976 0.024
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 1 0.2486 0.8616 0.932 0.060 0.008
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.4351 0.7800 0.004 0.828 0.168
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4452 0.7443 0.000 0.192 0.808
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.7199 0.6479 0.260 0.064 0.676
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 2 0.4351 0.7800 0.004 0.828 0.168
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 1 0.3983 0.8421 0.884 0.068 0.048
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.7413 0.5296 0.092 0.684 0.224
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.3141 0.8037 0.068 0.020 0.912
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2173 0.8147 0.048 0.944 0.008
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4291 0.7534 0.000 0.180 0.820
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.8853 1.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0424 0.8132 0.000 0.992 0.008
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 2 0.5891 0.7756 0.052 0.780 0.168
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0237 0.8142 0.000 0.996 0.004
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.5835 0.7764 0.052 0.784 0.164
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.8853 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0747 0.8826 0.984 0.016 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.4346 0.7754 0.000 0.816 0.184
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.4087 0.8403 0.880 0.068 0.052
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.6000 0.5982 0.200 0.760 0.040
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0592 0.8837 0.988 0.012 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6559 0.5307 0.252 0.708 0.040
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.5778 0.6123 0.200 0.768 0.032
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.8277 0.0272 0.460 0.076 0.464
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.2703 0.8615 0.928 0.056 0.016
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.9147 0.2761 0.540 0.260 0.200
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.3234 0.8499 0.908 0.072 0.020
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.0237 0.8843 0.996 0.004 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.0829 0.8831 0.984 0.004 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0747 0.8157 0.000 0.984 0.016
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0661 0.8141 0.004 0.988 0.008
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6829 0.6004 0.096 0.736 0.168
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2902 0.8085 0.016 0.920 0.064
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5356 0.7342 0.196 0.020 0.784
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.2356 0.8009 0.000 0.072 0.928
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.3045 0.8543 0.916 0.064 0.020
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.7180 0.6442 0.700 0.084 0.216
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.6489 0.0201 0.004 0.456 0.540
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.4745 0.8076 0.080 0.852 0.068
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0237 0.8142 0.000 0.996 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.8853 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.4351 0.7800 0.004 0.828 0.168
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.6027 0.7760 0.060 0.776 0.164
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.4821 0.8168 0.848 0.064 0.088
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.8853 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.9439 0.2000 0.276 0.500 0.224
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5167 0.7530 0.804 0.024 0.172
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.8853 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.3780 0.8447 0.892 0.064 0.044
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2681 0.7993 0.028 0.932 0.040
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.7777 0.3746 0.364 0.576 0.060
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0424 0.8132 0.000 0.992 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8853 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4235 0.7540 0.000 0.176 0.824
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.7265 0.5997 0.684 0.076 0.240
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0747 0.8835 0.984 0.016 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1525 0.8159 0.032 0.964 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.3764 0.8454 0.892 0.068 0.040
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.5803 0.7519 0.028 0.760 0.212
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.6398 0.4264 0.620 0.372 0.008
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8853 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1163 0.7975 0.000 0.028 0.972
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.2939 0.8540 0.916 0.072 0.012
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3816 0.7437 0.852 0.148 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.3983 0.8421 0.884 0.068 0.048
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6007 0.7203 0.768 0.048 0.184
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0983 0.8820 0.980 0.004 0.016
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2496 0.8040 0.004 0.068 0.928
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5710 0.7777 0.080 0.116 0.804
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0424 0.8140 0.000 0.992 0.008
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.3272 0.8083 0.004 0.892 0.104
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5062 0.7445 0.184 0.016 0.800
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.0707 0.8183 0.000 0.020 0.000 0.980
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4836 0.7427 0.188 0.020 0.772 0.020
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.1661 0.8912 0.944 0.052 0.000 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 4 0.4098 0.8036 0.000 0.012 0.204 0.784
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1716 0.8266 0.064 0.936 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.0707 0.8203 0.000 0.020 0.000 0.980
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.6275 0.5444 0.672 0.004 0.200 0.124
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 4 0.2074 0.8233 0.032 0.012 0.016 0.940
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.1716 0.8266 0.064 0.936 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1389 0.8909 0.952 0.048 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0921 0.8973 0.972 0.028 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.2469 0.7767 0.000 0.108 0.000 0.892
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4564 0.5784 0.672 0.328 0.000 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4389 0.7564 0.000 0.072 0.812 0.116
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.3681 0.7395 0.008 0.816 0.000 0.176
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4289 0.7273 0.000 0.172 0.796 0.032
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2329 0.8138 0.012 0.916 0.000 0.072
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.0000 0.8213 0.000 0.000 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.0779 0.8225 0.000 0.016 0.004 0.980
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4850 0.7017 0.052 0.168 0.004 0.776
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2111 0.8033 0.000 0.044 0.932 0.024
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5227 0.7452 0.148 0.064 0.772 0.016
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4487 0.7830 0.808 0.092 0.000 0.100
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2021 0.8315 0.056 0.932 0.000 0.012
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 4 0.4098 0.8036 0.000 0.012 0.204 0.784
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 4 0.4098 0.8036 0.000 0.012 0.204 0.784
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.3764 0.7357 0.216 0.784 0.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 4 0.4098 0.8036 0.000 0.012 0.204 0.784
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.1716 0.8025 0.000 0.064 0.000 0.936
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.3486 0.7089 0.000 0.188 0.000 0.812
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4744 0.7472 0.152 0.056 0.788 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0524 0.8042 0.000 0.008 0.988 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.3893 0.8085 0.000 0.008 0.196 0.796
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 1 0.4136 0.7839 0.788 0.196 0.000 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1557 0.8898 0.944 0.056 0.000 0.000
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#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 4 0.0336 0.8216 0.000 0.008 0.000 0.992
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 4 0.1635 0.8272 0.000 0.008 0.044 0.948
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0707 0.8934 0.980 0.000 0.000 0.020
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.1109 0.7942 0.000 0.004 0.968 0.028
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.2469 0.8615 0.892 0.108 0.000 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 3 0.6119 0.6444 0.000 0.152 0.680 0.168
#> 93429F04-8404-4E8C-B654-9D2216BA432C 1 0.5998 0.6511 0.684 0.200 0.000 0.116
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.2530 0.8593 0.888 0.112 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 4 0.4059 0.8056 0.000 0.012 0.200 0.788
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.2207 0.8235 0.040 0.932 0.024 0.004
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 1 0.4994 0.1303 0.520 0.480 0.000 0.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.7868 0.2066 0.012 0.496 0.240 0.252
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.5012 0.7858 0.112 0.772 0.000 0.116
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.5471 0.7582 0.140 0.008 0.752 0.100
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.4990 0.1826 0.000 0.008 0.640 0.352
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.7725 -0.0364 0.456 0.004 0.204 0.336
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.2843 0.8288 0.088 0.892 0.000 0.020
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 4 0.0469 0.8200 0.000 0.012 0.000 0.988
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.0592 0.8193 0.000 0.016 0.000 0.984
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 4 0.3569 0.7001 0.000 0.196 0.000 0.804
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.2408 0.8632 0.896 0.104 0.000 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.2589 0.8557 0.884 0.116 0.000 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 4 0.4690 0.7532 0.000 0.012 0.276 0.712
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.1716 0.8266 0.064 0.936 0.000 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 4 0.4214 0.8041 0.016 0.000 0.204 0.780
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 4 0.4137 0.8017 0.000 0.012 0.208 0.780
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.2466 0.7971 0.004 0.096 0.000 0.900
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.2704 0.8499 0.876 0.124 0.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.1302 0.8910 0.956 0.044 0.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.4682 0.7285 0.208 0.008 0.764 0.020
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.5995 0.5905 0.660 0.084 0.000 0.256
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.3567 0.8234 0.076 0.868 0.004 0.052
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.5257 0.7088 0.764 0.032 0.172 0.032
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 4 0.4355 0.6882 0.212 0.012 0.004 0.772
#> BDDB8226-723E-426F-973F-59D14E9EEB06 4 0.4238 0.8076 0.000 0.028 0.176 0.796
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.5111 0.7984 0.056 0.064 0.076 0.804
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.5112 0.0503 0.000 0.008 0.608 0.384
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.4882 0.6852 0.272 0.708 0.000 0.020
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 4 0.3933 0.8058 0.000 0.008 0.200 0.792
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.0592 0.8193 0.000 0.016 0.000 0.984
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.1398 0.8920 0.956 0.040 0.000 0.004
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 4 0.3852 0.8091 0.000 0.008 0.192 0.800
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 4 0.3831 0.8058 0.000 0.004 0.204 0.792
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.4175 0.8068 0.000 0.016 0.200 0.784
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.4502 0.7877 0.044 0.828 0.100 0.028
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.3117 0.7986 0.000 0.028 0.880 0.092
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.0188 0.8209 0.000 0.004 0.000 0.996
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.2589 0.8556 0.884 0.116 0.000 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.7895 0.4128 0.044 0.568 0.184 0.204
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 4 0.3280 0.8245 0.000 0.016 0.124 0.860
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.4731 0.7770 0.060 0.780 0.000 0.160
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.1297 0.8257 0.000 0.016 0.020 0.964
#> A2007795-C728-4688-B199-AE89500011D2 4 0.4956 0.6773 0.000 0.232 0.036 0.732
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 1 0.3942 0.6624 0.764 0.236 0.000 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 4 0.3791 0.8079 0.004 0.000 0.200 0.796
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4411 0.7582 0.000 0.080 0.812 0.108
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 4 0.9932 -0.3321 0.196 0.272 0.248 0.284
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.3791 0.8078 0.000 0.004 0.200 0.796
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.2011 0.8266 0.080 0.920 0.000 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1297 0.8151 0.000 0.964 0.016 0.020
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.2297 0.8166 0.024 0.044 0.928 0.004
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.4458 0.7136 0.116 0.076 0.000 0.808
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.3745 0.7859 0.000 0.060 0.852 0.088
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0188 0.9010 0.996 0.004 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.1792 0.8025 0.000 0.068 0.000 0.932
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 4 0.3972 0.8046 0.000 0.008 0.204 0.788
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.0469 0.8202 0.000 0.012 0.000 0.988
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.3725 0.8150 0.000 0.008 0.180 0.812
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1211 0.8817 0.960 0.000 0.000 0.040
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.7017 0.6310 0.004 0.260 0.152 0.584
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.1867 0.8246 0.072 0.928 0.000 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1890 0.8172 0.008 0.936 0.000 0.056
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1938 0.8745 0.936 0.012 0.000 0.052
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3863 0.7781 0.028 0.828 0.000 0.144
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.2281 0.7983 0.000 0.904 0.000 0.096
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.6411 0.3544 0.040 0.584 0.356 0.020
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.3196 0.7734 0.856 0.008 0.000 0.136
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 4 0.5833 0.7511 0.072 0.012 0.204 0.712
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.5386 0.5669 0.368 0.612 0.000 0.020
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.1389 0.8907 0.952 0.048 0.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.3311 0.8052 0.828 0.172 0.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.1975 0.8206 0.000 0.048 0.016 0.936
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.0336 0.8207 0.000 0.008 0.000 0.992
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.2153 0.8302 0.036 0.936 0.008 0.020
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.3659 0.7228 0.000 0.840 0.024 0.136
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4589 0.7379 0.188 0.024 0.780 0.008
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.2704 0.7819 0.000 0.124 0.876 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.4382 0.6531 0.296 0.704 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.4247 0.8087 0.104 0.836 0.044 0.016
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 4 0.4546 0.7766 0.000 0.012 0.256 0.732
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6592 0.5978 0.212 0.068 0.044 0.676
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 4 0.0000 0.8213 0.000 0.000 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0817 0.8988 0.976 0.024 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.3972 0.8046 0.000 0.008 0.204 0.788
#> C20F209A-2102-4502-80FA-17AF04601987 4 0.4074 0.8075 0.004 0.008 0.196 0.792
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.3351 0.7722 0.148 0.844 0.008 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2189 0.8158 0.004 0.932 0.020 0.044
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.6327 0.5778 0.648 0.124 0.228 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.2921 0.8018 0.140 0.860 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1716 0.8114 0.000 0.936 0.000 0.064
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6793 0.4190 0.328 0.032 0.052 0.588
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.3610 0.6950 0.000 0.200 0.000 0.800
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4297 0.7660 0.000 0.084 0.820 0.096
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.5835 0.5753 0.068 0.684 0.244 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0707 0.8934 0.980 0.000 0.000 0.020
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.3726 0.7045 0.000 0.212 0.000 0.788
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.2216 0.8244 0.092 0.908 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 4 0.3933 0.8058 0.000 0.008 0.200 0.792
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.4784 0.7684 0.788 0.112 0.000 0.100
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9009 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0376 0.8025 0.000 0.004 0.992 0.004
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5508 0.4529 0.408 0.572 0.000 0.020
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1389 0.8741 0.952 0.000 0.000 0.048
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.2647 0.7938 0.120 0.880 0.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.7572 0.4991 0.604 0.100 0.232 0.064
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2760 0.8467 0.872 0.128 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3925 0.7393 0.000 0.176 0.808 0.016
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4987 0.7641 0.056 0.024 0.796 0.124
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.0336 0.8207 0.000 0.008 0.000 0.992
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.3032 0.8243 0.000 0.008 0.124 0.868
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5010 0.7518 0.128 0.080 0.784 0.008
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2377 0.53603 0.000 0.872 0.128 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.6749 0.29428 0.180 0.000 0.348 0.012 0.460
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.2728 0.86568 0.888 0.004 0.040 0.068 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4287 0.11829 0.000 0.460 0.000 0.000 0.540
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0510 0.68847 0.000 0.000 0.016 0.984 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0510 0.60309 0.000 0.984 0.016 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0162 0.88630 0.996 0.000 0.004 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5195 0.66207 0.704 0.036 0.016 0.016 0.228
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.88624 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.5260 0.19067 0.060 0.592 0.000 0.000 0.348
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0703 0.68810 0.000 0.000 0.024 0.976 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3151 0.82940 0.836 0.000 0.020 0.144 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.2124 0.87274 0.916 0.000 0.028 0.056 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4192 -0.02837 0.000 0.596 0.404 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4455 0.12174 0.404 0.000 0.008 0.588 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 5 0.6469 0.24475 0.000 0.108 0.412 0.020 0.460
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 3 0.6387 0.24646 0.000 0.168 0.440 0.392 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 5 0.6237 0.24540 0.000 0.032 0.444 0.064 0.460
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.5353 0.05727 0.000 0.052 0.472 0.476 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0880 0.60582 0.000 0.968 0.000 0.000 0.032
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2690 0.54656 0.000 0.844 0.000 0.000 0.156
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.6538 0.06169 0.152 0.560 0.268 0.016 0.004
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4651 0.35955 0.000 0.000 0.372 0.020 0.608
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 5 0.6988 0.29379 0.156 0.000 0.352 0.032 0.460
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1502 0.88108 0.940 0.004 0.000 0.056 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.1671 0.67707 0.000 0.000 0.076 0.924 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.4443 0.09162 0.000 0.472 0.004 0.000 0.524
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#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0162 0.88636 0.996 0.000 0.004 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.3983 0.37644 0.000 0.000 0.340 0.000 0.660
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.6579 0.29248 0.332 0.000 0.220 0.448 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1915 0.85324 0.928 0.032 0.000 0.000 0.040
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0162 0.68674 0.000 0.000 0.004 0.996 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5796 0.68847 0.704 0.012 0.100 0.036 0.148
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2753 0.83924 0.856 0.000 0.008 0.136 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.5509 -0.29928 0.000 0.000 0.472 0.064 0.464
#> AB642383-1611-4355-B03C-08D42FF4676C 5 0.7409 0.26193 0.064 0.120 0.344 0.008 0.464
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1965 0.56541 0.000 0.904 0.096 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.3835 0.45326 0.000 0.744 0.012 0.000 0.244
#> EE118E80-F125-4655-8845-56A9CBBA0680 5 0.7277 0.28995 0.144 0.004 0.344 0.048 0.460
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3534 0.5822 0.000 0.740 0.000 0.016 0.244 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3701 0.7578 0.160 0.000 0.792 0.032 0.012 0.004
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.4716 -0.1387 0.576 0.004 0.000 0.376 0.000 0.044
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0993 0.7635 0.012 0.000 0.000 0.024 0.964 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0725 0.7071 0.000 0.000 0.012 0.012 0.000 0.976
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4180 0.5490 0.000 0.680 0.000 0.024 0.288 0.008
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0458 0.7734 0.984 0.000 0.000 0.016 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4962 0.3951 0.672 0.000 0.028 0.068 0.232 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.7747 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.4229 0.6312 0.056 0.148 0.012 0.008 0.772 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.0508 0.7082 0.000 0.004 0.012 0.000 0.000 0.984
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3372 0.6902 0.816 0.000 0.000 0.084 0.000 0.100
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.2554 0.7421 0.876 0.000 0.000 0.076 0.000 0.048
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1492 0.5883 0.000 0.940 0.000 0.036 0.024 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 6 0.4728 0.0976 0.324 0.000 0.004 0.056 0.000 0.616
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.2821 0.7790 0.000 0.096 0.860 0.040 0.004 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.6523 -0.3447 0.000 0.428 0.028 0.244 0.000 0.300
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.2500 0.7927 0.000 0.032 0.896 0.036 0.000 0.036
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.6670 -0.4380 0.000 0.368 0.032 0.260 0.000 0.340
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.4345 0.4452 0.000 0.604 0.000 0.012 0.372 0.012
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.4591 0.3479 0.000 0.552 0.000 0.040 0.408 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.5942 0.5480 0.084 0.684 0.088 0.024 0.108 0.012
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2212 0.8116 0.000 0.000 0.880 0.008 0.112 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3767 0.7618 0.152 0.000 0.792 0.040 0.012 0.004
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3536 0.6926 0.844 0.008 0.004 0.028 0.064 0.052
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.3225 0.7105 0.000 0.064 0.036 0.048 0.000 0.852
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.2135 0.7603 0.012 0.032 0.024 0.012 0.920 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0508 0.7665 0.012 0.000 0.000 0.004 0.984 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0547 0.7743 0.980 0.000 0.000 0.020 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.2328 0.6706 0.056 0.000 0.000 0.052 0.000 0.892
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0363 0.7669 0.012 0.000 0.000 0.000 0.988 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1245 0.5859 0.000 0.952 0.000 0.032 0.016 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0547 0.7743 0.980 0.000 0.000 0.020 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0260 0.7752 0.992 0.000 0.000 0.008 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1644 0.5575 0.000 0.920 0.000 0.076 0.004 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.3873 0.7769 0.120 0.000 0.796 0.068 0.012 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2333 0.8084 0.000 0.000 0.884 0.024 0.092 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.3700 0.6918 0.012 0.136 0.028 0.016 0.808 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0146 0.7752 0.996 0.000 0.000 0.000 0.000 0.004
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0146 0.7752 0.996 0.000 0.000 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.7046 0.6209 0.264 0.104 0.004 0.480 0.004 0.144
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1049 0.7762 0.960 0.000 0.000 0.032 0.000 0.008
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2431 0.5196 0.000 0.860 0.000 0.132 0.008 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.0725 0.7085 0.000 0.012 0.012 0.000 0.000 0.976
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4277 0.2814 0.700 0.016 0.000 0.004 0.260 0.020
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4770 0.3706 0.000 0.560 0.000 0.032 0.396 0.012
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.1092 0.7509 0.000 0.000 0.020 0.020 0.960 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3834 0.5656 0.000 0.708 0.000 0.024 0.268 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.5236 0.5569 0.000 0.692 0.120 0.024 0.152 0.012
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1657 0.5954 0.000 0.936 0.000 0.012 0.040 0.012
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.1418 0.8022 0.000 0.000 0.944 0.032 0.024 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2766 0.6175 0.852 0.000 0.000 0.020 0.124 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.2147 0.6898 0.896 0.000 0.000 0.020 0.084 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1003 0.7584 0.000 0.000 0.016 0.020 0.964 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5700 -0.0622 0.468 0.000 0.028 0.080 0.424 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0508 0.7740 0.984 0.000 0.000 0.012 0.000 0.004
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.5017 0.5316 0.000 0.632 0.036 0.024 0.300 0.008
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.2221 0.8077 0.000 0.000 0.896 0.032 0.072 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4663 0.4752 0.000 0.616 0.020 0.008 0.344 0.012
#> B730E9AD-DA24-46A3-BE56-A89447421C09 6 0.5665 0.6547 0.000 0.116 0.172 0.056 0.004 0.652
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0146 0.7748 0.996 0.000 0.000 0.004 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5956 -0.1359 0.000 0.548 0.020 0.192 0.000 0.240
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3693 0.6868 0.828 0.000 0.036 0.092 0.028 0.016
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0653 0.7675 0.012 0.004 0.000 0.004 0.980 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.3281 0.7213 0.200 0.000 0.784 0.004 0.012 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.6912 0.5272 0.000 0.268 0.112 0.084 0.024 0.512
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.4957 0.6320 0.000 0.204 0.000 0.148 0.000 0.648
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 6 0.3395 0.5737 0.132 0.000 0.000 0.060 0.000 0.808
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0547 0.7723 0.980 0.000 0.000 0.020 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3483 0.6748 0.832 0.000 0.028 0.080 0.060 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.2302 0.6901 0.872 0.000 0.000 0.120 0.000 0.008
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0146 0.7755 0.996 0.000 0.000 0.004 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.2174 0.8009 0.000 0.036 0.912 0.036 0.016 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.3372 0.6877 0.816 0.000 0.000 0.084 0.000 0.100
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.2888 0.7755 0.000 0.092 0.852 0.056 0.000 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.6402 0.5163 0.200 0.228 0.000 0.528 0.004 0.040
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.2913 0.5757 0.000 0.848 0.004 0.116 0.032 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 6 0.3736 0.6761 0.000 0.012 0.156 0.036 0.004 0.792
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1984 0.7629 0.912 0.000 0.000 0.056 0.000 0.032
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.7747 1.000 0.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.1680 0.7641 0.012 0.020 0.024 0.004 0.940 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.2240 0.8093 0.000 0.016 0.908 0.032 0.044 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.3497 0.8005 0.092 0.004 0.832 0.052 0.020 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.5395 0.5274 0.116 0.216 0.028 0.000 0.640 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3345 0.7836 0.000 0.000 0.788 0.028 0.184 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.1167 0.7638 0.012 0.000 0.008 0.020 0.960 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 6 0.5496 0.5798 0.000 0.292 0.012 0.120 0.000 0.576
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 6 0.4332 0.3046 0.288 0.000 0.000 0.048 0.000 0.664
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.3982 0.5581 0.000 0.696 0.000 0.016 0.280 0.008
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.1218 0.7666 0.012 0.028 0.004 0.000 0.956 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.3148 0.7173 0.840 0.000 0.000 0.092 0.004 0.064
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.4309 0.5384 0.000 0.660 0.000 0.044 0.296 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.3866 0.4646 0.000 0.792 0.000 0.104 0.012 0.092
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 6 0.4693 0.0304 0.012 0.000 0.432 0.024 0.000 0.532
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.5908 -0.1462 0.000 0.436 0.088 0.028 0.444 0.004
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0436 0.7758 0.988 0.000 0.000 0.004 0.004 0.004
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0260 0.7752 0.992 0.000 0.000 0.008 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.1858 0.7581 0.012 0.052 0.000 0.012 0.924 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.6187 -0.1409 0.484 0.400 0.056 0.012 0.032 0.016
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.3808 0.6514 0.784 0.000 0.004 0.080 0.000 0.132
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.2224 0.7583 0.012 0.036 0.036 0.004 0.912 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0603 0.7740 0.980 0.000 0.000 0.016 0.000 0.004
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 6 0.2866 0.7117 0.000 0.052 0.004 0.084 0.000 0.860
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.3508 0.8110 0.032 0.000 0.832 0.072 0.064 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 6 0.3746 0.6906 0.000 0.140 0.000 0.080 0.000 0.780
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.0405 0.7632 0.000 0.000 0.004 0.008 0.988 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 6 0.0436 0.7064 0.004 0.000 0.004 0.004 0.000 0.988
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.1720 0.8056 0.000 0.000 0.928 0.032 0.040 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.3916 0.6036 0.752 0.000 0.000 0.064 0.000 0.184
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.4210 0.3621 0.008 0.344 0.000 0.008 0.636 0.004
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 6 0.0935 0.7033 0.000 0.000 0.004 0.032 0.000 0.964
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.3621 0.5976 0.000 0.828 0.024 0.036 0.100 0.012
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.7747 1.000 0.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.1594 0.5815 0.000 0.932 0.000 0.052 0.016 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.6615 0.1606 0.596 0.140 0.120 0.004 0.124 0.016
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.2964 0.7764 0.000 0.000 0.792 0.004 0.204 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.4347 0.5305 0.000 0.660 0.000 0.024 0.304 0.012
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.4566 0.1890 0.452 0.000 0.520 0.016 0.012 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.3593 0.4441 0.000 0.764 0.024 0.208 0.004 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.4412 0.5121 0.000 0.644 0.000 0.024 0.320 0.012
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.3884 0.7701 0.132 0.000 0.792 0.060 0.012 0.004
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.0909 0.7637 0.012 0.000 0.000 0.020 0.968 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 1 0.5652 0.1922 0.632 0.228 0.056 0.080 0.000 0.004
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 5 0.5617 0.4398 0.032 0.284 0.040 0.024 0.616 0.004
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.1616 0.7670 0.932 0.000 0.000 0.048 0.000 0.020
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 6 0.6435 0.6242 0.000 0.144 0.144 0.140 0.000 0.572
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.4617 0.2948 0.012 0.540 0.000 0.020 0.428 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 2 0.5633 0.2123 0.016 0.488 0.036 0.032 0.428 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.3444 0.6015 0.000 0.812 0.000 0.036 0.140 0.012
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.5160 0.3855 0.000 0.660 0.192 0.132 0.000 0.016
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.3270 0.8021 0.000 0.000 0.820 0.060 0.120 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.3717 0.7655 0.152 0.000 0.792 0.040 0.016 0.000
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#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 6 0.8560 0.3470 0.020 0.168 0.204 0.096 0.108 0.404
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.4214 0.6290 0.012 0.184 0.024 0.024 0.756 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 6 0.4402 0.6477 0.000 0.164 0.024 0.068 0.000 0.744
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0291 0.7751 0.992 0.000 0.000 0.004 0.000 0.004
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.5180 0.3055 0.008 0.532 0.028 0.016 0.412 0.004
#> A2007795-C728-4688-B199-AE89500011D2 2 0.3693 0.4874 0.000 0.788 0.092 0.120 0.000 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 6 0.3763 0.5039 0.172 0.000 0.000 0.060 0.000 0.768
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.6367 -0.0472 0.020 0.420 0.076 0.024 0.448 0.012
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.2001 0.7922 0.000 0.048 0.912 0.040 0.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5735 0.6550 0.180 0.012 0.676 0.020 0.056 0.056
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.3735 0.7028 0.008 0.128 0.032 0.016 0.812 0.004
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 6 0.1074 0.7062 0.000 0.012 0.000 0.028 0.000 0.960
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.6136 0.5928 0.000 0.248 0.052 0.140 0.000 0.560
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.3608 0.8085 0.016 0.000 0.816 0.072 0.096 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4788 0.5820 0.000 0.684 0.020 0.068 0.228 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.2314 0.7961 0.000 0.056 0.900 0.036 0.008 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1010 0.7740 0.960 0.000 0.000 0.036 0.000 0.004
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1625 0.5978 0.000 0.928 0.000 0.012 0.060 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.1555 0.7648 0.012 0.040 0.000 0.008 0.940 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.4197 0.5491 0.000 0.680 0.000 0.020 0.288 0.012
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.5810 -0.1404 0.000 0.436 0.068 0.044 0.452 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0692 0.7756 0.976 0.000 0.000 0.020 0.000 0.004
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0632 0.7742 0.976 0.000 0.000 0.000 0.000 0.024
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5589 0.4790 0.000 0.688 0.156 0.068 0.056 0.032
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 6 0.0858 0.7042 0.000 0.000 0.004 0.028 0.000 0.968
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.6742 0.4954 0.000 0.308 0.048 0.224 0.000 0.420
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0603 0.7765 0.980 0.000 0.000 0.016 0.000 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.6267 0.5152 0.000 0.328 0.024 0.184 0.000 0.464
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.6004 0.1015 0.000 0.572 0.048 0.252 0.000 0.128
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 6 0.4807 -0.1327 0.000 0.000 0.464 0.052 0.000 0.484
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.2701 0.7120 0.888 0.000 0.028 0.020 0.056 0.008
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.1788 0.7512 0.028 0.000 0.004 0.040 0.928 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 6 0.4718 0.2719 0.324 0.036 0.000 0.016 0.000 0.624
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.5095 0.0539 0.584 0.000 0.000 0.312 0.000 0.104
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.4209 0.5762 0.736 0.000 0.000 0.104 0.000 0.160
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4646 0.5921 0.000 0.736 0.056 0.024 0.172 0.012
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.3729 0.5497 0.000 0.692 0.000 0.000 0.296 0.012
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.5890 0.6517 0.000 0.156 0.112 0.100 0.000 0.632
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.6654 0.0689 0.000 0.528 0.124 0.220 0.000 0.128
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3686 0.7470 0.172 0.000 0.788 0.008 0.012 0.020
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0790 0.7942 0.000 0.000 0.968 0.032 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 6 0.2826 0.6351 0.092 0.000 0.000 0.052 0.000 0.856
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 6 0.5873 0.3705 0.220 0.004 0.140 0.016 0.012 0.608
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0806 0.7584 0.000 0.000 0.008 0.020 0.972 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.8478 0.2692 0.124 0.368 0.092 0.212 0.200 0.004
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3874 0.5619 0.000 0.704 0.000 0.008 0.276 0.012
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0993 0.7779 0.964 0.000 0.000 0.024 0.000 0.012
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3116 0.7416 0.008 0.072 0.040 0.012 0.864 0.004
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2051 0.7604 0.016 0.028 0.024 0.008 0.924 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 6 0.1405 0.7034 0.024 0.000 0.004 0.024 0.000 0.948
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.7747 1.000 0.000 0.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.5250 0.6150 0.000 0.244 0.016 0.108 0.000 0.632
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5467 0.4109 0.664 0.000 0.196 0.096 0.012 0.032
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0291 0.7751 0.992 0.000 0.000 0.004 0.000 0.004
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.1429 0.6997 0.004 0.004 0.000 0.052 0.000 0.940
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.6882 -0.2935 0.000 0.432 0.064 0.248 0.000 0.256
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6875 -0.1824 0.432 0.352 0.076 0.008 0.132 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2135 0.5150 0.000 0.872 0.000 0.128 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0547 0.7725 0.980 0.000 0.000 0.020 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.2272 0.7949 0.000 0.056 0.900 0.040 0.004 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 6 0.5431 0.3000 0.032 0.000 0.284 0.068 0.004 0.612
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1464 0.7680 0.944 0.000 0.000 0.016 0.004 0.036
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2542 0.5688 0.000 0.884 0.020 0.080 0.016 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.0937 0.7027 0.000 0.000 0.000 0.040 0.000 0.960
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.1837 0.7609 0.012 0.004 0.032 0.020 0.932 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.5241 0.3885 0.096 0.240 0.000 0.644 0.004 0.016
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0692 0.7743 0.976 0.000 0.000 0.020 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3141 0.7806 0.000 0.000 0.788 0.012 0.200 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.6653 0.4500 0.184 0.164 0.000 0.116 0.000 0.536
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3374 0.4645 0.772 0.000 0.000 0.020 0.208 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 6 0.0653 0.7064 0.012 0.000 0.004 0.004 0.000 0.980
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4533 0.5798 0.760 0.000 0.096 0.068 0.076 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3277 0.6935 0.824 0.000 0.000 0.092 0.000 0.084
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.1003 0.7986 0.000 0.000 0.964 0.016 0.000 0.020
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4204 0.7661 0.044 0.116 0.796 0.012 0.012 0.020
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3584 0.5816 0.000 0.740 0.000 0.004 0.244 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.5407 0.1963 0.000 0.376 0.040 0.024 0.548 0.012
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4007 0.7617 0.144 0.004 0.788 0.008 0.012 0.044
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.824 0.889 0.955 0.5008 0.499 0.499
#> 3 3 0.627 0.707 0.870 0.3066 0.686 0.455
#> 4 4 0.580 0.664 0.801 0.1328 0.799 0.499
#> 5 5 0.706 0.694 0.841 0.0726 0.852 0.519
#> 6 6 0.725 0.705 0.835 0.0360 0.901 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9362 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9665 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9362 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9665 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9362 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9362 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9665 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9665 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9665 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9665 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9362 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.9944 0.1285 0.544 0.456
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.9665 1.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9362 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.7139 0.7427 0.196 0.804
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.7219 0.7442 0.200 0.800
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9362 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.6973 0.7591 0.188 0.812
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9362 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6247 0.7990 0.844 0.156
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9362 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9362 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9665 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9665 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.9209 0.4645 0.664 0.336
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9362 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9665 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9665 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9665 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9362 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9665 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9362 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9665 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9665 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9362 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9665 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.3733 0.8800 0.072 0.928
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#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.9129 0.5431 0.328 0.672
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.9665 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.9909 0.2199 0.444 0.556
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.8608 0.6096 0.284 0.716
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0000 0.9362 0.000 1.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.9665 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.9362 0.000 1.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.9665 1.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.0000 0.9665 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.9362 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.9362 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.0000 0.9665 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.7219 0.7442 0.200 0.800
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.1843 0.9427 0.972 0.028
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.0000 0.9665 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.9362 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.9362 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.9665 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.9362 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9710 0.3758 0.400 0.600
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.9665 1.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9362 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.9665 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9362 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.9362 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.9665 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.9665 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.9362 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.9362 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.9362 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.9665 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.9362 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9362 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.4939 0.8580 0.892 0.108
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.9665 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.9665 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.9661 0.3129 0.608 0.392
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.9362 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0938 0.9277 0.012 0.988
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9362 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.9362 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.9362 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.9362 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9665 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.0000 0.9362 0.000 1.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.3733 0.8798 0.072 0.928
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.9000 0.5712 0.316 0.684
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.9665 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.9635 0.3384 0.612 0.388
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9362 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9665 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.3879 0.8951 0.924 0.076
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.9665 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9608 0.4156 0.384 0.616
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9665 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9362 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9665 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9665 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9362 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9362 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9665 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9362 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9665 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.7219 0.7442 0.200 0.800
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9665 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9665 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9362 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9362 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9665 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9362 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9665 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9665 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9362 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9665 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9362 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9665 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9665 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.7299 0.7390 0.204 0.796
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9665 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9362 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0376 0.9633 0.996 0.004
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9665 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.91758 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4654 0.68272 0.208 0.000 0.792
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.3038 0.82645 0.104 0.896 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.6062 0.48994 0.616 0.000 0.384
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0237 0.91627 0.004 0.996 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.91758 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0237 0.81302 0.996 0.000 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4931 0.65714 0.768 0.000 0.232
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0237 0.81302 0.996 0.000 0.004
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3879 0.72217 0.848 0.000 0.152
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0237 0.91627 0.004 0.996 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0000 0.81306 1.000 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.81306 1.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.91758 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.6057 0.49531 0.340 0.656 0.004
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6008 0.42373 0.000 0.372 0.628
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.91758 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6045 0.40703 0.000 0.380 0.620
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.91758 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.9262 0.20466 0.436 0.408 0.156
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.8350 0.50422 0.600 0.280 0.120
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0747 0.90869 0.016 0.984 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.76192 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4654 0.68272 0.208 0.000 0.792
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.6798 0.25976 0.400 0.584 0.016
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0237 0.91627 0.004 0.996 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6111 0.47234 0.604 0.000 0.396
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6302 -0.19436 0.480 0.000 0.520
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0237 0.81302 0.996 0.000 0.004
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0424 0.91410 0.008 0.992 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.6267 -0.10928 0.452 0.000 0.548
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.91758 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.6267 0.39907 0.452 0.000 0.548
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0237 0.81302 0.996 0.000 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.91758 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4605 0.68540 0.204 0.000 0.796
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0424 0.76160 0.000 0.008 0.992
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6111 0.47234 0.604 0.000 0.396
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0237 0.81302 0.996 0.000 0.004
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3482 0.68211 0.872 0.000 0.128
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0424 0.91411 0.008 0.992 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0237 0.81302 0.996 0.000 0.004
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.91758 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0237 0.91627 0.004 0.996 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0237 0.81302 0.996 0.000 0.004
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.5560 0.51911 0.000 0.700 0.300
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.76192 0.000 0.000 1.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.91758 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.91758 0.000 1.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.91758 0.000 1.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.4887 0.65029 0.000 0.772 0.228
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0424 0.81136 0.992 0.000 0.008
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0424 0.81136 0.992 0.000 0.008
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0000 0.76192 0.000 0.000 1.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5098 0.64323 0.752 0.000 0.248
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0237 0.81302 0.996 0.000 0.004
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.6398 0.35579 0.580 0.416 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3116 0.73802 0.000 0.108 0.892
#> F043185A-D4D2-4503-93FA-A7B7DA684290 3 0.3686 0.70104 0.000 0.140 0.860
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.0475 0.91490 0.004 0.992 0.004
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0237 0.81302 0.996 0.000 0.004
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.91758 0.000 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3038 0.75554 0.896 0.000 0.104
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.6111 0.47234 0.604 0.000 0.396
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.5926 0.54159 0.356 0.000 0.644
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.91758 0.000 1.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0237 0.91627 0.004 0.996 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.5560 0.55372 0.300 0.700 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0237 0.81302 0.996 0.000 0.004
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4452 0.69011 0.808 0.000 0.192
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0237 0.81302 0.996 0.000 0.004
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0237 0.81302 0.996 0.000 0.004
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.4702 0.67837 0.000 0.788 0.212
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0000 0.81306 1.000 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.5835 0.42165 0.000 0.660 0.340
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0424 0.91411 0.008 0.992 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.91758 0.000 1.000 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.4784 0.69561 0.004 0.796 0.200
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.5810 0.21379 0.664 0.000 0.336
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0237 0.81302 0.996 0.000 0.004
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.6111 0.47234 0.604 0.000 0.396
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.5810 0.49142 0.000 0.336 0.664
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.5791 0.70861 0.060 0.148 0.792
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.5497 0.37894 0.292 0.000 0.708
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0237 0.76188 0.000 0.004 0.996
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.6299 0.30596 0.524 0.000 0.476
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.91758 0.000 1.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 3 0.6126 0.48898 0.400 0.000 0.600
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.91758 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.6111 0.47234 0.604 0.000 0.396
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.0000 0.81306 1.000 0.000 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 1 0.6235 0.30780 0.564 0.436 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.91758 0.000 1.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.6111 0.37209 0.000 0.396 0.604
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.9987 0.13228 0.356 0.332 0.312
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0747 0.80669 0.984 0.000 0.016
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.81306 1.000 0.000 0.000
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#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0237 0.91627 0.004 0.996 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.91758 0.000 1.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0237 0.81302 0.996 0.000 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.91758 0.000 1.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.91758 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6906 0.49665 0.032 0.324 0.644
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.6204 0.44857 0.424 0.000 0.576
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.5905 0.53126 0.648 0.000 0.352
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.9408 0.41879 0.196 0.316 0.488
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.5058 0.66979 0.244 0.756 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.4002 0.69996 0.840 0.160 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0237 0.91530 0.000 0.996 0.004
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.91758 0.000 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.91758 0.000 1.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.91758 0.000 1.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5810 0.56499 0.336 0.000 0.664
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6286 0.19047 0.000 0.464 0.536
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.6451 0.37225 0.384 0.608 0.008
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.5115 0.65597 0.004 0.768 0.228
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.76192 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.6109 0.66536 0.760 0.048 0.192
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.91758 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.81306 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0237 0.76188 0.000 0.004 0.996
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.6111 0.47234 0.604 0.000 0.396
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.8434 0.00706 0.088 0.496 0.416
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0424 0.81136 0.992 0.000 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.91758 0.000 1.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.6045 0.50576 0.380 0.000 0.620
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0237 0.81302 0.996 0.000 0.004
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0237 0.91627 0.004 0.996 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.91758 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6314 0.47511 0.604 0.004 0.392
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.91758 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0237 0.81302 0.996 0.000 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6008 0.42373 0.000 0.372 0.628
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6318 0.54391 0.356 0.008 0.636
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0237 0.81302 0.996 0.000 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.91758 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.1163 0.89803 0.028 0.972 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.76192 0.000 0.000 1.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0424 0.91411 0.008 0.992 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0237 0.81302 0.996 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.76192 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0237 0.91627 0.004 0.996 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0424 0.81136 0.992 0.000 0.008
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.2796 0.83503 0.092 0.908 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.0892 0.75991 0.020 0.000 0.980
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0237 0.81158 0.996 0.000 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.6045 0.40703 0.000 0.380 0.620
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4555 0.68787 0.200 0.000 0.800
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.91758 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.76192 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5269 0.68663 0.200 0.016 0.784
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1902 0.7798 0.000 0.932 0.004 0.064
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5723 0.6513 0.220 0.000 0.696 0.084
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6111 0.5990 0.256 0.652 0.092 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 4 0.2466 0.7318 0.056 0.000 0.028 0.916
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5949 0.6614 0.068 0.644 0.288 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2593 0.7591 0.000 0.892 0.004 0.104
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1489 0.8599 0.952 0.000 0.004 0.044
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 4 0.3649 0.6242 0.204 0.000 0.000 0.796
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1722 0.8563 0.944 0.000 0.008 0.048
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 4 0.4720 0.5238 0.264 0.016 0.000 0.720
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5512 0.6743 0.040 0.660 0.300 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1211 0.8449 0.960 0.000 0.040 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0469 0.8555 0.988 0.000 0.012 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1661 0.7842 0.000 0.944 0.004 0.052
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.6212 0.3950 0.560 0.060 0.380 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4610 0.6288 0.000 0.236 0.744 0.020
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0524 0.7941 0.004 0.988 0.008 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4175 0.6373 0.000 0.212 0.776 0.012
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1411 0.7965 0.020 0.960 0.020 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.4535 0.5767 0.000 0.292 0.004 0.704
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.4454 0.5568 0.000 0.308 0.000 0.692
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7160 0.5450 0.048 0.600 0.068 0.284
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4356 0.5737 0.000 0.000 0.708 0.292
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5669 0.6581 0.200 0.000 0.708 0.092
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.7563 0.1798 0.480 0.368 0.140 0.012
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.5222 0.6945 0.032 0.688 0.280 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 4 0.0895 0.7465 0.020 0.004 0.000 0.976
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 4 0.1807 0.7363 0.008 0.000 0.052 0.940
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1929 0.8517 0.940 0.000 0.036 0.024
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.4780 0.7478 0.096 0.788 0.116 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 4 0.1305 0.7415 0.004 0.000 0.036 0.960
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1118 0.7895 0.000 0.964 0.000 0.036
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4343 0.5715 0.732 0.000 0.264 0.004
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1452 0.8591 0.956 0.000 0.008 0.036
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1452 0.7885 0.000 0.956 0.008 0.036
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.5775 0.6528 0.212 0.000 0.696 0.092
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4808 0.6075 0.000 0.028 0.736 0.236
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.0707 0.7465 0.020 0.000 0.000 0.980
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.2214 0.8512 0.928 0.000 0.028 0.044
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3919 0.7808 0.840 0.000 0.104 0.056
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.6978 0.6842 0.112 0.656 0.192 0.040
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1975 0.8600 0.936 0.000 0.016 0.048
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.1398 0.7878 0.000 0.956 0.004 0.040
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.5624 0.6803 0.052 0.668 0.280 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.5471 0.7032 0.740 0.088 0.004 0.168
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.4720 0.5440 0.000 0.324 0.004 0.672
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4961 0.3069 0.000 0.000 0.552 0.448
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2334 0.7688 0.000 0.908 0.004 0.088
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.4030 0.7709 0.000 0.836 0.072 0.092
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1356 0.7892 0.000 0.960 0.008 0.032
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4584 0.2911 0.000 0.300 0.696 0.004
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.3885 0.7964 0.844 0.000 0.064 0.092
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.2918 0.8156 0.876 0.000 0.008 0.116
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 4 0.4356 0.4512 0.000 0.000 0.292 0.708
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 4 0.2530 0.7117 0.100 0.000 0.004 0.896
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.1389 0.8584 0.952 0.000 0.000 0.048
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.3837 0.6452 0.000 0.224 0.000 0.776
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.5056 0.6227 0.000 0.044 0.732 0.224
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.5577 0.5373 0.000 0.328 0.036 0.636
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.5475 0.6717 0.036 0.656 0.308 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.1118 0.8604 0.964 0.000 0.000 0.036
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0895 0.7920 0.000 0.976 0.020 0.004
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4098 0.6777 0.784 0.000 0.012 0.204
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 4 0.0707 0.7465 0.020 0.000 0.000 0.980
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.5184 0.5750 0.304 0.000 0.672 0.024
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1978 0.7891 0.000 0.928 0.068 0.004
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.5392 0.6868 0.040 0.680 0.280 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.4300 0.7175 0.820 0.088 0.092 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.1576 0.8588 0.948 0.000 0.004 0.048
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4406 0.5915 0.700 0.000 0.000 0.300
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.1743 0.8573 0.940 0.000 0.004 0.056
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1305 0.8594 0.960 0.000 0.004 0.036
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.5478 0.3634 0.000 0.628 0.344 0.028
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.4687 0.7335 0.784 0.012 0.176 0.028
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.4769 0.5474 0.000 0.308 0.684 0.008
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.2718 0.7934 0.056 0.912 0.020 0.012
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.2040 0.7921 0.004 0.936 0.012 0.048
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.5762 -0.0422 0.040 0.352 0.608 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1389 0.8466 0.952 0.000 0.048 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2048 0.8504 0.928 0.000 0.008 0.064
#> F4F647DC-C630-429C-AD49-ADA43B652781 4 0.0921 0.7453 0.028 0.000 0.000 0.972
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4951 0.6401 0.000 0.212 0.744 0.044
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.5687 0.6536 0.020 0.180 0.736 0.064
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.2271 0.7258 0.008 0.000 0.076 0.916
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.4910 0.5881 0.000 0.020 0.704 0.276
#> E435C03F-0277-49C1-83EF-19452082723E 4 0.2300 0.7372 0.028 0.000 0.048 0.924
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2266 0.7889 0.004 0.912 0.084 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.4797 0.5540 0.720 0.020 0.260 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.2048 0.7805 0.000 0.928 0.008 0.064
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 4 0.1305 0.7452 0.000 0.036 0.004 0.960
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.5889 0.6533 0.712 0.012 0.196 0.080
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.5419 0.3125 0.008 0.600 0.008 0.384
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.1256 0.7896 0.000 0.964 0.008 0.028
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4692 0.6535 0.040 0.176 0.780 0.004
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.2486 0.7397 0.004 0.048 0.028 0.920
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.5180 0.6475 0.740 0.000 0.196 0.064
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0592 0.8596 0.984 0.000 0.000 0.016
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 4 0.0921 0.7453 0.028 0.000 0.000 0.972
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.8501 0.4439 0.044 0.244 0.472 0.240
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.4429 0.6864 0.764 0.004 0.220 0.012
#> E3A5FB64-EB24-4A24-9B79-539012C57711 4 0.2831 0.6939 0.000 0.004 0.120 0.876
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.2081 0.8413 0.916 0.000 0.000 0.084
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.3392 0.7770 0.020 0.856 0.124 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.5714 0.6608 0.156 0.000 0.716 0.128
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.4100 0.7627 0.036 0.816 0.148 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.4955 0.3279 0.000 0.000 0.556 0.444
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.5764 0.6631 0.052 0.644 0.304 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.2342 0.6218 0.000 0.080 0.912 0.008
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.2281 0.8132 0.904 0.000 0.096 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 4 0.4963 0.5759 0.000 0.284 0.020 0.696
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#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4201 0.6812 0.004 0.788 0.012 0.196
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4959 0.6456 0.000 0.196 0.752 0.052
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0524 0.8579 0.988 0.000 0.004 0.008
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1743 0.7829 0.000 0.940 0.004 0.056
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 4 0.1637 0.7309 0.000 0.000 0.060 0.940
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.4252 0.5887 0.000 0.744 0.004 0.252
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.3681 0.7116 0.004 0.104 0.036 0.856
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1209 0.8598 0.964 0.000 0.004 0.032
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1545 0.8586 0.952 0.000 0.008 0.040
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.4980 0.7029 0.008 0.708 0.272 0.012
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.6907 0.5544 0.120 0.532 0.348 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1661 0.7931 0.004 0.944 0.052 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1545 0.8585 0.952 0.000 0.008 0.040
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1743 0.7898 0.004 0.940 0.056 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.2611 0.7991 0.020 0.920 0.040 0.020
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.1139 0.6358 0.008 0.012 0.972 0.008
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.5364 0.1943 0.592 0.000 0.392 0.016
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 4 0.2675 0.7114 0.100 0.000 0.008 0.892
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.7210 0.6226 0.228 0.156 0.600 0.016
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.6595 0.4967 0.628 0.160 0.212 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.6675 0.5395 0.644 0.092 0.244 0.020
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4868 0.6378 0.000 0.720 0.024 0.256
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.2179 0.7809 0.000 0.924 0.012 0.064
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4776 0.7090 0.016 0.712 0.272 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4049 0.7401 0.008 0.780 0.212 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4720 0.6635 0.212 0.008 0.760 0.020
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.3401 0.6329 0.000 0.152 0.840 0.008
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.4188 0.7158 0.812 0.040 0.148 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.7650 0.4486 0.124 0.464 0.392 0.020
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 4 0.4790 0.2316 0.000 0.000 0.380 0.620
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6927 0.5801 0.100 0.060 0.164 0.676
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1975 0.7845 0.000 0.936 0.016 0.048
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1151 0.8607 0.968 0.000 0.008 0.024
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.3710 0.6166 0.000 0.004 0.192 0.804
#> C20F209A-2102-4502-80FA-17AF04601987 4 0.1284 0.7454 0.024 0.000 0.012 0.964
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6201 0.4043 0.300 0.080 0.620 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2124 0.8486 0.924 0.000 0.008 0.068
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2197 0.7872 0.004 0.916 0.080 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.7068 0.2286 0.548 0.000 0.296 0.156
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.1398 0.8590 0.956 0.000 0.004 0.040
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4123 0.7629 0.044 0.820 0.136 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2053 0.7965 0.004 0.924 0.072 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.3325 0.6966 0.112 0.000 0.024 0.864
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1109 0.7918 0.000 0.968 0.004 0.028
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2011 0.8467 0.920 0.000 0.000 0.080
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4399 0.6342 0.000 0.224 0.760 0.016
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3584 0.6676 0.152 0.008 0.836 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1624 0.8568 0.952 0.000 0.028 0.020
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1890 0.7860 0.000 0.936 0.008 0.056
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.7080 0.5556 0.196 0.568 0.236 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 4 0.4907 0.1145 0.000 0.000 0.420 0.580
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2650 0.7911 0.036 0.916 0.008 0.040
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1624 0.8556 0.952 0.000 0.028 0.020
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4560 0.5707 0.004 0.000 0.700 0.296
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1833 0.7949 0.024 0.944 0.032 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4194 0.6973 0.764 0.000 0.008 0.228
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.7518 0.4847 0.204 0.476 0.320 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.4936 0.5809 0.020 0.000 0.700 0.280
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2101 0.8445 0.928 0.000 0.060 0.012
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3306 0.6500 0.000 0.156 0.840 0.004
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.6352 0.6589 0.044 0.160 0.712 0.084
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2089 0.7834 0.000 0.932 0.020 0.048
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.4008 0.5517 0.000 0.000 0.244 0.756
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5239 0.6770 0.176 0.016 0.760 0.048
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0324 0.83914 0.000 0.992 0.004 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3480 0.65272 0.248 0.000 0.752 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5317 0.69566 0.072 0.084 0.104 0.740 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0290 0.83640 0.000 0.000 0.008 0.000 0.992
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.1211 0.73399 0.000 0.024 0.016 0.960 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.83897 0.000 1.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1153 0.86578 0.964 0.000 0.004 0.024 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.0579 0.83646 0.008 0.000 0.008 0.000 0.984
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2954 0.79353 0.876 0.056 0.004 0.000 0.064
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.1522 0.73375 0.000 0.012 0.044 0.944 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.4193 0.52621 0.304 0.000 0.012 0.684 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.1597 0.84754 0.940 0.000 0.012 0.048 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0703 0.84112 0.000 0.976 0.024 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.1831 0.72426 0.000 0.000 0.076 0.920 0.004
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.1732 0.76336 0.000 0.080 0.920 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1942 0.83819 0.000 0.920 0.068 0.012 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0963 0.78371 0.000 0.036 0.964 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2782 0.82865 0.000 0.880 0.072 0.048 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.4101 0.44131 0.000 0.628 0.000 0.000 0.372
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 5 0.4816 -0.03311 0.008 0.488 0.008 0.000 0.496
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.5162 0.54203 0.000 0.004 0.076 0.248 0.672
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4223 0.63354 0.000 0.000 0.724 0.028 0.248
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.2621 0.75740 0.112 0.000 0.876 0.004 0.008
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6171 0.44560 0.588 0.256 0.144 0.012 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.2012 0.72900 0.000 0.060 0.020 0.920 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0404 0.83408 0.000 0.012 0.000 0.000 0.988
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0404 0.83627 0.000 0.000 0.012 0.000 0.988
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.6279 0.27308 0.004 0.328 0.148 0.520 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0162 0.83649 0.000 0.000 0.004 0.000 0.996
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0162 0.83962 0.000 0.996 0.004 0.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4113 0.65627 0.740 0.000 0.232 0.028 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1270 0.83951 0.000 0.948 0.052 0.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.2286 0.76422 0.108 0.000 0.888 0.000 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.5353 0.67147 0.000 0.004 0.684 0.156 0.156
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0404 0.83412 0.000 0.012 0.000 0.000 0.988
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0162 0.87594 0.996 0.000 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.2358 0.73014 0.000 0.104 0.008 0.888 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5075 0.35200 0.604 0.000 0.016 0.360 0.020
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0566 0.84035 0.000 0.984 0.012 0.000 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.2144 0.72701 0.000 0.068 0.020 0.912 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.1965 0.80471 0.904 0.096 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.3508 0.64441 0.000 0.748 0.000 0.000 0.252
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4273 0.20383 0.000 0.000 0.552 0.000 0.448
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0609 0.84108 0.000 0.980 0.020 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.5387 0.60245 0.000 0.684 0.008 0.120 0.188
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1410 0.83819 0.000 0.940 0.060 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.5155 0.58603 0.000 0.168 0.692 0.140 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0290 0.87504 0.992 0.000 0.008 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.3816 0.55100 0.000 0.000 0.304 0.000 0.696
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.0566 0.83661 0.004 0.000 0.012 0.000 0.984
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.3053 0.72531 0.000 0.164 0.008 0.000 0.828
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.1106 0.79219 0.000 0.012 0.964 0.000 0.024
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.1478 0.82489 0.000 0.936 0.000 0.000 0.064
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.1357 0.73188 0.000 0.000 0.048 0.948 0.004
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0162 0.87624 0.996 0.000 0.000 0.004 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.1478 0.83846 0.000 0.936 0.064 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.7065 0.11655 0.072 0.000 0.092 0.440 0.396
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0162 0.83564 0.000 0.004 0.000 0.000 0.996
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4074 0.45488 0.364 0.000 0.636 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2462 0.82113 0.000 0.880 0.112 0.008 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.2464 0.71399 0.000 0.096 0.016 0.888 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.4752 0.43209 0.648 0.000 0.036 0.316 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0324 0.87549 0.992 0.000 0.004 0.004 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.1854 0.81847 0.036 0.000 0.008 0.020 0.936
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0324 0.87549 0.992 0.000 0.004 0.004 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4375 0.13100 0.000 0.420 0.576 0.000 0.004
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4920 0.46092 0.348 0.024 0.008 0.620 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.2648 0.70004 0.000 0.152 0.848 0.000 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4049 0.57943 0.004 0.724 0.004 0.264 0.004
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.2199 0.81914 0.000 0.916 0.008 0.060 0.016
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.1116 0.73450 0.000 0.004 0.028 0.964 0.004
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2574 0.80291 0.876 0.000 0.112 0.012 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0162 0.83564 0.000 0.004 0.000 0.000 0.996
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.1197 0.78130 0.000 0.048 0.952 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.1469 0.78492 0.016 0.036 0.948 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.1544 0.81444 0.000 0.000 0.068 0.000 0.932
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.1522 0.79405 0.000 0.012 0.944 0.000 0.044
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.0404 0.83610 0.000 0.000 0.012 0.000 0.988
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2727 0.81668 0.000 0.868 0.116 0.016 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.3727 0.67683 0.768 0.000 0.216 0.016 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.83897 0.000 1.000 0.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.1121 0.82084 0.000 0.044 0.000 0.000 0.956
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.3458 0.72808 0.072 0.008 0.012 0.860 0.048
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#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.3707 0.59077 0.000 0.000 0.284 0.000 0.716
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.2891 0.73057 0.000 0.000 0.176 0.000 0.824
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.2153 0.83838 0.000 0.916 0.044 0.000 0.040
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.5320 0.21918 0.424 0.000 0.052 0.524 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.5256 0.14762 0.532 0.000 0.048 0.420 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.4242 0.19789 0.572 0.000 0.428 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.3661 0.69845 0.008 0.028 0.008 0.832 0.124
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.2338 0.82342 0.000 0.884 0.112 0.004 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.2283 0.81503 0.040 0.000 0.036 0.008 0.916
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 4 0.7129 -0.01710 0.000 0.024 0.204 0.408 0.364
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 5 0.4337 0.69930 0.004 0.156 0.008 0.052 0.780
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.3362 0.77418 0.000 0.080 0.844 0.000 0.076
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.3750 0.64699 0.232 0.012 0.756 0.000 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.5201 0.19447 0.000 0.000 0.424 0.044 0.532
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0290 0.83801 0.000 0.992 0.000 0.000 0.008
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.7411 0.45745 0.296 0.088 0.132 0.484 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.3697 0.72520 0.000 0.796 0.016 0.180 0.008
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.3661 0.59959 0.000 0.000 0.276 0.000 0.724
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.2241 0.79560 0.008 0.076 0.008 0.000 0.908
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.3476 0.76369 0.000 0.000 0.836 0.088 0.076
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.1701 0.79471 0.000 0.016 0.936 0.000 0.048
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.2588 0.80288 0.060 0.892 0.000 0.000 0.048
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.3596 0.65135 0.212 0.000 0.012 0.776 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.2424 0.81229 0.000 0.868 0.132 0.000 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.2050 0.80390 0.008 0.064 0.008 0.000 0.920
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.5119 0.25026 0.000 0.048 0.592 0.360 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0290 0.83640 0.000 0.000 0.008 0.000 0.992
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1364 0.83191 0.000 0.952 0.012 0.036 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.6674 0.44079 0.324 0.032 0.124 0.520 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.2471 0.76477 0.000 0.000 0.136 0.000 0.864
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.1043 0.78283 0.000 0.040 0.960 0.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5025 0.61140 0.172 0.124 0.704 0.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.1671 0.81181 0.000 0.000 0.076 0.000 0.924
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3764 0.67912 0.000 0.044 0.156 0.800 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.4803 0.05562 0.000 0.444 0.020 0.536 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.1564 0.79459 0.024 0.004 0.948 0.000 0.024
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4822 0.46863 0.000 0.628 0.008 0.020 0.344
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.1121 0.78190 0.000 0.044 0.956 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.3628 0.67019 0.772 0.000 0.012 0.216 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0609 0.84108 0.000 0.980 0.020 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0703 0.83376 0.000 0.000 0.024 0.000 0.976
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0579 0.83959 0.000 0.984 0.008 0.000 0.008
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.3636 0.76064 0.004 0.096 0.016 0.040 0.844
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.3501 0.70518 0.000 0.044 0.068 0.856 0.032
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.1478 0.72839 0.000 0.000 0.064 0.936 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.2707 0.80848 0.000 0.876 0.024 0.100 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.2361 0.82767 0.000 0.892 0.096 0.012 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.3561 0.63339 0.000 0.740 0.000 0.260 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.2848 0.72912 0.000 0.000 0.840 0.156 0.004
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.2230 0.79911 0.884 0.000 0.116 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.0451 0.83626 0.008 0.000 0.004 0.000 0.988
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.5759 0.30950 0.568 0.108 0.324 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2719 0.71366 0.144 0.004 0.000 0.852 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.1725 0.73772 0.044 0.000 0.020 0.936 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.2727 0.77241 0.000 0.116 0.016 0.000 0.868
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1410 0.83845 0.000 0.940 0.060 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.4671 0.37460 0.000 0.332 0.028 0.640 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.4648 0.00366 0.000 0.464 0.012 0.524 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.1469 0.78647 0.036 0.016 0.948 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0898 0.78578 0.000 0.020 0.972 0.008 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.1608 0.84004 0.928 0.000 0.072 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.1012 0.73543 0.000 0.000 0.012 0.968 0.020
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.3999 0.47120 0.000 0.000 0.344 0.000 0.656
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.4989 0.57014 0.004 0.048 0.008 0.244 0.696
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0162 0.83959 0.000 0.996 0.004 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0955 0.86668 0.968 0.000 0.004 0.028 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3177 0.69360 0.000 0.000 0.208 0.000 0.792
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.0162 0.83649 0.000 0.000 0.004 0.000 0.996
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.4825 0.13575 0.024 0.000 0.568 0.408 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1095 0.86854 0.968 0.000 0.008 0.012 0.012
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2488 0.81583 0.000 0.872 0.124 0.004 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.6745 0.47703 0.292 0.000 0.520 0.024 0.164
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6456 0.23959 0.000 0.468 0.192 0.340 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.3427 0.72717 0.000 0.796 0.012 0.192 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.2820 0.79893 0.004 0.000 0.056 0.056 0.884
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0451 0.83807 0.000 0.988 0.004 0.008 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0833 0.86970 0.976 0.000 0.004 0.004 0.016
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.1043 0.78283 0.000 0.040 0.960 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.2131 0.77909 0.008 0.000 0.920 0.056 0.016
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0290 0.87499 0.992 0.000 0.008 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2977 0.79475 0.000 0.876 0.008 0.076 0.040
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.2719 0.69730 0.000 0.004 0.144 0.852 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.4060 0.43800 0.000 0.000 0.360 0.000 0.640
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2234 0.81491 0.016 0.916 0.004 0.060 0.004
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.87713 1.000 0.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2280 0.76683 0.000 0.000 0.880 0.000 0.120
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1952 0.83220 0.000 0.912 0.084 0.004 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0162 0.87637 0.996 0.000 0.000 0.000 0.004
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.1121 0.73289 0.000 0.000 0.044 0.956 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.3462 0.70310 0.000 0.000 0.792 0.012 0.196
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.7135 0.30938 0.268 0.000 0.276 0.436 0.020
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0671 0.78691 0.000 0.004 0.980 0.016 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.1750 0.78482 0.028 0.036 0.936 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1043 0.84108 0.000 0.960 0.040 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3508 0.64741 0.000 0.000 0.252 0.000 0.748
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.1117 0.78739 0.016 0.020 0.964 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1485 0.80800 0.000 0.944 0.000 0.004 0.028 0.024
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3695 0.36972 0.376 0.000 0.624 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5360 0.66236 0.076 0.176 0.040 0.692 0.004 0.012
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0291 0.85651 0.000 0.000 0.000 0.004 0.992 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0937 0.80675 0.000 0.000 0.000 0.040 0.000 0.960
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1218 0.80954 0.000 0.956 0.000 0.004 0.028 0.012
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.3874 0.63237 0.276 0.008 0.000 0.704 0.012 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.2022 0.84334 0.000 0.000 0.008 0.052 0.916 0.024
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.87291 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0520 0.87081 0.984 0.000 0.000 0.008 0.008 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.4831 0.58988 0.000 0.000 0.168 0.668 0.000 0.164
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2920 0.73952 0.168 0.000 0.004 0.820 0.000 0.008
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3653 0.53261 0.692 0.000 0.008 0.300 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.81102 0.000 1.000 0.000 0.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.1647 0.75558 0.004 0.000 0.032 0.940 0.008 0.016
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.1910 0.74792 0.000 0.108 0.892 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1434 0.80896 0.000 0.948 0.024 0.008 0.000 0.020
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0547 0.78558 0.000 0.020 0.980 0.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2494 0.80531 0.000 0.896 0.028 0.040 0.000 0.036
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3243 0.70872 0.000 0.780 0.004 0.008 0.208 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.4032 0.36752 0.000 0.572 0.000 0.008 0.420 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4761 0.64092 0.000 0.012 0.088 0.688 0.212 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4756 0.64272 0.000 0.000 0.696 0.060 0.216 0.028
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.1663 0.75685 0.088 0.000 0.912 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5435 0.60140 0.660 0.180 0.112 0.048 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.1320 0.81177 0.000 0.016 0.000 0.036 0.000 0.948
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0520 0.85208 0.000 0.008 0.000 0.008 0.984 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0260 0.85664 0.000 0.000 0.008 0.000 0.992 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0806 0.86665 0.972 0.000 0.000 0.008 0.000 0.020
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.5933 0.46961 0.004 0.576 0.108 0.272 0.000 0.040
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0520 0.85577 0.000 0.000 0.008 0.008 0.984 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0713 0.81073 0.000 0.972 0.000 0.000 0.000 0.028
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.4854 0.57516 0.184 0.000 0.664 0.152 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.87291 1.000 0.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0837 0.81078 0.000 0.972 0.020 0.004 0.000 0.004
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.1949 0.75625 0.088 0.000 0.904 0.004 0.000 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 6 0.4402 0.51105 0.000 0.000 0.268 0.000 0.060 0.672
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0405 0.85396 0.000 0.008 0.000 0.004 0.988 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0146 0.87278 0.996 0.000 0.004 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0993 0.86368 0.964 0.000 0.000 0.012 0.000 0.024
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.3336 0.71530 0.000 0.056 0.000 0.812 0.000 0.132
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.3766 0.65757 0.256 0.000 0.000 0.720 0.024 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0508 0.81207 0.000 0.984 0.004 0.012 0.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.1010 0.80920 0.000 0.004 0.000 0.036 0.000 0.960
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3163 0.67632 0.780 0.212 0.000 0.004 0.004 0.000
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#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4289 0.43316 0.000 0.000 0.028 0.612 0.360 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2340 0.76587 0.000 0.852 0.000 0.000 0.000 0.148
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1036 0.86463 0.964 0.004 0.000 0.024 0.008 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.1444 0.76906 0.000 0.072 0.928 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3510 0.70625 0.000 0.000 0.772 0.204 0.008 0.016
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0260 0.87226 0.992 0.000 0.008 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4801 0.61331 0.000 0.672 0.000 0.016 0.068 0.244
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.4301 0.59192 0.000 0.000 0.240 0.696 0.000 0.064
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3828 0.64332 0.000 0.000 0.252 0.016 0.724 0.008
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3601 0.77023 0.044 0.824 0.000 0.040 0.000 0.092
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1003 0.86506 0.964 0.000 0.000 0.016 0.000 0.020
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1010 0.78656 0.000 0.000 0.960 0.004 0.036 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2168 0.80234 0.036 0.916 0.028 0.016 0.000 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0291 0.87237 0.992 0.000 0.000 0.004 0.004 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.1777 0.75047 0.004 0.000 0.024 0.928 0.000 0.044
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.4286 0.69717 0.000 0.000 0.728 0.108 0.164 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.2107 0.75521 0.012 0.000 0.036 0.920 0.008 0.024
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.1349 0.78395 0.000 0.004 0.940 0.056 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0972 0.78307 0.008 0.028 0.964 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0603 0.81143 0.000 0.980 0.016 0.000 0.000 0.004
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3081 0.72598 0.000 0.004 0.220 0.000 0.776 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0363 0.78637 0.000 0.012 0.988 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.155 0.516 0.789 0.3559 0.654 0.654
#> 3 3 0.173 0.509 0.721 0.4563 0.753 0.645
#> 4 4 0.304 0.463 0.706 0.2382 0.771 0.566
#> 5 5 0.373 0.479 0.691 0.0893 0.904 0.737
#> 6 6 0.397 0.371 0.621 0.0539 0.905 0.712
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.9996 0.3739 0.488 0.512
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.7224 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.9866 0.1444 0.568 0.432
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.7224 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.9427 0.4032 0.640 0.360
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 1 1.0000 -0.3409 0.500 0.500
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0938 0.7257 0.988 0.012
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.7224 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0376 0.7229 0.996 0.004
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0376 0.7229 0.996 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.9393 0.5588 0.356 0.644
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.8763 0.5073 0.704 0.296
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5059 0.7120 0.888 0.112
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.9977 0.4055 0.472 0.528
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.8909 0.4822 0.692 0.308
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.9954 -0.2062 0.540 0.460
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.7139 0.6631 0.196 0.804
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.9933 -0.1773 0.548 0.452
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.7139 0.6631 0.196 0.804
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.8267 0.5510 0.740 0.260
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.9944 -0.1890 0.544 0.456
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.9815 0.1762 0.580 0.420
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.5408 0.7052 0.876 0.124
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0938 0.7255 0.988 0.012
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3584 0.7244 0.932 0.068
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.9460 0.5597 0.364 0.636
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.1184 0.7259 0.984 0.016
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.7224 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.7224 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.9933 0.3402 0.452 0.548
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0672 0.7237 0.992 0.008
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.9686 0.5565 0.396 0.604
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.8207 0.5723 0.744 0.256
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.7224 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.7219 0.6641 0.200 0.800
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.7224 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.9881 0.3454 0.436 0.564
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.7224 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5842 0.7019 0.860 0.140
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.7224 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.7219 0.6636 0.200 0.800
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6148 0.6943 0.848 0.152
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.7219 0.6641 0.200 0.800
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0672 0.5510 0.008 0.992
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6148 0.6767 0.848 0.152
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.9963 -0.2192 0.536 0.464
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.1414 0.7266 0.980 0.020
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.9996 0.3739 0.488 0.512
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.8555 0.6464 0.280 0.720
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 1.0000 0.3456 0.496 0.504
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.9323 0.4814 0.348 0.652
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0376 0.7229 0.996 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.7224 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.7224 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.7224 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.7224 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.6531 0.6821 0.832 0.168
#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.9933 -0.1773 0.548 0.452
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.9522 0.1808 0.628 0.372
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.6712 0.6815 0.824 0.176
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.7224 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.9710 0.5516 0.400 0.600
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.8499 0.5372 0.724 0.276
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0376 0.7235 0.996 0.004
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0672 0.7249 0.992 0.008
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 1 0.9998 -0.3143 0.508 0.492
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 1 0.9881 0.1303 0.564 0.436
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.9850 0.1640 0.572 0.428
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0376 0.7229 0.996 0.004
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.7224 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.5946 0.6838 0.856 0.144
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.7224 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 1 0.9944 -0.1044 0.544 0.456
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9775 0.1961 0.588 0.412
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 1.0000 0.3453 0.496 0.504
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 1.0000 -0.1579 0.504 0.496
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.1633 0.5540 0.024 0.976
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.7139 0.6532 0.804 0.196
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3114 0.7261 0.944 0.056
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.7224 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0938 0.7254 0.988 0.012
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.9815 -0.0307 0.580 0.420
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.5842 0.6760 0.860 0.140
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.9129 0.3671 0.672 0.328
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.7950 0.4665 0.760 0.240
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.1633 0.7267 0.976 0.024
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 1 0.9998 -0.3143 0.508 0.492
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.5059 0.7129 0.888 0.112
#> 7DA4280C-511E-493E-B187-88ECCA427C33 1 0.9993 -0.2859 0.516 0.484
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0672 0.7241 0.992 0.008
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.8955 0.4873 0.688 0.312
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 1 0.8909 0.4051 0.692 0.308
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.9710 0.5516 0.400 0.600
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.6712 0.6636 0.824 0.176
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.9896 0.3366 0.440 0.560
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.5408 0.7007 0.876 0.124
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.1184 0.7262 0.984 0.016
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.1184 0.7259 0.984 0.016
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.8555 0.5535 0.720 0.280
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.8499 0.5372 0.724 0.276
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.3274 0.7233 0.940 0.060
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0376 0.7229 0.996 0.004
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.9286 0.6091 0.344 0.656
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0376 0.7235 0.996 0.004
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.7453 0.6315 0.788 0.212
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.7299 0.5947 0.796 0.204
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.9393 0.5572 0.356 0.644
#> 5D663B98-8416-4305-A891-111B7A4DC40B 1 0.8267 0.5488 0.740 0.260
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.8713 0.5221 0.708 0.292
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.8661 0.4326 0.712 0.288
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.9000 0.4741 0.684 0.316
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#> F17B682D-A902-4730-A300-5C163209F7CD 1 1.0000 -0.1473 0.504 0.496
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.9323 0.5667 0.348 0.652
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.7224 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.9996 0.2118 0.488 0.512
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0672 0.7246 0.992 0.008
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.7224 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.9044 0.4188 0.680 0.320
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.7224 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.8909 0.4822 0.692 0.308
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6148 0.6890 0.848 0.152
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.7453 0.6226 0.788 0.212
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.5946 0.6957 0.856 0.144
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3274 0.7167 0.940 0.060
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.9795 -0.0145 0.584 0.416
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6148 0.6834 0.848 0.152
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3274 0.7167 0.940 0.060
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5508 0.41038 0.188 0.784 0.028
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.77158 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.9364 0.23655 0.372 0.456 0.172
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.77158 1.000 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.9243 0.39657 0.528 0.264 0.208
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5115 0.40939 0.188 0.796 0.016
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1170 0.77614 0.976 0.008 0.016
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.77158 1.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0592 0.77433 0.988 0.012 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0747 0.77402 0.984 0.016 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.9804 0.26832 0.248 0.416 0.336
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.8624 0.49695 0.596 0.240 0.164
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4749 0.74456 0.844 0.116 0.040
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.6159 0.43826 0.196 0.756 0.048
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.8734 0.47694 0.584 0.248 0.168
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5803 0.44924 0.248 0.736 0.016
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 3 0.6305 0.30179 0.000 0.484 0.516
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.6445 0.46255 0.308 0.672 0.020
#> 479B4832-82DB-4176-9D24-D588F2903617 3 0.6302 0.30237 0.000 0.480 0.520
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.7256 0.04696 0.532 0.440 0.028
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.5619 0.44778 0.244 0.744 0.012
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.9181 0.15296 0.404 0.448 0.148
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.4960 0.74351 0.832 0.128 0.040
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0983 0.77218 0.980 0.016 0.004
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3722 0.76128 0.888 0.088 0.024
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.9356 0.30564 0.216 0.512 0.272
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.1525 0.77432 0.964 0.032 0.004
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.77158 1.000 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.77158 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.9271 0.36769 0.244 0.528 0.228
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0983 0.77438 0.980 0.016 0.004
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.7245 0.27690 0.120 0.712 0.168
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.7983 0.57074 0.648 0.228 0.124
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.77158 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.6309 -0.30522 0.000 0.504 0.496
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.77158 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.9940 0.15163 0.308 0.304 0.388
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0747 0.77431 0.984 0.016 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5852 0.70654 0.776 0.180 0.044
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.77158 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 3 0.7453 0.27389 0.036 0.436 0.528
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5955 0.70668 0.772 0.180 0.048
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.6308 -0.30268 0.000 0.508 0.492
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.4887 0.53601 0.000 0.228 0.772
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6742 0.41608 0.656 0.316 0.028
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.5775 0.45733 0.260 0.728 0.012
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.1647 0.77379 0.960 0.036 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.5508 0.41038 0.188 0.784 0.028
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.8337 0.11998 0.112 0.592 0.296
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.6168 0.45945 0.224 0.740 0.036
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.9715 0.18291 0.220 0.380 0.400
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0747 0.77402 0.984 0.016 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.77158 1.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.77158 1.000 0.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0424 0.77188 0.992 0.008 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0237 0.77243 0.996 0.004 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.7065 0.63754 0.700 0.228 0.072
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.6738 0.44078 0.356 0.624 0.020
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.6769 0.44154 0.392 0.592 0.016
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.6820 0.63588 0.700 0.248 0.052
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0475 0.77397 0.992 0.004 0.004
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.7309 0.27113 0.124 0.708 0.168
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.8245 0.53204 0.624 0.244 0.132
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0592 0.77375 0.988 0.012 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0661 0.77289 0.988 0.008 0.004
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.5414 0.43045 0.212 0.772 0.016
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.9405 0.21686 0.376 0.448 0.176
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.9425 0.24592 0.488 0.312 0.200
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0592 0.77433 0.988 0.012 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.77158 1.000 0.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.5449 0.72565 0.816 0.116 0.068
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0237 0.77243 0.996 0.004 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.7587 0.46581 0.288 0.640 0.072
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9243 0.23525 0.520 0.192 0.288
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.7112 0.47100 0.260 0.680 0.060
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.9347 0.38539 0.288 0.508 0.204
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.5884 0.52849 0.012 0.272 0.716
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.6757 0.67546 0.736 0.180 0.084
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2680 0.77258 0.924 0.068 0.008
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.77158 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.1315 0.77454 0.972 0.020 0.008
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.7748 0.40740 0.340 0.596 0.064
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.5919 0.50726 0.724 0.260 0.016
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.8834 0.29639 0.580 0.224 0.196
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.6753 0.00918 0.596 0.388 0.016
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.2384 0.77073 0.936 0.056 0.008
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.5414 0.43045 0.212 0.772 0.016
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.4489 0.75220 0.856 0.108 0.036
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.5171 0.42418 0.204 0.784 0.012
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0892 0.77464 0.980 0.020 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.8728 0.48141 0.592 0.208 0.200
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.6793 0.32679 0.452 0.536 0.012
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.7309 0.27113 0.124 0.708 0.168
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.6229 0.52288 0.700 0.280 0.020
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.9934 0.14758 0.320 0.292 0.388
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.5412 0.70024 0.796 0.172 0.032
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0892 0.77600 0.980 0.020 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.1399 0.77461 0.968 0.028 0.004
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.8462 0.48724 0.588 0.288 0.124
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.8245 0.53204 0.624 0.244 0.132
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.3459 0.75315 0.892 0.096 0.012
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0747 0.77402 0.984 0.016 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.8286 0.26150 0.140 0.624 0.236
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0424 0.77297 0.992 0.008 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.7209 0.35237 0.604 0.360 0.036
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.7416 0.37886 0.656 0.276 0.068
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.9815 0.27861 0.256 0.420 0.324
#> 5D663B98-8416-4305-A891-111B7A4DC40B 1 0.7448 0.37239 0.616 0.332 0.052
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.8528 0.51434 0.604 0.240 0.156
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.6676 0.28852 0.476 0.516 0.008
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.8694 0.47456 0.580 0.268 0.152
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.5219 0.41736 0.196 0.788 0.016
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0475 0.77387 0.992 0.004 0.004
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.6225 -0.23919 0.000 0.568 0.432
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.2269 0.77311 0.944 0.040 0.016
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.77158 1.000 0.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.9423 -0.05202 0.196 0.484 0.320
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.77158 1.000 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.6286 -0.28360 0.000 0.536 0.464
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.5798 0.41975 0.184 0.776 0.040
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.77158 1.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.77158 1.000 0.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.9563 0.32846 0.284 0.480 0.236
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.6446 0.67845 0.736 0.212 0.052
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.3886 0.75993 0.880 0.096 0.024
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.6215 -0.24052 0.000 0.572 0.428
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.6955 -0.22618 0.492 0.492 0.016
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.5053 0.70500 0.812 0.164 0.024
#> DAD951A3-C22E-42F0-BB02-854413DDC351 1 0.7674 -0.14378 0.484 0.472 0.044
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 3 0.5884 0.52849 0.012 0.272 0.716
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.0237 0.77182 0.996 0.004 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0000 0.77158 1.000 0.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.8760 0.39346 0.240 0.584 0.176
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.9624 0.31518 0.256 0.472 0.272
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 3 0.6302 0.30237 0.000 0.480 0.520
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.6960 0.35490 0.152 0.732 0.116
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 1 0.6962 0.49774 0.648 0.316 0.036
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.77158 1.000 0.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.9601 0.31962 0.252 0.476 0.272
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 1 0.7983 0.57074 0.648 0.228 0.124
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.7097 0.26162 0.108 0.720 0.172
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.9390 -0.04406 0.488 0.192 0.320
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0000 0.77158 1.000 0.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.1525 0.77435 0.964 0.032 0.004
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.6757 0.67546 0.736 0.180 0.084
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0000 0.77158 1.000 0.000 0.000
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.7624 0.59703 0.672 0.224 0.104
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.3856 0.76353 0.888 0.072 0.040
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 1 0.7580 0.38234 0.604 0.340 0.056
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.5136 0.73644 0.824 0.132 0.044
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.6975 0.45665 0.356 0.616 0.028
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.7807 0.39160 0.184 0.672 0.144
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 1 0.3377 0.76173 0.896 0.092 0.012
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.9543 0.36994 0.304 0.476 0.220
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 1 0.7591 0.46434 0.632 0.300 0.068
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.7380 0.62364 0.684 0.228 0.088
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 3 0.6305 0.30179 0.000 0.484 0.516
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#> 12178D82-CADF-49AD-BC2F-3956CB321EE9 1 0.4136 0.73930 0.864 0.116 0.020
#> 0EAC1C1B-4B84-479B-A8E9-DC7ED4D3E0F3 1 0.1267 0.77413 0.972 0.024 0.004
#> 362DEA8E-F338-42D8-AA20-21F3B5AF72C3 1 0.6576 0.68913 0.740 0.192 0.068
#> 9CC24423-CCFA-475B-84CC-5A884048222C 2 0.6225 -0.24109 0.000 0.568 0.432
#> E2625C62-2ABA-4670-A186-A7C03D69DD58 1 0.4253 0.75926 0.872 0.080 0.048
#> FCA5BADD-A6B2-4602-9B8F-0CD760E0AC2A 2 0.9331 0.30948 0.344 0.480 0.176
#> 36A4A073-CB26-4A65-8E47-A61F29929BDC 1 0.3031 0.76286 0.912 0.076 0.012
#> BB6D222E-585A-4C3E-ADD2-1B2BD5281F50 2 0.6225 -0.24109 0.000 0.568 0.432
#> 55CFCA9F-0704-4948-BFB3-9027DE73E4BC 1 0.0000 0.77158 1.000 0.000 0.000
#> 3A052FCB-69B1-4699-BE22-19A835E6D102 2 0.6579 -0.07947 0.020 0.652 0.328
#> 90AAB588-049D-4C56-B024-97831990F7CB 1 0.9167 0.34002 0.512 0.320 0.168
#> 75858032-A88A-4851-BCE5-66831D649D57 1 0.9249 0.27600 0.508 0.312 0.180
#> EA5B09C5-A45D-44BC-8477-DAF6B0DD79C7 2 0.9379 0.29919 0.348 0.472 0.180
#> 8026EF80-8CFB-4A62-9C72-BB5B50BDECFE 1 0.0000 0.77158 1.000 0.000 0.000
#> C1D05156-9AA7-48FD-9C3C-8894F9025D29 1 0.6678 0.67776 0.728 0.208 0.064
#> D3AEFD54-52E3-4761-898B-F05A5B6BA198 2 0.6680 0.25574 0.484 0.508 0.008
#> 33FAC29F-D146-454C-AE5D-07DF7C191DFC 1 0.6446 0.67866 0.736 0.212 0.052
#> E3E13B94-9335-4B34-9975-ECA99EB1BCBE 1 0.3375 0.76058 0.892 0.100 0.008
#> 2E1AC099-CE43-4605-BDFD-FA71DE8EAE44 2 0.5775 0.45733 0.260 0.728 0.012
#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.5521 0.40008 0.180 0.788 0.032
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.6318 0.39023 0.172 0.760 0.068
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.8426 0.33452 0.384 0.524 0.092
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 3 0.6215 0.35803 0.000 0.428 0.572
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.0237 0.77243 0.996 0.004 0.000
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 1 0.6955 -0.22618 0.492 0.492 0.016
#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.9489 0.32257 0.496 0.252 0.252
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.9120 0.35560 0.200 0.544 0.256
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 3 0.5098 0.53518 0.000 0.248 0.752
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 3 0.4842 0.53615 0.000 0.224 0.776
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.2200 0.76198 0.940 0.056 0.004
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 1 0.2229 0.77475 0.944 0.044 0.012
#> 976924B0-5799-4AC9-804F-78C8568037CA 1 0.3213 0.75569 0.900 0.092 0.008
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.9715 -0.27866 0.400 0.220 0.380
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0237 0.77243 0.996 0.004 0.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.0661 0.77331 0.988 0.004 0.008
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0000 0.77158 1.000 0.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0424 0.77279 0.992 0.008 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 1 0.6872 0.57914 0.680 0.276 0.044
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.5574 0.40675 0.184 0.784 0.032
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 1 0.7106 0.63301 0.696 0.232 0.072
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.1989 0.77353 0.948 0.048 0.004
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0000 0.77158 1.000 0.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.8262 0.45037 0.592 0.304 0.104
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.3502 0.76241 0.896 0.084 0.020
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.7528 0.46861 0.280 0.648 0.072
#> 93429F04-8404-4E8C-B654-9D2216BA432C 3 0.9790 0.09528 0.260 0.308 0.432
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.5105 0.73784 0.828 0.124 0.048
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.77158 1.000 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0592 0.77406 0.988 0.012 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 1 0.8607 0.50512 0.592 0.256 0.152
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.9601 0.31962 0.252 0.476 0.272
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.5414 0.43045 0.212 0.772 0.016
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.9805 0.28523 0.320 0.424 0.256
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.1163 0.77090 0.972 0.028 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.77158 1.000 0.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0475 0.77341 0.992 0.004 0.004
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.8007 0.19771 0.116 0.640 0.244
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.5603 0.72868 0.804 0.136 0.060
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.5450 0.44808 0.228 0.760 0.012
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.6486 0.33551 0.144 0.760 0.096
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.7245 0.27690 0.120 0.712 0.168
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.8349 0.52433 0.608 0.264 0.128
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.9228 0.31365 0.508 0.316 0.176
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.77158 1.000 0.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 3 0.6373 0.25813 0.004 0.408 0.588
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0424 0.77381 0.992 0.008 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.2280 0.77455 0.940 0.052 0.008
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.77158 1.000 0.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.9008 0.41063 0.296 0.540 0.164
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.8245 0.53204 0.624 0.244 0.132
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.1031 0.77368 0.976 0.024 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.7543 0.60882 0.680 0.216 0.104
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.77158 1.000 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.8872 0.39384 0.552 0.296 0.152
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.8460 0.28427 0.148 0.608 0.244
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.77158 1.000 0.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.77158 1.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.9934 0.14758 0.320 0.292 0.388
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.9111 0.39280 0.292 0.532 0.176
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.7178 0.32863 0.464 0.512 0.024
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.6950 0.60760 0.692 0.252 0.056
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.8159 0.40419 0.588 0.320 0.092
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.5171 0.42418 0.204 0.784 0.012
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.8891 0.34959 0.340 0.524 0.136
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.8716 0.36148 0.348 0.532 0.120
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.9837 0.09000 0.360 0.248 0.392
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.1525 0.77435 0.964 0.032 0.004
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.9100 0.33895 0.516 0.324 0.160
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.4679 0.69605 0.832 0.148 0.020
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.6823 0.24960 0.484 0.504 0.012
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.7835 0.57932 0.656 0.232 0.112
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.5414 0.43045 0.212 0.772 0.016
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.1525 0.77432 0.964 0.032 0.004
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.9547 0.33621 0.292 0.480 0.228
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.1636 0.77647 0.964 0.020 0.016
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6588 0.67420 0.732 0.208 0.060
#> A2007795-C728-4688-B199-AE89500011D2 2 0.6647 -0.19679 0.012 0.592 0.396
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 1 0.9501 0.18514 0.472 0.324 0.204
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.4196 0.74959 0.864 0.112 0.024
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.6416 0.46093 0.304 0.676 0.020
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.7251 0.36440 0.612 0.348 0.040
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.6714 0.48193 0.672 0.296 0.032
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.8918 0.17387 0.128 0.492 0.380
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 3 0.4842 0.53615 0.000 0.224 0.776
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0424 0.77297 0.992 0.008 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.8925 0.39167 0.256 0.564 0.180
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.6262 0.45845 0.284 0.696 0.020
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1781 0.77617 0.960 0.020 0.020
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.6701 -0.19972 0.012 0.576 0.412
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.3213 0.75569 0.900 0.092 0.008
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.5860 0.45809 0.228 0.748 0.024
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.6662 0.62166 0.704 0.252 0.044
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.77158 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.6183 0.63868 0.732 0.236 0.032
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.9536 0.25450 0.232 0.284 0.484
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.9501 0.22832 0.472 0.324 0.204
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 3 0.6267 0.33677 0.000 0.452 0.548
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.77158 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.9053 0.36612 0.220 0.556 0.224
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 3 0.6260 0.34086 0.000 0.448 0.552
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.4960 0.74351 0.832 0.128 0.040
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1399 0.76921 0.968 0.028 0.004
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.77158 1.000 0.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.6304 0.69215 0.752 0.192 0.056
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.9379 0.29681 0.348 0.472 0.180
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.8334 0.52696 0.616 0.248 0.136
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.7424 0.50929 0.640 0.300 0.060
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.7487 0.13999 0.552 0.408 0.040
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.8683 0.28073 0.172 0.592 0.236
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.4842 0.53615 0.000 0.224 0.776
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.4099 0.68244 0.852 0.140 0.008
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.8288 0.37591 0.332 0.572 0.096
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.6398 0.69026 0.748 0.192 0.060
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.6757 0.67546 0.736 0.180 0.084
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.77158 1.000 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.5955 0.70668 0.772 0.180 0.048
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.5578 0.45085 0.240 0.748 0.012
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0237 0.77238 0.996 0.004 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.2301 0.76535 0.936 0.060 0.004
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.1751 0.77623 0.960 0.028 0.012
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.8231 0.54367 0.628 0.236 0.136
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0424 0.77306 0.992 0.000 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.5414 0.43045 0.212 0.772 0.016
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.77158 1.000 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2229 0.77444 0.944 0.044 0.012
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.8918 0.17387 0.128 0.492 0.380
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.4555 0.53423 0.000 0.200 0.800
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.7003 0.56269 0.692 0.248 0.060
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6109 0.43403 0.192 0.760 0.048
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0829 0.77488 0.984 0.012 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.6195 0.46087 0.276 0.704 0.020
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.8300 0.52631 0.620 0.244 0.136
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5267 0.73520 0.816 0.140 0.044
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.9111 0.39280 0.292 0.532 0.176
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.9892 0.25314 0.268 0.392 0.340
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0424 0.77293 0.992 0.008 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.8727 0.39221 0.236 0.588 0.176
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1015 0.77479 0.980 0.012 0.008
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0747 0.77059 0.984 0.016 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.7453 0.31840 0.436 0.528 0.036
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.77158 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.8765 0.47149 0.580 0.252 0.168
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6425 0.69183 0.764 0.140 0.096
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.6719 0.65126 0.728 0.204 0.068
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.6295 0.61859 0.728 0.236 0.036
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.2866 0.74932 0.916 0.076 0.008
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.6473 0.46727 0.312 0.668 0.020
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6539 0.51047 0.684 0.288 0.028
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.2866 0.74932 0.916 0.076 0.008
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2505 0.52146 0.004 0.920 0.040 0.036
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#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1388 0.74654 0.960 0.028 0.000 0.012
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.7497 0.14869 0.200 0.520 0.004 0.276
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0188 0.74408 0.996 0.004 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.4690 0.59377 0.268 0.008 0.004 0.720
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6071 -0.04174 0.500 0.028 0.008 0.464
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5695 -0.10748 0.500 0.024 0.000 0.476
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.7578 0.09148 0.480 0.284 0.000 0.236
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3335 0.69628 0.860 0.120 0.000 0.020
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4558 0.56568 0.084 0.820 0.012 0.084
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7611 0.08227 0.476 0.268 0.000 0.256
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3335 0.69628 0.860 0.120 0.000 0.020
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3031 0.55988 0.000 0.856 0.120 0.020 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0486 0.76922 0.988 0.004 0.004 0.000 0.004
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.6961 0.41555 0.036 0.248 0.088 0.588 0.040
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0854 0.77066 0.976 0.000 0.008 0.012 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.5771 0.53502 0.132 0.032 0.008 0.700 0.128
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1768 0.57400 0.000 0.924 0.072 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2352 0.76192 0.896 0.004 0.000 0.092 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0960 0.77054 0.972 0.000 0.008 0.016 0.004
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1363 0.77494 0.956 0.004 0.004 0.032 0.004
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1900 0.77292 0.936 0.024 0.004 0.032 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.8628 0.35813 0.076 0.156 0.188 0.476 0.104
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.3936 0.48549 0.048 0.012 0.004 0.820 0.116
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5988 0.15756 0.520 0.044 0.000 0.400 0.036
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3079 0.57369 0.000 0.868 0.092 0.028 0.012
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3646 0.47173 0.044 0.000 0.008 0.828 0.120
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.4506 0.54126 0.048 0.812 0.056 0.016 0.068
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 3 0.3201 0.65164 0.000 0.132 0.844 0.008 0.016
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.4657 0.51776 0.048 0.800 0.012 0.072 0.068
#> 479B4832-82DB-4176-9D24-D588F2903617 3 0.3005 0.65425 0.000 0.124 0.856 0.008 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.7383 -0.07126 0.284 0.440 0.000 0.236 0.040
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2673 0.58112 0.024 0.900 0.048 0.028 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.7120 0.43536 0.064 0.264 0.056 0.572 0.044
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.6157 0.45487 0.640 0.056 0.004 0.232 0.068
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.1667 0.77613 0.948 0.024 0.004 0.012 0.012
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4738 0.64667 0.748 0.076 0.000 0.164 0.012
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.8485 0.12532 0.060 0.372 0.292 0.236 0.040
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.3107 0.75612 0.872 0.024 0.008 0.088 0.008
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1082 0.77169 0.964 0.000 0.008 0.028 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0324 0.77028 0.992 0.000 0.004 0.004 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.7661 0.29998 0.032 0.304 0.100 0.496 0.068
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.2484 0.76733 0.908 0.016 0.008 0.060 0.008
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5042 0.19652 0.000 0.580 0.388 0.008 0.024
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.4183 0.51111 0.088 0.016 0.004 0.812 0.080
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0963 0.77739 0.964 0.000 0.000 0.036 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 3 0.3421 0.64182 0.000 0.152 0.824 0.008 0.016
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0727 0.77275 0.980 0.004 0.000 0.012 0.004
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.6412 0.68949 0.116 0.260 0.000 0.036 0.588
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.2242 0.77526 0.920 0.008 0.008 0.052 0.012
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.6749 0.17444 0.520 0.124 0.004 0.324 0.028
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0162 0.76899 0.996 0.000 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 3 0.5759 0.55921 0.004 0.100 0.712 0.068 0.116
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.7513 0.09915 0.476 0.136 0.016 0.320 0.052
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 3 0.3379 0.64559 0.000 0.148 0.828 0.008 0.016
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.5192 0.39492 0.000 0.032 0.492 0.004 0.472
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.7521 -0.15332 0.384 0.368 0.004 0.204 0.040
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2404 0.57486 0.040 0.916 0.024 0.016 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.3058 0.76242 0.884 0.048 0.008 0.048 0.012
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3031 0.55988 0.000 0.856 0.120 0.020 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.7762 -0.04349 0.016 0.400 0.356 0.184 0.044
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.2804 0.58353 0.000 0.884 0.068 0.044 0.004
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 5 0.4920 0.36367 0.000 0.404 0.012 0.012 0.572
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1900 0.77292 0.936 0.024 0.004 0.032 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0324 0.77028 0.992 0.000 0.004 0.004 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0854 0.77066 0.976 0.000 0.008 0.012 0.004
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0981 0.77343 0.972 0.008 0.008 0.012 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0865 0.77284 0.972 0.000 0.004 0.024 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.7501 -0.12997 0.432 0.152 0.012 0.360 0.044
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.5437 0.46561 0.088 0.748 0.012 0.084 0.068
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4550 0.47770 0.116 0.776 0.004 0.096 0.008
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.7739 0.36540 0.336 0.160 0.020 0.436 0.048
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.1026 0.77400 0.968 0.004 0.004 0.024 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5028 0.11975 0.000 0.552 0.420 0.008 0.020
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.5758 0.50658 0.268 0.000 0.000 0.600 0.132
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.2359 0.76830 0.912 0.016 0.008 0.060 0.004
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1370 0.77678 0.960 0.012 0.004 0.012 0.012
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1439 0.57317 0.004 0.956 0.020 0.004 0.016
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.6891 0.42176 0.036 0.244 0.084 0.596 0.040
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.7763 0.55792 0.232 0.108 0.064 0.540 0.056
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.2017 0.76778 0.924 0.004 0.004 0.060 0.008
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0854 0.77048 0.976 0.000 0.008 0.012 0.004
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.6586 0.49539 0.640 0.096 0.008 0.172 0.084
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0771 0.77251 0.976 0.000 0.004 0.020 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.6669 0.42392 0.076 0.636 0.036 0.204 0.048
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 5 0.8498 0.01350 0.244 0.124 0.008 0.296 0.328
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.4700 0.55150 0.004 0.784 0.088 0.092 0.032
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.7527 0.33648 0.040 0.300 0.096 0.512 0.052
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.5778 0.39125 0.000 0.036 0.484 0.028 0.452
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.6985 0.35074 0.368 0.056 0.020 0.496 0.060
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3543 0.73295 0.852 0.044 0.004 0.084 0.016
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0324 0.77028 0.992 0.000 0.004 0.004 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.3361 0.73987 0.844 0.020 0.008 0.124 0.004
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.5334 0.41498 0.068 0.736 0.008 0.040 0.148
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.6873 0.23307 0.528 0.328 0.008 0.076 0.060
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.8338 -0.30163 0.360 0.124 0.008 0.184 0.324
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.6378 0.01089 0.488 0.420 0.016 0.048 0.028
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4035 0.73560 0.832 0.048 0.012 0.084 0.024
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1439 0.57317 0.004 0.956 0.020 0.004 0.016
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.5292 0.52182 0.688 0.036 0.004 0.240 0.032
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1697 0.57802 0.000 0.932 0.060 0.008 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.2713 0.76523 0.896 0.020 0.008 0.068 0.008
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.7362 0.51819 0.240 0.040 0.020 0.532 0.168
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.6504 0.31499 0.188 0.612 0.000 0.152 0.048
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.5014 0.13310 0.000 0.560 0.412 0.008 0.020
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.7364 0.09422 0.472 0.320 0.004 0.148 0.056
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.6497 0.70385 0.124 0.248 0.000 0.040 0.588
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.6376 0.51039 0.648 0.144 0.008 0.156 0.044
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.2073 0.77174 0.928 0.016 0.004 0.044 0.008
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.2925 0.75906 0.880 0.024 0.008 0.084 0.004
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.5867 0.55806 0.136 0.088 0.012 0.708 0.056
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.5673 0.51113 0.252 0.000 0.000 0.616 0.132
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.5156 0.67602 0.760 0.084 0.012 0.108 0.036
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.1900 0.77349 0.936 0.024 0.004 0.032 0.004
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.7154 0.14149 0.016 0.476 0.344 0.140 0.024
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.1574 0.77434 0.952 0.012 0.004 0.020 0.012
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.7941 0.25320 0.276 0.324 0.012 0.344 0.044
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.8329 -0.06402 0.428 0.272 0.020 0.112 0.168
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.8816 0.37804 0.104 0.156 0.184 0.460 0.096
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.8574 -0.11987 0.256 0.368 0.024 0.256 0.096
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.5809 0.56074 0.216 0.032 0.000 0.660 0.092
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.6425 0.29966 0.212 0.612 0.000 0.132 0.044
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.5769 0.54582 0.192 0.024 0.004 0.676 0.104
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.1952 0.57200 0.000 0.912 0.084 0.000 0.004
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.1116 0.77518 0.964 0.004 0.004 0.028 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 3 0.4921 0.46353 0.000 0.360 0.604 0.000 0.036
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.3631 0.72158 0.820 0.020 0.008 0.148 0.004
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0854 0.77066 0.976 0.000 0.008 0.012 0.004
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.5277 -0.03182 0.000 0.584 0.040 0.008 0.368
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0162 0.76899 0.996 0.000 0.004 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 3 0.3966 0.63840 0.000 0.176 0.784 0.004 0.036
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.3914 0.50386 0.000 0.780 0.192 0.016 0.012
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0324 0.76861 0.992 0.000 0.004 0.000 0.004
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0992 0.77130 0.968 0.000 0.008 0.024 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.6988 0.37507 0.004 0.164 0.112 0.600 0.120
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.7419 -0.16683 0.428 0.128 0.008 0.380 0.056
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.4630 0.60434 0.732 0.036 0.000 0.216 0.016
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 3 0.4908 0.46753 0.000 0.356 0.608 0.000 0.036
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.6701 0.23470 0.240 0.572 0.000 0.144 0.044
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.6828 0.36687 0.568 0.172 0.004 0.220 0.036
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.7620 -0.08857 0.176 0.444 0.016 0.324 0.040
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 3 0.5778 0.39125 0.000 0.036 0.484 0.028 0.452
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.1383 0.77353 0.960 0.008 0.008 0.012 0.012
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0324 0.76861 0.992 0.000 0.004 0.000 0.004
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.7085 0.23295 0.004 0.324 0.140 0.492 0.040
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.8646 0.13026 0.072 0.352 0.268 0.268 0.040
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 3 0.3005 0.65425 0.000 0.124 0.856 0.008 0.012
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.5205 0.39099 0.000 0.660 0.280 0.040 0.020
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 4 0.7982 0.34609 0.264 0.264 0.020 0.408 0.044
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0162 0.76899 0.996 0.000 0.004 0.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.8708 0.12276 0.080 0.348 0.284 0.248 0.040
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.4128 0.51010 0.084 0.016 0.004 0.816 0.080
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.5357 0.21341 0.000 0.580 0.372 0.020 0.028
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#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0486 0.77163 0.988 0.000 0.004 0.004 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.7429 0.22502 0.016 0.348 0.096 0.472 0.068
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 3 0.1956 0.64770 0.000 0.076 0.916 0.000 0.008
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.6248 0.44753 0.640 0.056 0.008 0.228 0.068
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1969 0.77180 0.932 0.044 0.004 0.012 0.008
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0960 0.77054 0.972 0.000 0.008 0.016 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.6937 0.01882 0.476 0.128 0.004 0.360 0.032
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.7744 0.43338 0.072 0.248 0.112 0.528 0.040
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4248 0.50074 0.056 0.016 0.008 0.808 0.112
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.7891 0.34014 0.340 0.212 0.020 0.388 0.040
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.7998 -0.14208 0.272 0.392 0.016 0.272 0.048
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.7820 0.16475 0.032 0.452 0.300 0.180 0.036
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.5048 0.40172 0.000 0.032 0.492 0.000 0.476
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.4921 0.60215 0.744 0.176 0.008 0.056 0.016
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.6613 0.24305 0.040 0.616 0.032 0.068 0.244
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.6927 -0.14749 0.424 0.120 0.004 0.420 0.032
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.6992 0.34277 0.372 0.056 0.020 0.492 0.060
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0960 0.77054 0.972 0.000 0.008 0.016 0.004
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.7513 0.09915 0.476 0.136 0.016 0.320 0.052
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1710 0.57995 0.020 0.944 0.024 0.012 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1026 0.77595 0.968 0.004 0.004 0.024 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.3709 0.74018 0.844 0.068 0.004 0.068 0.016
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4540 0.69082 0.764 0.032 0.012 0.180 0.012
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4696 0.50725 0.112 0.004 0.000 0.748 0.136
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2011 0.76727 0.908 0.004 0.000 0.088 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1439 0.57317 0.004 0.956 0.020 0.004 0.016
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1306 0.76608 0.960 0.000 0.008 0.016 0.016
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3493 0.72082 0.828 0.016 0.004 0.144 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.7902 0.13027 0.000 0.180 0.276 0.432 0.112
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.4574 0.45996 0.000 0.012 0.576 0.000 0.412
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.7782 -0.17884 0.396 0.196 0.012 0.348 0.048
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3047 0.57269 0.000 0.868 0.096 0.024 0.012
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2228 0.77138 0.912 0.012 0.000 0.068 0.008
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.4321 0.52756 0.044 0.824 0.020 0.044 0.068
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.5612 0.51411 0.248 0.000 0.000 0.624 0.128
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.6133 0.26604 0.380 0.056 0.004 0.532 0.028
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.7366 0.30642 0.028 0.308 0.116 0.508 0.040
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.7817 0.31927 0.044 0.108 0.192 0.552 0.104
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.1573 0.77462 0.948 0.004 0.008 0.036 0.004
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.7171 0.23176 0.004 0.312 0.156 0.488 0.040
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2179 0.75466 0.896 0.000 0.000 0.100 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1910 0.77426 0.940 0.016 0.008 0.016 0.020
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.8304 0.04323 0.160 0.440 0.076 0.284 0.040
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0324 0.77060 0.992 0.000 0.004 0.004 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3822 0.47941 0.052 0.004 0.004 0.820 0.120
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.5430 0.45104 0.256 0.008 0.008 0.664 0.064
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.6222 0.35125 0.384 0.016 0.012 0.524 0.064
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.8063 -0.21457 0.372 0.236 0.020 0.324 0.048
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3529 0.71218 0.840 0.112 0.000 0.032 0.016
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3640 0.54606 0.072 0.852 0.012 0.052 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7976 -0.10804 0.408 0.248 0.020 0.280 0.044
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3529 0.71218 0.840 0.112 0.000 0.032 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2954 0.57933 0.000 0.864 0.004 0.036 0.084 0.012
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0436 0.78396 0.988 0.004 0.004 0.000 0.004 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5152 0.22953 0.024 0.136 0.036 0.740 0.036 0.028
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1167 0.78312 0.960 0.000 0.020 0.008 0.012 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.6204 -0.48050 0.092 0.008 0.408 0.452 0.000 0.040
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1429 0.58960 0.000 0.940 0.000 0.004 0.052 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2666 0.76732 0.872 0.000 0.028 0.092 0.008 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1269 0.78292 0.956 0.000 0.020 0.012 0.012 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1340 0.78833 0.948 0.000 0.008 0.040 0.004 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1760 0.78527 0.928 0.000 0.004 0.048 0.020 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.8217 -0.15732 0.064 0.044 0.316 0.396 0.112 0.068
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.4454 0.52841 0.008 0.008 0.504 0.476 0.004 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6456 -0.01701 0.456 0.020 0.128 0.372 0.024 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3385 0.58893 0.000 0.840 0.004 0.064 0.076 0.016
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.4238 0.54501 0.008 0.000 0.580 0.404 0.008 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5318 0.55926 0.036 0.708 0.044 0.056 0.156 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 5 0.5555 0.76184 0.000 0.084 0.008 0.008 0.512 0.388
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5908 0.54744 0.040 0.664 0.044 0.140 0.112 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 5 0.5708 0.74804 0.000 0.080 0.016 0.008 0.488 0.408
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.7340 -0.24264 0.240 0.356 0.032 0.332 0.040 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2259 0.61563 0.020 0.908 0.000 0.040 0.032 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.6276 0.17117 0.048 0.148 0.112 0.644 0.040 0.008
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.6283 0.41860 0.604 0.020 0.132 0.188 0.056 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.1761 0.79059 0.936 0.008 0.008 0.032 0.016 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4813 0.61639 0.716 0.044 0.016 0.196 0.028 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.8644 -0.09699 0.036 0.292 0.048 0.308 0.100 0.216
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.3251 0.76438 0.852 0.012 0.024 0.088 0.024 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1599 0.78401 0.940 0.000 0.024 0.028 0.008 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0881 0.78673 0.972 0.000 0.012 0.008 0.008 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.7631 0.04082 0.024 0.188 0.256 0.452 0.048 0.032
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.2844 0.77687 0.880 0.008 0.028 0.060 0.024 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5698 0.09330 0.000 0.544 0.004 0.016 0.332 0.104
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.5048 0.52908 0.036 0.008 0.484 0.464 0.008 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1334 0.79239 0.948 0.000 0.020 0.032 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 5 0.5770 0.75824 0.000 0.100 0.008 0.012 0.508 0.372
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0984 0.78618 0.968 0.000 0.008 0.012 0.012 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 6 0.8476 0.37514 0.080 0.096 0.056 0.088 0.264 0.416
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.2295 0.78809 0.904 0.000 0.028 0.052 0.016 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.6823 0.02893 0.476 0.060 0.076 0.344 0.044 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0405 0.78453 0.988 0.000 0.008 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 5 0.7775 0.51367 0.000 0.060 0.140 0.088 0.364 0.348
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.7139 -0.10358 0.408 0.048 0.076 0.396 0.068 0.004
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 5 0.5783 0.75844 0.000 0.100 0.008 0.012 0.500 0.380
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.0798 0.23854 0.000 0.004 0.012 0.004 0.004 0.976
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.7222 -0.30910 0.344 0.276 0.020 0.320 0.040 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2220 0.61639 0.036 0.908 0.000 0.044 0.012 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.3357 0.76535 0.852 0.008 0.040 0.060 0.040 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2954 0.57933 0.000 0.864 0.004 0.036 0.084 0.012
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.8385 -0.11718 0.008 0.372 0.056 0.176 0.156 0.232
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3341 0.60014 0.000 0.836 0.000 0.088 0.060 0.016
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 6 0.7142 0.25770 0.000 0.268 0.048 0.024 0.216 0.444
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1826 0.78444 0.924 0.000 0.004 0.052 0.020 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0508 0.78461 0.984 0.000 0.004 0.012 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.1167 0.78312 0.960 0.000 0.020 0.008 0.012 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1167 0.78690 0.960 0.000 0.020 0.012 0.008 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.1010 0.78566 0.960 0.000 0.004 0.036 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.7454 0.21496 0.384 0.076 0.088 0.388 0.060 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.6319 0.52831 0.072 0.640 0.052 0.128 0.108 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4869 0.51861 0.100 0.720 0.016 0.152 0.012 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.7861 0.15037 0.272 0.100 0.184 0.396 0.048 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.1082 0.78670 0.956 0.000 0.004 0.040 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5677 -0.01358 0.000 0.508 0.008 0.012 0.384 0.088
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.6013 0.52617 0.236 0.000 0.496 0.260 0.008 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.2696 0.77815 0.884 0.004 0.044 0.056 0.012 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1396 0.79141 0.952 0.004 0.008 0.024 0.012 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1726 0.60084 0.000 0.932 0.012 0.012 0.044 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4768 0.21644 0.016 0.128 0.036 0.764 0.024 0.032
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.7623 -0.07598 0.196 0.052 0.228 0.468 0.028 0.028
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.2058 0.77794 0.908 0.000 0.012 0.072 0.008 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.1269 0.78406 0.956 0.000 0.020 0.012 0.012 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.6530 0.44258 0.604 0.040 0.028 0.228 0.052 0.048
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1049 0.78691 0.960 0.000 0.008 0.032 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.7026 0.39194 0.060 0.560 0.048 0.236 0.072 0.024
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.9102 0.13875 0.180 0.044 0.104 0.336 0.116 0.220
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.5199 0.53324 0.000 0.708 0.064 0.124 0.100 0.004
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.7397 0.08984 0.020 0.192 0.208 0.500 0.044 0.036
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 6 0.2357 0.22787 0.000 0.008 0.016 0.032 0.036 0.908
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.7164 0.01228 0.284 0.020 0.216 0.428 0.052 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3456 0.74018 0.832 0.012 0.012 0.108 0.036 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0622 0.78566 0.980 0.000 0.008 0.012 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.3513 0.74588 0.820 0.004 0.036 0.124 0.016 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.6931 0.47037 0.060 0.604 0.052 0.072 0.176 0.036
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.7137 0.16718 0.504 0.240 0.028 0.136 0.092 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.9308 -0.29742 0.288 0.044 0.096 0.204 0.176 0.192
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.6748 0.04287 0.472 0.348 0.036 0.100 0.044 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4398 0.73070 0.788 0.024 0.044 0.092 0.052 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1726 0.60084 0.000 0.932 0.012 0.012 0.044 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.5644 0.47185 0.640 0.020 0.108 0.212 0.020 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1461 0.59945 0.000 0.940 0.000 0.016 0.044 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.2952 0.77604 0.872 0.008 0.040 0.064 0.016 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.6280 0.10429 0.192 0.004 0.168 0.576 0.060 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.6501 0.20669 0.160 0.544 0.020 0.240 0.036 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.5582 0.00731 0.000 0.516 0.008 0.008 0.380 0.088
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#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 3 0.5939 0.23802 0.000 0.028 0.456 0.420 0.092 0.004
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.2638 0.77684 0.896 0.020 0.016 0.036 0.032 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.1269 0.78292 0.956 0.000 0.020 0.012 0.012 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.1649 0.79109 0.932 0.000 0.036 0.032 0.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.8165 -0.09998 0.016 0.392 0.024 0.156 0.216 0.196
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.6583 -0.00421 0.224 0.016 0.256 0.484 0.020 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.1155 0.61168 0.004 0.956 0.000 0.036 0.004 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.4510 0.38842 0.000 0.692 0.008 0.008 0.252 0.040
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.5719 0.06933 0.000 0.536 0.004 0.016 0.340 0.104
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.6474 -0.14859 0.192 0.032 0.260 0.508 0.008 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 3 0.5352 0.48966 0.024 0.008 0.480 0.452 0.036 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.1364 0.78314 0.952 0.000 0.020 0.016 0.012 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 6 0.7634 -0.02551 0.000 0.004 0.300 0.220 0.152 0.324
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.1542 0.78936 0.936 0.000 0.004 0.052 0.008 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.4737 0.67593 0.732 0.012 0.076 0.160 0.020 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.1262 0.78365 0.956 0.000 0.020 0.016 0.008 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.6410 0.19042 0.012 0.240 0.096 0.588 0.044 0.020
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 3 0.6129 0.53604 0.224 0.000 0.500 0.260 0.016 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.2704 0.77520 0.880 0.008 0.012 0.080 0.020 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.5687 -0.49099 0.084 0.008 0.436 0.460 0.012 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0520 0.78200 0.984 0.000 0.008 0.000 0.008 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.5876 0.22344 0.204 0.056 0.044 0.656 0.012 0.028
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.8011 0.06687 0.000 0.396 0.044 0.224 0.144 0.192
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.1269 0.78430 0.956 0.000 0.020 0.012 0.012 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0603 0.78630 0.980 0.000 0.004 0.016 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 6 0.8513 0.37851 0.088 0.084 0.056 0.096 0.264 0.412
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.5892 0.21905 0.012 0.252 0.024 0.624 0.056 0.032
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.7141 0.27386 0.200 0.500 0.024 0.196 0.080 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.7330 0.23706 0.352 0.104 0.084 0.416 0.044 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 4 0.8545 0.20567 0.176 0.156 0.144 0.412 0.096 0.016
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.1461 0.59945 0.000 0.940 0.000 0.016 0.044 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.6487 0.22453 0.044 0.224 0.088 0.596 0.040 0.008
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.8449 0.19224 0.020 0.388 0.052 0.144 0.232 0.164
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 6 0.8827 0.26657 0.152 0.040 0.072 0.148 0.208 0.380
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.3877 0.74195 0.816 0.016 0.044 0.096 0.028 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.6721 -0.30383 0.144 0.020 0.352 0.448 0.036 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.5461 0.59563 0.692 0.104 0.024 0.144 0.036 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.6629 0.16340 0.180 0.524 0.020 0.240 0.036 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.6478 -0.08317 0.260 0.016 0.232 0.480 0.012 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.1726 0.60084 0.000 0.932 0.012 0.012 0.044 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.3251 0.76465 0.852 0.012 0.024 0.088 0.024 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.6390 -0.18988 0.004 0.076 0.380 0.460 0.080 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.3269 0.73679 0.832 0.008 0.052 0.108 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.7154 0.00163 0.452 0.060 0.076 0.348 0.060 0.004
#> A2007795-C728-4688-B199-AE89500011D2 6 0.7068 -0.42154 0.000 0.344 0.004 0.060 0.236 0.356
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.8024 -0.04411 0.196 0.072 0.228 0.436 0.036 0.032
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.6058 0.47767 0.608 0.032 0.048 0.244 0.068 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.5825 0.55164 0.044 0.676 0.044 0.124 0.112 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 4 0.7753 0.28962 0.260 0.200 0.060 0.412 0.068 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.7600 -0.14920 0.400 0.160 0.056 0.320 0.064 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.7696 -0.11490 0.000 0.048 0.340 0.376 0.144 0.092
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.0551 0.23510 0.000 0.004 0.000 0.004 0.008 0.984
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.1592 0.78879 0.944 0.004 0.012 0.016 0.024 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.6013 0.17017 0.000 0.188 0.016 0.612 0.152 0.032
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.5596 0.55873 0.040 0.700 0.064 0.072 0.124 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.2956 0.76046 0.860 0.004 0.036 0.092 0.008 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 5 0.6595 0.62502 0.000 0.256 0.008 0.016 0.412 0.308
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.5295 0.66900 0.728 0.044 0.064 0.104 0.060 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2663 0.60835 0.000 0.880 0.000 0.068 0.040 0.012
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.7753 0.26857 0.300 0.112 0.072 0.428 0.084 0.004
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1353 0.78868 0.952 0.000 0.012 0.024 0.012 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.7243 -0.11516 0.428 0.128 0.040 0.340 0.064 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.7652 0.36288 0.040 0.076 0.052 0.092 0.220 0.520
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.6447 -0.40786 0.084 0.020 0.380 0.468 0.048 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.5975 -0.65871 0.000 0.056 0.044 0.012 0.412 0.476
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0767 0.78675 0.976 0.000 0.004 0.012 0.008 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.7609 0.05336 0.012 0.244 0.232 0.428 0.052 0.032
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.5972 -0.65627 0.000 0.056 0.044 0.012 0.408 0.480
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.6375 0.39758 0.596 0.020 0.140 0.184 0.060 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.2145 0.78663 0.920 0.016 0.012 0.032 0.020 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1269 0.78292 0.956 0.000 0.020 0.012 0.012 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.6991 -0.13138 0.432 0.068 0.080 0.376 0.044 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.6321 0.23178 0.060 0.176 0.036 0.648 0.044 0.036
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4184 -0.46811 0.008 0.004 0.432 0.556 0.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.7500 0.26344 0.292 0.108 0.076 0.460 0.060 0.004
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.7699 0.29030 0.220 0.296 0.040 0.372 0.072 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.8267 0.06921 0.020 0.408 0.036 0.204 0.144 0.188
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.0551 0.23510 0.000 0.004 0.000 0.004 0.008 0.984
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.5093 0.60013 0.720 0.120 0.016 0.112 0.032 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.8113 0.26665 0.032 0.464 0.056 0.092 0.216 0.140
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.7109 0.19457 0.372 0.060 0.104 0.420 0.044 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.7173 0.01598 0.288 0.020 0.216 0.424 0.052 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.1269 0.78292 0.956 0.000 0.020 0.012 0.012 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.7139 -0.10358 0.408 0.048 0.076 0.396 0.068 0.004
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1536 0.61610 0.016 0.940 0.000 0.040 0.004 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1605 0.78881 0.940 0.000 0.016 0.032 0.012 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.4040 0.74341 0.808 0.020 0.036 0.096 0.040 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4763 0.66851 0.720 0.008 0.104 0.156 0.012 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.5369 0.58400 0.072 0.004 0.548 0.364 0.012 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2645 0.77701 0.880 0.000 0.056 0.056 0.008 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1726 0.60084 0.000 0.932 0.012 0.012 0.044 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.2351 0.76372 0.900 0.000 0.052 0.012 0.036 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3908 0.69842 0.784 0.008 0.048 0.152 0.008 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.7696 -0.11490 0.000 0.048 0.340 0.376 0.144 0.092
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.1812 0.14587 0.000 0.000 0.008 0.000 0.080 0.912
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.7619 0.22158 0.340 0.112 0.108 0.392 0.048 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3212 0.58977 0.000 0.852 0.004 0.056 0.072 0.016
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2375 0.78134 0.896 0.000 0.020 0.068 0.016 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5594 0.55692 0.036 0.696 0.048 0.100 0.120 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6054 0.55412 0.216 0.000 0.500 0.272 0.012 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.6798 0.06812 0.304 0.016 0.228 0.428 0.024 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.5892 0.21905 0.012 0.252 0.024 0.624 0.056 0.032
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.7419 -0.21278 0.028 0.016 0.364 0.412 0.108 0.072
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.2095 0.78786 0.916 0.000 0.028 0.040 0.016 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.6020 0.20194 0.000 0.240 0.028 0.608 0.088 0.036
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2767 0.76184 0.868 0.000 0.072 0.056 0.004 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.2168 0.78588 0.916 0.004 0.028 0.016 0.036 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.7709 0.18421 0.128 0.344 0.040 0.368 0.120 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0508 0.78502 0.984 0.000 0.004 0.012 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 3 0.4552 0.55020 0.016 0.004 0.564 0.408 0.008 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.6357 0.34931 0.192 0.004 0.400 0.388 0.016 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.6630 0.12176 0.332 0.008 0.332 0.316 0.012 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 4 0.8271 0.17153 0.308 0.148 0.164 0.316 0.064 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3870 0.72015 0.816 0.076 0.008 0.068 0.032 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4085 0.60117 0.056 0.796 0.008 0.116 0.020 0.004
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.7761 0.24422 0.348 0.136 0.084 0.368 0.064 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3870 0.72015 0.816 0.076 0.008 0.068 0.032 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.795 0.874 0.946 0.4855 0.506 0.506
#> 3 3 0.588 0.783 0.848 0.3275 0.741 0.535
#> 4 4 0.514 0.484 0.672 0.1230 0.895 0.726
#> 5 5 0.575 0.502 0.697 0.0755 0.819 0.483
#> 6 6 0.620 0.489 0.670 0.0442 0.904 0.611
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0672 0.9194 0.008 0.992
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9618 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0672 0.9194 0.008 0.992
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9618 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.8016 0.6943 0.244 0.756
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0672 0.9194 0.008 0.992
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9618 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9618 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9618 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9618 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.7219 0.7585 0.200 0.800
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.9661 0.2754 0.608 0.392
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.9618 1.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0672 0.9194 0.008 0.992
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.9710 0.4268 0.400 0.600
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0672 0.9194 0.008 0.992
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0672 0.9194 0.008 0.992
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0672 0.9194 0.008 0.992
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0672 0.9194 0.008 0.992
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0000 0.9618 1.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.7453 0.7113 0.212 0.788
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.1184 0.9149 0.016 0.984
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9618 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9618 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0000 0.9618 1.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0672 0.9194 0.008 0.992
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9618 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9618 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9618 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0672 0.9194 0.008 0.992
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9618 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0672 0.9194 0.008 0.992
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9618 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9618 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0672 0.9194 0.008 0.992
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9618 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0672 0.9545 0.992 0.008
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9618 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9618 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9618 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0672 0.9194 0.008 0.992
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.9618 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0672 0.9194 0.008 0.992
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9144 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2043 0.9314 0.968 0.032
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0672 0.9194 0.008 0.992
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9618 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0672 0.9194 0.008 0.992
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0672 0.9194 0.008 0.992
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0672 0.9194 0.008 0.992
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.0000 0.9144 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9618 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9618 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9618 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9618 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9618 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.9710 0.2501 0.600 0.400
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.1184 0.9148 0.016 0.984
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0672 0.9194 0.008 0.992
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.8016 0.6329 0.756 0.244
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9618 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0672 0.9194 0.008 0.992
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9618 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9618 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9618 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0672 0.9194 0.008 0.992
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0672 0.9194 0.008 0.992
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.7219 0.7585 0.200 0.800
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.9618 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.9618 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.9618 1.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9618 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0672 0.9194 0.008 0.992
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0672 0.9545 0.992 0.008
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0672 0.9194 0.008 0.992
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0672 0.9194 0.008 0.992
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9144 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.9661 0.2755 0.608 0.392
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9618 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9618 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.9618 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.9491 0.3869 0.632 0.368
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.9618 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0672 0.9545 0.992 0.008
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.9618 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9618 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0672 0.9194 0.008 0.992
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.9618 1.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0672 0.9194 0.008 0.992
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.9618 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.0000 0.9618 1.000 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0672 0.9194 0.008 0.992
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0672 0.9194 0.008 0.992
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.0000 0.9618 1.000 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0938 0.9123 0.012 0.988
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.9618 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.9618 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.9618 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.9998 -0.1017 0.508 0.492
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.9552 0.3236 0.624 0.376
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0000 0.9618 1.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.9618 1.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0672 0.9194 0.008 0.992
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.9618 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 1.0000 0.1400 0.496 0.504
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.0376 0.9582 0.996 0.004
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.7219 0.7585 0.200 0.800
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.9988 0.1945 0.480 0.520
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.7056 0.7237 0.808 0.192
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.0000 0.9618 1.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.9933 0.0619 0.548 0.452
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0672 0.9194 0.008 0.992
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.9618 1.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0672 0.9194 0.008 0.992
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0000 0.9618 1.000 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.9618 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.9144 0.000 1.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.9618 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0672 0.9194 0.008 0.992
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0672 0.9194 0.008 0.992
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.9618 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.9618 1.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.7950 0.7078 0.240 0.760
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0000 0.9618 1.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.9618 1.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0672 0.9194 0.008 0.992
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.0000 0.9618 1.000 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.0000 0.9618 1.000 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0672 0.9194 0.008 0.992
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.0000 0.9144 0.000 1.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.0000 0.9618 1.000 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0000 0.9618 1.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0672 0.9194 0.008 0.992
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3114 0.8883 0.056 0.944
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0672 0.9194 0.008 0.992
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0672 0.9194 0.008 0.992
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.0672 0.9194 0.008 0.992
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.9618 1.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.0672 0.9194 0.008 0.992
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.9710 0.4268 0.400 0.600
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0672 0.9194 0.008 0.992
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0672 0.9545 0.992 0.008
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0000 0.9618 1.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.0000 0.9618 1.000 0.000
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.0000 0.9618 1.000 0.000
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0000 0.9618 1.000 0.000
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.6343 0.7727 0.840 0.160
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.0000 0.9618 1.000 0.000
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 1 0.1633 0.9401 0.976 0.024
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.0000 0.9618 1.000 0.000
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.0672 0.9194 0.008 0.992
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0672 0.9194 0.008 0.992
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 1 0.0000 0.9618 1.000 0.000
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.0672 0.9194 0.008 0.992
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 1 0.0000 0.9618 1.000 0.000
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.0000 0.9618 1.000 0.000
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 2 0.0672 0.9194 0.008 0.992
#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.0000 0.9144 0.000 1.000
#> EF3D2659-7C4A-4003-A1B1-9A47A5388034 1 0.0000 0.9618 1.000 0.000
#> 09A7BAD6-4AB2-428A-B96C-BC3C298C4496 2 0.0376 0.9149 0.004 0.996
#> 02D46E43-75BB-4A0A-8A02-403C7FBFB112 2 0.7219 0.7585 0.200 0.800
#> 450A8523-03F4-4EF5-BA7A-E8E5329BE218 1 0.0000 0.9618 1.000 0.000
#> 6EA613FC-FDDD-4D89-B73E-FB2357D12651 2 0.9710 0.4268 0.400 0.600
#> 9B979DBE-6BAE-4631-A37D-3F57CD81D98E 2 0.0672 0.9194 0.008 0.992
#> 467BF85C-E6B2-4EE0-98E1-84341089B13F 1 0.0000 0.9618 1.000 0.000
#> BDCEEABA-4D55-4FDD-A180-C6FDF6EEF46F 1 0.9460 0.3945 0.636 0.364
#> 692D9E91-B8E7-421B-8165-B4797FB63EBF 1 0.0000 0.9618 1.000 0.000
#> BEE00B8C-02E2-4730-B3D3-28B1921BC61C 2 0.0672 0.9194 0.008 0.992
#> E2DD2578-89C1-4450-A2E9-081B97C3D9E1 2 0.3733 0.8764 0.072 0.928
#> 1D8EDBA0-FE22-4B74-941B-379636CEB488 1 0.9661 0.3248 0.608 0.392
#> 7C64AB4D-F135-42E8-B90C-B17382D7DEF2 2 0.0672 0.9194 0.008 0.992
#> 64FFE05F-5B89-4037-B39F-4D3F2632A763 2 0.0000 0.9144 0.000 1.000
#> FAB10659-FFDB-4D2F-BA6E-5DDFB9E62B30 1 0.0672 0.9545 0.992 0.008
#> F0CE637A-2087-4A54-9FAA-D30808D4D4DE 1 0.0672 0.9545 0.992 0.008
#> 8890CB3F-8F04-4F16-BDD9-F02558619CDF 2 0.0000 0.9144 0.000 1.000
#> 517E939F-D96F-4567-93EB-5F12AEF517B7 1 0.0000 0.9618 1.000 0.000
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#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.0000 0.9618 1.000 0.000
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0000 0.9618 1.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0000 0.9618 1.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0672 0.9194 0.008 0.992
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0672 0.9194 0.008 0.992
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 1 0.2423 0.9230 0.960 0.040
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0000 0.9618 1.000 0.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0000 0.9618 1.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 2 0.9998 0.1545 0.492 0.508
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.0000 0.9618 1.000 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.0672 0.9194 0.008 0.992
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.9661 0.4308 0.392 0.608
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.9618 1.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.9618 1.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.9618 1.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 1 0.2043 0.9311 0.968 0.032
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.7299 0.7538 0.204 0.796
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.9754 0.3185 0.408 0.592
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0672 0.9194 0.008 0.992
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0000 0.9618 1.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.9618 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.9618 1.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0672 0.9194 0.008 0.992
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.1414 0.9433 0.980 0.020
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0672 0.9194 0.008 0.992
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0672 0.9194 0.008 0.992
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0672 0.9194 0.008 0.992
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.9710 0.2501 0.600 0.400
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.9710 0.4268 0.400 0.600
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.9618 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.9144 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.9618 1.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.0000 0.9618 1.000 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.9618 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0672 0.9194 0.008 0.992
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.9618 1.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.9618 1.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0000 0.9618 1.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.9618 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.9710 0.4268 0.400 0.600
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0672 0.9194 0.008 0.992
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.9618 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.9618 1.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.0672 0.9545 0.992 0.008
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0672 0.9194 0.008 0.992
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.0672 0.9194 0.008 0.992
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.0000 0.9618 1.000 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.9954 0.2616 0.460 0.540
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0672 0.9194 0.008 0.992
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0672 0.9194 0.008 0.992
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.9144 0.000 1.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.0672 0.9545 0.992 0.008
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.0000 0.9618 1.000 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.9710 0.4268 0.400 0.600
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.9618 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.1184 0.9149 0.016 0.984
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0000 0.9618 1.000 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.3584 0.8742 0.068 0.932
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.9618 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0672 0.9194 0.008 0.992
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.9618 1.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.0000 0.9618 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0672 0.9194 0.008 0.992
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.7219 0.7585 0.200 0.800
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.0000 0.9618 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.0672 0.9194 0.008 0.992
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.1633 0.9394 0.976 0.024
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.0000 0.9618 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0672 0.9194 0.008 0.992
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.9144 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.9618 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0672 0.9194 0.008 0.992
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.8207 0.6643 0.256 0.744
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.9618 1.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0672 0.9194 0.008 0.992
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.9618 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0672 0.9194 0.008 0.992
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.9000 0.4900 0.684 0.316
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.9618 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.9618 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.3584 0.8754 0.068 0.932
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.9710 0.4268 0.400 0.600
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0672 0.9194 0.008 0.992
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.9618 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0672 0.9194 0.008 0.992
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0672 0.9194 0.008 0.992
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.9618 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.9618 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.9618 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.9552 0.4782 0.376 0.624
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.2603 0.8967 0.044 0.956
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.9710 0.4268 0.400 0.600
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0672 0.9194 0.008 0.992
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.9850 0.2632 0.428 0.572
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0672 0.9194 0.008 0.992
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.9144 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9618 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.0376 0.9169 0.004 0.996
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.9209 0.4318 0.664 0.336
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.7376 0.6971 0.792 0.208
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.9618 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.0000 0.9618 1.000 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0672 0.9194 0.008 0.992
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9618 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.9618 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.9618 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.9618 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9618 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0672 0.9194 0.008 0.992
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9618 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9618 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0672 0.9194 0.008 0.992
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9144 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9618 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0672 0.9194 0.008 0.992
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9618 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0672 0.9194 0.008 0.992
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9618 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9618 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0672 0.9194 0.008 0.992
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.7219 0.7585 0.200 0.800
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9618 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0672 0.9194 0.008 0.992
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9618 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9618 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0672 0.9194 0.008 0.992
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9618 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.9710 0.4268 0.400 0.600
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9618 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9618 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.9618 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9618 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0672 0.9194 0.008 0.992
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7056 0.7289 0.808 0.192
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9618 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.94077 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.84696 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 3 0.5553 0.65592 0.004 0.272 0.724
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4605 0.83288 0.796 0.000 0.204
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.2434 0.76101 0.036 0.024 0.940
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.94077 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.84696 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4605 0.83288 0.796 0.000 0.204
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.84696 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0237 0.84729 0.996 0.000 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.5060 0.77332 0.064 0.100 0.836
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.5656 0.74712 0.284 0.004 0.712
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 3 0.5397 0.74732 0.280 0.000 0.720
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.94077 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.2772 0.76855 0.080 0.004 0.916
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0000 0.94077 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0237 0.94020 0.000 0.996 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.5560 0.62878 0.000 0.300 0.700
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0237 0.94020 0.000 0.996 0.004
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4999 0.82338 0.820 0.028 0.152
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0237 0.93805 0.004 0.996 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.3192 0.74987 0.000 0.112 0.888
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.5926 0.65028 0.644 0.000 0.356
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.84696 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0892 0.84792 0.980 0.000 0.020
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0424 0.93887 0.000 0.992 0.008
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4605 0.83288 0.796 0.000 0.204
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4605 0.83288 0.796 0.000 0.204
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.84696 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 3 0.6678 0.69895 0.060 0.216 0.724
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4605 0.83288 0.796 0.000 0.204
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.94077 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.5397 0.74732 0.280 0.000 0.720
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.84696 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0237 0.94020 0.000 0.996 0.004
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.84696 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.5291 0.79459 0.732 0.000 0.268
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4605 0.83288 0.796 0.000 0.204
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1031 0.83408 0.976 0.000 0.024
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.84696 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.1860 0.90047 0.000 0.948 0.052
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3192 0.76312 0.888 0.000 0.112
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0237 0.94020 0.000 0.996 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2261 0.90107 0.000 0.932 0.068
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3337 0.78220 0.908 0.060 0.032
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.94077 0.000 1.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.4605 0.83288 0.796 0.000 0.204
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#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.84696 1.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.5397 0.78067 0.720 0.000 0.280
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.4605 0.83288 0.796 0.000 0.204
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.5905 0.34486 0.000 0.648 0.352
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 3 0.3340 0.74916 0.120 0.000 0.880
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.84696 1.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 3 0.5397 0.74732 0.280 0.000 0.720
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.84696 1.000 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 3 0.3141 0.77200 0.068 0.020 0.912
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0237 0.93888 0.000 0.996 0.004
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.4605 0.83288 0.796 0.000 0.204
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.84696 1.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.5363 0.79010 0.724 0.000 0.276
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0892 0.93023 0.000 0.980 0.020
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.4974 0.68623 0.000 0.236 0.764
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.6008 0.65240 0.372 0.000 0.628
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.3030 0.75489 0.092 0.004 0.904
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.94077 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 3 0.5728 0.65895 0.008 0.272 0.720
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.2261 0.90107 0.000 0.932 0.068
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.6140 0.63618 0.596 0.000 0.404
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.4654 0.83150 0.792 0.000 0.208
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.2774 0.76527 0.072 0.008 0.920
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0892 0.84851 0.980 0.000 0.020
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.7430 0.27864 0.424 0.540 0.036
#> E9061D61-4774-464E-ABE4-EB15CD889141 3 0.6026 0.66170 0.376 0.000 0.624
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0424 0.93742 0.000 0.992 0.008
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.4605 0.83288 0.796 0.000 0.204
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.5327 0.65918 0.000 0.272 0.728
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.84696 1.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6140 0.58207 0.596 0.000 0.404
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0237 0.94020 0.000 0.996 0.004
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 3 0.6621 0.76366 0.228 0.052 0.720
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.5905 0.65723 0.648 0.000 0.352
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.5560 0.62878 0.000 0.300 0.700
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.3337 0.78220 0.908 0.060 0.032
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.4842 0.82485 0.776 0.000 0.224
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 3 0.5363 0.65194 0.000 0.276 0.724
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.2261 0.90107 0.000 0.932 0.068
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.1529 0.85027 0.960 0.000 0.040
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0237 0.94020 0.000 0.996 0.004
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.9752 0.20784 0.352 0.232 0.416
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 3 0.6192 0.59459 0.420 0.000 0.580
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.94077 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.4605 0.83288 0.796 0.000 0.204
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.94077 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.6180 0.69060 0.660 0.008 0.332
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.84696 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1031 0.83408 0.976 0.000 0.024
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.5859 0.31004 0.000 0.344 0.656
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 3 0.3141 0.77200 0.068 0.020 0.912
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0237 0.94020 0.000 0.996 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.84696 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.2066 0.88927 0.000 0.940 0.060
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0237 0.94020 0.000 0.996 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6154 0.08989 0.408 0.000 0.592
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.84696 1.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.4605 0.83288 0.796 0.000 0.204
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.6673 0.75555 0.224 0.056 0.720
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 3 0.7059 0.72584 0.112 0.164 0.724
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 3 0.2682 0.76490 0.076 0.004 0.920
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.3116 0.75120 0.000 0.108 0.892
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.8437 0.43184 0.596 0.276 0.128
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6280 -0.03603 0.000 0.540 0.460
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2261 0.90107 0.000 0.932 0.068
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.1031 0.83408 0.976 0.000 0.024
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.0747 0.93482 0.000 0.984 0.016
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.5588 0.74971 0.276 0.004 0.720
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.3784 0.72520 0.132 0.004 0.864
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.4605 0.83288 0.796 0.000 0.204
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 3 0.4654 0.62930 0.208 0.000 0.792
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.94077 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.84696 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.4605 0.83288 0.796 0.000 0.204
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4452 0.83581 0.808 0.000 0.192
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.2878 0.76509 0.096 0.000 0.904
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4399 0.83539 0.812 0.000 0.188
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0424 0.93742 0.000 0.992 0.008
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4452 0.83438 0.808 0.000 0.192
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0424 0.84329 0.992 0.000 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 3 0.5363 0.65194 0.000 0.276 0.724
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2261 0.90107 0.000 0.932 0.068
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.2448 0.76090 0.076 0.000 0.924
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.94077 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.84696 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6168 0.43517 0.000 0.412 0.588
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3192 0.75448 0.112 0.000 0.888
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.3752 0.70608 0.856 0.000 0.144
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0237 0.94020 0.000 0.996 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 3 0.7007 0.76605 0.176 0.100 0.724
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.4605 0.83288 0.796 0.000 0.204
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0237 0.94020 0.000 0.996 0.004
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.84696 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.4605 0.83288 0.796 0.000 0.204
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5497 0.50636 0.000 0.708 0.292
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.84696 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 3 0.3415 0.77577 0.080 0.020 0.900
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5016 0.80936 0.760 0.000 0.240
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.4452 0.67453 0.192 0.000 0.808
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.5882 0.69350 0.652 0.000 0.348
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.1031 0.83408 0.976 0.000 0.024
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1289 0.91691 0.000 0.968 0.032
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7787 0.62617 0.588 0.064 0.348
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.2448 0.79293 0.924 0.000 0.076
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2593 0.5932 0.000 0.892 0.104 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3711 0.6609 0.000 0.140 0.024 0.836
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0188 0.6380 0.996 0.000 0.004 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.3128 0.6419 0.032 0.004 0.076 0.888
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2408 0.5920 0.000 0.896 0.104 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4855 0.5804 0.600 0.000 0.400 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0188 0.6380 0.996 0.000 0.004 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.4641 0.7011 0.120 0.016 0.052 0.812
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.4323 0.6762 0.020 0.000 0.204 0.776
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.4720 0.6017 0.004 0.000 0.324 0.672
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4401 0.5127 0.000 0.724 0.272 0.004
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4194 0.6978 0.172 0.000 0.028 0.800
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.1059 0.5849 0.000 0.972 0.012 0.016
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5947 0.1241 0.004 0.556 0.032 0.408
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.9279 -0.0151 0.268 0.404 0.228 0.100
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1930 0.5674 0.004 0.936 0.056 0.004
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3805 0.7023 0.068 0.072 0.004 0.856
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.4897 0.4569 0.776 0.016 0.032 0.176
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.4713 0.5972 0.640 0.000 0.360 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.8768 0.3350 0.428 0.196 0.316 0.060
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.6407 0.4302 0.000 0.544 0.384 0.072
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0895 0.6314 0.976 0.000 0.020 0.004
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0188 0.6367 0.996 0.000 0.000 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4234 0.6518 0.000 0.132 0.052 0.816
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0779 0.6317 0.980 0.000 0.016 0.004
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.4713 0.4608 0.000 0.640 0.360 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.3831 0.6817 0.004 0.000 0.204 0.792
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4964 0.4458 0.000 0.616 0.380 0.004
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.4730 0.5961 0.636 0.000 0.364 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.9072 0.1339 0.480 0.208 0.168 0.144
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0895 0.6303 0.976 0.000 0.020 0.004
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5649 0.5627 0.580 0.000 0.392 0.028
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.6938 0.3537 0.000 0.488 0.400 0.112
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.7862 0.2197 0.388 0.000 0.332 0.280
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.7205 0.0490 0.000 0.296 0.532 0.172
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.8291 0.4237 0.448 0.084 0.380 0.088
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1109 0.5797 0.000 0.968 0.028 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0895 0.6303 0.976 0.000 0.020 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2266 0.5961 0.000 0.912 0.084 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.3758 0.5672 0.000 0.848 0.048 0.104
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3143 0.5970 0.000 0.876 0.100 0.024
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.6373 0.3193 0.000 0.652 0.200 0.148
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4776 0.5915 0.624 0.000 0.376 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.6378 1.000 0.000 0.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.6378 1.000 0.000 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4855 0.5786 0.600 0.000 0.400 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.9140 -0.0779 0.316 0.364 0.072 0.248
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.8605 -0.0550 0.240 0.404 0.036 0.320
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.3198 0.5531 0.004 0.884 0.032 0.080
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.7761 0.4851 0.340 0.100 0.044 0.516
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4866 0.5761 0.596 0.000 0.404 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.2408 0.5920 0.000 0.896 0.104 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.5384 0.6030 0.324 0.000 0.028 0.648
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#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.2530 0.5941 0.000 0.896 0.100 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.4679 0.4658 0.000 0.648 0.352 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.5309 0.6264 0.044 0.000 0.256 0.700
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.4071 0.7156 0.064 0.000 0.104 0.832
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.6378 1.000 0.000 0.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.5018 0.3224 0.000 0.012 0.332 0.656
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.4855 0.5786 0.600 0.000 0.400 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.3991 0.5309 0.832 0.000 0.048 0.120
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0188 0.6367 0.996 0.000 0.000 0.004
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.4220 0.4650 0.000 0.748 0.004 0.248
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.5141 0.6472 0.268 0.000 0.032 0.700
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.4855 0.5786 0.600 0.000 0.400 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.4059 0.6831 0.012 0.000 0.200 0.788
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.3907 0.7078 0.140 0.000 0.032 0.828
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.1624 0.5928 0.000 0.952 0.020 0.028
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0188 0.6380 0.996 0.000 0.004 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.9604 0.0361 0.400 0.212 0.200 0.188
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.7260 0.3446 0.000 0.464 0.388 0.148
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.7520 0.2578 0.108 0.564 0.036 0.292
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.8506 0.2115 0.036 0.204 0.372 0.388
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 4 0.7346 0.5554 0.304 0.084 0.040 0.572
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.2408 0.5920 0.000 0.896 0.104 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.3105 0.6686 0.000 0.140 0.004 0.856
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.6104 0.3333 0.000 0.680 0.180 0.140
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9557 0.0458 0.408 0.196 0.180 0.216
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.4683 0.5346 0.820 0.096 0.056 0.028
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.3105 0.7068 0.140 0.000 0.004 0.856
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.7599 0.5187 0.584 0.104 0.260 0.052
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.6701 0.2530 0.012 0.608 0.292 0.088
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.6136 0.5073 0.060 0.000 0.356 0.584
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.1624 0.5804 0.000 0.952 0.028 0.020
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.1489 0.6269 0.952 0.000 0.044 0.004
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.3105 0.6666 0.000 0.140 0.004 0.856
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.4817 0.5850 0.612 0.000 0.388 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.8252 0.1572 0.524 0.272 0.064 0.140
#> A2007795-C728-4688-B199-AE89500011D2 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.3105 0.6977 0.000 0.004 0.140 0.856
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.6838 0.3856 0.684 0.108 0.056 0.152
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.6065 0.0574 0.004 0.532 0.036 0.428
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.8378 0.4466 0.492 0.108 0.316 0.084
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.5712 0.4634 0.752 0.152 0.044 0.052
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.6715 0.3886 0.000 0.144 0.252 0.604
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 3 0.7072 0.0392 0.000 0.336 0.524 0.140
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.3688 0.6287 0.792 0.000 0.208 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4713 0.4608 0.000 0.640 0.360 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.7960 0.1978 0.144 0.528 0.040 0.288
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.7122 0.3803 0.144 0.000 0.340 0.516
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.4713 0.4608 0.000 0.640 0.360 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.4323 0.5446 0.840 0.088 0.040 0.032
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2530 0.5941 0.000 0.896 0.100 0.004
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.8376 0.1089 0.496 0.312 0.096 0.096
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5959 0.5505 0.568 0.000 0.388 0.044
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.9914 -0.0477 0.216 0.280 0.208 0.296
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.3606 0.7066 0.140 0.000 0.020 0.840
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.7178 0.4397 0.000 0.520 0.324 0.156
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.7243 0.0679 0.592 0.072 0.048 0.288
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4776 0.5908 0.624 0.000 0.376 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0188 0.6380 0.996 0.000 0.004 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6873 0.5049 0.000 0.252 0.160 0.588
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5742 0.5515 0.000 0.052 0.300 0.648
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4332 0.6960 0.176 0.000 0.032 0.792
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.8112 0.1783 0.088 0.412 0.068 0.432
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.7275 0.2834 0.056 0.624 0.232 0.088
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5928 0.1616 0.004 0.564 0.032 0.400
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.7072 0.0392 0.000 0.336 0.524 0.140
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.6000 0.5623 0.592 0.000 0.356 0.052
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.5100 0.4746 0.004 0.768 0.152 0.076
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.6750 0.4616 0.000 0.104 0.356 0.540
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.6110 0.5411 0.368 0.000 0.056 0.576
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0188 0.6367 0.996 0.000 0.000 0.004
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6443 0.5202 0.376 0.000 0.076 0.548
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0657 0.5852 0.000 0.984 0.012 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.5183 0.5684 0.584 0.000 0.408 0.008
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.3491 0.5539 0.864 0.104 0.028 0.004
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0592 0.6396 0.984 0.000 0.016 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4244 0.6991 0.168 0.000 0.032 0.800
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2408 0.6378 0.896 0.000 0.104 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2469 0.5923 0.000 0.892 0.108 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1389 0.6364 0.952 0.000 0.048 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.5508 0.5612 0.572 0.000 0.408 0.020
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.6609 0.4146 0.000 0.144 0.236 0.620
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.7084 0.0343 0.000 0.340 0.520 0.140
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4100 0.7052 0.148 0.000 0.036 0.816
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4713 0.4608 0.000 0.640 0.360 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4746 0.5959 0.632 0.000 0.368 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5399 0.4128 0.004 0.684 0.032 0.280
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.4728 0.6796 0.216 0.000 0.032 0.752
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.8304 -0.3665 0.396 0.040 0.408 0.156
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.3836 0.6906 0.000 0.016 0.168 0.816
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0592 0.6331 0.984 0.000 0.016 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4804 0.4434 0.000 0.616 0.384 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4761 0.5932 0.628 0.000 0.372 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0188 0.6367 0.996 0.000 0.000 0.004
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5649 0.4673 0.000 0.664 0.052 0.284
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4746 0.5947 0.632 0.000 0.368 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3659 0.7078 0.136 0.000 0.024 0.840
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.3149 0.5651 0.880 0.000 0.032 0.088
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5837 0.5226 0.400 0.000 0.036 0.564
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.6561 0.4102 0.696 0.104 0.040 0.160
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.7616 0.4866 0.504 0.088 0.368 0.040
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2984 0.5553 0.000 0.888 0.028 0.084
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.8141 0.1804 0.532 0.252 0.048 0.168
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.8364 0.4164 0.444 0.104 0.376 0.076
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4448 0.10160 0.000 0.516 0.480 0.004 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0963 0.76287 0.964 0.000 0.000 0.000 0.036
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2249 0.69178 0.000 0.040 0.020 0.920 0.020
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4126 0.64305 0.380 0.000 0.000 0.000 0.620
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4934 0.62509 0.000 0.012 0.224 0.708 0.056
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4449 0.09861 0.000 0.512 0.484 0.004 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1638 0.76350 0.932 0.000 0.004 0.000 0.064
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4138 0.64105 0.384 0.000 0.000 0.000 0.616
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0290 0.77529 0.992 0.000 0.000 0.000 0.008
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0290 0.77542 0.992 0.000 0.000 0.000 0.008
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.2067 0.71037 0.000 0.032 0.012 0.928 0.028
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5504 0.65303 0.160 0.000 0.032 0.704 0.104
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.7169 0.46014 0.284 0.000 0.048 0.496 0.172
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4430 0.14134 0.000 0.540 0.456 0.004 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4313 0.66076 0.000 0.000 0.040 0.732 0.228
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6255 0.23187 0.000 0.404 0.492 0.024 0.080
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0290 0.58280 0.000 0.992 0.000 0.008 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.7122 0.48832 0.000 0.056 0.456 0.364 0.124
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0290 0.58280 0.000 0.992 0.000 0.008 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 3 0.7896 0.49552 0.116 0.000 0.452 0.216 0.216
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 3 0.5368 0.22338 0.004 0.388 0.568 0.012 0.028
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.1710 0.70303 0.000 0.024 0.012 0.944 0.020
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.3129 0.64819 0.076 0.000 0.032 0.020 0.872
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.1697 0.75566 0.932 0.000 0.008 0.000 0.060
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.7643 0.28780 0.476 0.000 0.092 0.184 0.248
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3093 0.42355 0.000 0.824 0.008 0.168 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.4101 0.67369 0.332 0.000 0.000 0.004 0.664
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.4151 0.66865 0.344 0.000 0.000 0.004 0.652
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0404 0.77556 0.988 0.000 0.000 0.000 0.012
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.1764 0.68769 0.000 0.064 0.008 0.928 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.4135 0.67061 0.340 0.000 0.000 0.004 0.656
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2536 0.53138 0.000 0.868 0.128 0.004 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.5894 0.64805 0.148 0.000 0.036 0.672 0.144
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0290 0.77529 0.992 0.000 0.000 0.000 0.008
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1648 0.57385 0.000 0.940 0.040 0.020 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.1124 0.76196 0.960 0.000 0.004 0.000 0.036
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.5149 0.28757 0.024 0.004 0.424 0.004 0.544
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.4101 0.67460 0.332 0.000 0.000 0.004 0.664
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1483 0.77124 0.952 0.000 0.008 0.012 0.028
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0404 0.77408 0.988 0.000 0.000 0.000 0.012
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.3861 0.34924 0.000 0.728 0.008 0.264 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6947 0.28856 0.484 0.000 0.040 0.136 0.340
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0324 0.58332 0.000 0.992 0.004 0.004 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.5891 0.34672 0.000 0.556 0.364 0.052 0.028
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6019 0.52115 0.672 0.004 0.072 0.188 0.064
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 3 0.5089 0.21208 0.000 0.400 0.568 0.012 0.020
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.4218 0.67625 0.324 0.000 0.004 0.004 0.668
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.4451 0.06859 0.000 0.504 0.492 0.004 0.000
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#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.5302 0.18690 0.000 0.592 0.064 0.344 0.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.5869 0.35370 0.000 0.564 0.356 0.052 0.028
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.5309 0.36919 0.000 0.592 0.360 0.016 0.032
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.2017 0.74772 0.912 0.000 0.008 0.000 0.080
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 5 0.4868 0.68413 0.224 0.000 0.036 0.024 0.716
#> 976924B0-5799-4AC9-804F-78C8568037CA 5 0.4722 0.65240 0.104 0.000 0.084 0.036 0.776
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 5 0.5751 0.35040 0.076 0.000 0.404 0.004 0.516
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0671 0.77492 0.980 0.000 0.004 0.000 0.016
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.4599 0.06084 0.624 0.000 0.020 0.000 0.356
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 5 0.4088 0.65385 0.368 0.000 0.000 0.000 0.632
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 5 0.4114 0.64693 0.376 0.000 0.000 0.000 0.624
#> F3285881-878E-4190-BB96-9A2303C76346 3 0.7069 0.44730 0.004 0.028 0.476 0.164 0.328
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 3 0.4735 0.05385 0.000 0.460 0.524 0.016 0.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 5 0.6685 -0.17195 0.004 0.000 0.332 0.212 0.452
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.4279 0.68340 0.808 0.000 0.096 0.048 0.048
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 5 0.4238 0.65380 0.368 0.000 0.000 0.004 0.628
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 4 0.1883 0.71494 0.048 0.000 0.008 0.932 0.012
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.7214 0.17407 0.408 0.000 0.048 0.148 0.396
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 3 0.6736 0.44386 0.000 0.264 0.540 0.168 0.028
#> 93429F04-8404-4E8C-B654-9D2216BA432C 3 0.7412 -0.32062 0.000 0.040 0.384 0.364 0.212
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.5391 0.60960 0.708 0.000 0.024 0.108 0.160
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.4211 0.05135 0.636 0.000 0.000 0.004 0.360
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 5 0.4114 0.64693 0.376 0.000 0.000 0.000 0.624
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 4 0.5834 0.49549 0.028 0.000 0.044 0.536 0.392
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.4703 0.68813 0.012 0.016 0.072 0.780 0.120
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.5568 0.23684 0.004 0.368 0.576 0.020 0.032
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.1569 0.70258 0.000 0.032 0.008 0.948 0.012
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0963 0.76287 0.964 0.000 0.000 0.000 0.036
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 5 0.4126 0.64305 0.380 0.000 0.000 0.000 0.620
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 5 0.4114 0.64167 0.376 0.000 0.000 0.000 0.624
#> 6D711561-D549-44C7-885F-F3B846DB130C 3 0.6247 0.26670 0.000 0.364 0.484 0.152 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.3756 0.71079 0.012 0.000 0.044 0.824 0.120
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 3 0.4440 0.03316 0.000 0.468 0.528 0.000 0.004
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.4448 0.10160 0.000 0.516 0.480 0.004 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.2930 0.50512 0.000 0.832 0.164 0.004 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.6861 0.54515 0.252 0.000 0.044 0.548 0.156
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.3008 0.71166 0.004 0.000 0.036 0.868 0.092
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.4114 0.64693 0.376 0.000 0.000 0.000 0.624
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.6304 0.40654 0.000 0.224 0.216 0.556 0.004
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.1082 0.77253 0.964 0.000 0.008 0.000 0.028
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.3775 0.63610 0.092 0.000 0.016 0.060 0.832
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.4151 0.66865 0.344 0.000 0.000 0.004 0.652
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 3 0.6626 0.45114 0.000 0.144 0.476 0.364 0.016
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.5371 0.53261 0.020 0.000 0.032 0.596 0.352
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0771 0.77445 0.976 0.000 0.004 0.000 0.020
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.5664 0.65566 0.140 0.000 0.032 0.692 0.136
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0963 0.76287 0.964 0.000 0.000 0.000 0.036
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.2729 0.70674 0.000 0.004 0.028 0.884 0.084
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 3 0.4870 0.09881 0.000 0.448 0.532 0.016 0.004
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.4114 0.64444 0.376 0.000 0.000 0.000 0.624
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0404 0.77442 0.988 0.000 0.000 0.000 0.012
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.5109 0.25610 0.008 0.004 0.432 0.016 0.540
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.5878 0.05963 0.000 0.508 0.044 0.420 0.028
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.7371 0.52549 0.000 0.064 0.484 0.280 0.172
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.7676 0.23344 0.472 0.000 0.096 0.252 0.180
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.6060 -0.22429 0.008 0.000 0.092 0.424 0.476
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.4449 0.09861 0.000 0.512 0.484 0.004 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.2756 0.68408 0.004 0.040 0.036 0.900 0.020
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 3 0.4305 0.20494 0.000 0.128 0.780 0.004 0.088
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.5106 0.29814 0.020 0.000 0.408 0.012 0.560
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.5005 0.66405 0.160 0.000 0.072 0.028 0.740
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.1697 0.71091 0.000 0.000 0.008 0.932 0.060
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.7684 0.07829 0.440 0.000 0.092 0.160 0.308
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 3 0.7352 0.50136 0.176 0.032 0.568 0.180 0.044
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.7316 -0.20956 0.400 0.000 0.044 0.380 0.176
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.5267 0.17604 0.000 0.400 0.560 0.020 0.020
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.4236 0.66794 0.328 0.000 0.004 0.004 0.664
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.1538 0.70040 0.000 0.036 0.008 0.948 0.008
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0566 0.77521 0.984 0.000 0.004 0.000 0.012
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.4849 0.56869 0.040 0.000 0.128 0.068 0.764
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0290 0.58332 0.000 0.992 0.008 0.000 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.1679 0.71142 0.020 0.004 0.016 0.948 0.012
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.4034 0.65212 0.096 0.000 0.080 0.012 0.812
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.7135 0.49956 0.000 0.056 0.464 0.352 0.128
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6237 0.48879 0.664 0.012 0.060 0.188 0.076
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.5387 0.59120 0.084 0.000 0.092 0.088 0.736
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3916 0.52004 0.000 0.256 0.012 0.732 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.4897 0.38541 0.000 0.616 0.352 0.004 0.028
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.4088 0.32602 0.688 0.000 0.008 0.000 0.304
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2464 0.54587 0.000 0.888 0.096 0.016 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.7383 0.52512 0.004 0.052 0.484 0.288 0.172
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.7034 -0.02304 0.456 0.000 0.032 0.348 0.164
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1557 0.57002 0.000 0.940 0.052 0.008 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.3799 0.65028 0.068 0.000 0.072 0.024 0.836
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.4450 0.08731 0.000 0.508 0.488 0.004 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.5211 0.48906 0.032 0.000 0.220 0.048 0.700
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0290 0.77529 0.992 0.000 0.000 0.000 0.008
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1597 0.77134 0.948 0.000 0.008 0.020 0.024
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.6521 -0.07398 0.000 0.048 0.460 0.068 0.424
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.2325 0.71518 0.000 0.000 0.028 0.904 0.068
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0162 0.58292 0.000 0.996 0.000 0.004 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0162 0.77571 0.996 0.000 0.000 0.000 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6753 -0.16218 0.000 0.392 0.268 0.340 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0566 0.58087 0.000 0.984 0.012 0.004 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.4637 0.56107 0.056 0.000 0.052 0.108 0.784
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0162 0.77605 0.996 0.000 0.000 0.000 0.004
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.4126 0.64305 0.380 0.000 0.000 0.000 0.620
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.7014 0.11563 0.072 0.000 0.276 0.536 0.116
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2831 0.70063 0.008 0.068 0.016 0.892 0.016
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4552 0.64260 0.000 0.000 0.040 0.696 0.264
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.6868 0.38826 0.000 0.008 0.420 0.348 0.224
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.7455 0.52014 0.048 0.156 0.568 0.188 0.040
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.7250 -0.28217 0.000 0.076 0.356 0.456 0.112
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4897 0.38541 0.000 0.616 0.352 0.004 0.028
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.2518 0.74274 0.896 0.000 0.008 0.016 0.080
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6620 0.48827 0.000 0.080 0.620 0.168 0.132
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.7717 -0.10072 0.400 0.000 0.096 0.356 0.148
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.5311 -0.08849 0.012 0.000 0.036 0.368 0.584
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.4238 0.65355 0.368 0.000 0.000 0.004 0.628
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.5645 0.17082 0.028 0.000 0.052 0.296 0.624
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 3 0.5036 0.17883 0.000 0.416 0.556 0.012 0.016
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1892 0.75545 0.916 0.000 0.004 0.000 0.080
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.4295 0.65821 0.132 0.000 0.084 0.004 0.780
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.4893 0.61226 0.396 0.000 0.008 0.016 0.580
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4193 0.68577 0.000 0.000 0.040 0.748 0.212
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5300 -0.00863 0.600 0.000 0.024 0.024 0.352
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.4911 0.10497 0.000 0.504 0.476 0.012 0.008
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5380 -0.23590 0.532 0.000 0.028 0.016 0.424
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2908 0.73131 0.868 0.000 0.016 0.008 0.108
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.3388 0.58894 0.000 0.200 0.008 0.792 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.4151 0.40372 0.000 0.652 0.344 0.000 0.004
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4645 0.66831 0.000 0.000 0.044 0.688 0.268
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1638 0.56687 0.000 0.932 0.064 0.004 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1043 0.76442 0.960 0.000 0.000 0.000 0.040
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.7522 0.52425 0.000 0.116 0.480 0.288 0.116
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.4952 0.63428 0.016 0.000 0.040 0.692 0.252
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5066 0.66405 0.756 0.000 0.056 0.080 0.108
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0579 0.58152 0.000 0.984 0.008 0.008 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.2066 0.71202 0.008 0.028 0.008 0.932 0.024
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3816 0.67118 0.304 0.000 0.000 0.000 0.696
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0693 0.58175 0.000 0.980 0.008 0.012 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0671 0.77503 0.980 0.000 0.004 0.000 0.016
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.4335 0.66825 0.324 0.000 0.008 0.004 0.664
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 3 0.6492 0.42925 0.000 0.168 0.468 0.360 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0290 0.77529 0.992 0.000 0.000 0.000 0.008
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2905 0.71133 0.000 0.000 0.036 0.868 0.096
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.5363 0.59447 0.176 0.000 0.036 0.076 0.712
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5716 0.29996 0.028 0.000 0.032 0.472 0.468
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.6079 0.43595 0.056 0.000 0.088 0.204 0.652
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.4601 0.63298 0.772 0.000 0.064 0.024 0.140
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 3 0.6440 0.48467 0.000 0.212 0.572 0.200 0.016
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.6021 0.35090 0.028 0.000 0.120 0.212 0.640
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.5864 0.55165 0.676 0.000 0.088 0.052 0.184
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3843 0.2024 0.000 0.548 0.000 0.000 0.000 0.452
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.1700 0.7639 0.916 0.000 0.004 0.000 0.080 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.6455 0.5086 0.004 0.292 0.312 0.384 0.004 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3354 0.7312 0.240 0.000 0.004 0.004 0.752 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4883 0.3019 0.000 0.004 0.424 0.532 0.028 0.012
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.3944 0.2247 0.000 0.568 0.000 0.000 0.004 0.428
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2726 0.7570 0.884 0.004 0.016 0.052 0.044 0.000
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#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0865 0.7803 0.964 0.000 0.000 0.000 0.036 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1879 0.7733 0.932 0.016 0.016 0.008 0.028 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.5212 0.6090 0.000 0.068 0.668 0.016 0.228 0.020
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.4016 0.5602 0.000 0.108 0.120 0.768 0.004 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.0000 0.7857 0.000 0.000 0.000 0.000 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0790 0.7815 0.968 0.000 0.000 0.000 0.032 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6483 0.0939 0.000 0.540 0.236 0.128 0.000 0.096
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.0748 0.7836 0.000 0.016 0.004 0.000 0.004 0.976
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.6215 0.3291 0.012 0.028 0.116 0.336 0.508 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0790 0.7815 0.968 0.000 0.000 0.000 0.032 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.3404 0.7288 0.248 0.000 0.004 0.004 0.744 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.6707 0.0362 0.008 0.508 0.236 0.192 0.056 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.7129 0.5228 0.004 0.256 0.280 0.400 0.004 0.056
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.2401 0.5011 0.000 0.004 0.044 0.892 0.060 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5955 0.2687 0.004 0.580 0.260 0.040 0.116 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1849 0.5268 0.024 0.936 0.004 0.016 0.012 0.008
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6400 0.0990 0.000 0.536 0.268 0.140 0.048 0.008
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.4722 0.2814 0.000 0.000 0.492 0.004 0.036 0.468
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.4030 0.7204 0.804 0.036 0.060 0.008 0.092 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.5699 0.2501 0.000 0.596 0.276 0.016 0.096 0.016
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.8247 -0.0398 0.360 0.188 0.244 0.148 0.060 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.5611 0.1569 0.004 0.000 0.144 0.524 0.328 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.3163 0.7371 0.232 0.000 0.004 0.000 0.764 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.6910 0.2713 0.056 0.024 0.192 0.212 0.516 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3446 0.3709 0.000 0.692 0.000 0.000 0.000 0.308
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2507 0.7561 0.892 0.000 0.016 0.056 0.036 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.4269 0.6103 0.056 0.076 0.088 0.000 0.780 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.4537 0.7018 0.248 0.000 0.004 0.068 0.680 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.1562 0.5113 0.004 0.024 0.000 0.940 0.032 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.5516 0.4396 0.356 0.000 0.000 0.140 0.504 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.5254 0.2153 0.000 0.548 0.016 0.020 0.028 0.388
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.5824 0.4853 0.312 0.000 0.004 0.184 0.500 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2439 0.7594 0.904 0.008 0.028 0.040 0.020 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.6979 0.5000 0.000 0.260 0.216 0.440 0.000 0.084
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.3925 0.1604 0.000 0.000 0.332 0.004 0.008 0.656
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4527 0.5208 0.020 0.096 0.028 0.772 0.084 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.1663 0.7577 0.000 0.088 0.000 0.000 0.000 0.912
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1644 0.7568 0.920 0.000 0.000 0.004 0.076 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.4876 0.4231 0.000 0.732 0.136 0.064 0.064 0.004
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.2300 0.4790 0.000 0.000 0.000 0.856 0.144 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4819 0.6792 0.756 0.040 0.052 0.116 0.036 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 6 0.0692 0.7839 0.000 0.020 0.000 0.000 0.004 0.976
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.6213 0.5442 0.000 0.248 0.224 0.508 0.004 0.016
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3353 0.7404 0.160 0.000 0.004 0.032 0.804 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 6 0.0000 0.7857 0.000 0.000 0.000 0.000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1984 0.7751 0.912 0.000 0.000 0.032 0.056 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.3941 0.7315 0.180 0.012 0.036 0.004 0.768 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4842 0.2477 0.000 0.648 0.284 0.052 0.004 0.012
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1531 0.7704 0.928 0.000 0.004 0.000 0.068 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2263 0.5388 0.000 0.036 0.060 0.900 0.004 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.5016 -0.2591 0.060 0.000 0.004 0.504 0.432 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.4636 0.2894 0.044 0.000 0.020 0.676 0.260 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.7304 0.2288 0.020 0.240 0.132 0.132 0.476 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.5065 0.6576 0.728 0.084 0.072 0.008 0.108 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1812 0.5216 0.000 0.924 0.004 0.004 0.008 0.060
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.6404 0.1239 0.016 0.364 0.108 0.036 0.476 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.6234 0.5402 0.632 0.108 0.128 0.020 0.112 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.852 0.900 0.960 0.4991 0.501 0.501
#> 3 3 0.668 0.729 0.830 0.3140 0.782 0.592
#> 4 4 0.706 0.772 0.878 0.1343 0.829 0.556
#> 5 5 0.695 0.622 0.796 0.0615 0.908 0.669
#> 6 6 0.730 0.654 0.809 0.0425 0.910 0.623
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9499 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9631 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9499 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9631 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.7219 0.7478 0.200 0.800
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9499 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9631 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9631 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9631 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9631 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9499 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.9922 0.1417 0.552 0.448
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.9631 1.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9499 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.9686 0.3822 0.396 0.604
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0000 0.9499 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9499 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0000 0.9499 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9499 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.9933 0.1840 0.548 0.452
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3733 0.8866 0.072 0.928
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9499 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9631 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9631 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0000 0.9631 1.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9499 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9631 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9631 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9631 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9499 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9631 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9499 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9631 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9631 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9499 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9631 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.9631 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9631 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9631 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9631 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9499 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.9631 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9499 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9499 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.7219 0.7358 0.800 0.200
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9499 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9631 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9499 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9499 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9499 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.0000 0.9499 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9631 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9631 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9631 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9631 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9631 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0672 0.9441 0.008 0.992
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.0000 0.9499 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9499 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.9710 0.2970 0.600 0.400
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9631 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9499 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9631 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9631 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9631 1.000 0.000
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#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.4161 0.8785 0.084 0.916
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.9499 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.9631 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.9499 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9499 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.9631 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.9631 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.9631 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.9499 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.9499 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.9661 0.3922 0.392 0.608
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9499 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.9552 0.3837 0.376 0.624
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.9499 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.9499 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9631 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.0000 0.9499 0.000 1.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.9998 0.0832 0.492 0.508
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.9286 0.4461 0.656 0.344
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.9631 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.0000 0.9631 1.000 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9499 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9631 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.9631 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.9631 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.9631 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9631 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9499 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9631 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9631 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9499 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9499 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9631 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9499 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9631 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0000 0.9499 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9631 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9631 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9499 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9499 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9631 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9499 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9631 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9631 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9499 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9631 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.7219 0.7478 0.200 0.800
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9631 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9631 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.9631 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9631 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9499 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9491 0.4199 0.632 0.368
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9631 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9353 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.7434 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 3 0.6062 0.4773 0.000 0.384 0.616
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.6062 0.7191 0.616 0.000 0.384
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.5574 0.6600 0.032 0.184 0.784
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9353 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.7434 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.6062 0.7191 0.616 0.000 0.384
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.7434 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.7434 1.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.6008 0.4923 0.000 0.372 0.628
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.6062 0.6162 0.384 0.000 0.616
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 3 0.6062 0.6162 0.384 0.000 0.616
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9353 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.0000 0.6418 0.000 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0000 0.9353 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9353 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0000 0.9353 0.000 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9353 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6302 0.1395 0.520 0.480 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9353 0.000 1.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.6062 0.4773 0.000 0.384 0.616
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.6062 0.7191 0.616 0.000 0.384
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.7434 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0237 0.7438 0.996 0.000 0.004
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9353 0.000 1.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6062 0.7191 0.616 0.000 0.384
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.6062 0.7191 0.616 0.000 0.384
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.7434 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 3 0.6062 0.4773 0.000 0.384 0.616
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.6062 0.7191 0.616 0.000 0.384
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9353 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.6062 0.6162 0.384 0.000 0.616
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.7434 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9353 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.7434 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.6062 0.7191 0.616 0.000 0.384
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6062 0.7191 0.616 0.000 0.384
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.7434 1.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.7434 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 3 0.6180 0.4176 0.000 0.416 0.584
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0892 0.7444 0.980 0.000 0.020
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9353 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.4974 0.6000 0.000 0.764 0.236
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.1860 0.7201 0.948 0.052 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9353 0.000 1.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.6062 0.7191 0.616 0.000 0.384
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9353 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9353 0.000 1.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9353 0.000 1.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.0000 0.9353 0.000 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.7434 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.7434 1.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.6062 0.7191 0.616 0.000 0.384
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.6062 0.7191 0.616 0.000 0.384
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.7434 1.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.5098 0.5946 0.000 0.752 0.248
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.1529 0.8940 0.000 0.960 0.040
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9353 0.000 1.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.0000 0.6418 0.000 0.000 1.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.7434 1.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9353 0.000 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.0000 0.6418 0.000 0.000 1.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.6062 0.7191 0.616 0.000 0.384
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.7434 1.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9353 0.000 1.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 3 0.6180 0.4176 0.000 0.416 0.584
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 3 0.8466 0.6554 0.212 0.172 0.616
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.7434 1.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.6062 0.7191 0.616 0.000 0.384
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.7434 1.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.7434 1.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0000 0.9353 0.000 1.000 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.4605 0.6423 0.204 0.000 0.796
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0000 0.9353 0.000 1.000 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4974 0.6005 0.000 0.764 0.236
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9353 0.000 1.000 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.0000 0.6418 0.000 0.000 1.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.7434 1.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.7434 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.6062 0.7191 0.616 0.000 0.384
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.3551 0.7645 0.132 0.868 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.7434 1.000 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.4654 0.2762 0.208 0.000 0.792
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.6062 0.7191 0.616 0.000 0.384
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.6062 0.7191 0.616 0.000 0.384
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9353 0.000 1.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 3 0.6062 0.6162 0.384 0.000 0.616
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9353 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.6062 0.7191 0.616 0.000 0.384
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 3 0.0000 0.6418 0.000 0.000 1.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9353 0.000 1.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.9353 0.000 1.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.0000 0.7434 1.000 0.000 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.6062 0.3590 0.000 0.616 0.384
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.7434 1.000 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.7434 1.000 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.6062 0.7191 0.616 0.000 0.384
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.0000 0.6418 0.000 0.000 1.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 3 0.0000 0.6418 0.000 0.000 1.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.6062 0.7191 0.616 0.000 0.384
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.7434 1.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.9353 0.000 1.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.2066 0.7438 0.940 0.000 0.060
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.7690 -0.0473 0.048 0.536 0.416
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.6062 0.7191 0.616 0.000 0.384
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 3 0.8482 0.6508 0.200 0.184 0.616
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.6204 0.2896 0.000 0.576 0.424
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 3 0.6062 0.6162 0.384 0.000 0.616
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.3686 0.6599 0.860 0.140 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.6045 0.6174 0.380 0.000 0.620
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.9353 0.000 1.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.7434 1.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.9353 0.000 1.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 3 0.5968 -0.2458 0.364 0.000 0.636
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.6062 0.7191 0.616 0.000 0.384
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.9353 0.000 1.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.7434 1.000 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.9353 0.000 1.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.9353 0.000 1.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.7434 1.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.6062 0.7191 0.616 0.000 0.384
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 3 0.3941 0.6644 0.000 0.156 0.844
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.6062 0.7191 0.616 0.000 0.384
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#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 3 0.6062 0.4773 0.000 0.384 0.616
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9353 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.0000 0.6418 0.000 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9353 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.7434 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0000 0.9353 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.0000 0.6418 0.000 0.000 1.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0747 0.7297 0.984 0.000 0.016
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9353 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 3 0.8482 0.6508 0.200 0.184 0.616
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.6062 0.7191 0.616 0.000 0.384
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9353 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.7434 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.6062 0.7191 0.616 0.000 0.384
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9353 0.000 1.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.7434 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 3 0.2982 0.6706 0.024 0.056 0.920
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6111 0.7082 0.604 0.000 0.396
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.0000 0.6418 0.000 0.000 1.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.6062 0.7191 0.616 0.000 0.384
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.7434 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9353 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.8408 0.6366 0.612 0.144 0.244
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.7434 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.2011 0.8406 0.920 0.000 0.080 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3610 0.7526 0.000 0.200 0.000 0.800
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0188 0.7405 0.000 0.000 0.004 0.996
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0188 0.7442 0.000 0.004 0.000 0.996
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.3831 0.7382 0.204 0.000 0.004 0.792
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4188 0.6001 0.752 0.000 0.004 0.244
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3649 0.7328 0.000 0.000 0.204 0.796
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0592 0.9028 0.000 0.984 0.016 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0336 0.9081 0.000 0.992 0.000 0.008
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0592 0.9028 0.000 0.984 0.016 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0469 0.9061 0.000 0.988 0.000 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.6658 0.2692 0.092 0.532 0.376 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3610 0.7526 0.000 0.200 0.000 0.800
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0188 0.8912 0.004 0.000 0.996 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3074 0.7919 0.848 0.000 0.152 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.2149 0.8234 0.912 0.000 0.088 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3355 0.8094 0.000 0.836 0.004 0.160
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.3610 0.7526 0.000 0.200 0.000 0.800
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.3870 0.7355 0.208 0.000 0.004 0.788
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0469 0.9061 0.000 0.988 0.000 0.012
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.3024 0.7938 0.852 0.000 0.148 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3791 0.7473 0.004 0.000 0.796 0.200
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.3649 0.7495 0.000 0.204 0.000 0.796
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.2216 0.8203 0.908 0.000 0.092 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4122 0.5081 0.000 0.236 0.004 0.760
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3266 0.7183 0.832 0.168 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.3105 0.8212 0.000 0.856 0.004 0.140
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.4284 0.7628 0.000 0.780 0.020 0.200
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4888 0.2985 0.000 0.588 0.412 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.4948 0.2616 0.000 0.560 0.440 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.2760 0.7656 0.000 0.000 0.872 0.128
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.5112 0.3674 0.004 0.000 0.436 0.560
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1792 0.8480 0.932 0.000 0.068 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.3649 0.7495 0.000 0.204 0.000 0.796
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.3610 0.7417 0.200 0.000 0.000 0.800
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 3 0.1302 0.8850 0.044 0.000 0.956 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0188 0.8760 0.996 0.000 0.004 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0592 0.9028 0.000 0.984 0.016 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4535 0.4535 0.292 0.000 0.004 0.704
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0469 0.9048 0.000 0.988 0.012 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.4679 0.5510 0.000 0.352 0.000 0.648
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.5016 0.5337 0.000 0.600 0.004 0.396
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.4941 0.0384 0.000 0.000 0.564 0.436
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.7254 0.2094 0.000 0.468 0.384 0.148
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.3444 0.7626 0.816 0.000 0.184 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.4250 0.6877 0.000 0.000 0.724 0.276
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0895 0.8619 0.976 0.000 0.004 0.020
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.4072 0.6889 0.000 0.000 0.252 0.748
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.3400 0.7696 0.820 0.000 0.180 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.6229 0.6190 0.000 0.132 0.664 0.204
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.2011 0.8406 0.920 0.000 0.080 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0188 0.8760 0.996 0.000 0.004 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.3649 0.7328 0.000 0.000 0.204 0.796
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.3688 0.7298 0.000 0.000 0.208 0.792
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.4972 0.0298 0.456 0.000 0.544 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.5902 0.2695 0.012 0.452 0.016 0.520
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.3933 0.7499 0.008 0.000 0.792 0.200
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.3610 0.7417 0.200 0.000 0.000 0.800
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.2647 0.8131 0.000 0.000 0.880 0.120
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.3831 0.7382 0.204 0.000 0.004 0.792
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.6621 0.5713 0.628 0.184 0.188 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.3933 0.7411 0.200 0.000 0.008 0.792
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 3 0.0804 0.8897 0.008 0.000 0.980 0.012
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.3610 0.7733 0.000 0.800 0.000 0.200
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0592 0.8728 0.984 0.000 0.016 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.1792 0.8480 0.932 0.000 0.068 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.4121 0.7449 0.000 0.020 0.184 0.796
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 3 0.0188 0.8912 0.004 0.000 0.996 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0188 0.8760 0.996 0.000 0.004 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.2408 0.8021 0.896 0.104 0.000 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 4 0.3831 0.5660 0.000 0.204 0.004 0.792
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.2011 0.8406 0.920 0.000 0.080 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0469 0.9061 0.000 0.988 0.000 0.012
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3870 0.7702 0.000 0.788 0.004 0.208
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0336 0.9081 0.000 0.992 0.000 0.008
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.0188 0.9091 0.000 0.996 0.000 0.004
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.1716 0.8630 0.000 0.936 0.000 0.064
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.3791 0.7411 0.200 0.000 0.004 0.796
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#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.1637 0.8732 0.060 0.000 0.940 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4267 0.7421 0.024 0.000 0.188 0.788
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4877 0.2937 0.592 0.000 0.408 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.3172 0.7779 0.160 0.000 0.840 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.3610 0.7526 0.000 0.200 0.000 0.800
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.3831 0.7699 0.000 0.792 0.004 0.204
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4500 0.6074 0.000 0.000 0.316 0.684
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0188 0.9093 0.000 0.996 0.000 0.004
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0336 0.8751 0.992 0.000 0.008 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0592 0.9028 0.000 0.984 0.016 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.3688 0.7298 0.000 0.000 0.208 0.792
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0336 0.9081 0.000 0.992 0.000 0.008
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.3937 0.7488 0.188 0.012 0.000 0.800
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0817 0.8974 0.024 0.000 0.976 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0336 0.9081 0.000 0.992 0.000 0.008
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0336 0.9081 0.000 0.992 0.000 0.008
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8781 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3649 0.7328 0.000 0.000 0.204 0.796
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.0707 0.8961 0.020 0.000 0.980 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.3384 0.7767 0.024 0.000 0.860 0.116
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0336 0.8928 0.008 0.000 0.992 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3356 0.7701 0.824 0.000 0.176 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9099 0.000 1.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.3088 0.7683 0.008 0.128 0.864 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3356 0.7701 0.824 0.000 0.176 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0880 0.87334 0.968 0.000 0.000 0.000 0.032
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4074 0.50398 0.000 0.000 0.364 0.636 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.3333 0.38675 0.000 0.000 0.788 0.208 0.004
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0693 0.87918 0.980 0.000 0.000 0.008 0.012
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.3932 0.52832 0.000 0.000 0.328 0.672 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2891 0.53554 0.176 0.000 0.000 0.824 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.4227 0.16969 0.420 0.000 0.000 0.580 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1792 0.71124 0.000 0.916 0.084 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.0510 0.58115 0.000 0.000 0.000 0.984 0.016
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.2712 0.67154 0.000 0.880 0.088 0.000 0.032
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4101 0.52411 0.000 0.628 0.372 0.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5940 0.46102 0.000 0.652 0.108 0.208 0.032
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4126 0.51665 0.000 0.620 0.380 0.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3581 0.64290 0.052 0.852 0.064 0.000 0.032
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3796 0.54344 0.000 0.000 0.300 0.700 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.1608 0.82829 0.000 0.000 0.000 0.072 0.928
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3479 0.79742 0.836 0.000 0.080 0.000 0.084
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.2471 0.78192 0.864 0.000 0.000 0.000 0.136
#> C6AD4922-9981-4493-9F33-87A449B6EE55 3 0.3816 0.27534 0.000 0.304 0.696 0.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4402 0.50704 0.000 0.012 0.352 0.636 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3895 0.56807 0.000 0.680 0.320 0.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.2377 0.55858 0.128 0.000 0.000 0.872 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4299 0.50542 0.000 0.608 0.388 0.004 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.2729 0.83027 0.884 0.000 0.056 0.000 0.060
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4302 0.17580 0.000 0.000 0.520 0.000 0.480
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.6405 0.30190 0.000 0.172 0.384 0.444 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3264 0.77597 0.840 0.000 0.004 0.024 0.132
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.4088 0.52805 0.000 0.632 0.368 0.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.2393 0.48697 0.000 0.016 0.900 0.080 0.004
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3039 0.68056 0.808 0.192 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.0703 0.87843 0.024 0.000 0.000 0.000 0.976
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 3 0.4227 -0.05841 0.000 0.420 0.580 0.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4731 0.34125 0.000 0.328 0.640 0.000 0.032
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4625 0.29889 0.000 0.660 0.012 0.012 0.316
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.6214 0.45776 0.000 0.652 0.088 0.184 0.076
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.4503 0.58756 0.000 0.000 0.036 0.268 0.696
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0162 0.73579 0.000 0.996 0.004 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.4210 0.14772 0.000 0.000 0.000 0.588 0.412
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0609 0.87876 0.980 0.000 0.000 0.000 0.020
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4457 0.49395 0.000 0.012 0.368 0.620 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.4219 0.56649 0.024 0.000 0.260 0.716 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0162 0.88355 0.996 0.000 0.000 0.000 0.004
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.2712 0.67154 0.000 0.880 0.088 0.000 0.032
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.5668 0.25397 0.084 0.000 0.580 0.332 0.004
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.4988 0.57616 0.000 0.752 0.092 0.124 0.032
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 3 0.6775 -0.10815 0.000 0.284 0.388 0.328 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.2376 0.52400 0.000 0.052 0.904 0.044 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.6734 0.00909 0.000 0.000 0.332 0.404 0.264
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.4843 0.38647 0.000 0.660 0.292 0.000 0.048
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.3754 0.78153 0.816 0.000 0.084 0.000 0.100
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.6031 0.29187 0.000 0.000 0.520 0.128 0.352
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 5 0.3047 0.78286 0.004 0.000 0.084 0.044 0.868
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0162 0.73579 0.000 0.996 0.004 0.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.3895 0.54821 0.680 0.000 0.000 0.320 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.3819 0.48465 0.000 0.000 0.016 0.756 0.228
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.6318 0.59087 0.644 0.000 0.084 0.184 0.088
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.4015 0.42222 0.000 0.000 0.652 0.000 0.348
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0963 0.87217 0.964 0.000 0.000 0.000 0.036
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0880 0.86625 0.968 0.000 0.000 0.032 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.0162 0.58254 0.000 0.000 0.004 0.996 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.3109 0.50637 0.000 0.000 0.000 0.800 0.200
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0693 0.86474 0.008 0.000 0.000 0.012 0.980
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.4060 0.53596 0.000 0.640 0.360 0.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.5616 0.39681 0.552 0.000 0.084 0.000 0.364
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.4995 0.43791 0.000 0.004 0.420 0.552 0.024
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.3496 0.63645 0.012 0.000 0.200 0.000 0.788
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.4323 0.52815 0.012 0.000 0.332 0.656 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.6066 0.25561 0.000 0.000 0.504 0.128 0.368
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.3109 0.52140 0.200 0.000 0.000 0.800 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.5724 0.32232 0.284 0.628 0.032 0.000 0.056
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.2852 0.53814 0.172 0.000 0.000 0.828 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.4045 0.53943 0.000 0.644 0.356 0.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.2674 0.77782 0.000 0.000 0.004 0.140 0.856
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.3913 0.28781 0.000 0.676 0.324 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0404 0.88173 0.988 0.000 0.000 0.000 0.012
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.4074 0.53135 0.000 0.636 0.364 0.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0794 0.87523 0.972 0.000 0.000 0.000 0.028
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
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#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.5504 0.52926 0.000 0.704 0.104 0.160 0.032
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6282 0.60297 0.660 0.012 0.084 0.188 0.056
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.0162 0.86544 0.004 0.000 0.000 0.000 0.996
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3999 0.51782 0.000 0.000 0.344 0.656 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 3 0.2389 0.56033 0.000 0.116 0.880 0.000 0.004
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.5409 0.53399 0.612 0.000 0.084 0.000 0.304
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4101 0.52493 0.000 0.628 0.372 0.000 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.3209 0.66350 0.000 0.864 0.088 0.016 0.032
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.4632 0.26281 0.540 0.000 0.000 0.448 0.012
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.4015 0.54629 0.000 0.652 0.348 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.1106 0.87481 0.024 0.000 0.000 0.012 0.964
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.4657 0.48101 0.000 0.036 0.668 0.000 0.296
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.3431 0.54281 0.000 0.020 0.828 0.008 0.144
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.0000 0.58216 0.000 0.000 0.000 1.000 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4101 0.52411 0.000 0.628 0.372 0.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.4114 0.52245 0.000 0.624 0.376 0.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4101 0.52411 0.000 0.628 0.372 0.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.5271 0.49621 0.000 0.000 0.076 0.296 0.628
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8165 0.06600 0.324 0.404 0.140 0.120 0.012
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5299 0.50042 0.036 0.012 0.364 0.588 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3209 0.48227 0.000 0.000 0.180 0.812 0.008
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.6581 0.26745 0.000 0.444 0.372 0.180 0.004
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.2112 0.68224 0.004 0.908 0.084 0.000 0.004
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.3242 0.45851 0.000 0.216 0.784 0.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.2389 0.56033 0.000 0.116 0.880 0.000 0.004
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.3455 0.80320 0.844 0.000 0.084 0.004 0.068
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4836 0.32940 0.000 0.336 0.628 0.000 0.036
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.4878 0.64387 0.728 0.000 0.164 0.104 0.004
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.5857 0.12833 0.000 0.000 0.096 0.444 0.460
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.5680 0.47722 0.008 0.000 0.160 0.176 0.656
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0162 0.88365 0.996 0.000 0.000 0.004 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0609 0.87624 0.020 0.000 0.000 0.000 0.980
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.1410 0.86775 0.060 0.000 0.000 0.000 0.940
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.0671 0.58178 0.004 0.000 0.000 0.980 0.016
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.4774 0.31107 0.424 0.000 0.000 0.020 0.556
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0162 0.73579 0.000 0.996 0.004 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.4252 0.60448 0.280 0.000 0.000 0.020 0.700
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.4306 0.52500 0.000 0.012 0.328 0.660 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.2329 0.55659 0.000 0.124 0.876 0.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.3932 0.33736 0.000 0.000 0.000 0.672 0.328
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3999 0.54974 0.000 0.656 0.344 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1197 0.86078 0.952 0.000 0.000 0.000 0.048
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5160 0.55908 0.000 0.736 0.092 0.140 0.032
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.3109 0.50637 0.000 0.000 0.000 0.800 0.200
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1121 0.86126 0.956 0.000 0.000 0.044 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4114 0.52069 0.000 0.624 0.376 0.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.3480 0.56560 0.000 0.000 0.248 0.752 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0963 0.88378 0.036 0.000 0.000 0.000 0.964
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4126 0.51684 0.000 0.620 0.380 0.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0290 0.88259 0.992 0.000 0.000 0.008 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.1831 0.82078 0.004 0.000 0.076 0.000 0.920
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5204 0.47119 0.000 0.580 0.368 0.052 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.88535 1.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0000 0.58216 0.000 0.000 0.000 1.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.4029 0.57258 0.004 0.000 0.000 0.316 0.680
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.4726 0.37805 0.020 0.000 0.000 0.400 0.580
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.4732 0.61452 0.004 0.000 0.084 0.176 0.736
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.3593 0.79115 0.828 0.000 0.084 0.000 0.088
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.73621 0.000 1.000 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3511 0.66429 0.004 0.000 0.012 0.184 0.800
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3648 0.78821 0.824 0.000 0.084 0.000 0.092
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0146 0.81193 0.000 0.996 0.000 0.000 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0146 0.86279 0.996 0.000 0.000 0.000 0.004 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 6 0.1196 0.69113 0.000 0.000 0.008 0.040 0.000 0.952
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.4312 0.56902 0.000 0.000 0.676 0.052 0.000 0.272
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1633 0.83094 0.932 0.000 0.000 0.044 0.024 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.2706 0.66837 0.000 0.000 0.024 0.124 0.000 0.852
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2744 0.76273 0.072 0.000 0.000 0.864 0.000 0.064
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.3834 0.66316 0.232 0.000 0.000 0.732 0.000 0.036
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.2048 0.75450 0.000 0.880 0.000 0.000 0.000 0.120
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.1807 0.77095 0.000 0.000 0.000 0.920 0.020 0.060
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5207 0.56157 0.000 0.612 0.308 0.044 0.004 0.032
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.3833 0.47244 0.000 0.344 0.008 0.000 0.000 0.648
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 6 0.7135 -0.05832 0.000 0.280 0.320 0.060 0.004 0.336
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.3290 0.59884 0.000 0.252 0.004 0.000 0.000 0.744
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.2564 0.76093 0.000 0.896 0.028 0.040 0.032 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 6 0.2333 0.67755 0.000 0.000 0.024 0.092 0.000 0.884
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.2950 0.73305 0.000 0.000 0.024 0.148 0.828 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.4173 0.62565 0.696 0.000 0.268 0.024 0.012 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.2946 0.72619 0.824 0.000 0.000 0.012 0.160 0.004
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.5214 0.44050 0.000 0.216 0.172 0.000 0.000 0.612
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0551 0.86324 0.004 0.000 0.004 0.008 0.984 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0291 0.86388 0.004 0.000 0.000 0.004 0.992 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.1890 0.68913 0.000 0.000 0.024 0.060 0.000 0.916
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0436 0.86377 0.004 0.000 0.004 0.004 0.988 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3595 0.53247 0.000 0.704 0.008 0.000 0.000 0.288
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.2179 0.77105 0.036 0.000 0.000 0.900 0.000 0.064
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0260 0.86158 0.992 0.000 0.000 0.008 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.3265 0.60164 0.000 0.248 0.004 0.000 0.000 0.748
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.3313 0.73936 0.808 0.000 0.160 0.024 0.008 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3547 0.46804 0.000 0.000 0.668 0.000 0.332 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0551 0.86351 0.004 0.000 0.004 0.008 0.984 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0865 0.84760 0.964 0.000 0.000 0.036 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 6 0.2355 0.67906 0.000 0.112 0.008 0.004 0.000 0.876
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.4558 0.63351 0.720 0.000 0.008 0.124 0.148 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 6 0.3769 0.45574 0.000 0.356 0.004 0.000 0.000 0.640
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.3531 0.56332 0.000 0.000 0.672 0.000 0.000 0.328
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3352 0.71752 0.820 0.120 0.000 0.004 0.000 0.056
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.1644 0.83539 0.004 0.000 0.000 0.076 0.920 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0146 0.81193 0.000 0.996 0.000 0.000 0.000 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.6071 0.07045 0.000 0.348 0.268 0.000 0.000 0.384
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0547 0.81276 0.000 0.980 0.000 0.000 0.000 0.020
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0622 0.53563 0.000 0.008 0.980 0.000 0.000 0.012
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.0405 0.86393 0.004 0.000 0.000 0.008 0.988 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.5008 0.47590 0.000 0.680 0.012 0.076 0.220 0.012
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.7671 0.28365 0.000 0.400 0.320 0.132 0.048 0.100
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.5583 0.17781 0.000 0.000 0.124 0.480 0.392 0.004
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0790 0.81077 0.000 0.968 0.000 0.000 0.000 0.032
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.3333 0.73085 0.000 0.000 0.000 0.784 0.192 0.024
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0551 0.86324 0.004 0.000 0.004 0.008 0.984 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0146 0.86279 0.996 0.000 0.000 0.000 0.004 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0632 0.81227 0.000 0.976 0.000 0.000 0.000 0.024
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.0363 0.68969 0.000 0.000 0.000 0.012 0.000 0.988
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 6 0.3447 0.64270 0.012 0.000 0.024 0.164 0.000 0.800
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0146 0.86264 0.996 0.000 0.004 0.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.4496 0.56389 0.000 0.644 0.308 0.044 0.004 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.4926 0.42039 0.084 0.000 0.668 0.232 0.000 0.016
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.6475 0.43731 0.000 0.492 0.316 0.052 0.004 0.136
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 6 0.1700 0.69083 0.000 0.080 0.000 0.004 0.000 0.916
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.3684 0.50820 0.000 0.000 0.628 0.000 0.000 0.372
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#> F3285881-878E-4190-BB96-9A2303C76346 3 0.3927 0.42684 0.000 0.344 0.644 0.000 0.000 0.012
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0260 0.81237 0.000 0.992 0.000 0.000 0.000 0.008
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 5 0.4679 0.58415 0.000 0.240 0.004 0.072 0.680 0.004
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0865 0.84760 0.964 0.000 0.000 0.036 0.000 0.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 5 0.0405 0.86393 0.004 0.000 0.000 0.008 0.988 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 6 0.4780 0.21341 0.020 0.000 0.024 0.388 0.000 0.568
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.5463 0.46022 0.612 0.000 0.012 0.212 0.164 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.1257 0.80275 0.000 0.952 0.020 0.000 0.000 0.028
#> 93429F04-8404-4E8C-B654-9D2216BA432C 3 0.4079 0.57509 0.000 0.000 0.680 0.032 0.000 0.288
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.3323 0.64127 0.752 0.000 0.000 0.240 0.000 0.008
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 5 0.5187 0.07148 0.440 0.000 0.000 0.088 0.472 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 4 0.3350 0.77008 0.024 0.000 0.012 0.844 0.096 0.024
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 6 0.6595 0.27285 0.012 0.072 0.076 0.360 0.004 0.476
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.0632 0.81227 0.000 0.976 0.000 0.000 0.000 0.024
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 6 0.2988 0.63792 0.000 0.000 0.024 0.152 0.000 0.824
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0146 0.86279 0.996 0.000 0.000 0.000 0.004 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 5 0.0692 0.86297 0.004 0.000 0.000 0.020 0.976 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.3993 0.45843 0.000 0.676 0.024 0.000 0.000 0.300
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.2100 0.75614 0.004 0.000 0.000 0.884 0.000 0.112
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0790 0.81077 0.000 0.968 0.000 0.000 0.000 0.032
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.1714 0.77739 0.000 0.908 0.000 0.000 0.000 0.092
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.3677 0.73851 0.156 0.000 0.008 0.796 0.008 0.032
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.2617 0.75763 0.000 0.000 0.040 0.876 0.004 0.080
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.0405 0.86393 0.004 0.000 0.000 0.008 0.988 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 6 0.4091 0.54370 0.000 0.000 0.224 0.056 0.000 0.720
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.2969 0.70504 0.000 0.000 0.000 0.224 0.776 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.0405 0.86342 0.004 0.000 0.000 0.008 0.988 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 6 0.1858 0.67925 0.000 0.092 0.000 0.004 0.000 0.904
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.2250 0.77348 0.000 0.000 0.000 0.896 0.064 0.040
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.2474 0.76918 0.032 0.000 0.000 0.884 0.004 0.080
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0146 0.86279 0.996 0.000 0.000 0.000 0.004 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 6 0.3756 0.59332 0.000 0.000 0.008 0.052 0.156 0.784
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.1204 0.80487 0.000 0.944 0.000 0.000 0.000 0.056
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.3652 0.48116 0.000 0.000 0.672 0.000 0.324 0.004
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 3 0.4091 0.28659 0.000 0.008 0.520 0.000 0.000 0.472
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.6495 0.42195 0.000 0.492 0.316 0.056 0.004 0.132
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.5883 0.48352 0.556 0.000 0.316 0.076 0.004 0.048
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.3558 0.42979 0.000 0.000 0.736 0.248 0.000 0.016
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 6 0.1890 0.68866 0.000 0.000 0.024 0.060 0.000 0.916
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 3 0.3888 0.46089 0.000 0.312 0.672 0.000 0.000 0.016
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.3607 0.44408 0.000 0.000 0.652 0.000 0.348 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.1843 0.83232 0.004 0.000 0.004 0.080 0.912 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 6 0.5478 -0.01667 0.000 0.000 0.064 0.448 0.024 0.464
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.6486 0.39380 0.484 0.000 0.292 0.048 0.176 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0146 0.81054 0.004 0.996 0.000 0.000 0.000 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.3643 0.71355 0.200 0.000 0.008 0.768 0.000 0.024
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0632 0.81227 0.000 0.976 0.000 0.000 0.000 0.024
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.0436 0.86377 0.004 0.000 0.004 0.004 0.988 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 6 0.4002 0.47706 0.000 0.000 0.036 0.260 0.000 0.704
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0260 0.86120 0.992 0.000 0.000 0.008 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0603 0.86179 0.004 0.000 0.000 0.016 0.980 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.4273 0.26354 0.000 0.596 0.024 0.000 0.000 0.380
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 6 0.2734 0.68182 0.008 0.000 0.024 0.104 0.000 0.864
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.0405 0.86333 0.000 0.000 0.008 0.004 0.988 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.6781 0.35012 0.000 0.448 0.320 0.060 0.004 0.168
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.7035 0.37394 0.476 0.004 0.272 0.076 0.008 0.164
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.0363 0.86232 0.000 0.000 0.000 0.012 0.988 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 6 0.1950 0.68756 0.000 0.000 0.024 0.064 0.000 0.912
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 3 0.4253 0.57862 0.000 0.044 0.672 0.000 0.000 0.284
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.6901 0.26298 0.396 0.000 0.292 0.056 0.256 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 6 0.3887 0.44471 0.000 0.360 0.008 0.000 0.000 0.632
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.5279 0.55508 0.000 0.604 0.312 0.048 0.004 0.032
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.4062 0.72387 0.160 0.000 0.000 0.764 0.064 0.012
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.3982 0.07832 0.000 0.536 0.004 0.000 0.000 0.460
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.1753 0.83088 0.004 0.000 0.000 0.084 0.912 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.4421 0.56725 0.000 0.004 0.684 0.000 0.256 0.056
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0405 0.86032 0.988 0.000 0.000 0.008 0.000 0.004
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.4165 0.59003 0.000 0.004 0.676 0.000 0.028 0.292
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.3516 0.70681 0.000 0.000 0.024 0.792 0.012 0.172
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.4105 0.45685 0.000 0.348 0.020 0.000 0.000 0.632
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.3168 0.65476 0.000 0.172 0.024 0.000 0.000 0.804
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.4131 0.46741 0.000 0.356 0.020 0.000 0.000 0.624
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.4969 0.49790 0.000 0.000 0.104 0.616 0.280 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.86368 1.000 0.000 0.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.0508 0.86327 0.004 0.000 0.000 0.012 0.984 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.8733 0.00894 0.216 0.172 0.308 0.092 0.004 0.208
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 6 0.2001 0.68873 0.008 0.000 0.012 0.068 0.000 0.912
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.2515 0.76413 0.000 0.000 0.040 0.892 0.016 0.052
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 6 0.4156 0.63720 0.000 0.132 0.004 0.088 0.008 0.768
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.2950 0.76192 0.000 0.868 0.032 0.036 0.000 0.064
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.5886 0.16811 0.000 0.200 0.412 0.000 0.000 0.388
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.4253 0.58123 0.000 0.044 0.672 0.000 0.000 0.284
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.4592 0.58012 0.652 0.000 0.292 0.048 0.008 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.1338 0.51256 0.000 0.004 0.952 0.032 0.004 0.008
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.5867 0.54073 0.624 0.000 0.180 0.072 0.000 0.124
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.3490 0.69578 0.000 0.000 0.040 0.784 0.176 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0146 0.86423 0.004 0.000 0.000 0.000 0.996 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.5557 0.41658 0.000 0.000 0.056 0.244 0.624 0.076
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0260 0.86086 0.992 0.000 0.000 0.008 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0291 0.86401 0.004 0.000 0.004 0.000 0.992 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.1701 0.83156 0.008 0.000 0.000 0.072 0.920 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.1588 0.76783 0.000 0.000 0.000 0.924 0.004 0.072
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.5775 0.22447 0.328 0.000 0.000 0.192 0.480 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0632 0.81227 0.000 0.976 0.000 0.000 0.000 0.024
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.5989 0.12987 0.248 0.000 0.000 0.320 0.432 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0713 0.85219 0.972 0.000 0.000 0.028 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.1950 0.68756 0.000 0.000 0.024 0.064 0.000 0.912
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.4882 0.47082 0.000 0.072 0.576 0.000 0.000 0.352
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.2697 0.76112 0.000 0.000 0.000 0.864 0.092 0.044
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3945 0.28749 0.000 0.612 0.008 0.000 0.000 0.380
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2358 0.77751 0.876 0.000 0.000 0.016 0.108 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.6615 0.40897 0.000 0.472 0.320 0.056 0.004 0.148
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.2842 0.76779 0.000 0.000 0.000 0.852 0.104 0.044
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.2112 0.80601 0.896 0.000 0.000 0.088 0.000 0.016
#> F17B682D-A902-4730-A300-5C163209F7CD 6 0.4155 0.45383 0.000 0.364 0.020 0.000 0.000 0.616
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.2872 0.65795 0.000 0.000 0.024 0.140 0.000 0.836
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0603 0.86270 0.004 0.000 0.000 0.016 0.980 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 6 0.3360 0.58985 0.000 0.264 0.004 0.000 0.000 0.732
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1957 0.79776 0.888 0.000 0.000 0.112 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.3619 0.65741 0.000 0.000 0.232 0.024 0.744 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.2003 0.67747 0.000 0.116 0.000 0.000 0.000 0.884
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0260 0.86052 0.992 0.000 0.000 0.000 0.008 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2121 0.75875 0.000 0.000 0.012 0.892 0.000 0.096
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.2597 0.70460 0.000 0.000 0.000 0.824 0.176 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.2454 0.74340 0.000 0.000 0.000 0.840 0.160 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.6924 0.22749 0.000 0.000 0.292 0.248 0.400 0.060
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.4685 0.57621 0.648 0.000 0.292 0.048 0.012 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.81176 0.000 1.000 0.000 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.4368 0.69830 0.000 0.000 0.028 0.092 0.760 0.120
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.5184 0.54431 0.608 0.000 0.292 0.088 0.012 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.407 0.723 0.872 0.4690 0.502 0.502
#> 3 3 0.582 0.832 0.885 0.3193 0.719 0.506
#> 4 4 0.605 0.617 0.814 0.1466 0.883 0.690
#> 5 5 0.669 0.632 0.835 0.0742 0.888 0.643
#> 6 6 0.661 0.542 0.781 0.0160 0.922 0.712
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.8547 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.2236 0.8204 0.964 0.036
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6247 0.8186 0.156 0.844
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.8254 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.7299 0.7958 0.204 0.796
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.8547 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.8254 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.8254 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2043 0.8217 0.968 0.032
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2236 0.8204 0.964 0.036
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.7219 0.7993 0.200 0.800
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7299 0.7958 0.204 0.796
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.9754 0.2239 0.592 0.408
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.8547 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.7299 0.7958 0.204 0.796
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0000 0.8547 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.8547 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0672 0.8547 0.008 0.992
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.8547 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6048 0.7519 0.852 0.148
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.8547 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.6247 0.8192 0.156 0.844
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.9881 0.2132 0.564 0.436
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.2236 0.8204 0.964 0.036
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.9896 0.1998 0.560 0.440
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.7056 0.8052 0.192 0.808
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5629 0.7399 0.868 0.132
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.8254 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.8254 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.1633 0.8537 0.024 0.976
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.8254 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.8547 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.9909 0.1225 0.556 0.444
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.8254 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.8547 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.1414 0.8243 0.980 0.020
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.9881 0.2132 0.564 0.436
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.1414 0.8243 0.980 0.020
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1843 0.8228 0.972 0.028
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0938 0.8252 0.988 0.012
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.1184 0.8516 0.016 0.984
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.9209 0.4346 0.664 0.336
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.8547 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.6438 0.8143 0.164 0.836
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.9754 0.2544 0.592 0.408
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.8547 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.8763 0.5614 0.704 0.296
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.8547 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0376 0.8547 0.004 0.996
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.8547 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.4690 0.8415 0.100 0.900
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2236 0.8204 0.964 0.036
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.2043 0.8217 0.968 0.032
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.8254 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.8254 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2236 0.8204 0.964 0.036
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.7219 0.7995 0.200 0.800
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.7219 0.7535 0.200 0.800
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.3584 0.8472 0.068 0.932
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.7299 0.7958 0.204 0.796
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.8254 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.8547 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.1414 0.8203 0.980 0.020
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4161 0.7817 0.916 0.084
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.2236 0.8204 0.964 0.036
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2778 0.8506 0.048 0.952
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.1633 0.8536 0.024 0.976
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.6438 0.8143 0.164 0.836
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.8254 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.8254 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.7453 0.6532 0.788 0.212
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.2043 0.8217 0.968 0.032
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.4431 0.8421 0.092 0.908
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.9983 0.2399 0.476 0.524
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0000 0.8547 0.000 1.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.8547 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.8547 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.7299 0.7958 0.204 0.796
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.8254 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.8254 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.9866 0.2391 0.568 0.432
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.9993 0.1302 0.516 0.484
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.2236 0.8204 0.964 0.036
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 2 0.9323 0.5529 0.348 0.652
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.8267 0.6199 0.740 0.260
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0672 0.8255 0.992 0.008
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.8547 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.9732 0.4537 0.404 0.596
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.8547 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.5408 0.7665 0.876 0.124
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.7299 0.7958 0.204 0.796
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.4298 0.8429 0.088 0.912
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.8547 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.8661 0.5725 0.712 0.288
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.7139 0.7907 0.196 0.804
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.8254 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.6712 0.6820 0.824 0.176
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.9881 0.2132 0.564 0.436
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.7219 0.7994 0.200 0.800
#> 60A51C36-7423-4C84-8034-325DE57046BE 2 0.7299 0.7958 0.204 0.796
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.9977 0.1569 0.528 0.472
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.2236 0.8204 0.964 0.036
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.2423 0.8453 0.040 0.960
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.8254 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.7139 0.8004 0.196 0.804
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.2236 0.8204 0.964 0.036
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.7219 0.7993 0.200 0.800
#> 5D663B98-8416-4305-A891-111B7A4DC40B 1 0.9977 0.1569 0.528 0.472
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 2 0.9983 0.2399 0.476 0.524
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.2778 0.8136 0.952 0.048
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.7299 0.7958 0.204 0.796
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.8547 0.000 1.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.8254 1.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.8547 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 2 0.9815 0.3514 0.420 0.580
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.8254 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.8547 0.000 1.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.8254 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.8547 0.000 1.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.8547 0.000 1.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0672 0.8255 0.992 0.008
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.8254 1.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.6438 0.8143 0.164 0.836
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 2 0.9661 0.3768 0.392 0.608
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.8254 1.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.8547 0.000 1.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.2236 0.8204 0.964 0.036
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.9881 0.2132 0.564 0.436
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0000 0.8547 0.000 1.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.6048 0.8229 0.148 0.852
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.2043 0.8217 0.968 0.032
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.2236 0.8204 0.964 0.036
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0000 0.8547 0.000 1.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.7219 0.7993 0.200 0.800
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0000 0.8547 0.000 1.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0000 0.8547 0.000 1.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.5946 0.8293 0.144 0.856
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.8254 1.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.6343 0.8168 0.160 0.840
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.7299 0.7958 0.204 0.796
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0000 0.8547 0.000 1.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.5178 0.7576 0.884 0.116
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0000 0.8254 1.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.3879 0.7877 0.924 0.076
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 2 0.7299 0.7958 0.204 0.796
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0376 0.8255 0.996 0.004
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 2 0.9775 0.4330 0.412 0.588
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.0376 0.8255 0.996 0.004
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 2 0.9248 0.5537 0.340 0.660
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.2236 0.8204 0.964 0.036
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.0000 0.8547 0.000 1.000
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0000 0.8547 0.000 1.000
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 1 0.8813 0.5171 0.700 0.300
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.5059 0.8375 0.112 0.888
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 1 0.9977 0.1569 0.528 0.472
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#> EA5B09C5-A45D-44BC-8477-DAF6B0DD79C7 2 0.5178 0.8362 0.116 0.884
#> 8026EF80-8CFB-4A62-9C72-BB5B50BDECFE 1 0.0000 0.8254 1.000 0.000
#> C1D05156-9AA7-48FD-9C3C-8894F9025D29 2 0.8661 0.6636 0.288 0.712
#> D3AEFD54-52E3-4761-898B-F05A5B6BA198 1 0.9795 0.2278 0.584 0.416
#> 33FAC29F-D146-454C-AE5D-07DF7C191DFC 2 0.6623 0.8124 0.172 0.828
#> E3E13B94-9335-4B34-9975-ECA99EB1BCBE 1 0.1414 0.8242 0.980 0.020
#> 2E1AC099-CE43-4605-BDFD-FA71DE8EAE44 2 0.0000 0.8547 0.000 1.000
#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.0000 0.8547 0.000 1.000
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.0000 0.8547 0.000 1.000
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.0000 0.8547 0.000 1.000
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.0000 0.8547 0.000 1.000
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.2236 0.8204 0.964 0.036
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.6247 0.8185 0.156 0.844
#> 4C838D35-B667-46DA-836F-068453D254DA 2 0.7299 0.7958 0.204 0.796
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0000 0.8547 0.000 1.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0938 0.8545 0.012 0.988
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.7219 0.7993 0.200 0.800
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.2236 0.8204 0.964 0.036
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 1 0.8207 0.6206 0.744 0.256
#> 976924B0-5799-4AC9-804F-78C8568037CA 1 0.9970 0.1641 0.532 0.468
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.0000 0.8254 1.000 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.1633 0.8236 0.976 0.024
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.0000 0.8254 1.000 0.000
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0000 0.8254 1.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0000 0.8254 1.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.9044 0.5735 0.320 0.680
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0000 0.8547 0.000 1.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.5059 0.8394 0.112 0.888
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.2778 0.8136 0.952 0.048
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0000 0.8254 1.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 2 0.9993 0.1414 0.484 0.516
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.9988 -0.0749 0.520 0.480
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.0000 0.8547 0.000 1.000
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.7299 0.7958 0.204 0.796
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.8254 1.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.8254 1.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.8254 1.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.9993 0.1994 0.484 0.516
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.7139 0.8024 0.196 0.804
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 1 0.9881 0.2888 0.564 0.436
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.8547 0.000 1.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.2236 0.8204 0.964 0.036
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.8254 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.8254 1.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.6247 0.8186 0.156 0.844
#> 4BF521F6-7804-49BA-8C56-28E253531628 2 0.6438 0.8141 0.164 0.836
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.8547 0.000 1.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.8547 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.8547 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.9209 0.6066 0.336 0.664
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.7219 0.7993 0.200 0.800
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.8254 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.8547 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.2236 0.8204 0.964 0.036
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.9944 0.1834 0.544 0.456
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.8254 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.8547 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 2 0.8909 0.6474 0.308 0.692
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.8254 1.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.7299 0.7958 0.204 0.796
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.1843 0.8228 0.972 0.028
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.7299 0.7958 0.204 0.796
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0000 0.8547 0.000 1.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.8254 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.2236 0.8204 0.964 0.036
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.9954 0.1771 0.540 0.460
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.1414 0.8540 0.020 0.980
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.0000 0.8547 0.000 1.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.9833 0.1916 0.576 0.424
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.8267 0.7249 0.260 0.740
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.8547 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.6343 0.8168 0.160 0.840
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.8547 0.000 1.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9909 0.1860 0.556 0.444
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.9881 0.2132 0.564 0.436
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.6887 0.8060 0.184 0.816
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.2236 0.8204 0.964 0.036
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.5059 0.8365 0.112 0.888
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.9993 -0.0898 0.516 0.484
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.6343 0.8062 0.160 0.840
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.8254 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.5294 0.8342 0.120 0.880
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.8254 1.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.9209 0.5805 0.336 0.664
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.8547 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.6438 0.8143 0.164 0.836
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.9896 0.2840 0.440 0.560
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.6247 0.8185 0.156 0.844
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.2603 0.8184 0.956 0.044
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.9954 0.1959 0.540 0.460
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.8547 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.8547 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.2043 0.8217 0.968 0.032
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.8547 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.7219 0.7477 0.200 0.800
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1414 0.8193 0.980 0.020
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.8547 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.9881 0.2132 0.564 0.436
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.8547 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.9983 0.0894 0.476 0.524
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.8254 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.2236 0.8204 0.964 0.036
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.7299 0.7958 0.204 0.796
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.7299 0.7958 0.204 0.796
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.8547 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.8254 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.8547 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.8547 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.9833 0.2471 0.576 0.424
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1843 0.8228 0.972 0.028
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.8254 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.9460 0.4979 0.364 0.636
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.7219 0.7993 0.200 0.800
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.7299 0.7958 0.204 0.796
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.6247 0.8185 0.156 0.844
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.8547 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4690 0.8408 0.100 0.900
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.8547 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.2236 0.8204 0.964 0.036
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.6438 0.8143 0.164 0.836
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.6531 0.8114 0.168 0.832
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.7299 0.7958 0.204 0.796
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.8254 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7745 0.7696 0.228 0.772
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.8547 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.8254 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.9933 0.1897 0.548 0.452
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0376 0.8250 0.996 0.004
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.9686 0.3358 0.604 0.396
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.8254 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.8547 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.8254 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.6048 0.7340 0.852 0.148
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.8547 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.8547 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.8763 0.6306 0.296 0.704
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.8547 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8254 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0000 0.8547 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.8763 0.6795 0.296 0.704
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5519 0.7621 0.872 0.128
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.8547 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6531 0.8133 0.168 0.832
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.9881 0.2132 0.564 0.436
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.8547 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8254 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.2236 0.8204 0.964 0.036
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.8547 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8254 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.7219 0.7993 0.200 0.800
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.7745 0.6316 0.772 0.228
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.9209 0.4545 0.664 0.336
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9977 0.1569 0.528 0.472
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.2236 0.8204 0.964 0.036
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.8547 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9993 0.1302 0.516 0.484
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.2236 0.8204 0.964 0.036
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9431 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0892 0.9221 0.980 0.020 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 3 0.5292 0.8665 0.172 0.028 0.800
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9263 1.000 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.3038 0.8424 0.104 0.000 0.896
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9431 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9263 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9263 1.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0747 0.9237 0.984 0.016 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0892 0.9221 0.980 0.020 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.3941 0.8786 0.156 0.000 0.844
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.4555 0.8603 0.200 0.000 0.800
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6252 -0.1167 0.556 0.000 0.444
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9431 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.3941 0.8786 0.156 0.000 0.844
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4750 0.7324 0.000 0.216 0.784
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9431 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4861 0.7725 0.012 0.180 0.808
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9431 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.5939 0.6106 0.748 0.028 0.224
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1031 0.9280 0.000 0.976 0.024
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.4609 0.8776 0.128 0.028 0.844
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3941 0.8786 0.156 0.000 0.844
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0892 0.9221 0.980 0.020 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.4555 0.8603 0.200 0.000 0.800
#> C6AD4922-9981-4493-9F33-87A449B6EE55 3 0.4228 0.8792 0.148 0.008 0.844
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#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 3 0.4121 0.7717 0.000 0.168 0.832
#> 93429F04-8404-4E8C-B654-9D2216BA432C 3 0.0000 0.7890 0.000 0.000 1.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.9263 1.000 0.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.9263 1.000 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.9263 1.000 0.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.5948 0.6662 0.360 0.000 0.640
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 3 0.3941 0.8786 0.156 0.000 0.844
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.6772 0.6826 0.304 0.032 0.664
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.5905 0.4529 0.000 0.648 0.352
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0892 0.9221 0.980 0.020 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.9263 1.000 0.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.9263 1.000 0.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 3 0.8703 0.6747 0.168 0.244 0.588
#> 4BF521F6-7804-49BA-8C56-28E253531628 3 0.4551 0.8780 0.132 0.024 0.844
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.9431 0.000 1.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.9431 0.000 1.000 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.9431 0.000 1.000 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 3 0.5810 0.7065 0.336 0.000 0.664
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 3 0.3941 0.8786 0.156 0.000 0.844
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.9263 1.000 0.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.4842 0.8195 0.000 0.776 0.224
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0892 0.9221 0.980 0.020 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.4411 0.8789 0.140 0.016 0.844
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0237 0.9249 0.996 0.000 0.004
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 3 0.4002 0.7763 0.000 0.160 0.840
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 3 0.4750 0.8493 0.216 0.000 0.784
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.9263 1.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 3 0.3941 0.8786 0.156 0.000 0.844
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0424 0.9258 0.992 0.008 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 3 0.3941 0.8786 0.156 0.000 0.844
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.6140 0.2192 0.000 0.596 0.404
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.9263 1.000 0.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0892 0.9221 0.980 0.020 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.1643 0.7983 0.044 0.000 0.956
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 3 0.4411 0.7967 0.016 0.140 0.844
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.3941 0.7786 0.000 0.156 0.844
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.2743 0.8808 0.928 0.020 0.052
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.4062 0.8770 0.164 0.000 0.836
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.9431 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 3 0.4485 0.8783 0.136 0.020 0.844
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 3 0.0747 0.7837 0.000 0.016 0.984
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.7890 0.000 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 3 0.3941 0.8786 0.156 0.000 0.844
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.4228 0.8793 0.148 0.008 0.844
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0892 0.9221 0.980 0.020 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 3 0.7651 0.7525 0.124 0.196 0.680
#> E9061D61-4774-464E-ABE4-EB15CD889141 3 0.6180 0.5559 0.416 0.000 0.584
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.4902 0.8645 0.092 0.064 0.844
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.9263 1.000 0.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.4887 0.8668 0.096 0.060 0.844
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.9263 1.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.3941 0.8786 0.156 0.000 0.844
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1643 0.9177 0.000 0.956 0.044
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 3 0.4921 0.8726 0.164 0.020 0.816
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.4346 0.8693 0.184 0.000 0.816
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4609 0.8773 0.128 0.028 0.844
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.2636 0.8879 0.932 0.020 0.048
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.4802 0.8759 0.156 0.020 0.824
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0237 0.9413 0.000 0.996 0.004
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.3941 0.8564 0.000 0.844 0.156
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0747 0.9236 0.984 0.016 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 3 0.5882 0.4906 0.000 0.348 0.652
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4925 0.8538 0.076 0.080 0.844
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.9263 1.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9431 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.3941 0.8786 0.156 0.000 0.844
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9431 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.4915 0.8663 0.184 0.012 0.804
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.9263 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0892 0.9221 0.980 0.020 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.0000 0.7890 0.000 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 3 0.3941 0.8786 0.156 0.000 0.844
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0237 0.9408 0.000 0.996 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.9263 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1163 0.9284 0.000 0.972 0.028
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9431 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.4702 0.8525 0.212 0.000 0.788
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0747 0.9236 0.984 0.016 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.9263 1.000 0.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.7203 0.5060 0.416 0.028 0.556
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.6107 0.6863 0.184 0.764 0.052
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 3 0.3941 0.8786 0.156 0.000 0.844
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.4609 0.8773 0.128 0.028 0.844
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.4555 0.7496 0.000 0.200 0.800
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.4925 0.8561 0.080 0.076 0.844
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4002 0.8553 0.000 0.840 0.160
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0892 0.9221 0.980 0.020 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4280 0.8780 0.124 0.020 0.856
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.5147 0.8643 0.180 0.020 0.800
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.3941 0.8786 0.156 0.000 0.844
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0424 0.9231 0.992 0.000 0.008
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 3 0.4291 0.8712 0.180 0.000 0.820
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9431 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9263 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.3941 0.8786 0.156 0.000 0.844
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0592 0.9214 0.988 0.000 0.012
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.5815 0.7272 0.304 0.004 0.692
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9263 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.4887 0.6993 0.000 0.772 0.228
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9263 1.000 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0892 0.9221 0.980 0.020 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9431 0.000 1.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.3941 0.8564 0.000 0.844 0.156
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.4411 0.8790 0.140 0.016 0.844
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9431 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9263 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4504 0.7526 0.000 0.196 0.804
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.5465 0.7740 0.288 0.000 0.712
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5938 0.5583 0.732 0.020 0.248
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9431 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 3 0.4744 0.8784 0.136 0.028 0.836
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.3941 0.8786 0.156 0.000 0.844
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9431 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9263 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1315 0.9191 0.972 0.020 0.008
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9431 0.000 1.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9263 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 3 0.4121 0.8758 0.168 0.000 0.832
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5650 0.4586 0.688 0.000 0.312
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.6008 0.6484 0.372 0.000 0.628
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4485 0.8783 0.136 0.020 0.844
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0892 0.9221 0.980 0.020 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9431 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.4609 0.8773 0.128 0.028 0.844
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0892 0.9221 0.980 0.020 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 3 0.5035 0.52721 0.196 0.000 0.748 0.056
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0469 0.86775 0.988 0.000 0.012 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.7939 0.44744 0.052 0.264 0.132 0.552
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4989 0.89911 0.000 0.528 0.000 0.472
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0469 0.86775 0.988 0.000 0.012 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.5388 -0.07450 0.012 0.000 0.532 0.456
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.7295 0.48565 0.188 0.000 0.288 0.524
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.6546 0.41220 0.396 0.000 0.080 0.524
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.4761 0.15284 0.000 0.000 0.628 0.372
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.3257 0.64676 0.000 0.004 0.844 0.152
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4916 0.89284 0.000 0.576 0.000 0.424
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3024 0.65273 0.000 0.000 0.852 0.148
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4916 0.89284 0.000 0.576 0.000 0.424
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.3837 0.57734 0.776 0.000 0.224 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.5696 0.88499 0.000 0.496 0.024 0.480
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.0469 0.72254 0.012 0.000 0.988 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3172 0.61103 0.000 0.000 0.840 0.160
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.6393 0.38209 0.188 0.000 0.652 0.160
#> C6AD4922-9981-4493-9F33-87A449B6EE55 3 0.1302 0.71083 0.000 0.044 0.956 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.3569 0.63915 0.804 0.000 0.196 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.3610 0.63100 0.800 0.000 0.200 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4057 -0.23119 0.028 0.160 0.000 0.812
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.4925 0.89398 0.000 0.572 0.000 0.428
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6663 0.41605 0.100 0.000 0.344 0.556
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0804 0.86384 0.980 0.000 0.012 0.008
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4916 0.44299 0.000 0.424 0.576 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.6067 0.86704 0.000 0.572 0.052 0.376
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 3 0.7362 0.03123 0.372 0.000 0.464 0.164
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.4916 0.89284 0.000 0.576 0.000 0.424
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#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0336 0.86971 0.992 0.000 0.008 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.5427 -0.03561 0.568 0.000 0.016 0.416
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 3 0.7644 -0.06726 0.380 0.000 0.412 0.208
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 3 0.1940 0.69953 0.000 0.000 0.924 0.076
#> 93429F04-8404-4E8C-B654-9D2216BA432C 3 0.5636 0.42410 0.000 0.424 0.552 0.024
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 4 0.5399 0.24791 0.468 0.000 0.012 0.520
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.3625 0.70958 0.828 0.000 0.012 0.160
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0469 0.86775 0.988 0.000 0.012 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.7198 0.13551 0.320 0.000 0.520 0.160
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.4916 0.27914 0.000 0.000 0.424 0.576
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.3528 0.54883 0.192 0.000 0.808 0.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 3 0.6957 -0.11346 0.000 0.112 0.472 0.416
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0469 0.86775 0.988 0.000 0.012 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.3577 0.71490 0.832 0.000 0.012 0.156
#> 6D711561-D549-44C7-885F-F3B846DB130C 3 0.8382 0.26768 0.192 0.068 0.532 0.208
#> 4BF521F6-7804-49BA-8C56-28E253531628 3 0.5320 0.05379 0.012 0.000 0.572 0.416
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.6120 0.87741 0.000 0.520 0.048 0.432
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.4925 0.89398 0.000 0.572 0.000 0.428
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.6765 0.55226 0.300 0.000 0.124 0.576
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.4916 0.27914 0.000 0.000 0.424 0.576
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0469 0.86775 0.988 0.000 0.012 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.5543 0.01075 0.000 0.360 0.028 0.612
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0336 0.72284 0.008 0.000 0.992 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.1042 0.86113 0.972 0.000 0.020 0.008
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 3 0.0592 0.72098 0.000 0.000 0.984 0.016
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.7336 0.48925 0.196 0.000 0.284 0.520
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0188 0.87115 0.996 0.000 0.004 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.5158 0.19674 0.004 0.000 0.472 0.524
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 3 0.0336 0.72286 0.008 0.000 0.992 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 4 0.7368 -0.34739 0.000 0.164 0.376 0.460
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0336 0.86971 0.992 0.000 0.008 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.5220 0.43741 0.000 0.424 0.568 0.008
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 3 0.0000 0.72183 0.000 0.000 1.000 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.0469 0.72144 0.000 0.000 0.988 0.012
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.4804 0.13696 0.616 0.000 0.000 0.384
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.5853 0.56812 0.052 0.056 0.748 0.144
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.4992 0.89906 0.000 0.524 0.000 0.476
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 3 0.5125 0.12118 0.008 0.000 0.604 0.388
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 3 0.4916 0.44299 0.000 0.424 0.576 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.6600 0.39262 0.000 0.396 0.520 0.084
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 3 0.0000 0.72183 0.000 0.000 1.000 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.0336 0.72284 0.008 0.000 0.992 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 3 0.7538 0.43326 0.148 0.072 0.632 0.148
#> E9061D61-4774-464E-ABE4-EB15CD889141 3 0.7310 0.06043 0.360 0.000 0.480 0.160
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.0524 0.72231 0.004 0.000 0.988 0.008
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0657 0.86613 0.984 0.000 0.012 0.004
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.0895 0.72031 0.004 0.000 0.976 0.020
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.0000 0.72183 0.000 0.000 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.6773 0.76876 0.000 0.588 0.136 0.276
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 3 0.6792 0.20258 0.140 0.000 0.588 0.272
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.3311 0.59310 0.172 0.000 0.828 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0921 0.72005 0.028 0.000 0.972 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.3311 0.67742 0.828 0.000 0.172 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.1867 0.70139 0.072 0.000 0.928 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.5764 0.88420 0.000 0.520 0.028 0.452
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.53591 0.000 1.000 0.000 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 3 0.4832 0.52814 0.000 0.176 0.768 0.056
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0469 0.72144 0.000 0.000 0.988 0.012
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.5396 0.25832 0.464 0.000 0.012 0.524
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.4992 0.89906 0.000 0.524 0.000 0.476
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0188 0.72246 0.004 0.000 0.996 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.3444 0.57781 0.184 0.000 0.816 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0188 0.87115 0.996 0.000 0.004 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.4916 0.44299 0.000 0.424 0.576 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 3 0.0000 0.72183 0.000 0.000 1.000 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4916 0.89284 0.000 0.576 0.000 0.424
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6727 0.81892 0.000 0.520 0.096 0.384
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4916 0.89284 0.000 0.576 0.000 0.424
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6457 0.36864 0.200 0.000 0.644 0.156
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0336 0.86971 0.992 0.000 0.008 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.7251 -0.36830 0.440 0.000 0.144 0.416
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.6986 0.40366 0.120 0.088 0.108 0.684
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4994 0.17938 0.000 0.000 0.480 0.520
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.0524 0.72273 0.008 0.000 0.988 0.004
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.3688 0.60167 0.000 0.000 0.792 0.208
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.0592 0.71818 0.000 0.000 0.984 0.016
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.53591 0.000 1.000 0.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.2944 0.66808 0.004 0.128 0.868 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.4669 0.54045 0.200 0.000 0.764 0.036
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0921 0.71337 0.000 0.000 0.972 0.028
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0469 0.86755 0.988 0.000 0.012 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 3 0.6080 0.43734 0.156 0.000 0.684 0.160
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.6242 0.87058 0.000 0.520 0.056 0.424
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0707 0.86234 0.980 0.000 0.000 0.020
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0592 0.72260 0.016 0.000 0.984 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0469 0.86523 0.988 0.000 0.012 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.6602 0.25876 0.080 0.000 0.436 0.484
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3479 0.72516 0.840 0.000 0.012 0.148
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.6871 0.31011 0.000 0.480 0.416 0.104
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.3625 0.70958 0.828 0.000 0.012 0.160
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0707 0.85794 0.980 0.000 0.000 0.020
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2408 0.64752 0.000 0.896 0.000 0.104
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.0469 0.72309 0.012 0.000 0.988 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0524 0.86864 0.988 0.000 0.004 0.008
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3219 0.64083 0.000 0.000 0.836 0.164
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.7082 0.56085 0.252 0.000 0.184 0.564
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4675 0.50102 0.736 0.000 0.244 0.020
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4916 0.89284 0.000 0.576 0.000 0.424
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 3 0.5492 0.04558 0.012 0.004 0.568 0.416
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.3074 0.61957 0.000 0.000 0.848 0.152
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4925 0.89398 0.000 0.572 0.000 0.428
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1584 0.84334 0.952 0.000 0.012 0.036
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0336 0.86761 0.992 0.000 0.008 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.6110 0.37972 0.056 0.000 0.368 0.576
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.7475 -0.10133 0.420 0.000 0.404 0.176
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.7346 0.54116 0.280 0.000 0.200 0.520
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0469 0.72254 0.012 0.000 0.988 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.87234 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4994 0.89875 0.000 0.520 0.000 0.480
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0469 0.72254 0.012 0.000 0.988 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.87234 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0162 0.84648 0.000 0.996 0.000 0.004 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 5 0.4221 0.61315 0.188 0.004 0.000 0.044 0.764
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3074 0.72735 0.804 0.000 0.000 0.196 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.1404 0.61360 0.004 0.004 0.008 0.956 0.028
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0162 0.84648 0.000 0.996 0.000 0.004 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0794 0.86397 0.972 0.000 0.000 0.028 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3123 0.73865 0.812 0.000 0.004 0.184 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.86916 1.000 0.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.3123 0.51159 0.000 0.004 0.000 0.812 0.184
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.1357 0.61597 0.004 0.000 0.000 0.948 0.048
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.2871 0.59916 0.088 0.000 0.004 0.876 0.032
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0404 0.84652 0.000 0.988 0.000 0.012 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.4307 0.06554 0.000 0.000 0.000 0.500 0.500
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 5 0.3039 0.66498 0.000 0.152 0.000 0.012 0.836
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0404 0.84326 0.000 0.988 0.012 0.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 5 0.3055 0.67065 0.000 0.144 0.000 0.016 0.840
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.3143 0.73132 0.000 0.796 0.204 0.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.3612 0.60462 0.764 0.008 0.000 0.000 0.228
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1739 0.82735 0.000 0.940 0.004 0.032 0.024
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.0290 0.76625 0.000 0.000 0.000 0.008 0.992
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4278 0.00122 0.000 0.000 0.000 0.452 0.548
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.4390 0.27509 0.004 0.000 0.000 0.568 0.428
#> C6AD4922-9981-4493-9F33-87A449B6EE55 5 0.4068 0.63516 0.000 0.004 0.144 0.060 0.792
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4926 0.65085 0.724 0.000 0.004 0.108 0.164
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4088 0.72797 0.792 0.000 0.004 0.064 0.140
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.4855 0.39724 0.024 0.552 0.000 0.424 0.000
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#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0290 0.86956 0.992 0.000 0.000 0.008 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0451 0.61319 0.000 0.004 0.000 0.988 0.008
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.6432 0.22786 0.372 0.000 0.004 0.468 0.156
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.1549 0.61808 0.016 0.000 0.000 0.944 0.040
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.0510 0.76334 0.016 0.000 0.000 0.000 0.984
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0794 0.84070 0.000 0.972 0.000 0.028 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0000 0.76697 0.000 0.000 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0162 0.87042 0.996 0.000 0.000 0.004 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.6572 0.51123 0.152 0.004 0.044 0.424 0.376 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2964 0.74152 0.792 0.000 0.004 0.000 0.204 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 5 0.4562 0.47193 0.004 0.004 0.008 0.388 0.584 0.012
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1168 0.84633 0.956 0.000 0.016 0.000 0.028 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3253 0.74614 0.788 0.000 0.020 0.000 0.192 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0909 0.84487 0.968 0.000 0.020 0.000 0.012 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.4418 -0.37937 0.008 0.004 0.012 0.592 0.384 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 5 0.4543 0.47484 0.032 0.000 0.004 0.380 0.584 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 5 0.6014 0.45114 0.100 0.000 0.044 0.344 0.512 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0363 0.84158 0.000 0.988 0.000 0.012 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2454 0.17305 0.000 0.000 0.000 0.840 0.160 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 4 0.5651 0.55933 0.000 0.152 0.000 0.448 0.400 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0458 0.83921 0.000 0.984 0.000 0.000 0.000 0.016
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 4 0.6085 0.57685 0.000 0.112 0.036 0.452 0.400 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2883 0.72227 0.000 0.788 0.000 0.000 0.000 0.212
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4860 0.59021 0.724 0.012 0.036 0.056 0.172 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3124 0.74268 0.000 0.844 0.108 0.016 0.032 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3774 0.65649 0.000 0.000 0.000 0.592 0.408 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.2135 0.16633 0.000 0.000 0.000 0.128 0.872 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.0622 0.35072 0.012 0.000 0.000 0.008 0.980 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.5491 0.53544 0.000 0.000 0.000 0.524 0.332 0.144
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5838 0.59518 0.636 0.000 0.084 0.148 0.132 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.5111 0.68485 0.708 0.000 0.084 0.132 0.076 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.5392 0.28704 0.032 0.504 0.048 0.416 0.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.2786 0.80599 0.860 0.000 0.084 0.000 0.056 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0653 0.84125 0.000 0.980 0.004 0.004 0.000 0.012
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 5 0.4778 0.47093 0.032 0.000 0.012 0.400 0.556 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2378 0.77910 0.848 0.000 0.000 0.000 0.152 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0363 0.84158 0.000 0.988 0.000 0.012 0.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0260 0.84846 0.992 0.000 0.000 0.000 0.008 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 6 0.3489 0.59748 0.000 0.000 0.000 0.004 0.288 0.708
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.1225 0.84090 0.952 0.000 0.000 0.036 0.012 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0363 0.84806 0.988 0.000 0.012 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.2036 0.79655 0.000 0.912 0.008 0.064 0.000 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 5 0.1897 0.40761 0.004 0.000 0.084 0.004 0.908 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0458 0.83921 0.000 0.984 0.000 0.000 0.000 0.016
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.0405 0.52941 0.000 0.004 0.000 0.008 0.000 0.988
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2190 0.81790 0.908 0.008 0.044 0.040 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1528 0.80003 0.000 0.936 0.000 0.048 0.016 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 4 0.4175 -0.02049 0.464 0.000 0.000 0.524 0.012 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.5912 0.60822 0.000 0.092 0.036 0.476 0.396 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 6 0.3656 0.61601 0.000 0.012 0.000 0.004 0.256 0.728
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0632 0.84500 0.976 0.000 0.024 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4147 0.68320 0.716 0.000 0.060 0.000 0.224 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5132 0.28189 0.500 0.000 0.084 0.000 0.416 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.4029 0.11370 0.004 0.204 0.036 0.748 0.008 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0146 0.83972 0.000 0.996 0.000 0.000 0.000 0.004
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 5 0.5225 0.46964 0.024 0.000 0.060 0.328 0.588 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.5217 0.52787 0.624 0.000 0.084 0.272 0.020 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0547 0.84586 0.980 0.000 0.020 0.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 3 0.2230 0.83770 0.000 0.000 0.892 0.024 0.084 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4699 0.64042 0.000 0.036 0.008 0.580 0.376 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.3585 0.16611 0.156 0.004 0.048 0.792 0.000 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3637 0.75465 0.792 0.000 0.084 0.000 0.124 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.4904 0.24945 0.316 0.000 0.084 0.000 0.600 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.1313 0.83530 0.952 0.004 0.016 0.028 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 4 0.5071 0.62757 0.000 0.080 0.000 0.520 0.400 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 5 0.5891 0.44099 0.000 0.000 0.084 0.316 0.548 0.052
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 4 0.1901 0.29137 0.000 0.076 0.008 0.912 0.004 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.1863 0.81129 0.000 0.920 0.036 0.044 0.000 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 6 0.3608 0.32577 0.000 0.272 0.000 0.012 0.000 0.716
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0146 0.84850 0.996 0.000 0.000 0.000 0.004 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 4 0.5354 0.60624 0.016 0.000 0.084 0.572 0.328 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 4 0.6753 0.50704 0.172 0.012 0.036 0.392 0.388 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0865 0.84262 0.964 0.000 0.036 0.000 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.6576 0.21549 0.000 0.000 0.024 0.340 0.364 0.272
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.3930 0.34953 0.576 0.000 0.000 0.420 0.004 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.1152 0.84468 0.952 0.000 0.004 0.000 0.044 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 3 0.2686 0.88094 0.000 0.100 0.868 0.024 0.008 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 5 0.6067 0.39578 0.148 0.004 0.012 0.416 0.420 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0146 0.83938 0.000 0.996 0.000 0.004 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.5118 0.56033 0.644 0.000 0.084 0.252 0.020 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 5 0.4889 0.46068 0.000 0.000 0.084 0.312 0.604 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.4274 0.19131 0.068 0.108 0.048 0.776 0.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0363 0.84158 0.000 0.988 0.000 0.012 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.6299 -0.18745 0.432 0.000 0.036 0.144 0.388 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 6 0.3652 0.55645 0.000 0.000 0.000 0.004 0.324 0.672
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.2838 0.74775 0.808 0.000 0.004 0.000 0.188 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.3872 0.31205 0.604 0.000 0.004 0.392 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 4 0.5015 0.60817 0.000 0.000 0.084 0.564 0.352 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.1007 0.34979 0.000 0.000 0.000 0.956 0.044 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 5 0.4549 0.46622 0.028 0.004 0.000 0.416 0.552 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0146 0.84801 0.996 0.000 0.004 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 4 0.5963 -0.29517 0.000 0.372 0.016 0.468 0.144 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.2178 0.79957 0.868 0.000 0.000 0.000 0.132 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.3765 0.65619 0.000 0.000 0.000 0.596 0.404 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.1546 0.84333 0.944 0.000 0.020 0.016 0.020 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 5 0.4573 0.46472 0.012 0.004 0.012 0.416 0.556 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 5 0.4746 0.46366 0.032 0.004 0.004 0.416 0.544 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.1483 0.83805 0.944 0.012 0.036 0.008 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 5 0.4100 0.47563 0.004 0.000 0.008 0.388 0.600 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0790 0.83614 0.000 0.968 0.000 0.000 0.000 0.032
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.1753 0.39976 0.000 0.000 0.084 0.004 0.912 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.1152 0.84442 0.952 0.000 0.004 0.000 0.044 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 6 0.5219 0.53638 0.000 0.120 0.000 0.004 0.272 0.604
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.3266 0.66986 0.000 0.728 0.000 0.000 0.000 0.272
#> DFADB933-D083-4175-88A6-72086FD5115E 4 0.5154 0.62207 0.000 0.076 0.004 0.524 0.396 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.2877 0.77740 0.820 0.000 0.012 0.000 0.168 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.0436 0.32751 0.000 0.004 0.004 0.988 0.004 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.2454 0.76217 0.840 0.000 0.000 0.000 0.160 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 6 0.3812 0.26073 0.000 0.264 0.024 0.000 0.000 0.712
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.1483 0.83914 0.944 0.012 0.036 0.000 0.008 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 5 0.5554 -0.53658 0.136 0.000 0.000 0.408 0.456 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.6025 0.38079 0.000 0.576 0.048 0.140 0.236 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 6 0.3383 0.61496 0.000 0.000 0.000 0.004 0.268 0.728
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.1003 0.84518 0.964 0.000 0.000 0.020 0.016 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0260 0.84775 0.992 0.000 0.008 0.000 0.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.1265 0.82569 0.000 0.948 0.008 0.044 0.000 0.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 5 0.0937 0.32958 0.000 0.000 0.000 0.040 0.960 0.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.3151 0.68786 0.000 0.748 0.000 0.000 0.000 0.252
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#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0146 0.84819 0.996 0.000 0.004 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.3817 0.65180 0.000 0.000 0.000 0.568 0.432 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.6007 0.16959 0.000 0.436 0.028 0.116 0.000 0.420
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.4593 0.39781 0.108 0.004 0.012 0.732 0.144 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.5295 -0.52492 0.104 0.000 0.000 0.396 0.500 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 4 0.4922 0.64118 0.016 0.000 0.036 0.548 0.400 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.3893 0.76820 0.796 0.000 0.036 0.044 0.124 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.6065 0.59253 0.052 0.000 0.088 0.484 0.376 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.1265 0.82593 0.000 0.948 0.008 0.044 0.000 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.0000 0.53203 0.000 0.000 0.000 0.000 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0858 0.84545 0.968 0.000 0.028 0.000 0.004 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.5413 0.49686 0.000 0.196 0.004 0.600 0.200 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 5 0.4744 0.47519 0.028 0.000 0.016 0.376 0.580 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0363 0.84158 0.000 0.988 0.000 0.012 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 4 0.4917 0.61941 0.000 0.000 0.076 0.576 0.348 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.6859 -0.47185 0.124 0.000 0.104 0.380 0.392 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0146 0.84839 0.996 0.000 0.000 0.000 0.004 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0865 0.84262 0.964 0.000 0.036 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.3383 0.61496 0.000 0.000 0.000 0.004 0.268 0.728
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.3782 0.65655 0.000 0.000 0.000 0.588 0.412 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.3266 0.66986 0.000 0.728 0.000 0.000 0.000 0.272
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0260 0.84852 0.992 0.000 0.000 0.000 0.008 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.2553 0.73324 0.000 0.848 0.008 0.144 0.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.3309 0.66390 0.000 0.720 0.000 0.000 0.000 0.280
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.2145 0.28926 0.072 0.000 0.000 0.028 0.900 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.84808 1.000 0.000 0.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1686 0.83904 0.924 0.000 0.012 0.000 0.064 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.4822 -0.12354 0.400 0.004 0.048 0.548 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.6447 -0.45661 0.028 0.136 0.012 0.416 0.408 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3995 -0.45036 0.000 0.000 0.004 0.516 0.480 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.6516 0.51800 0.000 0.164 0.044 0.396 0.396 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 5 0.4420 -0.44362 0.000 0.000 0.036 0.360 0.604 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.0000 0.53203 0.000 0.000 0.000 0.000 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0865 0.84262 0.964 0.000 0.036 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 6 0.6791 0.26068 0.004 0.004 0.036 0.240 0.264 0.452
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.6515 0.50991 0.160 0.004 0.036 0.416 0.384 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.3620 -0.37612 0.000 0.000 0.000 0.352 0.648 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.1498 0.84053 0.940 0.000 0.000 0.032 0.028 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.1610 0.40263 0.000 0.000 0.084 0.000 0.916 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1010 0.82529 0.000 0.960 0.036 0.004 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1418 0.83689 0.944 0.000 0.032 0.000 0.024 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.4246 0.65230 0.020 0.000 0.000 0.580 0.400 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3351 0.79379 0.840 0.000 0.084 0.028 0.048 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4962 -0.38112 0.068 0.000 0.000 0.516 0.416 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.4993 0.18975 0.344 0.000 0.084 0.000 0.572 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 3 0.2629 0.89385 0.000 0.092 0.868 0.040 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.3828 0.08074 0.440 0.000 0.000 0.000 0.560 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0458 0.84448 0.984 0.000 0.000 0.016 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0806 0.83729 0.000 0.972 0.008 0.020 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.1663 0.48364 0.000 0.088 0.000 0.000 0.000 0.912
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4594 0.63906 0.004 0.000 0.032 0.560 0.404 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.84108 0.000 1.000 0.000 0.000 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3646 0.74962 0.776 0.000 0.052 0.000 0.172 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 4 0.6295 0.54588 0.000 0.152 0.032 0.416 0.400 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.4703 0.47162 0.032 0.004 0.004 0.392 0.568 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4372 0.49602 0.692 0.000 0.020 0.028 0.260 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0458 0.83921 0.000 0.984 0.000 0.000 0.000 0.016
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0622 0.31564 0.000 0.008 0.012 0.980 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3481 0.24226 0.000 0.000 0.072 0.124 0.804 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0881 0.84059 0.000 0.972 0.008 0.008 0.000 0.012
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.3607 0.50186 0.652 0.000 0.000 0.000 0.348 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1141 0.83432 0.948 0.000 0.000 0.052 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1265 0.82569 0.000 0.948 0.008 0.044 0.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0146 0.84837 0.996 0.000 0.000 0.000 0.004 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 5 0.4382 0.46735 0.012 0.004 0.004 0.416 0.564 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.6629 0.25861 0.300 0.000 0.084 0.132 0.484 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.4397 0.47756 0.024 0.000 0.004 0.376 0.596 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 4 0.4168 0.65305 0.016 0.000 0.000 0.584 0.400 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0865 0.84262 0.964 0.000 0.036 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0632 0.83672 0.000 0.976 0.000 0.024 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.3789 0.65630 0.000 0.000 0.000 0.584 0.416 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0865 0.84262 0.964 0.000 0.036 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.282 0.707 0.789 0.3908 0.556 0.556
#> 3 3 0.170 0.461 0.667 0.4392 0.815 0.681
#> 4 4 0.304 0.255 0.615 0.1408 0.636 0.346
#> 5 5 0.407 0.431 0.654 0.1347 0.732 0.390
#> 6 6 0.477 0.301 0.636 0.0569 0.915 0.722
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1184 0.6984 0.016 0.984
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.5178 0.8896 0.884 0.116
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.8763 0.7260 0.296 0.704
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.5178 0.8896 0.884 0.116
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5059 0.6410 0.112 0.888
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1184 0.6984 0.016 0.984
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.9732 0.3017 0.596 0.404
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5178 0.8896 0.884 0.116
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.5294 0.8904 0.880 0.120
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.5294 0.8904 0.880 0.120
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.8763 0.7260 0.296 0.704
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.8763 0.7260 0.296 0.704
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.9170 0.6731 0.332 0.668
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1184 0.6984 0.016 0.984
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.8763 0.7260 0.296 0.704
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.1843 0.7033 0.028 0.972
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0376 0.6912 0.004 0.996
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.8661 0.7274 0.288 0.712
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.6886 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.8955 0.7046 0.312 0.688
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1843 0.7035 0.028 0.972
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.8763 0.7260 0.296 0.704
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 1.0000 0.1924 0.496 0.504
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.5294 0.8904 0.880 0.120
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.9129 0.5658 0.672 0.328
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0938 0.6916 0.012 0.988
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5178 0.8896 0.884 0.116
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.5178 0.8896 0.884 0.116
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.7056 0.8273 0.808 0.192
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.8763 0.7260 0.296 0.704
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.5294 0.8865 0.880 0.120
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0938 0.6962 0.012 0.988
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.8763 0.7260 0.296 0.704
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.5294 0.8904 0.880 0.120
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1843 0.7033 0.028 0.972
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.5842 0.8763 0.860 0.140
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.7139 0.5436 0.196 0.804
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.5178 0.8896 0.884 0.116
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5408 0.8886 0.876 0.124
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#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.5737 0.6064 0.136 0.864
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.1184 0.6984 0.016 0.984
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.8763 0.7260 0.296 0.704
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.5294 0.5892 0.120 0.880
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 2 0.5946 0.5917 0.144 0.856
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.9522 0.4317 0.628 0.372
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.8763 0.7260 0.296 0.704
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.6712 0.8465 0.824 0.176
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.8661 0.7285 0.288 0.712
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.8763 0.7260 0.296 0.704
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.7883 0.7320 0.236 0.764
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.5178 0.8896 0.884 0.116
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.6623 0.7307 0.172 0.828
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.5294 0.8904 0.880 0.120
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.9998 0.2002 0.492 0.508
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0938 0.6800 0.012 0.988
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.8763 0.7260 0.296 0.704
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.9977 -0.0401 0.528 0.472
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.8661 0.7274 0.288 0.712
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.9427 0.4571 0.640 0.360
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.8267 0.7248 0.740 0.260
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.6048 0.7276 0.148 0.852
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.5294 0.5892 0.120 0.880
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.5946 0.8731 0.856 0.144
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2948 0.7118 0.052 0.948
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.8661 0.7274 0.288 0.712
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.9129 0.6797 0.328 0.672
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1184 0.6984 0.016 0.984
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.7883 0.7635 0.764 0.236
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2236 0.7065 0.036 0.964
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.5178 0.6117 0.116 0.884
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.5294 0.8904 0.880 0.120
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5294 0.8904 0.880 0.120
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5519 0.5939 0.128 0.872
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.8763 0.7260 0.296 0.704
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1633 0.6708 0.024 0.976
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.5294 0.8904 0.880 0.120
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.7883 0.7348 0.236 0.764
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4022 0.6248 0.080 0.920
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.9970 0.2953 0.468 0.532
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.5294 0.8904 0.880 0.120
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.5178 0.8896 0.884 0.116
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8763 0.7260 0.296 0.704
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.8763 0.7260 0.296 0.704
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.6247 0.7278 0.156 0.844
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.8763 0.7260 0.296 0.704
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.7815 0.7318 0.232 0.768
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.3431 0.7134 0.064 0.936
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.5294 0.5892 0.120 0.880
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.7453 0.8022 0.788 0.212
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.2778 0.6525 0.048 0.952
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8763 0.7260 0.296 0.704
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.8763 0.7249 0.296 0.704
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.5178 0.8896 0.884 0.116
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.8813 0.7242 0.300 0.700
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3274 0.7141 0.060 0.940
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.9922 0.1049 0.552 0.448
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.7299 0.8096 0.796 0.204
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5294 0.8904 0.880 0.120
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.8763 0.7260 0.296 0.704
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5294 0.8904 0.880 0.120
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2423 0.7080 0.040 0.960
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.7602 0.7906 0.780 0.220
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.9087 0.5797 0.676 0.324
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.8144 0.7338 0.252 0.748
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.5294 0.5892 0.120 0.880
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.8763 0.7260 0.296 0.704
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1184 0.6984 0.016 0.984
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5294 0.8904 0.880 0.120
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5519 0.7267 0.128 0.872
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.8763 0.7260 0.296 0.704
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.9881 0.1661 0.564 0.436
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0376 0.6858 0.004 0.996
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.8763 0.7260 0.296 0.704
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.6623 0.8473 0.828 0.172
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3584 0.7160 0.068 0.932
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.5294 0.8904 0.880 0.120
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.6887 0.8335 0.816 0.184
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.8713 0.7268 0.292 0.708
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.5178 0.8896 0.884 0.116
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.8763 0.7260 0.296 0.704
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.9963 0.3211 0.464 0.536
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.9170 0.6731 0.332 0.668
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9754 0.2986 0.592 0.408
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.8909 0.6259 0.692 0.308
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.7883 0.7320 0.236 0.764
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.9754 0.5038 0.408 0.592
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.9833 0.2316 0.576 0.424
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4235 -0.0769 0.000 0.824 0.176
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.4665 0.7381 0.852 0.100 0.048
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.8911 0.5938 0.224 0.572 0.204
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0661 0.7309 0.988 0.008 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.6624 0.4265 0.044 0.248 0.708
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4750 -0.1622 0.000 0.784 0.216
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.8755 0.3400 0.400 0.488 0.112
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3695 0.6871 0.880 0.108 0.012
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3193 0.7410 0.896 0.100 0.004
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3193 0.7410 0.896 0.100 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.9111 0.6046 0.212 0.548 0.240
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.9145 0.5924 0.240 0.544 0.216
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.8948 0.5788 0.248 0.564 0.188
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5098 -0.2542 0.000 0.752 0.248
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.9581 0.5709 0.288 0.476 0.236
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.3816 0.0724 0.000 0.852 0.148
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 3 0.6309 0.6693 0.000 0.500 0.500
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5660 0.5835 0.200 0.772 0.028
#> 479B4832-82DB-4176-9D24-D588F2903617 3 0.6309 0.6725 0.000 0.496 0.504
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.6516 0.2241 0.480 0.516 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3637 0.2316 0.024 0.892 0.084
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.9472 0.5770 0.288 0.492 0.220
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.9584 0.4983 0.372 0.428 0.200
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.4742 0.7380 0.848 0.104 0.048
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.6495 0.1959 0.460 0.536 0.004
#> C6AD4922-9981-4493-9F33-87A449B6EE55 3 0.7581 0.6195 0.040 0.464 0.496
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0848 0.7295 0.984 0.008 0.008
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1315 0.7298 0.972 0.008 0.020
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4629 0.6920 0.808 0.188 0.004
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.8950 0.5983 0.216 0.568 0.216
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.3445 0.6489 0.896 0.088 0.016
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5882 -0.4634 0.000 0.652 0.348
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.9523 0.5825 0.276 0.488 0.236
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3193 0.7410 0.896 0.100 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5815 -0.2886 0.004 0.692 0.304
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.4742 0.7380 0.848 0.104 0.048
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.8689 0.5258 0.200 0.204 0.596
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0848 0.7295 0.984 0.008 0.008
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4733 0.6853 0.800 0.196 0.004
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4665 0.7383 0.852 0.100 0.048
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 3 0.6897 0.5285 0.040 0.292 0.668
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6672 -0.1437 0.520 0.472 0.008
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 3 0.6309 0.6736 0.000 0.496 0.504
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.4413 0.6711 0.008 0.160 0.832
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6521 -0.0681 0.500 0.496 0.004
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4345 0.1240 0.016 0.848 0.136
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.2339 0.7280 0.940 0.012 0.048
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2959 0.1401 0.000 0.900 0.100
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.7222 0.1244 0.072 0.684 0.244
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3267 0.0753 0.000 0.884 0.116
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6111 0.6688 0.000 0.396 0.604
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.3193 0.7410 0.896 0.100 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.3193 0.7410 0.896 0.100 0.004
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4790 0.6333 0.848 0.096 0.056
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1989 0.7287 0.948 0.048 0.004
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.3375 0.7407 0.892 0.100 0.008
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.6460 0.4240 0.440 0.556 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.6867 0.5456 0.336 0.636 0.028
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.3607 0.4909 0.112 0.880 0.008
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.9306 0.5471 0.348 0.480 0.172
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.5843 0.5905 0.732 0.252 0.016
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5497 -0.3516 0.000 0.708 0.292
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 2 0.9624 0.5687 0.292 0.468 0.240
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.1315 0.7246 0.972 0.008 0.020
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.4665 0.7381 0.852 0.100 0.048
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2636 0.2972 0.020 0.932 0.048
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.8398 0.6191 0.192 0.624 0.184
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.8977 0.6007 0.204 0.564 0.232
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.7143 0.2345 0.576 0.396 0.028
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4994 0.6468 0.836 0.112 0.052
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.7901 0.4714 0.312 0.608 0.080
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.3193 0.7410 0.896 0.100 0.004
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.4558 0.2649 0.044 0.856 0.100
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.7147 0.4174 0.076 0.228 0.696
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.6402 0.0961 0.056 0.744 0.200
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.8058 0.6125 0.212 0.648 0.140
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.6140 0.6815 0.000 0.404 0.596
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9509 0.4597 0.220 0.484 0.296
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3826 0.7338 0.868 0.124 0.008
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.3375 0.7402 0.892 0.100 0.008
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0661 0.7306 0.988 0.008 0.004
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.3791 0.3441 0.048 0.892 0.060
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.6912 0.1404 0.540 0.444 0.016
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.7318 0.5172 0.068 0.264 0.668
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 2 0.7248 0.3793 0.436 0.536 0.028
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.2173 0.7272 0.944 0.008 0.048
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.3482 0.0601 0.000 0.872 0.128
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.8823 0.5461 0.280 0.564 0.156
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.4452 -0.0919 0.000 0.808 0.192
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#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.2339 0.7310 0.940 0.012 0.048
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.3755 0.2209 0.008 0.872 0.120
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.6407 0.5791 0.272 0.700 0.028
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.8972 0.5860 0.236 0.564 0.200
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.5621 -0.3931 0.000 0.692 0.308
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.6189 0.1519 0.632 0.364 0.004
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.3340 0.0989 0.000 0.880 0.120
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.8316 0.5977 0.080 0.424 0.496
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.3193 0.7410 0.896 0.100 0.004
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.4293 0.7132 0.832 0.164 0.004
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.7481 0.6398 0.048 0.356 0.596
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.9606 0.5723 0.288 0.472 0.240
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 3 0.6291 0.6905 0.000 0.468 0.532
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3193 0.7410 0.896 0.100 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.4269 0.4493 0.076 0.872 0.052
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 3 0.6192 0.7076 0.000 0.420 0.580
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.9328 0.5288 0.356 0.472 0.172
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.3193 0.7410 0.896 0.100 0.004
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0475 0.7313 0.992 0.004 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.7607 0.5612 0.280 0.644 0.076
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.8985 0.5955 0.220 0.564 0.216
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.8953 0.5475 0.180 0.560 0.260
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.6954 0.5526 0.352 0.620 0.028
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.5897 0.4178 0.132 0.792 0.076
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6663 0.3679 0.096 0.748 0.156
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.5397 0.7202 0.000 0.280 0.720
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.5298 0.7153 0.804 0.164 0.032
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.6305 -0.6252 0.000 0.516 0.484
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.7874 0.5101 0.320 0.604 0.076
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.9907 0.4874 0.280 0.396 0.324
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.2280 0.7263 0.940 0.008 0.052
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.9527 0.5537 0.332 0.464 0.204
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2301 0.2393 0.004 0.936 0.060
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.9322 0.3654 0.392 0.444 0.164
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.5502 0.4829 0.744 0.248 0.008
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0661 0.7306 0.988 0.008 0.004
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9606 0.5712 0.288 0.472 0.240
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3573 0.6784 0.876 0.120 0.004
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2959 0.1412 0.000 0.900 0.100
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4634 0.6265 0.824 0.164 0.012
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.6669 0.0290 0.524 0.468 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.8792 0.6108 0.176 0.580 0.244
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.5465 0.7202 0.000 0.288 0.712
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.9379 0.5425 0.348 0.472 0.180
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.5650 -0.3989 0.000 0.688 0.312
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2590 0.7453 0.924 0.072 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.3987 0.2307 0.020 0.872 0.108
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.9599 0.5708 0.292 0.472 0.236
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.6521 -0.0768 0.500 0.496 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 3 0.6280 0.6967 0.000 0.460 0.540
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.8965 0.6017 0.196 0.564 0.240
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5514 0.6037 0.800 0.156 0.044
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.7481 -0.2133 0.064 0.640 0.296
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.5109 0.6636 0.780 0.212 0.008
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.3039 0.7242 0.920 0.044 0.036
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4602 0.5248 0.152 0.832 0.016
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3193 0.7410 0.896 0.100 0.004
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.9624 0.5723 0.292 0.468 0.240
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.9389 0.5386 0.352 0.468 0.180
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.9624 0.5687 0.292 0.468 0.240
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.6669 -0.2339 0.524 0.468 0.008
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.6931 0.0971 0.528 0.456 0.016
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4768 0.4154 0.100 0.848 0.052
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6495 -0.1950 0.536 0.460 0.004
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.7396 -0.0754 0.488 0.480 0.032
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0672 0.67318 0.000 0.984 0.008 0.008
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.4905 0.62698 0.632 0.000 0.004 0.364
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3881 0.24339 0.172 0.016 0.000 0.812
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 4 0.5126 -0.24324 0.444 0.000 0.004 0.552
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.7609 -0.34232 0.200 0.000 0.396 0.404
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2053 0.66745 0.000 0.924 0.072 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4977 -0.34258 0.460 0.000 0.000 0.540
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 4 0.4967 -0.24245 0.452 0.000 0.000 0.548
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.6752 0.04591 0.440 0.092 0.000 0.468
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.4992 -0.23818 0.524 0.000 0.000 0.476
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.4543 0.20878 0.324 0.000 0.000 0.676
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1209 0.66700 0.004 0.964 0.032 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4679 0.10946 0.352 0.000 0.000 0.648
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5744 0.58609 0.000 0.708 0.184 0.108
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.3743 0.59748 0.000 0.824 0.160 0.016
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.9050 0.24292 0.092 0.428 0.184 0.296
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4874 0.54604 0.000 0.764 0.180 0.056
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.6626 -0.26772 0.364 0.092 0.000 0.544
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2760 0.65752 0.000 0.872 0.000 0.128
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3858 0.33236 0.100 0.056 0.000 0.844
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 4 0.4948 0.10390 0.440 0.000 0.000 0.560
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.4905 0.62698 0.632 0.000 0.004 0.364
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4994 0.48066 0.520 0.000 0.000 0.480
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.8968 -0.10214 0.064 0.380 0.336 0.220
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4746 0.62436 0.632 0.000 0.000 0.368
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4164 0.26313 0.264 0.000 0.000 0.736
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 4 0.6447 -0.26808 0.448 0.068 0.000 0.484
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1022 0.66475 0.000 0.968 0.032 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.4989 0.12898 0.472 0.000 0.000 0.528
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5770 0.48000 0.000 0.712 0.148 0.140
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.4950 0.61259 0.620 0.000 0.004 0.376
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.6548 0.49175 0.116 0.000 0.608 0.276
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4817 0.60326 0.612 0.000 0.000 0.388
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4905 0.62698 0.632 0.000 0.004 0.364
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.8953 -0.11928 0.088 0.272 0.188 0.452
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.4996 -0.45282 0.484 0.000 0.000 0.516
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.3024 0.61024 0.000 0.852 0.148 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.5067 0.51634 0.000 0.216 0.736 0.048
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.5147 0.49533 0.536 0.004 0.000 0.460
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2919 0.67260 0.000 0.896 0.060 0.044
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 4 0.5126 -0.24324 0.444 0.000 0.004 0.552
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2238 0.66892 0.004 0.920 0.072 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.6231 0.21020 0.004 0.336 0.060 0.600
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.2469 0.66616 0.000 0.892 0.000 0.108
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.5160 0.44624 0.000 0.136 0.760 0.104
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 4 0.6612 -0.26210 0.444 0.068 0.004 0.484
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.6157 -0.04453 0.232 0.108 0.000 0.660
#> 97A49141-0141-4583-B366-A4720270D6F2 4 0.9147 0.13776 0.148 0.196 0.184 0.472
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4266 0.65279 0.032 0.828 0.016 0.124
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.0895 0.29273 0.020 0.004 0.000 0.976
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4981 0.49248 0.536 0.000 0.000 0.464
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0524 0.67251 0.000 0.988 0.004 0.008
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.4697 0.11056 0.356 0.000 0.000 0.644
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.4905 0.62698 0.632 0.000 0.004 0.364
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.3721 0.66145 0.056 0.864 0.072 0.008
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.6901 0.25668 0.080 0.208 0.052 0.660
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.4679 0.26527 0.352 0.000 0.000 0.648
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4977 0.50003 0.540 0.000 0.000 0.460
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4996 0.19279 0.516 0.000 0.000 0.484
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.7551 -0.27140 0.368 0.004 0.168 0.460
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.6492 0.54080 0.004 0.656 0.184 0.156
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.6733 0.41258 0.092 0.000 0.492 0.416
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.7248 0.33688 0.000 0.532 0.184 0.284
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.5143 0.22721 0.172 0.076 0.000 0.752
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.5434 0.50165 0.000 0.252 0.696 0.052
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.3346 0.32092 0.024 0.060 0.028 0.888
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4761 0.62120 0.628 0.000 0.000 0.372
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> F4F647DC-C630-429C-AD49-ADA43B652781 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.7493 0.54534 0.072 0.628 0.192 0.108
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.7248 0.26669 0.532 0.000 0.184 0.284
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.5584 0.50012 0.012 0.008 0.580 0.400
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 4 0.7432 -0.02903 0.336 0.000 0.184 0.480
#> E435C03F-0277-49C1-83EF-19452082723E 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2384 0.66985 0.008 0.916 0.072 0.004
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.3528 0.23021 0.192 0.000 0.000 0.808
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.2053 0.66745 0.000 0.924 0.072 0.004
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 4 0.6961 -0.27469 0.448 0.076 0.012 0.464
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.3311 0.31179 0.172 0.000 0.000 0.828
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.7005 0.31846 0.172 0.572 0.000 0.256
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.2281 0.67117 0.000 0.904 0.000 0.096
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.7407 0.26524 0.520 0.004 0.172 0.304
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.6690 0.55980 0.004 0.108 0.600 0.288
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.4916 0.56104 0.576 0.000 0.000 0.424
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.4830 -0.16955 0.392 0.000 0.000 0.608
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.3764 0.27975 0.216 0.000 0.000 0.784
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#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.5536 0.26033 0.180 0.096 0.000 0.724
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.4624 -0.17008 0.340 0.000 0.000 0.660
#> A2007795-C728-4688-B199-AE89500011D2 2 0.2814 0.62054 0.000 0.868 0.132 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.3486 0.23374 0.188 0.000 0.000 0.812
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 4 0.4624 -0.17008 0.340 0.000 0.000 0.660
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.9299 0.20437 0.116 0.400 0.184 0.300
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6252 0.48158 0.512 0.056 0.000 0.432
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.4837 -0.18107 0.348 0.004 0.000 0.648
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 1 0.9048 -0.33582 0.416 0.196 0.084 0.304
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 3 0.4164 0.47097 0.000 0.264 0.736 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.6357 0.41567 0.544 0.000 0.068 0.388
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.3182 0.65901 0.004 0.860 0.004 0.132
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.8871 0.13851 0.068 0.380 0.184 0.368
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.4998 0.18099 0.488 0.000 0.000 0.512
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.2921 0.61441 0.000 0.860 0.140 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 4 0.4661 -0.18081 0.348 0.000 0.000 0.652
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2053 0.67757 0.000 0.924 0.004 0.072
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.7597 0.49634 0.008 0.176 0.504 0.312
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.6538 0.55890 0.000 0.108 0.600 0.292
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.4679 0.10946 0.352 0.000 0.000 0.648
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4220 0.49941 0.000 0.748 0.248 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6692 0.46686 0.064 0.652 0.040 0.244
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4991 0.22015 0.000 0.608 0.388 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.4877 0.08476 0.408 0.000 0.000 0.592
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 4 0.5126 -0.24324 0.444 0.000 0.004 0.552
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6580 0.15140 0.196 0.172 0.000 0.632
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5760 0.25853 0.360 0.024 0.008 0.608
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.7098 0.13373 0.232 0.076 0.056 0.636
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.6580 0.03588 0.172 0.196 0.000 0.632
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.6025 0.50578 0.172 0.688 0.000 0.140
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.6863 -0.02388 0.016 0.412 0.064 0.508
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.4164 0.47097 0.000 0.264 0.736 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.6264 0.48690 0.560 0.000 0.064 0.376
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.7164 0.25554 0.004 0.464 0.416 0.116
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.5250 0.00536 0.316 0.024 0.000 0.660
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.5406 0.26146 0.172 0.024 0.048 0.756
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 4 0.5126 -0.24324 0.444 0.000 0.004 0.552
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.1624 0.29068 0.020 0.000 0.028 0.952
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3731 0.65799 0.064 0.860 0.072 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.4916 0.26082 0.576 0.000 0.000 0.424
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.4746 -0.20380 0.368 0.000 0.000 0.632
#> C20F209A-2102-4502-80FA-17AF04601987 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4888 0.12314 0.412 0.000 0.000 0.588
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 4 0.4961 -0.24438 0.448 0.000 0.000 0.552
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3150 0.66885 0.036 0.888 0.072 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5000 0.21796 0.504 0.000 0.000 0.496
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.4977 -0.34289 0.460 0.000 0.000 0.540
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.7178 -0.22431 0.492 0.108 0.008 0.392
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.4193 0.46790 0.000 0.268 0.732 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.0000 0.30390 0.000 0.000 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3447 0.62635 0.020 0.852 0.128 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4877 0.56027 0.592 0.000 0.000 0.408
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5850 0.58013 0.000 0.700 0.184 0.116
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.4679 0.10946 0.352 0.000 0.000 0.648
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.4999 -0.41860 0.492 0.000 0.000 0.508
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4891 0.38678 0.000 0.680 0.308 0.012
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.5277 -0.23365 0.532 0.008 0.000 0.460
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 4 0.4994 -0.23157 0.480 0.000 0.000 0.520
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.5768 0.57057 0.104 0.740 0.140 0.016
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4730 0.62791 0.636 0.000 0.000 0.364
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.7281 0.15142 0.440 0.000 0.148 0.412
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.7450 0.09563 0.172 0.404 0.000 0.424
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4817 0.59566 0.612 0.000 0.000 0.388
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.4730 0.11318 0.364 0.000 0.000 0.636
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.4605 0.28952 0.336 0.000 0.000 0.664
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.4877 0.13391 0.408 0.000 0.000 0.592
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 4 0.6074 -0.13071 0.340 0.000 0.060 0.600
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.7229 0.27266 0.536 0.000 0.184 0.280
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.5678 0.53392 0.172 0.716 0.000 0.112
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.4936 -0.16704 0.340 0.008 0.000 0.652
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.6747 0.38272 0.528 0.000 0.100 0.372
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0566 0.71031 0.000 0.984 0.004 0.012 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.1809 0.67583 0.928 0.000 0.060 0.012 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2753 0.33849 0.104 0.008 0.012 0.876 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4192 0.64714 0.596 0.000 0.404 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 5 0.6232 0.25982 0.000 0.004 0.124 0.408 0.464
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0324 0.70525 0.000 0.992 0.004 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4290 0.45208 0.680 0.000 0.016 0.304 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5037 0.64882 0.584 0.000 0.376 0.040 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1195 0.67627 0.960 0.000 0.028 0.012 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3055 0.68131 0.864 0.000 0.064 0.072 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.6011 0.42900 0.028 0.052 0.480 0.440 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.6418 -0.27719 0.172 0.000 0.412 0.416 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.5616 0.25818 0.384 0.000 0.080 0.536 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1965 0.69220 0.000 0.904 0.000 0.000 0.096
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.4313 0.64464 0.000 0.000 0.636 0.356 0.008
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5268 0.57363 0.000 0.692 0.016 0.076 0.216
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4813 0.58015 0.000 0.724 0.048 0.016 0.212
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7736 0.40759 0.052 0.492 0.020 0.220 0.216
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.5251 0.50029 0.000 0.668 0.048 0.020 0.264
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.7569 0.40961 0.504 0.212 0.104 0.180 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3839 0.62298 0.108 0.816 0.004 0.072 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5487 -0.33263 0.024 0.028 0.392 0.556 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.6177 0.15300 0.232 0.000 0.556 0.212 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.2260 0.67745 0.908 0.000 0.064 0.028 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3615 0.65576 0.808 0.000 0.036 0.156 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 5 0.7524 0.07191 0.020 0.368 0.016 0.216 0.380
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4564 0.64558 0.612 0.000 0.372 0.016 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4446 0.64346 0.592 0.000 0.400 0.008 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2067 0.67317 0.920 0.000 0.032 0.048 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.5618 0.01922 0.112 0.000 0.280 0.608 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.5774 0.63512 0.588 0.056 0.332 0.024 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2127 0.68755 0.000 0.892 0.000 0.000 0.108
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6153 -0.21949 0.136 0.000 0.380 0.484 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0898 0.67638 0.972 0.000 0.020 0.008 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5458 0.54853 0.000 0.688 0.040 0.056 0.216
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.4226 0.61355 0.808 0.000 0.068 0.028 0.096
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.6036 0.33430 0.356 0.000 0.020 0.076 0.548
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4588 0.64220 0.604 0.000 0.380 0.016 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1893 0.66564 0.928 0.000 0.024 0.048 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1502 0.67534 0.940 0.000 0.056 0.004 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.7744 -0.15755 0.004 0.200 0.060 0.396 0.340
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5220 0.16027 0.516 0.000 0.044 0.440 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.3621 0.63195 0.000 0.788 0.020 0.000 0.192
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 5 0.4622 0.54172 0.000 0.084 0.004 0.164 0.748
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4320 0.63265 0.792 0.052 0.024 0.132 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1981 0.69875 0.000 0.924 0.048 0.028 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.4327 0.65935 0.632 0.000 0.360 0.008 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0324 0.70525 0.000 0.992 0.004 0.000 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.7480 0.08028 0.048 0.484 0.032 0.336 0.100
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1270 0.70813 0.000 0.948 0.000 0.052 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 5 0.4245 0.46282 0.000 0.124 0.028 0.048 0.800
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1117 0.67827 0.964 0.000 0.016 0.020 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1168 0.67638 0.960 0.000 0.032 0.008 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.5363 0.63274 0.572 0.052 0.372 0.004 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4599 0.64709 0.600 0.000 0.384 0.016 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.1403 0.66819 0.952 0.000 0.024 0.024 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.7660 0.34356 0.448 0.076 0.200 0.276 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.9911 -0.11179 0.172 0.260 0.184 0.168 0.216
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.5026 0.59686 0.096 0.752 0.036 0.116 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.6519 0.06571 0.352 0.000 0.200 0.448 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.2727 0.61956 0.868 0.000 0.016 0.116 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0566 0.71031 0.000 0.984 0.004 0.012 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.4867 0.56181 0.024 0.000 0.544 0.432 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4726 0.64206 0.580 0.000 0.400 0.020 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1571 0.67452 0.936 0.000 0.060 0.004 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2150 0.69639 0.008 0.916 0.004 0.068 0.004
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.5980 0.19232 0.052 0.160 0.008 0.688 0.092
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.5788 -0.02054 0.120 0.000 0.300 0.580 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4000 0.52779 0.748 0.000 0.024 0.228 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.5857 0.49666 0.460 0.000 0.444 0.096 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.7625 -0.13741 0.384 0.000 0.132 0.388 0.096
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0992 0.67677 0.968 0.000 0.024 0.008 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.6218 0.53753 0.008 0.644 0.036 0.100 0.212
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 5 0.5119 0.35162 0.028 0.000 0.004 0.464 0.504
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.5815 0.55393 0.004 0.660 0.020 0.100 0.216
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.4583 0.30619 0.112 0.140 0.000 0.748 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 5 0.6427 0.52297 0.000 0.144 0.060 0.164 0.632
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.7804 -0.20458 0.112 0.056 0.360 0.436 0.036
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2423 0.68730 0.896 0.000 0.080 0.024 0.000
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#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.4763 0.66062 0.632 0.000 0.336 0.032 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.4139 0.60532 0.084 0.784 0.000 0.132 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.3339 0.34187 0.124 0.000 0.040 0.836 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0486 0.70653 0.000 0.988 0.004 0.004 0.004
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0324 0.70525 0.000 0.992 0.004 0.000 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.2852 0.65739 0.000 0.828 0.000 0.000 0.172
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.4528 0.29626 0.144 0.000 0.104 0.752 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.5865 -0.35660 0.052 0.020 0.448 0.480 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.4235 0.64013 0.576 0.000 0.424 0.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 3 0.7898 0.29648 0.000 0.092 0.404 0.300 0.204
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.2236 0.66952 0.908 0.000 0.024 0.068 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.6482 0.36652 0.492 0.000 0.232 0.276 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.4341 0.64396 0.592 0.000 0.404 0.004 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.4727 0.55094 0.028 0.704 0.016 0.252 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 3 0.4482 0.64802 0.012 0.000 0.612 0.376 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.4666 0.66693 0.732 0.000 0.180 0.088 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 3 0.6160 0.31980 0.132 0.000 0.448 0.420 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.1571 0.67452 0.936 0.000 0.060 0.004 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.3863 0.11468 0.028 0.000 0.200 0.772 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.4049 0.61355 0.084 0.792 0.000 0.124 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.5095 0.62666 0.560 0.000 0.400 0.040 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.1485 0.67798 0.948 0.000 0.032 0.020 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.6414 0.44791 0.280 0.000 0.012 0.160 0.548
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 5 0.6711 0.30387 0.004 0.156 0.008 0.408 0.424
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.8816 0.27596 0.068 0.436 0.172 0.108 0.216
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.4786 0.37059 0.620 0.012 0.012 0.356 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.8724 0.29701 0.116 0.064 0.120 0.288 0.412
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0324 0.70525 0.000 0.992 0.004 0.000 0.004
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.4477 0.33301 0.252 0.040 0.000 0.708 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 5 0.4717 0.38507 0.000 0.396 0.020 0.000 0.584
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.6359 0.36233 0.328 0.000 0.008 0.144 0.520
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.5026 0.64107 0.588 0.000 0.372 0.040 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.4894 0.50458 0.024 0.000 0.520 0.456 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.3085 0.67286 0.852 0.000 0.032 0.116 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.6378 0.26861 0.312 0.516 0.004 0.168 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.5191 0.22847 0.192 0.000 0.124 0.684 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.2692 0.69403 0.016 0.884 0.008 0.092 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.4709 0.64828 0.612 0.000 0.364 0.024 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.5886 -0.43107 0.024 0.048 0.448 0.480 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.1485 0.66979 0.948 0.000 0.020 0.032 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.5975 0.55747 0.588 0.000 0.224 0.188 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.2852 0.64967 0.000 0.828 0.000 0.000 0.172
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.3477 0.31746 0.112 0.000 0.056 0.832 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.5770 0.59306 0.532 0.000 0.372 0.096 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.8505 0.22910 0.104 0.380 0.020 0.280 0.216
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.5006 0.58229 0.732 0.112 0.012 0.144 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.4876 0.65934 0.700 0.000 0.220 0.080 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 3 0.7442 0.32245 0.016 0.156 0.424 0.372 0.032
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 5 0.3940 0.48712 0.000 0.220 0.024 0.000 0.756
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.5878 0.54096 0.664 0.000 0.136 0.028 0.172
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.5814 0.54782 0.000 0.656 0.044 0.232 0.068
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9335 0.20323 0.120 0.384 0.152 0.128 0.216
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.6447 -0.12661 0.192 0.000 0.336 0.472 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.2929 0.65323 0.000 0.820 0.000 0.000 0.180
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.5810 0.60686 0.580 0.000 0.296 0.124 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0865 0.71095 0.000 0.972 0.004 0.024 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.7779 0.40528 0.236 0.072 0.004 0.236 0.452
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1670 0.68507 0.936 0.000 0.052 0.012 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1965 0.66933 0.924 0.000 0.024 0.052 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 5 0.6917 0.47253 0.204 0.048 0.000 0.192 0.556
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 3 0.4088 0.64853 0.000 0.000 0.632 0.368 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.5028 0.49129 0.000 0.668 0.048 0.008 0.276
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3090 0.68480 0.860 0.000 0.088 0.052 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.4203 0.63447 0.012 0.760 0.004 0.208 0.016
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 5 0.6030 0.11660 0.000 0.432 0.072 0.016 0.480
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6798 0.05203 0.300 0.000 0.376 0.324 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1082 0.67709 0.964 0.000 0.028 0.008 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.4310 0.64871 0.604 0.000 0.392 0.004 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6325 0.16128 0.392 0.124 0.008 0.476 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5715 0.23401 0.104 0.004 0.108 0.716 0.068
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.5446 -0.08674 0.000 0.072 0.268 0.648 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.8185 0.11339 0.368 0.152 0.168 0.312 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.6337 0.27389 0.308 0.524 0.004 0.164 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5894 -0.04095 0.048 0.480 0.008 0.452 0.012
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 5 0.3882 0.48606 0.000 0.224 0.020 0.000 0.756
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.4484 0.58162 0.788 0.004 0.016 0.076 0.116
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 5 0.6245 -0.07622 0.004 0.408 0.016 0.080 0.492
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.4794 -0.00781 0.520 0.004 0.012 0.464 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.6647 0.41787 0.040 0.012 0.472 0.416 0.060
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.4464 0.64359 0.584 0.000 0.408 0.008 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6122 0.15128 0.128 0.008 0.200 0.644 0.020
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2212 0.69374 0.004 0.908 0.004 0.080 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.5810 -0.19761 0.480 0.000 0.092 0.428 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.5037 0.63490 0.584 0.000 0.376 0.040 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3398 0.67610 0.780 0.000 0.216 0.004 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4961 -0.42403 0.028 0.000 0.448 0.524 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5510 0.62203 0.648 0.000 0.208 0.144 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0727 0.70781 0.000 0.980 0.004 0.012 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5875 0.58240 0.592 0.000 0.256 0.152 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3675 0.57278 0.788 0.000 0.024 0.188 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.6609 -0.26674 0.072 0.052 0.404 0.472 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 5 0.4766 0.47490 0.000 0.220 0.072 0.000 0.708
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6469 0.09993 0.336 0.000 0.196 0.468 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3167 0.66049 0.004 0.820 0.000 0.004 0.172
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2446 0.68742 0.900 0.000 0.056 0.044 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5426 0.57064 0.000 0.680 0.016 0.088 0.216
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4313 0.64966 0.008 0.000 0.636 0.356 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4184 0.55934 0.740 0.004 0.024 0.232 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.5362 0.42502 0.000 0.632 0.028 0.032 0.308
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.5777 -0.28503 0.088 0.000 0.444 0.468 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5836 0.56453 0.516 0.000 0.384 0.100 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.6571 0.56645 0.052 0.628 0.008 0.124 0.188
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2694 0.67118 0.884 0.000 0.040 0.076 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.6938 0.42113 0.392 0.000 0.384 0.012 0.212
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5215 0.52237 0.088 0.656 0.000 0.256 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1992 0.68037 0.924 0.000 0.044 0.032 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 3 0.4599 0.63206 0.016 0.000 0.600 0.384 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6814 -0.05672 0.352 0.000 0.344 0.304 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.5467 0.52835 0.064 0.000 0.524 0.412 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.7477 0.47339 0.512 0.000 0.204 0.192 0.092
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.5718 0.42730 0.668 0.008 0.012 0.100 0.212
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4478 0.59717 0.088 0.764 0.004 0.144 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.5566 0.61387 0.656 0.004 0.200 0.140 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.5589 0.43973 0.676 0.000 0.016 0.120 0.188
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0146 0.692107 0.004 0.996 0.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.4467 0.311200 0.004 0.000 0.376 0.028 0.592 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.1872 0.303869 0.064 0.008 0.004 0.920 0.004 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.1913 0.433961 0.012 0.000 0.080 0.000 0.908 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.6738 0.097593 0.368 0.008 0.020 0.288 0.000 0.316
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0405 0.691636 0.008 0.988 0.000 0.000 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 5 0.6534 -0.218406 0.012 0.000 0.316 0.316 0.352 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.3024 0.430224 0.040 0.000 0.088 0.016 0.856 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 5 0.4384 0.254120 0.004 0.000 0.460 0.016 0.520 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.5043 0.289820 0.008 0.000 0.360 0.064 0.568 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.4943 0.433602 0.584 0.044 0.004 0.360 0.004 0.004
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5386 0.479791 0.652 0.000 0.152 0.168 0.028 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.6241 0.281777 0.056 0.000 0.244 0.572 0.120 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0935 0.690297 0.004 0.964 0.000 0.000 0.000 0.032
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.3943 0.572339 0.760 0.000 0.000 0.084 0.156 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.5659 0.487539 0.020 0.612 0.248 0.004 0.004 0.112
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.5649 0.410934 0.032 0.580 0.080 0.004 0.000 0.304
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7866 0.274471 0.020 0.356 0.256 0.252 0.004 0.112
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.6244 0.329139 0.056 0.532 0.092 0.008 0.000 0.312
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.7309 -0.053833 0.004 0.184 0.124 0.268 0.420 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3519 0.610106 0.016 0.836 0.096 0.024 0.028 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.6031 -0.178611 0.356 0.032 0.004 0.504 0.104 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.5610 0.090603 0.192 0.000 0.044 0.128 0.636 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 5 0.4407 0.308415 0.004 0.000 0.380 0.024 0.592 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.5932 0.013367 0.000 0.000 0.224 0.336 0.440 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.8115 0.194308 0.112 0.212 0.052 0.228 0.004 0.392
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.3314 0.404398 0.048 0.000 0.128 0.004 0.820 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.1644 0.436727 0.040 0.000 0.028 0.000 0.932 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 5 0.5620 0.248905 0.008 0.000 0.296 0.116 0.572 0.008
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.3977 -0.018955 0.304 0.004 0.004 0.680 0.004 0.004
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.3965 0.391959 0.076 0.024 0.108 0.000 0.792 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1010 0.689500 0.004 0.960 0.000 0.000 0.000 0.036
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6934 -0.055502 0.332 0.000 0.132 0.424 0.112 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 5 0.4721 0.253166 0.000 0.000 0.420 0.048 0.532 0.000
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#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6795 0.141344 0.172 0.004 0.032 0.472 0.304 0.016
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2737 0.643475 0.004 0.832 0.000 0.160 0.000 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.7494 -0.239016 0.132 0.000 0.284 0.308 0.276 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3510 0.410742 0.048 0.028 0.052 0.024 0.848 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.3895 0.382134 0.016 0.000 0.284 0.004 0.696 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.5511 0.436696 0.536 0.000 0.024 0.364 0.076 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.5151 0.332533 0.028 0.000 0.160 0.132 0.680 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1364 0.690181 0.004 0.944 0.000 0.048 0.000 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.4831 0.372419 0.076 0.000 0.092 0.068 0.752 0.012
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 3 0.6327 0.165134 0.008 0.000 0.360 0.300 0.332 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.5117 0.367079 0.548 0.016 0.004 0.396 0.004 0.032
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.4843 0.488603 0.008 0.164 0.140 0.000 0.000 0.688
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6760 0.078315 0.096 0.016 0.044 0.424 0.408 0.012
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2593 0.656169 0.000 0.844 0.000 0.008 0.000 0.148
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 5 0.4621 0.313513 0.000 0.000 0.332 0.056 0.612 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5804 0.487725 0.020 0.604 0.248 0.016 0.000 0.112
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.4516 0.576937 0.724 0.000 0.012 0.092 0.172 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.6074 -0.135286 0.000 0.000 0.268 0.356 0.376 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.6490 0.149195 0.056 0.460 0.120 0.004 0.000 0.360
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.4070 0.394717 0.568 0.004 0.004 0.424 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3639 0.384631 0.092 0.000 0.044 0.028 0.828 0.008
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.7100 0.286185 0.016 0.364 0.036 0.280 0.000 0.304
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 5 0.5392 0.250379 0.004 0.000 0.244 0.140 0.608 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.3815 0.288210 0.016 0.000 0.088 0.000 0.800 0.096
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4714 0.414149 0.008 0.548 0.004 0.416 0.000 0.024
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.4571 0.271938 0.004 0.000 0.432 0.028 0.536 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.4588 0.584020 0.716 0.000 0.008 0.156 0.120 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.6477 0.032328 0.184 0.000 0.044 0.212 0.548 0.012
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.6177 0.449364 0.512 0.000 0.024 0.260 0.204 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.5952 0.258001 0.044 0.024 0.112 0.180 0.640 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.6912 0.088287 0.000 0.008 0.436 0.108 0.348 0.100
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3213 0.617200 0.000 0.784 0.008 0.204 0.004 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.5927 0.272130 0.076 0.004 0.120 0.168 0.632 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 5 0.5814 0.168048 0.004 0.000 0.280 0.200 0.516 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.843 0.901 0.960 0.4996 0.500 0.500
#> 3 3 0.517 0.599 0.803 0.3074 0.783 0.592
#> 4 4 0.551 0.382 0.684 0.1285 0.843 0.591
#> 5 5 0.720 0.701 0.847 0.0741 0.825 0.461
#> 6 6 0.755 0.722 0.836 0.0411 0.899 0.583
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9600 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9534 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9600 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9534 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.4022 0.8889 0.080 0.920
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9600 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9534 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9534 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9534 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9534 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.1414 0.9447 0.020 0.980
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0000 0.9534 1.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.9534 1.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9600 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.0000 0.9534 1.000 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0000 0.9600 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9600 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0000 0.9600 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9600 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.9600 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9600 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9600 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9534 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9534 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.8861 0.5607 0.304 0.696
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9600 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9534 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9534 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9534 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9600 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9534 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9600 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9534 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9534 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9600 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9534 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.0000 0.9600 0.000 1.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9534 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9534 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9534 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9600 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.9534 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9600 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9600 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6973 0.7527 0.812 0.188
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9600 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9534 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9600 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9600 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9600 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.0000 0.9600 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9534 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9534 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9534 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9534 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9534 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.5946 0.8167 0.144 0.856
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.0000 0.9600 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9600 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.7299 0.7370 0.796 0.204
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9534 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.9600 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9534 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9534 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9534 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9600 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9600 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.9815 0.2718 0.420 0.580
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.9534 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.9534 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.2236 0.9246 0.964 0.036
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9534 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0000 0.9600 0.000 1.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.3274 0.9079 0.060 0.940
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0000 0.9600 0.000 1.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.9600 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9600 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.7453 0.7256 0.788 0.212
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9534 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9534 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.9534 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.0000 0.9600 0.000 1.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.9534 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.9534 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.9635 0.3670 0.612 0.388
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9534 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9600 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.9534 1.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9600 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.0376 0.9570 0.004 0.996
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.9815 0.2944 0.580 0.420
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9600 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.9600 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.9460 0.4589 0.636 0.364
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.9600 0.000 1.000
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#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9534 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9600 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9600 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9534 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9600 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9534 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.0000 0.9600 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9534 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9534 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9600 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.9608 0.3753 0.384 0.616
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9534 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9600 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9534 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9534 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9600 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9534 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.4815 0.8593 0.896 0.104
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9534 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9534 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0672 0.9473 0.992 0.008
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9534 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9600 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.9983 0.0814 0.476 0.524
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9534 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.83941 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.76798 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 3 0.6154 0.38670 0.000 0.408 0.592
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4605 0.69931 0.796 0.000 0.204
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.1031 0.55129 0.000 0.024 0.976
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.83941 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.6154 0.04275 0.592 0.000 0.408
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4178 0.72477 0.828 0.000 0.172
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1289 0.76177 0.968 0.000 0.032
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0424 0.76799 0.992 0.000 0.008
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 3 0.6906 0.45676 0.032 0.324 0.644
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.6095 0.45919 0.392 0.000 0.608
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 3 0.6309 0.27140 0.496 0.000 0.504
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.83941 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.5678 0.48696 0.316 0.000 0.684
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.0592 0.83422 0.012 0.988 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0237 0.83789 0.000 0.996 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.0661 0.83539 0.004 0.988 0.008
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0424 0.83600 0.000 0.992 0.008
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.83941 0.000 1.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.83941 0.000 1.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.6126 0.39513 0.000 0.400 0.600
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.4654 0.69619 0.792 0.000 0.208
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.76798 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.5061 0.59468 0.208 0.784 0.008
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.4452 0.70981 0.000 0.808 0.192
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5327 0.65494 0.728 0.000 0.272
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.5254 0.65227 0.736 0.000 0.264
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0747 0.76647 0.984 0.000 0.016
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 3 0.6252 0.31948 0.000 0.444 0.556
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.5968 0.53453 0.636 0.000 0.364
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.83941 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.1753 0.75914 0.952 0.000 0.048
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1031 0.76456 0.976 0.000 0.024
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0592 0.83375 0.000 0.988 0.012
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.76798 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.6955 0.34556 0.016 0.496 0.488
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.5178 0.65988 0.744 0.000 0.256
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0747 0.76647 0.984 0.000 0.016
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0237 0.76766 0.996 0.000 0.004
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 3 0.5678 0.44915 0.000 0.316 0.684
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.6244 -0.07882 0.560 0.000 0.440
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.83941 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.6291 -0.24681 0.000 0.468 0.532
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6600 0.23098 0.604 0.384 0.012
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.83941 0.000 1.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.4235 0.71633 0.824 0.000 0.176
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.83941 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.5650 0.59731 0.000 0.688 0.312
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.83941 0.000 1.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.6126 0.49874 0.000 0.600 0.400
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0237 0.76766 0.996 0.000 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0747 0.76647 0.984 0.000 0.016
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.5529 0.62014 0.704 0.000 0.296
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5431 0.67831 0.716 0.000 0.284
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4452 0.59875 0.808 0.000 0.192
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.1529 0.81959 0.000 0.960 0.040
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.6057 0.64451 0.044 0.760 0.196
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.1031 0.82653 0.024 0.976 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.7835 -0.15078 0.456 0.052 0.492
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4974 0.51961 0.764 0.000 0.236
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.83941 0.000 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.5560 0.48349 0.300 0.000 0.700
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.6140 0.48972 0.596 0.000 0.404
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.76798 1.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.83941 0.000 1.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 3 0.6299 0.24178 0.000 0.476 0.524
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 3 0.7992 0.52530 0.328 0.080 0.592
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3619 0.67704 0.864 0.000 0.136
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4399 0.73210 0.812 0.000 0.188
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.5529 0.49745 0.704 0.000 0.296
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1031 0.76456 0.976 0.000 0.024
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0000 0.83941 0.000 1.000 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.0592 0.54488 0.000 0.012 0.988
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0661 0.83540 0.008 0.988 0.004
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.5926 0.23239 0.000 0.644 0.356
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.5926 0.55309 0.000 0.644 0.356
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.6465 0.31441 0.232 0.044 0.724
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1031 0.76456 0.976 0.000 0.024
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0892 0.76562 0.980 0.000 0.020
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.5138 0.67256 0.748 0.000 0.252
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.0661 0.83592 0.008 0.988 0.004
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.3851 0.64129 0.860 0.136 0.004
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.6518 0.33748 0.512 0.004 0.484
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.8793 0.08962 0.452 0.436 0.112
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4931 0.67973 0.768 0.000 0.232
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.83941 0.000 1.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.1753 0.75468 0.952 0.000 0.048
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.83941 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.7001 0.47125 0.024 0.588 0.388
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 3 0.2165 0.54959 0.064 0.000 0.936
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.83941 0.000 1.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.83941 0.000 1.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.6416 0.24078 0.616 0.376 0.008
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.6305 0.37285 0.000 0.516 0.484
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0592 0.76687 0.988 0.000 0.012
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.2448 0.73686 0.924 0.000 0.076
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.5621 0.64438 0.692 0.000 0.308
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.7652 0.22588 0.444 0.044 0.512
#> 60A51C36-7423-4C84-8034-325DE57046BE 3 0.5363 0.50467 0.276 0.000 0.724
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.8762 0.44256 0.576 0.160 0.264
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.1964 0.75988 0.944 0.000 0.056
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.83941 0.000 1.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.1529 0.76524 0.960 0.000 0.040
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.6473 0.27557 0.016 0.652 0.332
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 2 0.8403 0.36537 0.088 0.512 0.400
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 3 0.8549 0.41966 0.100 0.384 0.516
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.6500 -0.29290 0.004 0.464 0.532
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 3 0.5465 0.53075 0.288 0.000 0.712
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.2448 0.78481 0.076 0.924 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.6095 0.45415 0.392 0.000 0.608
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.83941 0.000 1.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0592 0.76691 0.988 0.000 0.012
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.83941 0.000 1.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.5859 0.61083 0.656 0.000 0.344
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.2448 0.75707 0.924 0.000 0.076
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.1964 0.81276 0.000 0.944 0.056
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.76798 1.000 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.83941 0.000 1.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.83941 0.000 1.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.76798 1.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.3686 0.73480 0.860 0.000 0.140
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 3 0.7027 0.52640 0.044 0.296 0.660
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.5202 0.68407 0.772 0.008 0.220
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.6267 -0.12826 0.548 0.000 0.452
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.1163 0.82804 0.000 0.972 0.028
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.0237 0.83788 0.004 0.996 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.7860 0.52026 0.664 0.204 0.132
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0424 0.83600 0.000 0.992 0.008
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.6302 0.37957 0.000 0.520 0.480
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.2066 0.76090 0.940 0.000 0.060
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0000 0.76798 1.000 0.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.4291 0.63670 0.000 0.820 0.180
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3618 0.77378 0.012 0.884 0.104
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0000 0.83941 0.000 1.000 0.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0237 0.83789 0.000 0.996 0.004
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.0424 0.83592 0.000 0.992 0.008
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0747 0.76647 0.984 0.000 0.016
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.0237 0.83789 0.000 0.996 0.004
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 3 0.6274 0.35972 0.456 0.000 0.544
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0237 0.83789 0.000 0.996 0.004
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.6513 0.47134 0.592 0.008 0.400
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.5216 0.66129 0.740 0.000 0.260
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.5058 0.67020 0.756 0.000 0.244
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.8825 0.39980 0.532 0.132 0.336
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0747 0.76647 0.984 0.000 0.016
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 3 0.6291 0.32721 0.468 0.000 0.532
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.1860 0.75247 0.948 0.000 0.052
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 3 0.8162 0.46747 0.084 0.348 0.568
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#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.76798 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.83941 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.8450 0.03639 0.428 0.484 0.088
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0892 0.76707 0.980 0.000 0.020
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1211 0.805434 0.000 0.960 0.040 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.7340 0.430032 0.500 0.000 0.176 0.324
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5231 0.455336 0.000 0.296 0.028 0.676
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4941 0.270866 0.000 0.000 0.436 0.564
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1022 0.807905 0.000 0.968 0.032 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4996 -0.231403 0.484 0.000 0.000 0.516
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4522 0.519008 0.680 0.000 0.000 0.320
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.6033 0.467967 0.000 0.204 0.116 0.680
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.0188 0.552189 0.004 0.000 0.000 0.996
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.4925 -0.095253 0.428 0.000 0.000 0.572
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.812266 0.000 1.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4454 0.408357 0.308 0.000 0.000 0.692
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.3726 0.641583 0.000 0.788 0.212 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.812266 0.000 1.000 0.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.3982 0.629013 0.000 0.776 0.220 0.004
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0188 0.812363 0.000 0.996 0.004 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0188 0.811690 0.000 0.996 0.004 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1557 0.799111 0.000 0.944 0.056 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5648 0.458017 0.036 0.284 0.008 0.672
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.4999 -0.115723 0.508 0.000 0.492 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.7923 -0.358732 0.332 0.000 0.344 0.324
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.0469 0.810666 0.012 0.988 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.6219 0.393507 0.000 0.588 0.344 0.068
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4661 0.109996 0.652 0.000 0.348 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4543 0.428253 0.000 0.324 0.000 0.676
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4697 0.079045 0.644 0.000 0.356 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1211 0.805434 0.000 0.960 0.040 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.6669 0.465759 0.564 0.000 0.104 0.332
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0188 0.811983 0.000 0.996 0.000 0.004
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.7922 0.350536 0.340 0.000 0.340 0.320
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0921 0.397732 0.000 0.028 0.972 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4406 0.149727 0.700 0.000 0.300 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.6098 0.464066 0.000 0.200 0.124 0.676
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5000 0.277114 0.500 0.000 0.000 0.500
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0469 0.811837 0.000 0.988 0.012 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.7304 0.022179 0.000 0.164 0.492 0.344
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6170 0.046451 0.528 0.420 0.000 0.052
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0817 0.810059 0.000 0.976 0.024 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4999 0.126806 0.492 0.000 0.508 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0707 0.810695 0.000 0.980 0.020 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.7347 0.194158 0.228 0.528 0.244 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1118 0.799003 0.000 0.964 0.036 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.5847 0.039395 0.000 0.320 0.628 0.052
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4888 0.026749 0.588 0.000 0.412 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4998 0.558499 0.200 0.748 0.052 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.7296 0.297667 0.320 0.172 0.508 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.1302 0.796253 0.000 0.956 0.044 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.5938 0.138739 0.476 0.000 0.488 0.036
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.812266 0.000 1.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.6098 0.321894 0.316 0.000 0.068 0.616
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4967 -0.123581 0.548 0.000 0.452 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.7031 0.457050 0.536 0.000 0.140 0.324
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0188 0.812363 0.000 0.996 0.004 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4699 0.432724 0.000 0.320 0.004 0.676
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.2081 0.487986 0.084 0.000 0.000 0.916
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.7790 0.310193 0.492 0.016 0.168 0.324
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.3074 0.707740 0.000 0.848 0.152 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.6137 -0.169727 0.048 0.000 0.504 0.448
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.3801 0.631921 0.000 0.780 0.220 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.2999 0.730416 0.000 0.864 0.004 0.132
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.6442 -0.108019 0.000 0.440 0.492 0.068
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.5884 0.309787 0.328 0.000 0.620 0.052
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.4277 0.613681 0.000 0.720 0.280 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 2 0.9169 -0.093521 0.088 0.360 0.352 0.200
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.3569 0.328084 0.196 0.000 0.804 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.7453 0.315949 0.232 0.260 0.508 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4888 0.026749 0.588 0.000 0.412 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0188 0.812363 0.000 0.996 0.004 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.4720 0.518465 0.672 0.000 0.004 0.324
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1389 0.802673 0.000 0.952 0.048 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.7916 -0.265984 0.320 0.356 0.324 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.6084 0.434925 0.204 0.000 0.120 0.676
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.1557 0.799111 0.000 0.944 0.056 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0817 0.804870 0.000 0.976 0.024 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.7900 0.193893 0.064 0.508 0.344 0.084
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.6234 0.093906 0.000 0.348 0.584 0.068
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.8468 0.386708 0.396 0.024 0.280 0.300
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.4356 0.156435 0.708 0.000 0.292 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 3 0.7870 0.204812 0.324 0.000 0.388 0.288
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.5596 0.443155 0.236 0.000 0.068 0.696
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.6000 0.179686 0.452 0.040 0.508 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.7441 0.342493 0.516 0.008 0.152 0.324
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.812266 0.000 1.000 0.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.7398 -0.075195 0.324 0.000 0.492 0.184
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.5151 0.028291 0.000 0.532 0.004 0.464
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.3427 0.398708 0.112 0.028 0.860 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.3164 0.551519 0.000 0.064 0.052 0.884
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.7693 0.330516 0.224 0.052 0.592 0.132
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.2011 0.546005 0.000 0.000 0.080 0.920
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.0000 0.812266 0.000 1.000 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.0592 0.553141 0.016 0.000 0.000 0.984
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0469 0.809590 0.000 0.988 0.012 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.1792 0.792766 0.000 0.932 0.068 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.4761 0.084854 0.628 0.000 0.372 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.4989 -0.081121 0.528 0.000 0.472 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.3837 0.633063 0.000 0.776 0.224 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.5090 0.515703 0.660 0.000 0.016 0.324
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.3074 0.726155 0.000 0.848 0.152 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0592 0.808115 0.000 0.984 0.016 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.6374 0.491191 0.592 0.000 0.084 0.324
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.4776 0.080141 0.624 0.000 0.376 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.5314 0.409841 0.296 0.024 0.004 0.676
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 3 0.5000 0.120661 0.496 0.000 0.504 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 4 0.4992 -0.190462 0.476 0.000 0.000 0.524
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.4776 0.411404 0.000 0.624 0.376 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.2222 0.792188 0.000 0.924 0.060 0.016
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.6811 -0.072168 0.588 0.144 0.268 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0469 0.809694 0.000 0.988 0.012 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 3 0.6844 -0.056086 0.000 0.104 0.500 0.396
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.5000 0.120110 0.496 0.000 0.504 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.7264 0.435945 0.512 0.000 0.168 0.320
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0779 0.810395 0.000 0.980 0.004 0.016
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.4655 0.533588 0.000 0.684 0.312 0.004
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.1211 0.805434 0.000 0.960 0.040 0.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.1211 0.796591 0.000 0.960 0.040 0.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.2408 0.794079 0.000 0.920 0.044 0.036
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.3088 0.725976 0.000 0.864 0.128 0.008
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.3143 0.503289 0.024 0.000 0.100 0.876
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.1389 0.792011 0.000 0.952 0.048 0.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 3 0.3873 0.319153 0.228 0.000 0.772 0.000
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.4713 0.098008 0.640 0.000 0.360 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.4624 0.116840 0.660 0.000 0.340 0.000
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 3 0.7219 0.334720 0.364 0.148 0.488 0.000
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 4 0.1637 0.510046 0.060 0.000 0.000 0.940
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 4 0.5250 0.528236 0.080 0.176 0.000 0.744
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.2973 0.715100 0.000 0.856 0.144 0.000
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.1557 0.799111 0.000 0.944 0.056 0.000
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 3 0.8010 0.137854 0.352 0.012 0.428 0.208
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.4839 0.606932 0.000 0.756 0.044 0.200
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 3 0.8610 0.305130 0.252 0.092 0.508 0.148
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 1 0.5859 -0.315848 0.496 0.000 0.032 0.472
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#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0707 0.810720 0.000 0.980 0.020 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.3975 0.605825 0.000 0.760 0.240 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.5113 0.406631 0.292 0.000 0.024 0.684
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5717 0.477553 0.632 0.044 0.000 0.324
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4283 0.609216 0.000 0.740 0.256 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0592 0.559650 0.000 0.016 0.000 0.984
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.4790 0.074672 0.620 0.000 0.380 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.1557 0.799111 0.000 0.944 0.056 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4999 0.126806 0.492 0.000 0.508 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0188 0.811690 0.000 0.996 0.004 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4543 0.519100 0.676 0.000 0.000 0.324
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.4535 0.466142 0.240 0.000 0.016 0.744
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5125 0.062041 0.604 0.000 0.388 0.008
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5882 0.092459 0.608 0.000 0.344 0.048
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.7424 0.267180 0.364 0.116 0.504 0.016
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.9523 -0.198468 0.212 0.128 0.364 0.296
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0592 0.808115 0.000 0.984 0.016 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.7425 0.308666 0.280 0.212 0.508 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.9003 -0.303253 0.272 0.056 0.348 0.324
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2732 0.73777 0.000 0.840 0.160 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.2482 0.82656 0.892 0.000 0.024 0.000 0.084
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0162 0.76421 0.000 0.000 0.004 0.996 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.1478 0.87271 0.064 0.000 0.000 0.000 0.936
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 3 0.4015 0.31558 0.000 0.000 0.652 0.348 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2424 0.75768 0.000 0.868 0.132 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.3949 0.42149 0.668 0.000 0.000 0.332 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.1544 0.87068 0.068 0.000 0.000 0.000 0.932
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0162 0.76421 0.000 0.000 0.004 0.996 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2890 0.70988 0.160 0.000 0.004 0.836 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3636 0.57782 0.728 0.000 0.000 0.272 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1608 0.78312 0.000 0.928 0.072 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2629 0.71915 0.000 0.000 0.004 0.860 0.136
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.2661 0.73973 0.000 0.896 0.044 0.008 0.052
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0865 0.78852 0.000 0.972 0.024 0.004 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.5439 0.58546 0.000 0.696 0.044 0.204 0.056
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2331 0.78331 0.000 0.900 0.080 0.020 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0794 0.78886 0.000 0.972 0.028 0.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.3913 0.53902 0.000 0.676 0.324 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.0000 0.76431 0.000 0.000 0.000 1.000 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.0000 0.87420 0.000 0.000 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.6071 0.51462 0.608 0.072 0.040 0.000 0.280
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.1493 0.78716 0.024 0.948 0.028 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 3 0.3353 0.67856 0.000 0.196 0.796 0.008 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.1638 0.87187 0.064 0.000 0.004 0.000 0.932
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.1270 0.87758 0.052 0.000 0.000 0.000 0.948
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.0162 0.76354 0.000 0.004 0.000 0.996 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.1725 0.87539 0.044 0.000 0.020 0.000 0.936
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3143 0.69891 0.000 0.796 0.204 0.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6614 0.12191 0.416 0.000 0.012 0.424 0.148
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1668 0.78655 0.000 0.940 0.028 0.032 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.5693 0.40248 0.572 0.028 0.040 0.000 0.360
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2424 0.72724 0.000 0.000 0.868 0.000 0.132
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.1845 0.87222 0.056 0.000 0.016 0.000 0.928
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0912 0.75969 0.000 0.012 0.016 0.972 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.2997 0.74991 0.840 0.000 0.000 0.148 0.012
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2179 0.76793 0.000 0.888 0.112 0.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 3 0.1484 0.78114 0.000 0.008 0.944 0.048 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.4305 0.13617 0.488 0.512 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2471 0.75537 0.000 0.864 0.136 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.0703 0.86783 0.000 0.000 0.024 0.000 0.976
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2280 0.76389 0.000 0.880 0.120 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 3 0.4424 0.63496 0.000 0.224 0.728 0.000 0.048
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0404 0.77990 0.000 0.988 0.012 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.2127 0.72474 0.000 0.108 0.892 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.0609 0.87973 0.020 0.000 0.000 0.000 0.980
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.1478 0.87271 0.064 0.000 0.000 0.000 0.936
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.6432 0.28995 0.000 0.492 0.304 0.000 0.204
#> 97A49141-0141-4583-B366-A4720270D6F2 5 0.5217 0.38233 0.000 0.364 0.044 0.004 0.588
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0880 0.78871 0.000 0.968 0.032 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.0290 0.87424 0.000 0.000 0.000 0.008 0.992
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0963 0.78797 0.000 0.964 0.036 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.3715 0.60497 0.000 0.000 0.004 0.736 0.260
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.2370 0.85898 0.040 0.000 0.056 0.000 0.904
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.1877 0.84892 0.924 0.000 0.012 0.000 0.064
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1792 0.78023 0.000 0.916 0.084 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.0162 0.76421 0.000 0.000 0.004 0.996 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.0794 0.76295 0.028 0.000 0.000 0.972 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.1544 0.87068 0.068 0.000 0.000 0.000 0.932
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.2446 0.74087 0.000 0.900 0.044 0.000 0.056
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 3 0.1952 0.74796 0.004 0.000 0.912 0.084 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.4755 0.65614 0.000 0.768 0.044 0.136 0.052
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.5979 0.45474 0.000 0.588 0.220 0.192 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 3 0.1205 0.79871 0.000 0.040 0.956 0.004 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.2824 0.83323 0.000 0.000 0.096 0.032 0.872
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.1571 0.87391 0.060 0.000 0.004 0.000 0.936
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.3176 0.71909 0.000 0.856 0.080 0.000 0.064
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 2 0.5994 0.50675 0.212 0.660 0.044 0.004 0.080
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.4182 0.38002 0.000 0.000 0.400 0.000 0.600
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 5 0.5091 0.46550 0.000 0.328 0.044 0.004 0.624
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.0510 0.87896 0.016 0.000 0.000 0.000 0.984
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1892 0.78225 0.000 0.916 0.080 0.004 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.3143 0.69929 0.000 0.796 0.204 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 3 0.4440 0.14190 0.000 0.004 0.528 0.000 0.468
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.3388 0.67544 0.000 0.000 0.008 0.792 0.200
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.3796 0.57659 0.000 0.700 0.300 0.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0404 0.77990 0.000 0.988 0.012 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.5705 0.56574 0.000 0.676 0.044 0.208 0.072
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.1195 0.79630 0.000 0.012 0.960 0.000 0.028
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.7015 0.17380 0.480 0.380 0.040 0.020 0.080
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.1830 0.86884 0.068 0.000 0.008 0.000 0.924
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.4387 0.40753 0.000 0.000 0.012 0.640 0.348
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.3266 0.67620 0.000 0.000 0.004 0.796 0.200
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0000 0.87420 0.000 0.000 0.000 0.000 1.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.1121 0.78746 0.000 0.956 0.044 0.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 5 0.4937 0.65697 0.168 0.044 0.044 0.000 0.744
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.4549 0.06353 0.000 0.464 0.008 0.528 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.4294 0.18487 0.000 0.000 0.468 0.000 0.532
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.1356 0.74993 0.000 0.028 0.012 0.956 0.004
#> 5D663B98-8416-4305-A891-111B7A4DC40B 4 0.7940 0.28746 0.000 0.156 0.140 0.440 0.264
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.3266 0.67577 0.200 0.000 0.004 0.796 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.1792 0.78077 0.000 0.916 0.084 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.2513 0.73324 0.116 0.000 0.008 0.876 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0794 0.78822 0.000 0.972 0.028 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.4291 0.18180 0.000 0.536 0.464 0.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.1121 0.87968 0.044 0.000 0.000 0.000 0.956
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 5 0.0609 0.86930 0.000 0.000 0.020 0.000 0.980
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.3424 0.69420 0.000 0.760 0.240 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0162 0.89070 0.996 0.000 0.004 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 3 0.4235 0.21695 0.000 0.424 0.576 0.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0404 0.78650 0.000 0.988 0.012 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.1502 0.85636 0.940 0.000 0.004 0.000 0.056
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.1197 0.87881 0.048 0.000 0.000 0.000 0.952
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.0000 0.76431 0.000 0.000 0.000 1.000 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 5 0.0000 0.87420 0.000 0.000 0.000 0.000 1.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.1043 0.86801 0.960 0.000 0.000 0.040 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 3 0.4304 0.17419 0.000 0.484 0.516 0.000 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.5820 0.26153 0.100 0.524 0.376 0.000 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 5 0.3685 0.82640 0.052 0.052 0.048 0.000 0.848
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0566 0.78619 0.000 0.984 0.012 0.004 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 3 0.1608 0.76049 0.000 0.000 0.928 0.072 0.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 5 0.2151 0.84326 0.000 0.016 0.040 0.020 0.924
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.2233 0.83509 0.904 0.000 0.016 0.000 0.080
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#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1851 0.77874 0.000 0.912 0.088 0.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0404 0.87803 0.012 0.000 0.000 0.000 0.988
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.1478 0.78470 0.000 0.936 0.064 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.1121 0.79806 0.000 0.044 0.956 0.000 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1357 0.85905 0.948 0.004 0.000 0.048 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.1571 0.77825 0.000 0.000 0.936 0.004 0.060
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.1502 0.75434 0.000 0.000 0.004 0.940 0.056
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4294 0.17090 0.000 0.532 0.468 0.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0693 0.77846 0.000 0.980 0.012 0.008 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 3 0.3480 0.61731 0.000 0.248 0.752 0.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.1522 0.85181 0.000 0.012 0.044 0.000 0.944
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.1851 0.85883 0.088 0.000 0.000 0.000 0.912
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.5816 0.19495 0.380 0.552 0.040 0.004 0.024
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.3388 0.67513 0.200 0.000 0.008 0.792 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3353 0.67920 0.000 0.000 0.008 0.796 0.196
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5345 0.57541 0.000 0.668 0.136 0.000 0.196
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0290 0.78569 0.000 0.992 0.008 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.2139 0.79140 0.000 0.052 0.916 0.032 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 3 0.1121 0.79806 0.000 0.044 0.956 0.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.8604 0.09818 0.364 0.312 0.044 0.208 0.072
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.5554 0.27266 0.000 0.360 0.568 0.004 0.068
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.2973 0.82014 0.884 0.052 0.020 0.000 0.044
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.3301 0.81696 0.000 0.000 0.072 0.080 0.848
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0000 0.87420 0.000 0.000 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 3 0.5572 0.47441 0.004 0.000 0.612 0.088 0.296
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2516 0.75263 0.000 0.860 0.140 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.1478 0.85915 0.000 0.000 0.064 0.000 0.936
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2891 0.78198 0.176 0.000 0.000 0.000 0.824
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.0000 0.76431 0.000 0.000 0.000 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.4030 0.52880 0.352 0.000 0.000 0.000 0.648
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1270 0.78649 0.000 0.948 0.052 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.1478 0.87417 0.064 0.000 0.000 0.000 0.936
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.0000 0.76431 0.000 0.000 0.000 1.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 3 0.1270 0.79568 0.000 0.052 0.948 0.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.3816 0.52835 0.000 0.000 0.000 0.304 0.696
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2471 0.75515 0.000 0.864 0.136 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.5225 0.62034 0.000 0.728 0.044 0.164 0.064
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.2488 0.72628 0.000 0.000 0.004 0.872 0.124
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0609 0.87916 0.980 0.020 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 3 0.4030 0.41104 0.000 0.352 0.648 0.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0000 0.76431 0.000 0.000 0.000 1.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0963 0.88040 0.036 0.000 0.000 0.000 0.964
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3999 0.50168 0.000 0.656 0.344 0.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.1522 0.85181 0.000 0.012 0.044 0.000 0.944
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1168 0.78919 0.000 0.960 0.032 0.008 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.89225 1.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0162 0.76421 0.000 0.000 0.004 0.996 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.0740 0.87743 0.008 0.000 0.004 0.008 0.980
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.2286 0.82610 0.000 0.000 0.004 0.108 0.888
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.6743 0.43709 0.000 0.204 0.044 0.176 0.576
#> AB642383-1611-4355-B03C-08D42FF4676C 2 0.6730 0.12453 0.372 0.496 0.044 0.004 0.084
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.78366 0.000 1.000 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.4723 0.64852 0.000 0.132 0.000 0.132 0.736
#> EE118E80-F125-4655-8845-56A9CBBA0680 2 0.8531 0.07587 0.300 0.400 0.044 0.176 0.080
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0858 0.86600 0.000 0.968 0.028 0.000 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0865 0.91992 0.964 0.000 0.036 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0146 0.76120 0.000 0.000 0.004 0.996 0.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0146 0.80890 0.000 0.000 0.004 0.000 0.996 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0363 0.81704 0.000 0.000 0.000 0.012 0.000 0.988
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0291 0.86483 0.000 0.992 0.004 0.000 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.5063 0.55935 0.284 0.000 0.112 0.604 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.3136 0.75828 0.000 0.000 0.228 0.000 0.768 0.004
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1036 0.91546 0.964 0.024 0.008 0.000 0.004 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0146 0.76196 0.000 0.000 0.004 0.996 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2750 0.74981 0.020 0.000 0.136 0.844 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3136 0.68855 0.768 0.000 0.004 0.228 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0363 0.86572 0.000 0.988 0.012 0.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2872 0.74170 0.000 0.000 0.140 0.836 0.024 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.3360 0.57534 0.000 0.264 0.732 0.004 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1910 0.84373 0.000 0.892 0.108 0.000 0.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4431 0.64366 0.000 0.096 0.704 0.200 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1471 0.86208 0.000 0.932 0.064 0.004 0.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3290 0.67628 0.000 0.776 0.016 0.000 0.208 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1003 0.85524 0.000 0.964 0.016 0.000 0.020 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.0458 0.75704 0.000 0.000 0.016 0.984 0.000 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.3489 0.71710 0.000 0.000 0.288 0.000 0.708 0.004
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3955 0.28041 0.436 0.000 0.560 0.000 0.004 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.1349 0.86284 0.004 0.940 0.056 0.000 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.3552 0.72505 0.000 0.084 0.116 0.000 0.000 0.800
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0405 0.80586 0.000 0.004 0.008 0.000 0.988 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0260 0.80824 0.000 0.000 0.008 0.000 0.992 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0146 0.94160 0.996 0.000 0.000 0.000 0.000 0.004
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.0603 0.75629 0.000 0.004 0.016 0.980 0.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0363 0.80553 0.000 0.000 0.012 0.000 0.988 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1082 0.86544 0.000 0.956 0.040 0.000 0.000 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.6024 0.13121 0.352 0.000 0.452 0.188 0.008 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1225 0.86533 0.000 0.952 0.036 0.012 0.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.3807 0.41394 0.368 0.000 0.628 0.000 0.004 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 6 0.0146 0.82258 0.000 0.004 0.000 0.000 0.000 0.996
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0260 0.80655 0.000 0.000 0.008 0.000 0.992 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.1225 0.75799 0.000 0.036 0.012 0.952 0.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.5501 0.49908 0.344 0.004 0.052 0.564 0.036 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.1075 0.86422 0.000 0.952 0.048 0.000 0.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.0146 0.82258 0.000 0.004 0.000 0.000 0.000 0.996
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.4306 0.45420 0.344 0.624 0.032 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0291 0.86320 0.000 0.992 0.004 0.000 0.004 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.3995 0.39655 0.000 0.000 0.480 0.000 0.516 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0146 0.86502 0.000 0.996 0.004 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.5830 0.47702 0.000 0.320 0.016 0.000 0.140 0.524
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.2135 0.82905 0.000 0.872 0.128 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 6 0.0260 0.81880 0.000 0.000 0.008 0.000 0.000 0.992
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1700 0.80647 0.000 0.000 0.080 0.000 0.916 0.004
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.2135 0.79766 0.000 0.000 0.128 0.000 0.872 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.3189 0.67615 0.000 0.760 0.004 0.000 0.236 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4176 0.64404 0.000 0.068 0.720 0.000 0.212 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0458 0.86467 0.000 0.984 0.016 0.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.3468 0.72079 0.000 0.000 0.284 0.000 0.712 0.004
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.1910 0.84501 0.000 0.892 0.108 0.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.4367 0.66422 0.000 0.000 0.220 0.708 0.068 0.004
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0405 0.80586 0.000 0.004 0.008 0.000 0.988 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0363 0.93741 0.988 0.000 0.012 0.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2053 0.84725 0.000 0.888 0.108 0.000 0.000 0.004
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.0146 0.76095 0.000 0.004 0.000 0.996 0.000 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.2805 0.67320 0.160 0.000 0.012 0.828 0.000 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.3136 0.75828 0.000 0.000 0.228 0.000 0.768 0.004
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.3758 0.55491 0.000 0.324 0.668 0.000 0.008 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 6 0.0405 0.81819 0.004 0.000 0.000 0.008 0.000 0.988
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.4065 0.61838 0.000 0.220 0.724 0.056 0.000 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.3596 0.65007 0.008 0.740 0.008 0.244 0.000 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 6 0.1444 0.78659 0.000 0.072 0.000 0.000 0.000 0.928
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 6 0.4400 0.54992 0.000 0.000 0.248 0.000 0.068 0.684
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0146 0.94160 0.996 0.000 0.000 0.000 0.000 0.004
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0146 0.80776 0.000 0.000 0.004 0.000 0.996 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4861 0.60306 0.000 0.244 0.660 0.000 0.008 0.088
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.4258 0.63263 0.204 0.068 0.724 0.000 0.004 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.4294 0.31912 0.000 0.000 0.020 0.000 0.552 0.428
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3835 0.66969 0.000 0.060 0.772 0.004 0.164 0.000
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#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1387 0.88505 0.932 0.000 0.000 0.068 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.0146 0.82258 0.000 0.004 0.000 0.000 0.000 0.996
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.2923 0.74676 0.000 0.000 0.100 0.848 0.052 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.3211 0.80278 0.000 0.824 0.056 0.000 0.000 0.120
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#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.2482 0.81367 0.000 0.848 0.148 0.004 0.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.4199 0.36016 0.000 0.416 0.016 0.000 0.000 0.568
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.3405 0.30620 0.000 0.000 0.724 0.000 0.272 0.004
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#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.1219 0.81411 0.000 0.000 0.048 0.000 0.948 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.4783 0.30405 0.428 0.052 0.520 0.000 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.3156 0.69793 0.180 0.000 0.020 0.800 0.000 0.000
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#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.2563 0.78853 0.000 0.044 0.028 0.036 0.000 0.892
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#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4111 0.22776 0.000 0.004 0.536 0.000 0.004 0.456
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.0458 0.93521 0.984 0.000 0.016 0.000 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.6111 0.22669 0.000 0.000 0.232 0.004 0.404 0.360
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0458 0.80952 0.000 0.000 0.016 0.000 0.984 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.4300 0.64968 0.000 0.028 0.012 0.176 0.756 0.028
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0405 0.86386 0.000 0.988 0.008 0.000 0.000 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0964 0.81040 0.000 0.012 0.016 0.000 0.968 0.004
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.0713 0.81397 0.000 0.000 0.028 0.000 0.972 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.2664 0.73265 0.000 0.000 0.184 0.816 0.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.3640 0.75537 0.028 0.000 0.204 0.000 0.764 0.004
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2362 0.83066 0.000 0.860 0.136 0.000 0.000 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.4702 0.67903 0.076 0.000 0.260 0.000 0.660 0.004
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.0260 0.75947 0.000 0.000 0.008 0.992 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.0146 0.82258 0.000 0.004 0.000 0.000 0.000 0.996
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.3440 0.69638 0.000 0.000 0.028 0.196 0.776 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0520 0.86374 0.000 0.984 0.008 0.000 0.000 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4124 0.66007 0.000 0.120 0.748 0.132 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.4013 0.68370 0.000 0.000 0.228 0.728 0.040 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2146 0.82793 0.000 0.908 0.024 0.000 0.008 0.060
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0146 0.76045 0.000 0.000 0.004 0.996 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.2994 0.76993 0.000 0.000 0.208 0.000 0.788 0.004
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.1528 0.86477 0.000 0.936 0.048 0.000 0.000 0.016
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2994 0.70388 0.788 0.000 0.208 0.000 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3684 0.38548 0.000 0.000 0.628 0.000 0.372 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.3223 0.80566 0.008 0.836 0.052 0.104 0.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.94322 1.000 0.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2260 0.74800 0.000 0.000 0.140 0.860 0.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3656 0.73585 0.000 0.000 0.256 0.012 0.728 0.004
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.5933 0.42675 0.000 0.000 0.252 0.248 0.496 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.1555 0.62019 0.000 0.004 0.932 0.004 0.060 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4105 0.61238 0.236 0.036 0.720 0.000 0.008 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0713 0.86400 0.000 0.972 0.028 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.4423 0.58932 0.000 0.032 0.176 0.052 0.740 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4225 0.64574 0.124 0.004 0.748 0.124 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.231 0.636 0.824 0.4468 0.513 0.513
#> 3 3 0.180 0.415 0.658 0.3245 0.727 0.543
#> 4 4 0.250 0.404 0.615 0.1355 0.659 0.372
#> 5 5 0.312 0.446 0.583 0.0733 0.878 0.673
#> 6 6 0.390 0.421 0.566 0.0572 0.844 0.516
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1184 0.80734 0.016 0.984
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0672 0.73851 0.992 0.008
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.2236 0.80989 0.036 0.964
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0672 0.73876 0.992 0.008
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1184 0.80805 0.016 0.984
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1184 0.80734 0.016 0.984
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.6343 0.73388 0.840 0.160
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1633 0.74243 0.976 0.024
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4939 0.74647 0.892 0.108
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.9608 0.48190 0.616 0.384
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.2778 0.80963 0.048 0.952
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.5629 0.77664 0.132 0.868
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.9209 0.50455 0.336 0.664
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0938 0.80577 0.012 0.988
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.7815 0.68356 0.232 0.768
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.9988 0.16374 0.520 0.480
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.79966 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.9988 0.16374 0.520 0.480
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.79966 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.9881 0.18646 0.436 0.564
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1843 0.81035 0.028 0.972
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.5178 0.79154 0.116 0.884
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.7528 0.68636 0.784 0.216
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3584 0.74764 0.932 0.068
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.8499 0.61294 0.276 0.724
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.79966 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.9323 0.55718 0.652 0.348
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0376 0.73673 0.996 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0672 0.73829 0.992 0.008
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.3431 0.80715 0.064 0.936
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0672 0.73844 0.992 0.008
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.79966 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 1.0000 0.11339 0.504 0.496
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6973 0.72518 0.812 0.188
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0672 0.80410 0.008 0.992
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0938 0.74024 0.988 0.012
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.7056 0.70099 0.808 0.192
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.8955 0.61219 0.688 0.312
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.8813 0.62710 0.700 0.300
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0672 0.73829 0.992 0.008
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.5059 0.78160 0.112 0.888
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.9896 0.13792 0.440 0.560
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.79966 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0938 0.80634 0.012 0.988
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.9732 0.44542 0.596 0.404
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1843 0.80980 0.028 0.972
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.3114 0.74891 0.944 0.056
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.1184 0.80734 0.016 0.984
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1633 0.80819 0.024 0.976
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1184 0.80734 0.016 0.984
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.9944 0.08267 0.456 0.544
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.9686 0.45469 0.604 0.396
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4022 0.74701 0.920 0.080
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0938 0.74008 0.988 0.012
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.3879 0.74968 0.924 0.076
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.8207 0.66969 0.744 0.256
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.6801 0.74255 0.180 0.820
#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.9988 0.16374 0.520 0.480
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.2236 0.81058 0.036 0.964
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.9661 0.36761 0.392 0.608
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.8207 0.67438 0.744 0.256
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0376 0.80211 0.004 0.996
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.9866 0.35874 0.568 0.432
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.2423 0.74825 0.960 0.040
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.3584 0.74830 0.932 0.068
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0376 0.80211 0.004 0.996
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.1843 0.80957 0.028 0.972
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.3431 0.80850 0.064 0.936
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.8207 0.66969 0.744 0.256
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.1633 0.74243 0.976 0.024
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.9661 0.46326 0.608 0.392
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.5629 0.74244 0.868 0.132
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.9000 0.53711 0.316 0.684
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.9988 -0.04530 0.480 0.520
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.9323 0.47585 0.348 0.652
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.2236 0.80956 0.036 0.964
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.1843 0.80919 0.028 0.972
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9661 0.36171 0.392 0.608
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 2 0.9970 0.06493 0.468 0.532
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4562 0.74610 0.904 0.096
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.5408 0.74897 0.876 0.124
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.9996 0.13287 0.512 0.488
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.1843 0.73900 0.972 0.028
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.8713 0.63153 0.708 0.292
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.1184 0.74156 0.984 0.016
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.5842 0.74340 0.860 0.140
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0376 0.80211 0.004 0.996
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.9286 0.50152 0.344 0.656
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1184 0.80734 0.016 0.984
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.3879 0.75104 0.924 0.076
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.5408 0.77390 0.124 0.876
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.2043 0.81074 0.032 0.968
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0938 0.80599 0.012 0.988
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.9286 0.49679 0.344 0.656
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.8763 0.57274 0.296 0.704
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.9209 0.57309 0.664 0.336
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.9129 0.58913 0.672 0.328
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.9323 0.55718 0.652 0.348
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.8267 0.65598 0.260 0.740
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.9970 0.23995 0.532 0.468
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.9850 0.35078 0.572 0.428
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.9635 0.47194 0.612 0.388
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.4022 0.80212 0.080 0.920
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.4815 0.74082 0.896 0.104
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.4815 0.79307 0.104 0.896
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.6247 0.71886 0.844 0.156
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.3114 0.81014 0.056 0.944
#> 5D663B98-8416-4305-A891-111B7A4DC40B 1 1.0000 0.07284 0.500 0.500
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 2 0.9552 0.40001 0.376 0.624
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.2778 0.81021 0.048 0.952
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.8555 0.63181 0.280 0.720
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.1843 0.80866 0.028 0.972
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.3879 0.75098 0.924 0.076
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.79966 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.9775 0.36989 0.588 0.412
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.73416 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.1184 0.80734 0.016 0.984
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.73416 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.79966 0.000 1.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.3733 0.80567 0.072 0.928
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.73416 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.1633 0.74348 0.976 0.024
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.8661 0.60586 0.288 0.712
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.9580 0.49059 0.620 0.380
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.9977 0.22647 0.528 0.472
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0376 0.80211 0.004 0.996
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.7745 0.67524 0.228 0.772
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.9996 0.14664 0.512 0.488
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.4562 0.79878 0.096 0.904
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.2043 0.81183 0.032 0.968
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.0938 0.74024 0.988 0.012
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0672 0.73851 0.992 0.008
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.2423 0.80990 0.040 0.960
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3733 0.80203 0.072 0.928
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0000 0.79966 0.000 1.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.1184 0.80734 0.016 0.984
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.2778 0.80937 0.048 0.952
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.4562 0.74663 0.904 0.096
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.4022 0.80212 0.080 0.920
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.8016 0.68295 0.244 0.756
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0000 0.79966 0.000 1.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.9460 0.50084 0.636 0.364
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0000 0.73416 1.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.5842 0.74400 0.860 0.140
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 2 0.9996 -0.03416 0.488 0.512
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.0672 0.73829 0.992 0.008
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 2 0.9286 0.47603 0.344 0.656
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.9286 0.57105 0.656 0.344
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 2 0.6343 0.76213 0.160 0.840
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.9248 0.56819 0.660 0.340
#> 5206C997-CCAE-463E-9902-C60ADA86E632 2 0.9209 0.49182 0.336 0.664
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0672 0.80407 0.008 0.992
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 2 0.9775 0.25679 0.412 0.588
#> 4A070C05-E214-46D3-B4E1-2B164E9D71FC 2 0.3431 0.80715 0.064 0.936
#> 2D1961B5-4758-40B4-9775-97286EC99AC3 2 0.9881 0.21423 0.436 0.564
#> BF21E3C8-662D-4651-BDC8-311DD6012EB0 2 0.8327 0.62908 0.264 0.736
#> 1A785678-EE7B-4E75-9C14-C3EFCC25488E 2 0.0000 0.79966 0.000 1.000
#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.0938 0.80606 0.012 0.988
#> EF3D2659-7C4A-4003-A1B1-9A47A5388034 1 0.6048 0.73188 0.852 0.148
#> 09A7BAD6-4AB2-428A-B96C-BC3C298C4496 2 0.9954 0.11041 0.460 0.540
#> 02D46E43-75BB-4A0A-8A02-403C7FBFB112 2 0.2423 0.80990 0.040 0.960
#> 450A8523-03F4-4EF5-BA7A-E8E5329BE218 1 0.7299 0.71148 0.796 0.204
#> 6EA613FC-FDDD-4D89-B73E-FB2357D12651 2 0.3114 0.80918 0.056 0.944
#> 9B979DBE-6BAE-4631-A37D-3F57CD81D98E 2 0.1184 0.80734 0.016 0.984
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#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.1184 0.80734 0.016 0.984
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.1184 0.80734 0.016 0.984
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.1184 0.80790 0.016 0.984
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.0000 0.79966 0.000 1.000
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.1843 0.74515 0.972 0.028
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.7139 0.72534 0.196 0.804
#> 4C838D35-B667-46DA-836F-068453D254DA 2 0.8081 0.65942 0.248 0.752
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0938 0.80092 0.012 0.988
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0672 0.80427 0.008 0.992
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.0000 0.79966 0.000 1.000
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.0938 0.74024 0.988 0.012
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 1 0.7139 0.71598 0.804 0.196
#> 976924B0-5799-4AC9-804F-78C8568037CA 1 0.9866 0.33396 0.568 0.432
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.6712 0.71057 0.824 0.176
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.6048 0.73655 0.852 0.148
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.1414 0.74238 0.980 0.020
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0672 0.73879 0.992 0.008
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0000 0.73416 1.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.8207 0.65872 0.256 0.744
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.2236 0.81058 0.036 0.964
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.6801 0.74255 0.180 0.820
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 2 0.8267 0.65019 0.260 0.740
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.5294 0.73793 0.880 0.120
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 2 0.9170 0.50756 0.332 0.668
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 2 0.9909 0.12064 0.444 0.556
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.8955 0.54520 0.312 0.688
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.2603 0.81142 0.044 0.956
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 2 0.9963 0.05442 0.464 0.536
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.6343 0.73815 0.840 0.160
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.5408 0.74816 0.876 0.124
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.8081 0.66529 0.248 0.752
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.4022 0.80212 0.080 0.920
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.0376 0.80211 0.004 0.996
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.3114 0.81035 0.056 0.944
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.1843 0.74506 0.972 0.028
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.73416 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.5408 0.74725 0.876 0.124
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.2603 0.80982 0.044 0.956
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.9954 0.28085 0.540 0.460
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.1184 0.80734 0.016 0.984
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.1843 0.81035 0.028 0.972
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.79966 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.7674 0.70548 0.224 0.776
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.9795 0.26543 0.416 0.584
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.73416 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.79966 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.8207 0.66969 0.744 0.256
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.9775 0.36989 0.588 0.412
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.1414 0.74379 0.980 0.020
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.5178 0.78899 0.116 0.884
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.9933 0.29603 0.548 0.452
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.9686 0.45469 0.604 0.396
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.9710 0.32052 0.400 0.600
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.73416 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.1843 0.80900 0.028 0.972
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.2603 0.80982 0.044 0.956
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.73416 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.3879 0.74669 0.924 0.076
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.9993 0.00965 0.484 0.516
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.2778 0.81144 0.048 0.952
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.9881 0.21893 0.436 0.564
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.8016 0.67838 0.244 0.756
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.9993 0.00965 0.484 0.516
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.1184 0.80734 0.016 0.984
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.4562 0.79986 0.096 0.904
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.9427 0.45008 0.360 0.640
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9998 0.10302 0.508 0.492
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.9522 0.51243 0.628 0.372
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.7453 0.71548 0.212 0.788
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.8081 0.64353 0.752 0.248
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.5737 0.77073 0.136 0.864
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.9170 0.50101 0.332 0.668
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0376 0.80211 0.004 0.996
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.9323 0.55718 0.652 0.348
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.6973 0.73995 0.188 0.812
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.5294 0.74508 0.880 0.120
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.6801 0.74255 0.180 0.820
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1633 0.80819 0.024 0.976
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.3114 0.80873 0.056 0.944
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.9996 0.14402 0.512 0.488
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 1 0.9988 0.16374 0.520 0.480
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.9909 0.33500 0.556 0.444
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.9983 0.19042 0.524 0.476
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.79966 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.79966 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0938 0.74024 0.988 0.012
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2043 0.80980 0.032 0.968
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.9988 0.16374 0.520 0.480
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.9933 0.29777 0.548 0.452
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.79966 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.6623 0.73106 0.828 0.172
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2043 0.81170 0.032 0.968
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.8713 0.57530 0.292 0.708
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.5408 0.74495 0.876 0.124
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.9963 0.26435 0.536 0.464
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.7883 0.69133 0.236 0.764
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.7745 0.70053 0.228 0.772
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.79966 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1414 0.74375 0.980 0.020
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3879 0.80526 0.076 0.924
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.79966 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.9896 0.21211 0.440 0.560
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.9286 0.56444 0.656 0.344
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.73416 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8327 0.64892 0.264 0.736
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.2423 0.80990 0.040 0.960
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.7528 0.70076 0.216 0.784
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.3114 0.81115 0.056 0.944
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.4161 0.80344 0.084 0.916
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.2236 0.80892 0.036 0.964
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.79966 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0938 0.74024 0.988 0.012
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.9944 0.08267 0.456 0.544
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.6973 0.73642 0.188 0.812
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.9686 0.34879 0.396 0.604
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.73416 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7674 0.68750 0.224 0.776
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1414 0.80853 0.020 0.980
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.5408 0.74495 0.876 0.124
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.8813 0.61055 0.700 0.300
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5842 0.74422 0.860 0.140
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9970 0.06815 0.468 0.532
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5842 0.74116 0.860 0.140
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0376 0.80211 0.004 0.996
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.73416 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.8909 0.61527 0.692 0.308
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.3431 0.80715 0.064 0.936
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.79966 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.9170 0.51236 0.332 0.668
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1414 0.80898 0.020 0.980
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5842 0.74085 0.860 0.140
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.9988 0.16374 0.520 0.480
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.9732 0.39634 0.596 0.404
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.9522 0.40956 0.372 0.628
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1843 0.80900 0.028 0.972
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.2778 0.80865 0.048 0.952
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.6438 0.72288 0.836 0.164
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.1414 0.80784 0.020 0.980
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.6438 0.73404 0.836 0.164
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0938 0.74024 0.988 0.012
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4431 0.80110 0.092 0.908
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4431 0.74628 0.908 0.092
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.4022 0.80301 0.080 0.920
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.9129 0.58624 0.672 0.328
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.9933 0.12554 0.452 0.548
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.9996 0.12453 0.512 0.488
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0938 0.74024 0.988 0.012
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.7883 0.68613 0.236 0.764
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9850 0.35078 0.572 0.428
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.3431 0.73756 0.936 0.064
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.496 0.7568 0.128 0.832 0.040
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.565 0.4499 0.312 0.000 0.688
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.570 0.7269 0.252 0.736 0.012
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.629 -0.1530 0.532 0.000 0.468
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.475 0.7462 0.080 0.852 0.068
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.489 0.7570 0.124 0.836 0.040
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.566 0.2663 0.728 0.008 0.264
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.628 -0.1313 0.540 0.000 0.460
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.630 0.1342 0.640 0.008 0.352
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.632 0.4774 0.772 0.124 0.104
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.538 0.7490 0.112 0.820 0.068
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.708 0.5599 0.412 0.564 0.024
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.755 0.0313 0.580 0.372 0.048
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.404 0.7527 0.080 0.880 0.040
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.738 -0.3252 0.512 0.456 0.032
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.875 0.2170 0.124 0.344 0.532
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.236 0.7120 0.000 0.928 0.072
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.875 0.2170 0.124 0.344 0.532
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.236 0.7120 0.000 0.928 0.072
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.778 0.3218 0.620 0.304 0.076
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.552 0.7532 0.164 0.796 0.040
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.698 0.6945 0.304 0.656 0.040
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.738 0.0044 0.584 0.040 0.376
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.650 0.3986 0.396 0.008 0.596
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.679 -0.2103 0.536 0.452 0.012
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.240 0.7208 0.004 0.932 0.064
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.797 0.4073 0.656 0.140 0.204
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.630 -0.1916 0.516 0.000 0.484
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.631 -0.1997 0.512 0.000 0.488
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.595 0.7507 0.172 0.776 0.052
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#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.668 -0.2576 0.496 0.008 0.496
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.631 0.2051 0.500 0.000 0.500
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.559 0.2189 0.720 0.004 0.276
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.482 0.7502 0.088 0.848 0.064
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.689 0.4947 0.728 0.184 0.088
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.489 0.7570 0.124 0.836 0.040
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.552 0.7541 0.164 0.796 0.040
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.228 0.7266 0.008 0.940 0.052
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.719 -0.3826 0.500 0.476 0.024
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.811 0.3312 0.624 0.264 0.112
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.631 -0.2236 0.500 0.000 0.500
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.323 0.7225 0.020 0.908 0.072
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.685 0.3802 0.716 0.068 0.216
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.722 0.4378 0.716 0.148 0.136
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.668 -0.1784 0.496 0.008 0.496
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.645 0.6651 0.328 0.656 0.016
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.692 0.4830 0.732 0.164 0.104
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.585 0.4817 0.796 0.124 0.080
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.730 0.3125 0.664 0.272 0.064
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.613 0.3585 0.400 0.000 0.600
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.574 0.7214 0.256 0.732 0.012
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.482 0.7502 0.088 0.848 0.064
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.631 -0.2052 0.508 0.000 0.492
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.606 0.0576 0.616 0.000 0.384
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.829 0.3707 0.616 0.256 0.128
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.599 0.7061 0.284 0.704 0.012
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 1 0.976 -0.0631 0.392 0.380 0.228
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.805 0.4269 0.432 0.504 0.064
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.829 0.3707 0.616 0.256 0.128
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.489 0.7570 0.124 0.836 0.040
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.647 0.6864 0.312 0.668 0.020
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.903 0.1826 0.432 0.436 0.132
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.784 0.4331 0.660 0.220 0.120
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.832 0.4073 0.628 0.160 0.212
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.826 0.5788 0.340 0.568 0.092
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.920 0.2673 0.340 0.164 0.496
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.704 0.6454 0.328 0.636 0.036
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.716 0.1168 0.628 0.332 0.040
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.509 0.7523 0.088 0.836 0.076
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.797 0.4073 0.656 0.140 0.204
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.719 0.5329 0.412 0.560 0.028
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.615 0.1789 0.664 0.008 0.328
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.711 0.5261 0.424 0.552 0.024
#> A2007795-C728-4688-B199-AE89500011D2 2 0.483 0.7502 0.068 0.848 0.084
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.522 0.7581 0.176 0.800 0.024
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.715 0.4788 0.708 0.200 0.092
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.875 0.2170 0.124 0.344 0.532
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.779 0.4723 0.672 0.192 0.136
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.859 0.4214 0.592 0.260 0.148
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.323 0.7225 0.020 0.908 0.072
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.254 0.7091 0.000 0.920 0.080
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.556 0.4701 0.300 0.000 0.700
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.546 0.7461 0.216 0.768 0.016
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.875 0.2170 0.124 0.344 0.532
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.706 0.4910 0.716 0.192 0.092
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.379 0.7528 0.060 0.892 0.048
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.592 0.2290 0.724 0.016 0.260
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.545 0.7598 0.152 0.804 0.044
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.703 -0.0814 0.580 0.396 0.024
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.628 0.1928 0.664 0.012 0.324
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.739 0.4830 0.696 0.196 0.108
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.839 0.5197 0.372 0.536 0.092
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.809 0.4843 0.416 0.516 0.068
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.254 0.7091 0.000 0.920 0.080
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.631 -0.2384 0.500 0.000 0.500
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.606 0.7486 0.188 0.764 0.048
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.254 0.7091 0.000 0.920 0.080
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.911 0.2125 0.536 0.284 0.180
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.786 0.4285 0.664 0.132 0.204
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.631 -0.2236 0.500 0.000 0.500
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.821 0.3794 0.452 0.476 0.072
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.566 0.7185 0.264 0.728 0.008
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.748 -0.3560 0.504 0.460 0.036
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.592 0.7261 0.260 0.724 0.016
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.659 0.7296 0.244 0.712 0.044
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.464 0.7498 0.084 0.856 0.060
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.254 0.7091 0.000 0.920 0.080
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.562 0.4660 0.308 0.000 0.692
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.811 0.0407 0.068 0.428 0.504
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.786 0.5775 0.364 0.572 0.064
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.756 0.2547 0.644 0.284 0.072
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.627 0.2764 0.456 0.000 0.544
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.695 -0.3896 0.496 0.488 0.016
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.496 0.7568 0.128 0.832 0.040
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.628 0.1928 0.664 0.012 0.324
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.756 0.3546 0.676 0.100 0.224
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.552 0.2274 0.728 0.004 0.268
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.846 0.3887 0.612 0.232 0.156
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.573 0.2412 0.720 0.008 0.272
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.509 0.7523 0.088 0.836 0.076
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.631 0.2051 0.500 0.000 0.500
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.683 0.4337 0.736 0.096 0.168
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.583 0.7514 0.164 0.784 0.052
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.254 0.7091 0.000 0.920 0.080
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.788 -0.0335 0.548 0.392 0.060
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.489 0.7652 0.124 0.836 0.040
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.573 0.2437 0.720 0.008 0.272
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.875 0.2170 0.124 0.344 0.532
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.905 0.2059 0.528 0.160 0.312
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.738 0.1853 0.616 0.336 0.048
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.541 0.7468 0.212 0.772 0.016
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.520 0.7552 0.136 0.820 0.044
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.714 0.1257 0.644 0.044 0.312
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.517 0.7492 0.204 0.784 0.012
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.636 0.2644 0.696 0.024 0.280
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.556 0.4701 0.300 0.000 0.700
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.668 0.7324 0.244 0.708 0.048
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.623 0.0951 0.624 0.004 0.372
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.685 0.7361 0.232 0.708 0.060
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.771 0.4388 0.676 0.128 0.196
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.738 0.4117 0.676 0.244 0.080
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.960 0.1521 0.220 0.320 0.460
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.553 0.4711 0.296 0.000 0.704
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.815 0.4932 0.408 0.520 0.072
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.692 0.4704 0.732 0.164 0.104
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.698 0.4428 0.304 0.040 0.656
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.7784 0.33314 0.000 0.392 0.244 0.364
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.5289 0.39952 0.636 0.000 0.344 0.020
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5835 0.12492 0.000 0.372 0.040 0.588
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1798 0.70462 0.944 0.000 0.016 0.040
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.3900 0.56358 0.000 0.816 0.020 0.164
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.7758 0.33968 0.000 0.396 0.236 0.368
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.5231 0.57257 0.676 0.000 0.028 0.296
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.2363 0.70899 0.920 0.000 0.024 0.056
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4121 0.67370 0.796 0.000 0.020 0.184
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 4 0.5911 0.14107 0.372 0.000 0.044 0.584
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5574 0.51928 0.008 0.724 0.064 0.204
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5179 0.40367 0.000 0.220 0.052 0.728
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.7480 0.55450 0.168 0.136 0.064 0.632
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.7382 0.47008 0.000 0.520 0.220 0.260
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.5556 0.50334 0.028 0.156 0.060 0.756
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.6396 0.74569 0.008 0.244 0.652 0.096
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1174 0.51291 0.000 0.968 0.020 0.012
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.6396 0.74569 0.008 0.244 0.652 0.096
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1059 0.51081 0.000 0.972 0.016 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.7422 0.53012 0.208 0.080 0.084 0.628
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7754 -0.23957 0.000 0.336 0.244 0.420
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.6976 0.19531 0.032 0.340 0.060 0.568
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.7908 0.24009 0.416 0.004 0.240 0.340
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.6930 0.33608 0.524 0.000 0.356 0.120
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.7521 0.52360 0.160 0.184 0.044 0.612
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.1610 0.53065 0.000 0.952 0.016 0.032
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5774 0.21329 0.496 0.004 0.020 0.480
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0927 0.69588 0.976 0.000 0.008 0.016
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1059 0.69657 0.972 0.000 0.012 0.016
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.6242 0.44314 0.020 0.624 0.040 0.316
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1151 0.69926 0.968 0.000 0.008 0.024
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2928 0.57517 0.000 0.880 0.012 0.108
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.6746 0.45005 0.236 0.036 0.076 0.652
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6054 0.48624 0.592 0.000 0.056 0.352
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.6187 0.57152 0.000 0.656 0.108 0.236
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.5467 0.36937 0.612 0.000 0.364 0.024
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.8288 0.06339 0.320 0.016 0.400 0.264
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.6066 -0.10575 0.456 0.008 0.028 0.508
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.6103 0.21199 0.492 0.004 0.036 0.468
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1059 0.69657 0.972 0.000 0.012 0.016
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.6147 0.31491 0.000 0.112 0.224 0.664
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.6305 0.50651 0.204 0.060 0.040 0.696
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2376 0.55055 0.000 0.916 0.016 0.068
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2918 0.56834 0.000 0.876 0.008 0.116
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.6712 0.17003 0.360 0.020 0.056 0.564
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.7810 -0.30285 0.000 0.364 0.252 0.384
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.5257 0.63470 0.752 0.000 0.144 0.104
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.7784 0.33314 0.000 0.392 0.244 0.364
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.5427 0.57331 0.000 0.736 0.100 0.164
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.7774 0.32469 0.000 0.388 0.240 0.372
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6263 0.62909 0.008 0.364 0.580 0.048
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 4 0.5823 0.19034 0.348 0.000 0.044 0.608
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.3658 0.69083 0.836 0.000 0.020 0.144
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#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 4 0.8669 0.07523 0.044 0.340 0.216 0.400
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.6428 0.50187 0.036 0.664 0.052 0.248
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.7830 0.36561 0.000 0.400 0.268 0.332
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.6152 0.44779 0.016 0.612 0.036 0.336
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.3266 0.67981 0.876 0.000 0.084 0.040
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0817 0.68363 0.976 0.000 0.024 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.4927 0.62555 0.712 0.000 0.024 0.264
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.4668 0.55914 0.016 0.800 0.036 0.148
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.6968 0.31335 0.320 0.024 0.076 0.580
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.7758 0.33968 0.000 0.396 0.236 0.368
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.7763 -0.24216 0.000 0.332 0.248 0.420
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.2741 0.57121 0.000 0.892 0.012 0.096
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.7117 0.49031 0.072 0.216 0.068 0.644
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.7076 0.51415 0.160 0.056 0.120 0.664
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0707 0.68469 0.980 0.000 0.020 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.2032 0.51931 0.000 0.936 0.028 0.036
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.5827 0.39247 0.568 0.000 0.036 0.396
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 4 0.6445 0.31353 0.300 0.012 0.068 0.620
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.2411 0.70123 0.920 0.000 0.040 0.040
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.7034 0.28099 0.036 0.292 0.072 0.600
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.5927 0.35029 0.264 0.000 0.076 0.660
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 4 0.5823 0.19034 0.348 0.000 0.044 0.608
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.6334 0.55378 0.148 0.064 0.068 0.720
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.3486 0.58749 0.812 0.000 0.188 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.5884 0.13415 0.000 0.364 0.044 0.592
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.4668 0.55914 0.016 0.800 0.036 0.148
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0779 0.68915 0.980 0.000 0.016 0.004
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.3606 0.69623 0.844 0.000 0.024 0.132
#> BDDB8226-723E-426F-973F-59D14E9EEB06 4 0.7408 0.47175 0.168 0.068 0.124 0.640
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.6069 0.18966 0.008 0.352 0.040 0.600
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 4 0.9539 -0.04450 0.148 0.184 0.296 0.372
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.8217 0.41707 0.112 0.256 0.088 0.544
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 4 0.7408 0.47175 0.168 0.068 0.124 0.640
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.7758 0.33968 0.000 0.396 0.236 0.368
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.6765 0.19097 0.024 0.348 0.056 0.572
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 4 0.9148 0.41833 0.156 0.204 0.168 0.472
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 4 0.7275 0.44157 0.216 0.040 0.120 0.624
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.5704 0.17139 0.492 0.008 0.012 0.488
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.8394 0.21777 0.080 0.324 0.112 0.484
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.8759 0.31462 0.292 0.080 0.464 0.164
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.8266 0.16241 0.052 0.220 0.200 0.528
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.6027 0.56408 0.108 0.064 0.080 0.748
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.7830 0.36561 0.000 0.400 0.268 0.332
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.5774 0.21329 0.496 0.004 0.020 0.480
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.7077 0.38601 0.064 0.268 0.052 0.616
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.4507 0.64725 0.756 0.000 0.020 0.224
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.6850 0.40360 0.040 0.248 0.072 0.640
#> A2007795-C728-4688-B199-AE89500011D2 2 0.5325 0.57529 0.000 0.744 0.096 0.160
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.6516 0.37985 0.016 0.580 0.052 0.352
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 4 0.6722 0.43140 0.268 0.044 0.052 0.636
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.6396 0.74569 0.008 0.244 0.652 0.096
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 4 0.7064 0.22848 0.384 0.048 0.040 0.528
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.7969 0.43195 0.260 0.072 0.108 0.560
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.1936 0.51493 0.000 0.940 0.028 0.032
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1209 0.49207 0.000 0.964 0.032 0.004
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.5933 0.29358 0.552 0.000 0.408 0.040
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.6182 -0.04867 0.000 0.428 0.052 0.520
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.6396 0.74569 0.008 0.244 0.652 0.096
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.6845 0.36906 0.296 0.032 0.064 0.608
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.5361 0.59060 0.000 0.724 0.068 0.208
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.4957 0.57674 0.684 0.000 0.016 0.300
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.7546 0.29827 0.000 0.408 0.188 0.404
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.5335 0.54647 0.072 0.096 0.044 0.788
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.4507 0.64610 0.756 0.000 0.020 0.224
#> DDC71530-38B7-483F-83DC-1BCC550719C3 4 0.6901 0.29734 0.352 0.040 0.044 0.564
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.8442 0.25820 0.096 0.356 0.092 0.456
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.8148 0.34911 0.084 0.304 0.092 0.520
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1004 0.49293 0.000 0.972 0.024 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.4982 0.67557 0.772 0.000 0.136 0.092
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.6316 0.41192 0.020 0.608 0.040 0.332
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.1004 0.49293 0.000 0.972 0.024 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.8682 0.36611 0.132 0.128 0.220 0.520
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6990 0.09815 0.472 0.020 0.064 0.444
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0707 0.68469 0.980 0.000 0.020 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.8531 0.45826 0.120 0.188 0.148 0.544
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5855 0.14855 0.000 0.356 0.044 0.600
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.5063 0.49077 0.012 0.144 0.064 0.780
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.6403 0.09556 0.008 0.388 0.052 0.552
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.8251 -0.03877 0.036 0.316 0.176 0.472
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4551 0.56345 0.012 0.804 0.036 0.148
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1209 0.49207 0.000 0.964 0.032 0.004
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.5905 0.30654 0.564 0.000 0.396 0.040
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6263 0.62909 0.008 0.364 0.580 0.048
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.8048 0.27021 0.076 0.336 0.084 0.504
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.7200 0.54036 0.148 0.084 0.104 0.664
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.2635 0.67288 0.904 0.000 0.076 0.020
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5936 0.47899 0.044 0.180 0.048 0.728
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.7760 0.33334 0.000 0.392 0.236 0.372
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.4507 0.64610 0.756 0.000 0.020 0.224
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.7594 -0.12489 0.416 0.020 0.116 0.448
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5308 0.58870 0.684 0.000 0.036 0.280
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.7708 0.43864 0.180 0.048 0.176 0.596
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5157 0.59599 0.688 0.000 0.028 0.284
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.7830 0.36561 0.000 0.400 0.268 0.332
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0707 0.68469 0.980 0.000 0.020 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.5948 0.20370 0.492 0.004 0.028 0.476
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6077 0.46620 0.020 0.644 0.036 0.300
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1004 0.49293 0.000 0.972 0.024 0.004
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6542 0.54786 0.116 0.124 0.052 0.708
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.7046 0.43590 0.000 0.524 0.136 0.340
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5062 0.59492 0.692 0.000 0.024 0.284
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6396 0.74569 0.008 0.244 0.652 0.096
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.8336 0.06522 0.172 0.040 0.332 0.456
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.7626 0.55882 0.196 0.116 0.072 0.616
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.6192 -0.06614 0.000 0.436 0.052 0.512
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5706 0.51408 0.020 0.684 0.028 0.268
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.6188 0.52056 0.620 0.004 0.064 0.312
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.5838 -0.04476 0.000 0.444 0.032 0.524
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.5130 0.57072 0.668 0.000 0.020 0.312
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.5933 0.29358 0.552 0.000 0.408 0.040
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.6830 0.23074 0.020 0.516 0.056 0.408
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3813 0.68880 0.828 0.000 0.024 0.148
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.7209 0.19473 0.036 0.508 0.060 0.396
#> E258343D-271F-419D-A083-9AB6DF9A377B 4 0.6214 -0.12464 0.468 0.000 0.052 0.480
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.7026 0.49671 0.216 0.052 0.084 0.648
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.8124 0.64347 0.044 0.196 0.536 0.224
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.5933 0.28884 0.552 0.000 0.408 0.040
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.8795 0.39299 0.104 0.204 0.188 0.504
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.6925 0.31741 0.324 0.024 0.072 0.580
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.7005 0.17498 0.492 0.024 0.424 0.060
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5810 0.731289 0.000 0.604 0.000 0.244 0.152
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.5159 0.276606 0.604 0.036 0.352 0.000 0.008
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 5 0.7210 0.139014 0.000 0.220 0.028 0.320 0.432
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2630 0.696910 0.892 0.016 0.012 0.000 0.080
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.3827 0.630699 0.000 0.020 0.024 0.812 0.144
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5762 0.728607 0.000 0.608 0.000 0.248 0.144
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.5244 0.448846 0.568 0.016 0.024 0.000 0.392
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.2629 0.699548 0.880 0.012 0.004 0.000 0.104
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4241 0.623971 0.716 0.008 0.012 0.000 0.264
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.5566 0.341144 0.276 0.044 0.036 0.000 0.644
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.5657 0.572583 0.000 0.056 0.068 0.692 0.184
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 5 0.6583 0.351560 0.000 0.200 0.036 0.176 0.588
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 5 0.7021 0.549807 0.100 0.104 0.040 0.116 0.640
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5843 0.524700 0.000 0.512 0.000 0.388 0.100
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.5632 0.473722 0.012 0.124 0.024 0.128 0.712
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.5015 0.723634 0.000 0.100 0.744 0.132 0.024
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.1059 0.628405 0.000 0.020 0.008 0.968 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.5007 0.726533 0.000 0.096 0.744 0.136 0.024
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0854 0.629247 0.000 0.012 0.008 0.976 0.004
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.7169 0.502670 0.128 0.168 0.036 0.060 0.608
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.5999 0.712457 0.000 0.604 0.004 0.196 0.196
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.7436 0.204545 0.004 0.192 0.052 0.268 0.484
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.7344 -0.206490 0.340 0.028 0.252 0.000 0.380
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.6866 0.184492 0.488 0.040 0.348 0.000 0.124
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.7493 0.486256 0.092 0.176 0.016 0.156 0.560
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.2095 0.638811 0.000 0.024 0.020 0.928 0.028
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.6342 -0.002965 0.404 0.088 0.024 0.000 0.484
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1484 0.686886 0.944 0.000 0.008 0.000 0.048
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2047 0.684211 0.928 0.020 0.012 0.000 0.040
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.6036 0.475817 0.004 0.076 0.024 0.604 0.292
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1628 0.689918 0.936 0.000 0.008 0.000 0.056
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.3164 0.597208 0.000 0.104 0.000 0.852 0.044
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 5 0.5718 0.543066 0.140 0.048 0.064 0.024 0.724
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.5631 0.330408 0.504 0.024 0.032 0.000 0.440
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.5772 0.119615 0.000 0.300 0.004 0.592 0.104
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.5232 0.228400 0.580 0.036 0.376 0.000 0.008
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.7407 0.184694 0.296 0.028 0.424 0.004 0.248
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#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.7121 0.244238 0.012 0.076 0.064 0.476 0.372
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.5575 0.152411 0.344 0.028 0.036 0.000 0.592
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.6133 0.571335 0.132 0.072 0.048 0.044 0.704
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.7222 0.608407 0.028 0.092 0.604 0.104 0.172
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.5533 0.101438 0.512 0.036 0.436 0.000 0.016
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 5 0.7612 0.289529 0.032 0.244 0.048 0.152 0.524
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.6836 0.419560 0.240 0.104 0.048 0.016 0.592
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.6472 -0.042266 0.464 0.048 0.440 0.020 0.028
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.590 0.73247 0.012 0.504 0.000 0.324 0.000 0.160
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.494 0.37709 0.056 0.020 0.288 0.000 0.636 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.287 0.51284 0.008 0.012 0.000 0.840 0.000 0.140
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.315 0.62929 0.196 0.000 0.008 0.000 0.792 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.410 0.68321 0.008 0.004 0.016 0.276 0.000 0.696
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.592 0.72950 0.012 0.508 0.000 0.312 0.000 0.168
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.530 0.02871 0.516 0.000 0.004 0.092 0.388 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.355 0.62200 0.216 0.008 0.004 0.008 0.764 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 5 0.487 0.37756 0.396 0.000 0.004 0.052 0.548 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.558 0.55568 0.568 0.000 0.008 0.272 0.152 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.589 0.53974 0.032 0.016 0.072 0.320 0.000 0.560
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.345 0.51403 0.136 0.004 0.008 0.816 0.000 0.036
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.555 0.06682 0.384 0.008 0.024 0.540 0.016 0.028
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.614 0.52628 0.004 0.420 0.000 0.260 0.000 0.316
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.431 0.39640 0.248 0.012 0.008 0.708 0.000 0.024
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.431 0.72945 0.008 0.068 0.776 0.028 0.000 0.120
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.222 0.71379 0.000 0.012 0.000 0.104 0.000 0.884
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.430 0.73017 0.008 0.064 0.776 0.028 0.000 0.124
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.212 0.71470 0.000 0.008 0.000 0.104 0.000 0.888
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.747 0.21189 0.424 0.104 0.024 0.352 0.068 0.028
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.577 0.65017 0.012 0.472 0.000 0.392 0.000 0.124
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.596 0.53645 0.108 0.044 0.044 0.660 0.000 0.144
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.752 -0.08263 0.320 0.004 0.228 0.124 0.324 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 5 0.666 0.26823 0.156 0.020 0.288 0.036 0.500 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.583 0.26123 0.272 0.028 0.000 0.604 0.032 0.064
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.255 0.70297 0.000 0.016 0.004 0.112 0.000 0.868
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.689 0.41679 0.428 0.016 0.020 0.256 0.276 0.004
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.328 0.63264 0.172 0.000 0.016 0.004 0.804 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 5 0.224 0.64918 0.112 0.004 0.004 0.000 0.880 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.573 0.23107 0.072 0.012 0.016 0.440 0.000 0.460
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.343 0.62892 0.176 0.000 0.016 0.008 0.796 0.004
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.398 0.65447 0.000 0.064 0.000 0.192 0.000 0.744
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.573 0.38259 0.528 0.008 0.044 0.372 0.048 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.532 0.23067 0.568 0.000 0.004 0.112 0.316 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.609 0.08444 0.008 0.232 0.000 0.288 0.000 0.472
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 5 0.506 0.33747 0.056 0.020 0.316 0.000 0.608 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.753 0.17058 0.180 0.024 0.416 0.100 0.280 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.651 0.50861 0.504 0.016 0.020 0.232 0.228 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.613 0.49636 0.496 0.008 0.004 0.240 0.252 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.229 0.64903 0.116 0.004 0.004 0.000 0.876 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.708 0.16842 0.152 0.516 0.104 0.208 0.000 0.020
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.526 -0.29063 0.468 0.012 0.004 0.472 0.036 0.008
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 6 0.295 0.69905 0.000 0.012 0.000 0.176 0.000 0.812
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.338 0.71418 0.000 0.004 0.008 0.228 0.000 0.760
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.636 0.54865 0.532 0.032 0.008 0.284 0.140 0.004
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.577 0.72950 0.016 0.532 0.000 0.320 0.000 0.132
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.527 0.57343 0.176 0.008 0.108 0.020 0.684 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.590 0.73247 0.012 0.504 0.000 0.324 0.000 0.160
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.593 0.53622 0.008 0.132 0.020 0.276 0.000 0.564
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.586 0.73129 0.012 0.504 0.000 0.332 0.000 0.152
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.464 0.63436 0.004 0.044 0.696 0.020 0.000 0.236
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.549 0.54509 0.572 0.000 0.008 0.288 0.132 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.463 0.45043 0.364 0.000 0.004 0.040 0.592 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.186 0.64489 0.056 0.008 0.008 0.000 0.924 0.004
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.468 0.53889 0.292 0.004 0.008 0.036 0.656 0.004
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.568 0.30320 0.500 0.000 0.000 0.176 0.324 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.552 0.47967 0.176 0.080 0.004 0.668 0.000 0.072
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.430 0.73017 0.008 0.064 0.776 0.028 0.000 0.124
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.584 0.72300 0.020 0.524 0.000 0.328 0.000 0.128
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.842 0.11492 0.272 0.052 0.252 0.296 0.008 0.120
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.551 0.36123 0.544 0.000 0.000 0.164 0.292 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 6 0.200 0.65155 0.000 0.048 0.004 0.032 0.000 0.916
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.557 0.49827 0.644 0.012 0.032 0.236 0.072 0.004
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.428 0.58164 0.264 0.008 0.016 0.008 0.700 0.004
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 5 0.545 0.54044 0.148 0.012 0.124 0.036 0.680 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.501 0.37015 0.008 0.732 0.112 0.080 0.000 0.068
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.521 0.33866 0.044 0.016 0.004 0.432 0.000 0.504
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.579 0.03191 0.076 0.016 0.016 0.516 0.000 0.376
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.568 0.30320 0.500 0.000 0.000 0.176 0.324 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.355 0.62200 0.216 0.008 0.004 0.008 0.764 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.548 0.54844 0.576 0.000 0.008 0.284 0.132 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 5 0.515 0.30982 0.392 0.000 0.004 0.076 0.528 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.816 0.38885 0.104 0.108 0.420 0.200 0.000 0.168
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.537 0.36280 0.492 0.012 0.008 0.440 0.044 0.004
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.776 0.48545 0.104 0.088 0.484 0.164 0.000 0.160
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.523 -0.14466 0.040 0.020 0.004 0.504 0.000 0.432
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.304 0.51246 0.008 0.024 0.000 0.836 0.000 0.132
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.629 0.05189 0.448 0.028 0.040 0.436 0.016 0.032
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.590 0.30489 0.500 0.020 0.008 0.400 0.056 0.016
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 5 0.487 0.41297 0.372 0.000 0.004 0.056 0.568 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.565 0.31961 0.396 0.008 0.024 0.052 0.516 0.004
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.448 0.72185 0.008 0.080 0.760 0.024 0.000 0.128
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 5 0.574 0.13100 0.056 0.024 0.440 0.004 0.468 0.008
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.634 0.50140 0.540 0.008 0.016 0.208 0.220 0.008
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 5 0.525 0.22685 0.056 0.020 0.388 0.000 0.536 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.513 0.15859 0.464 0.000 0.008 0.060 0.468 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.501 0.37015 0.008 0.732 0.112 0.080 0.000 0.068
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.633 0.11774 0.368 0.020 0.048 0.508 0.020 0.036
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.592 0.72950 0.012 0.508 0.000 0.312 0.000 0.168
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.513 0.45624 0.352 0.008 0.020 0.028 0.588 0.004
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.706 0.15990 0.164 0.512 0.104 0.204 0.000 0.016
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.598 -0.49676 0.020 0.392 0.000 0.456 0.000 0.132
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.629 0.63201 0.016 0.448 0.000 0.300 0.000 0.236
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 4 0.805 0.14482 0.176 0.032 0.284 0.360 0.004 0.144
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.566 0.24053 0.300 0.028 0.028 0.604 0.008 0.032
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.608 0.55553 0.548 0.012 0.004 0.212 0.220 0.004
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.595 0.52596 0.520 0.004 0.004 0.228 0.244 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.689 0.41679 0.428 0.016 0.020 0.256 0.276 0.004
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.693 0.38031 0.276 0.064 0.056 0.528 0.004 0.072
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.535 0.45732 0.648 0.016 0.032 0.264 0.032 0.008
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.752 0.48386 0.460 0.060 0.044 0.268 0.160 0.008
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.549 0.55013 0.576 0.000 0.008 0.280 0.136 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 6 0.610 0.40603 0.064 0.016 0.048 0.348 0.000 0.524
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.643 -0.02372 0.132 0.016 0.432 0.024 0.396 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 6 0.681 0.38636 0.096 0.040 0.052 0.320 0.000 0.492
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.721 0.15175 0.164 0.016 0.292 0.072 0.452 0.004
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 6 0.560 0.56661 0.024 0.016 0.060 0.316 0.000 0.584
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.649 0.67586 0.080 0.056 0.652 0.100 0.016 0.096
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.532 -0.04919 0.432 0.024 0.016 0.508 0.012 0.008
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.608 0.71430 0.036 0.516 0.000 0.320 0.000 0.128
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.767 0.30637 0.176 0.032 0.216 0.444 0.000 0.132
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.670 0.62441 0.020 0.452 0.016 0.272 0.000 0.240
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 5 0.488 0.57180 0.264 0.000 0.040 0.036 0.660 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 6 0.239 0.70777 0.000 0.008 0.000 0.128 0.000 0.864
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.697 0.43429 0.464 0.008 0.068 0.304 0.152 0.004
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 5 0.348 0.56489 0.044 0.028 0.100 0.000 0.828 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.580 0.73346 0.012 0.524 0.000 0.316 0.000 0.148
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 5 0.280 0.64089 0.068 0.012 0.048 0.000 0.872 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 6 0.247 0.70992 0.000 0.008 0.000 0.136 0.000 0.856
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.671 0.67580 0.044 0.452 0.016 0.352 0.000 0.136
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 5 0.358 0.55388 0.044 0.028 0.108 0.000 0.820 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.371 0.61869 0.212 0.000 0.016 0.008 0.760 0.004
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.644 0.30897 0.288 0.064 0.036 0.564 0.016 0.032
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.722 0.53556 0.480 0.020 0.044 0.256 0.184 0.016
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.567 0.47772 0.548 0.008 0.020 0.344 0.080 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 6 0.183 0.65163 0.000 0.028 0.008 0.036 0.000 0.928
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 4 0.741 0.13217 0.220 0.252 0.008 0.440 0.020 0.060
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.647 0.45492 0.504 0.020 0.024 0.336 0.108 0.008
#> DAD951A3-C22E-42F0-BB02-854413DDC351 4 0.684 -0.06140 0.092 0.292 0.000 0.492 0.012 0.112
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 6 0.471 0.57572 0.012 0.016 0.012 0.356 0.000 0.604
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 5 0.525 0.23056 0.056 0.020 0.388 0.000 0.536 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 5 0.494 0.37709 0.056 0.020 0.288 0.000 0.636 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.274 0.52184 0.012 0.008 0.000 0.852 0.000 0.128
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 6 0.580 0.53477 0.064 0.020 0.032 0.300 0.000 0.584
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 6 0.295 0.69905 0.000 0.012 0.000 0.176 0.000 0.812
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.607 0.71147 0.012 0.472 0.000 0.328 0.000 0.188
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 6 0.552 0.62455 0.036 0.024 0.044 0.264 0.000 0.632
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 5 0.486 0.41877 0.368 0.000 0.004 0.056 0.572 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 6 0.612 0.39589 0.064 0.016 0.048 0.356 0.000 0.516
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 4 0.721 0.43744 0.192 0.028 0.140 0.516 0.000 0.124
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#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.405 0.42392 0.012 0.040 0.000 0.744 0.000 0.204
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.430 0.73017 0.008 0.064 0.776 0.028 0.000 0.124
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.585 0.48699 0.524 0.012 0.004 0.344 0.112 0.004
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 6 0.574 0.32033 0.008 0.180 0.000 0.264 0.000 0.548
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.587 0.07962 0.440 0.004 0.020 0.084 0.448 0.004
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.672 0.65077 0.032 0.420 0.012 0.356 0.000 0.180
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.490 0.18166 0.316 0.016 0.012 0.632 0.008 0.016
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 5 0.502 0.28731 0.440 0.000 0.004 0.060 0.496 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.683 0.48719 0.492 0.040 0.004 0.292 0.152 0.020
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.763 0.39145 0.200 0.028 0.064 0.448 0.016 0.244
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.707 0.45626 0.228 0.024 0.060 0.508 0.004 0.176
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.153 0.69688 0.000 0.004 0.000 0.068 0.000 0.928
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 5 0.526 0.58744 0.276 0.008 0.088 0.008 0.620 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.573 -0.15689 0.072 0.012 0.016 0.472 0.000 0.428
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.153 0.69688 0.000 0.004 0.000 0.068 0.000 0.928
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.766 -0.03560 0.376 0.028 0.164 0.356 0.020 0.056
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.691 0.50225 0.432 0.016 0.032 0.248 0.272 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.161 0.64374 0.056 0.008 0.004 0.000 0.932 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.771 0.32148 0.276 0.128 0.060 0.456 0.012 0.068
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.270 0.52352 0.012 0.008 0.000 0.856 0.000 0.124
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.375 0.40186 0.232 0.004 0.008 0.744 0.000 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.442 0.49585 0.048 0.048 0.000 0.752 0.000 0.152
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.677 -0.24355 0.072 0.316 0.000 0.472 0.008 0.132
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.509 0.65250 0.024 0.016 0.044 0.252 0.000 0.664
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.158 0.66297 0.000 0.016 0.008 0.036 0.000 0.940
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 5 0.522 0.25331 0.056 0.020 0.372 0.000 0.552 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.464 0.63436 0.004 0.044 0.696 0.020 0.000 0.236
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.681 0.47439 0.184 0.024 0.064 0.560 0.004 0.164
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.629 0.06177 0.452 0.028 0.040 0.432 0.016 0.032
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.343 0.64962 0.116 0.000 0.064 0.000 0.816 0.004
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.422 0.41100 0.232 0.008 0.004 0.724 0.004 0.028
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.595 0.73168 0.016 0.512 0.000 0.312 0.000 0.160
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 5 0.502 0.28731 0.440 0.000 0.004 0.060 0.496 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.750 0.36476 0.384 0.012 0.084 0.216 0.300 0.004
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.516 -0.04173 0.504 0.000 0.008 0.064 0.424 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.681 0.22683 0.464 0.028 0.180 0.308 0.008 0.012
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.541 -0.06212 0.500 0.000 0.008 0.076 0.412 0.004
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.501 0.37015 0.008 0.732 0.112 0.080 0.000 0.068
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.221 0.64653 0.076 0.008 0.016 0.000 0.900 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.617 0.46187 0.484 0.008 0.004 0.240 0.264 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.572 0.28555 0.072 0.012 0.016 0.420 0.000 0.480
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.153 0.69688 0.000 0.004 0.000 0.068 0.000 0.928
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.661 0.17150 0.348 0.044 0.036 0.508 0.020 0.044
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.661 0.45787 0.012 0.352 0.008 0.340 0.000 0.288
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.532 -0.05367 0.496 0.000 0.008 0.080 0.416 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.430 0.73017 0.008 0.064 0.776 0.028 0.000 0.124
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.712 0.00681 0.412 0.020 0.348 0.176 0.036 0.008
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.575 -0.06512 0.404 0.004 0.020 0.508 0.036 0.028
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.402 0.41670 0.008 0.044 0.000 0.744 0.000 0.204
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.544 0.37235 0.056 0.012 0.012 0.404 0.000 0.516
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.633 0.07978 0.372 0.004 0.052 0.104 0.468 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.359 0.43368 0.012 0.008 0.000 0.752 0.000 0.228
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.559 0.07723 0.512 0.004 0.004 0.096 0.380 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 5 0.525 0.23648 0.056 0.020 0.384 0.000 0.540 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.577 0.16283 0.084 0.020 0.012 0.552 0.000 0.332
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.472 0.45445 0.356 0.000 0.004 0.048 0.592 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.661 0.13834 0.092 0.016 0.068 0.492 0.000 0.332
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.644 0.53447 0.516 0.012 0.024 0.220 0.228 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.551 0.28253 0.488 0.012 0.008 0.432 0.056 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.668 0.65718 0.100 0.060 0.632 0.104 0.012 0.092
#> AB642383-1611-4355-B03C-08D42FF4676C 5 0.525 0.23586 0.056 0.020 0.384 0.000 0.540 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.777 0.35611 0.232 0.188 0.056 0.444 0.004 0.076
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.756 0.48604 0.452 0.060 0.044 0.272 0.164 0.008
#> EE118E80-F125-4655-8845-56A9CBBA0680 5 0.628 0.12468 0.052 0.028 0.388 0.024 0.492 0.016
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.796 0.895 0.954 0.5005 0.499 0.499
#> 3 3 0.504 0.515 0.776 0.3034 0.745 0.537
#> 4 4 0.475 0.528 0.739 0.1300 0.720 0.368
#> 5 5 0.521 0.416 0.649 0.0686 0.853 0.517
#> 6 6 0.606 0.453 0.642 0.0456 0.848 0.422
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.94752 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.95341 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.94752 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.95341 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.94752 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.94752 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2948 0.92292 0.948 0.052
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.95341 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.95341 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.95341 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.94752 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7139 0.73471 0.196 0.804
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.9881 0.19168 0.436 0.564
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.94752 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.94752 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.9661 0.40321 0.392 0.608
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.94752 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7815 0.70822 0.232 0.768
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.94752 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.1843 0.92629 0.028 0.972
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.94752 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.94752 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.95341 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.95341 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.7139 0.75096 0.804 0.196
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.94752 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.95341 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.95341 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.95341 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.94752 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.95341 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.94752 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.95341 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.95341 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.94752 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.95341 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.95341 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.95341 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.95341 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.95341 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.94752 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3431 0.91377 0.936 0.064
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.94752 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.94752 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.95341 1.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.94752 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.95341 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.94752 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.94752 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.94752 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.7299 0.74618 0.204 0.796
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.95341 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.95341 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.95341 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.95341 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2948 0.92292 0.948 0.052
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.94752 0.000 1.000
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#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.95341 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.94752 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9710 0.38301 0.400 0.600
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.95341 1.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.94752 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.95341 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.94752 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.94752 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.95341 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.95341 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.94752 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.94752 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.94752 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.95341 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.94752 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.94752 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.95341 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.95341 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.95341 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.6048 0.80845 0.148 0.852
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.94752 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0672 0.94135 0.008 0.992
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.94752 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1184 0.93548 0.016 0.984
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.94752 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.94752 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.95341 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.7299 0.74618 0.204 0.796
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0938 0.93851 0.012 0.988
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.6148 0.81112 0.848 0.152
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.95341 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.5842 0.81003 0.140 0.860
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.94752 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2948 0.92292 0.948 0.052
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.95341 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.95341 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.95341 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.95341 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.94752 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.95341 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.95341 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.94752 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.94752 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.3431 0.91377 0.936 0.064
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.94752 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.95341 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.9393 0.48678 0.356 0.644
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.95341 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4022 0.89264 0.920 0.080
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.94752 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.94752 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.95341 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.94752 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.95341 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.95341 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.94752 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.95341 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.94752 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.95341 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.95341 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.7376 0.73272 0.792 0.208
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.95341 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.94752 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7299 0.73877 0.796 0.204
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.95341 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0747 0.82137 0.016 0.984 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.1643 0.56662 0.044 0.000 0.956
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6062 0.62535 0.384 0.616 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 3 0.6308 -0.22588 0.492 0.000 0.508
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.4002 0.77614 0.160 0.840 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0747 0.82137 0.016 0.984 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.5968 0.41507 0.636 0.000 0.364
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 3 0.6308 -0.22588 0.492 0.000 0.508
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.6291 0.26897 0.532 0.000 0.468
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.6295 0.26246 0.528 0.000 0.472
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.3038 0.79897 0.104 0.896 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1482 0.61084 0.968 0.020 0.012
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0592 0.61641 0.988 0.012 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0747 0.82137 0.016 0.984 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.6809 0.49457 0.464 0.524 0.012
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.6954 0.03511 0.016 0.500 0.484
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0747 0.82128 0.016 0.984 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.8768 0.04625 0.112 0.408 0.480
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0892 0.82138 0.020 0.980 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.3607 0.52646 0.880 0.112 0.008
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.5407 0.52397 0.804 0.156 0.040
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.6659 0.51196 0.460 0.532 0.008
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4842 0.43880 0.224 0.000 0.776
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.1643 0.56662 0.044 0.000 0.956
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1482 0.61872 0.968 0.012 0.020
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0237 0.81944 0.004 0.996 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6305 0.24994 0.516 0.000 0.484
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 3 0.6299 -0.19706 0.476 0.000 0.524
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.6291 0.26897 0.532 0.000 0.468
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.1643 0.81810 0.044 0.956 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.6302 -0.19769 0.480 0.000 0.520
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0747 0.82137 0.016 0.984 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.1289 0.62293 0.968 0.000 0.032
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6286 0.27389 0.536 0.000 0.464
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0747 0.82137 0.016 0.984 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.1643 0.56662 0.044 0.000 0.956
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.6648 0.32741 0.364 0.016 0.620
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4452 0.57342 0.808 0.000 0.192
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5835 0.43929 0.660 0.000 0.340
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.6295 0.26131 0.528 0.000 0.472
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.2165 0.81884 0.064 0.936 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0592 0.62154 0.988 0.000 0.012
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0747 0.82137 0.016 0.984 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.1643 0.81804 0.044 0.956 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4796 0.53699 0.780 0.000 0.220
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1411 0.82154 0.036 0.964 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0592 0.56728 0.012 0.000 0.988
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0747 0.82137 0.016 0.984 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0747 0.82234 0.016 0.984 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0237 0.82033 0.004 0.996 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.6822 0.05555 0.012 0.508 0.480
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.6111 0.36365 0.604 0.000 0.396
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.6291 0.26897 0.532 0.000 0.468
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0892 0.56730 0.020 0.000 0.980
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 3 0.6307 -0.22839 0.488 0.000 0.512
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.5905 0.42954 0.648 0.000 0.352
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.6664 0.50516 0.464 0.528 0.008
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.9355 0.29107 0.320 0.188 0.492
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.5864 0.68701 0.288 0.704 0.008
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.8188 0.53402 0.372 0.548 0.080
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.5905 0.42954 0.648 0.000 0.352
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.81943 0.000 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 3 0.6309 -0.23886 0.500 0.000 0.500
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.6308 -0.21838 0.492 0.000 0.508
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.1643 0.56662 0.044 0.000 0.956
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0237 0.81944 0.004 0.996 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.2066 0.81932 0.060 0.940 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.4002 0.78587 0.160 0.840 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.5905 0.42954 0.648 0.000 0.352
#> 40424A8F-CE23-436B-8F65-4919F90F6691 3 0.6309 -0.23396 0.496 0.000 0.504
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.1163 0.62393 0.972 0.000 0.028
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.6286 0.27389 0.536 0.000 0.464
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.6944 0.07936 0.016 0.516 0.468
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0747 0.62146 0.984 0.000 0.016
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.6664 0.09854 0.008 0.528 0.464
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.2356 0.81757 0.072 0.928 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.3752 0.78990 0.144 0.856 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.8295 -0.02595 0.548 0.088 0.364
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2165 0.61897 0.936 0.000 0.064
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.6291 0.26897 0.532 0.000 0.468
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.6309 -0.22632 0.496 0.000 0.504
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.7491 0.00397 0.036 0.472 0.492
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.1529 0.56776 0.040 0.000 0.960
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.2959 0.60239 0.900 0.000 0.100
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.1950 0.56247 0.040 0.008 0.952
#> E435C03F-0277-49C1-83EF-19452082723E 3 0.6291 -0.19758 0.468 0.000 0.532
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0237 0.81944 0.004 0.996 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.3183 0.57301 0.908 0.016 0.076
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0747 0.82137 0.016 0.984 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.6307 0.23380 0.512 0.000 0.488
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.5859 0.43582 0.656 0.000 0.344
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.5363 0.70335 0.276 0.724 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.81943 0.000 1.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.9268 0.27505 0.348 0.168 0.484
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.6783 -0.17488 0.588 0.396 0.016
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.1289 0.62353 0.968 0.000 0.032
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.5859 0.43738 0.656 0.000 0.344
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.6062 0.41084 0.616 0.000 0.384
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.6307 0.10115 0.660 0.328 0.012
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.2625 0.61302 0.916 0.000 0.084
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.6209 0.32428 0.368 0.004 0.628
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.5905 0.42954 0.648 0.000 0.352
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0237 0.81944 0.004 0.996 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.1964 0.56750 0.056 0.000 0.944
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.5621 0.67987 0.308 0.692 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.1529 0.56352 0.040 0.000 0.960
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.3192 0.79558 0.112 0.888 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.9335 0.28843 0.324 0.184 0.492
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.1163 0.62308 0.972 0.000 0.028
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.7960 0.37896 0.656 0.136 0.208
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.9702 0.22086 0.364 0.220 0.416
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#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5497 0.70061 0.292 0.708 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.5216 0.71959 0.260 0.740 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.1163 0.82034 0.028 0.972 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0424 0.82029 0.008 0.992 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.1753 0.56566 0.048 0.000 0.952
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.6822 0.05555 0.012 0.508 0.480
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.6244 0.53397 0.440 0.560 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.4539 0.50309 0.836 0.016 0.148
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0424 0.56776 0.008 0.000 0.992
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.2663 0.59553 0.932 0.024 0.044
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0237 0.82033 0.004 0.996 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.5905 0.42954 0.648 0.000 0.352
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.5948 0.33090 0.360 0.000 0.640
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.6308 -0.23093 0.492 0.000 0.508
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.6824 -0.04465 0.576 0.016 0.408
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.6291 0.26897 0.532 0.000 0.468
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0237 0.81944 0.004 0.996 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.6026 0.06807 0.376 0.000 0.624
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.5760 0.45172 0.672 0.000 0.328
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1031 0.82056 0.024 0.976 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0424 0.82029 0.008 0.992 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.1989 0.60586 0.948 0.004 0.048
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0592 0.82121 0.012 0.988 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.6079 0.38410 0.612 0.000 0.388
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.6954 0.03511 0.016 0.500 0.484
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6129 0.37659 0.324 0.008 0.668
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1129 0.62263 0.976 0.004 0.020
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0747 0.82137 0.016 0.984 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.3340 0.79274 0.120 0.880 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.2356 0.55580 0.072 0.000 0.928
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0892 0.82138 0.020 0.980 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.6286 0.27389 0.536 0.000 0.464
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0592 0.56728 0.012 0.000 0.988
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2261 0.81826 0.068 0.932 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.6291 0.26897 0.532 0.000 0.468
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.5760 0.66120 0.328 0.672 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.6111 -0.02038 0.396 0.000 0.604
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3267 0.60016 0.884 0.000 0.116
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.8037 0.31624 0.352 0.076 0.572
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.2625 0.56178 0.084 0.000 0.916
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2711 0.80937 0.088 0.912 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6527 0.04840 0.588 0.008 0.404
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.6410 0.30867 0.420 0.004 0.576
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2473 0.80778 0.000 0.908 0.012 0.080
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.5279 0.19207 0.588 0.000 0.400 0.012
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4690 0.50046 0.000 0.260 0.016 0.724
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2125 0.66291 0.920 0.000 0.076 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.6262 0.54124 0.000 0.628 0.092 0.280
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2845 0.80424 0.000 0.896 0.028 0.076
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4866 0.38746 0.596 0.000 0.000 0.404
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.2699 0.67503 0.904 0.000 0.068 0.028
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2921 0.68266 0.860 0.000 0.000 0.140
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2773 0.68902 0.880 0.000 0.004 0.116
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5257 0.68766 0.000 0.752 0.104 0.144
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2287 0.63400 0.060 0.004 0.012 0.924
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.2676 0.63005 0.092 0.000 0.012 0.896
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.2402 0.80891 0.000 0.912 0.012 0.076
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4972 0.54787 0.004 0.080 0.136 0.780
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4567 0.48526 0.000 0.276 0.716 0.008
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1488 0.81655 0.000 0.956 0.012 0.032
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.5582 0.56515 0.000 0.168 0.724 0.108
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1584 0.81662 0.000 0.952 0.012 0.036
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.6926 0.54478 0.044 0.092 0.208 0.656
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7054 0.50977 0.024 0.152 0.188 0.636
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.5813 0.53697 0.008 0.088 0.188 0.716
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3842 0.55384 0.128 0.000 0.836 0.036
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5493 0.14324 0.456 0.000 0.528 0.016
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.4982 0.58257 0.136 0.000 0.092 0.772
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.1888 0.80410 0.000 0.940 0.044 0.016
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.6187 0.54359 0.656 0.000 0.236 0.108
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.3498 0.61502 0.832 0.000 0.160 0.008
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2281 0.68597 0.904 0.000 0.000 0.096
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.5343 0.63988 0.000 0.708 0.052 0.240
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4295 0.54491 0.752 0.000 0.240 0.008
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1890 0.81388 0.000 0.936 0.008 0.056
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.5018 0.38319 0.332 0.000 0.012 0.656
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3123 0.67697 0.844 0.000 0.000 0.156
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.2255 0.81106 0.000 0.920 0.012 0.068
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.5279 0.19207 0.588 0.000 0.400 0.012
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2594 0.60220 0.044 0.004 0.916 0.036
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.7808 0.19695 0.416 0.000 0.272 0.312
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4761 0.44612 0.628 0.000 0.000 0.372
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1637 0.68390 0.940 0.000 0.000 0.060
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.3764 0.76854 0.000 0.816 0.012 0.172
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.2928 0.62649 0.108 0.000 0.012 0.880
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2048 0.81279 0.000 0.928 0.008 0.064
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.4017 0.75177 0.000 0.828 0.044 0.128
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4999 0.17174 0.508 0.000 0.000 0.492
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.7047 0.47567 0.008 0.604 0.172 0.216
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4991 0.17265 0.388 0.000 0.608 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3117 0.79660 0.000 0.880 0.028 0.092
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6167 0.55891 0.000 0.664 0.116 0.220
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.2300 0.81313 0.000 0.924 0.028 0.048
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4718 0.48263 0.000 0.280 0.708 0.012
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4072 0.62075 0.748 0.000 0.000 0.252
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1716 0.68452 0.936 0.000 0.000 0.064
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4500 0.45980 0.684 0.000 0.316 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4171 0.67481 0.828 0.000 0.088 0.084
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4933 0.34093 0.568 0.000 0.000 0.432
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.5163 0.58958 0.008 0.080 0.140 0.772
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3858 0.61795 0.000 0.056 0.844 0.100
#> F043185A-D4D2-4503-93FA-A7B7DA684290 3 0.8147 -0.08129 0.008 0.276 0.360 0.356
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.7769 -0.01415 0.004 0.200 0.388 0.408
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4933 0.34093 0.568 0.000 0.000 0.432
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.1118 0.80651 0.000 0.964 0.036 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3754 0.68491 0.852 0.000 0.064 0.084
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.5693 0.56104 0.688 0.000 0.240 0.072
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.5387 0.18794 0.584 0.000 0.400 0.016
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1940 0.80117 0.000 0.924 0.076 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.3495 0.77962 0.000 0.844 0.016 0.140
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.5933 0.30844 0.000 0.552 0.040 0.408
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4907 0.36007 0.580 0.000 0.000 0.420
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3164 0.68252 0.884 0.000 0.064 0.052
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4122 0.51446 0.236 0.000 0.004 0.760
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.2921 0.68266 0.860 0.000 0.000 0.140
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.5013 0.47656 0.000 0.292 0.688 0.020
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.2401 0.63244 0.092 0.000 0.004 0.904
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.5173 0.43301 0.000 0.320 0.660 0.020
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.5285 0.26954 0.000 0.524 0.008 0.468
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.5602 0.17286 0.000 0.408 0.024 0.568
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.8221 0.08829 0.064 0.104 0.440 0.392
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 4 0.5894 0.25204 0.392 0.000 0.040 0.568
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2921 0.68266 0.860 0.000 0.000 0.140
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.5250 0.62389 0.744 0.000 0.176 0.080
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.3972 0.60736 0.004 0.164 0.816 0.016
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.5310 0.23627 0.412 0.000 0.576 0.012
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.7597 0.23466 0.204 0.000 0.356 0.440
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.3591 0.51229 0.168 0.000 0.824 0.008
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.3166 0.64548 0.868 0.000 0.116 0.016
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1716 0.80277 0.000 0.936 0.064 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.7290 0.27919 0.112 0.032 0.256 0.600
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.2742 0.80575 0.000 0.900 0.024 0.076
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.5998 0.51478 0.664 0.000 0.248 0.088
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.5999 0.37554 0.552 0.000 0.044 0.404
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.6409 0.33308 0.000 0.364 0.076 0.560
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.1798 0.81603 0.000 0.944 0.040 0.016
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.5267 0.54561 0.000 0.048 0.712 0.240
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.5829 0.53473 0.024 0.048 0.216 0.712
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 4 0.6137 -0.02577 0.448 0.000 0.048 0.504
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.4830 0.40420 0.608 0.000 0.000 0.392
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.7478 0.38874 0.504 0.000 0.240 0.256
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.6447 0.51423 0.028 0.076 0.220 0.676
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.4079 0.58298 0.180 0.000 0.020 0.800
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.5021 0.53009 0.180 0.000 0.756 0.064
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.4916 0.35136 0.576 0.000 0.000 0.424
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.1545 0.80279 0.000 0.952 0.040 0.008
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.5452 0.32183 0.360 0.000 0.616 0.024
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.7287 0.03852 0.000 0.384 0.152 0.464
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.3908 0.45790 0.212 0.000 0.784 0.004
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.5540 0.66398 0.000 0.728 0.108 0.164
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.3894 0.61991 0.000 0.068 0.844 0.088
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.3577 0.60159 0.156 0.000 0.012 0.832
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 3 0.9153 0.18310 0.316 0.080 0.380 0.224
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.7298 0.37835 0.004 0.152 0.524 0.320
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.2882 0.80026 0.000 0.892 0.084 0.024
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.2149 0.68518 0.912 0.000 0.000 0.088
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.1890 0.81388 0.000 0.936 0.008 0.056
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 4 0.7352 0.30646 0.176 0.000 0.328 0.496
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.4713 0.38439 0.640 0.000 0.360 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.3463 0.78798 0.000 0.864 0.040 0.096
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.4720 0.45513 0.720 0.000 0.264 0.016
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.1389 0.81610 0.000 0.952 0.000 0.048
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.7852 -0.09628 0.008 0.404 0.192 0.396
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#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.7437 0.21954 0.004 0.212 0.248 0.536
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1284 0.81593 0.000 0.964 0.012 0.024
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3311 0.67135 0.828 0.000 0.000 0.172
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0657 0.81500 0.000 0.984 0.012 0.004
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.1584 0.81662 0.000 0.952 0.012 0.036
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.5378 0.54351 0.036 0.004 0.696 0.264
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.7404 0.19906 0.484 0.000 0.336 0.180
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.2271 0.66429 0.916 0.000 0.076 0.008
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6944 0.30607 0.004 0.152 0.248 0.596
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5004 0.24745 0.000 0.392 0.004 0.604
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.2807 0.63729 0.020 0.044 0.024 0.912
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.7767 0.26572 0.004 0.296 0.232 0.468
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.7405 0.17671 0.004 0.400 0.144 0.452
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4599 0.72388 0.000 0.800 0.112 0.088
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1629 0.81547 0.000 0.952 0.024 0.024
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5856 0.23265 0.408 0.000 0.556 0.036
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4882 0.49309 0.000 0.272 0.708 0.020
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.6638 0.43513 0.012 0.168 0.160 0.660
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.7761 0.15850 0.100 0.040 0.368 0.492
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.4679 0.41737 0.648 0.000 0.352 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.3462 0.62298 0.020 0.004 0.116 0.860
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.2466 0.81097 0.000 0.916 0.028 0.056
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.4877 0.38022 0.592 0.000 0.000 0.408
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.5165 0.52869 0.168 0.000 0.752 0.080
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4856 0.65365 0.780 0.000 0.136 0.084
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.7656 0.34232 0.096 0.036 0.492 0.376
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2944 0.68624 0.868 0.000 0.004 0.128
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1716 0.80277 0.000 0.936 0.064 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1109 0.67426 0.968 0.000 0.028 0.004
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.5000 -0.17856 0.500 0.000 0.000 0.500
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.3877 0.75872 0.000 0.840 0.048 0.112
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1284 0.81593 0.000 0.964 0.012 0.024
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4852 0.59602 0.072 0.000 0.152 0.776
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1807 0.81495 0.000 0.940 0.008 0.052
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4331 0.56010 0.712 0.000 0.000 0.288
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4482 0.50141 0.000 0.264 0.728 0.008
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6163 0.51981 0.164 0.000 0.676 0.160
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.2988 0.62441 0.112 0.000 0.012 0.876
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2480 0.80651 0.000 0.904 0.008 0.088
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6238 0.54871 0.000 0.632 0.092 0.276
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5800 0.23425 0.548 0.000 0.420 0.032
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2675 0.79915 0.000 0.892 0.008 0.100
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2281 0.68597 0.904 0.000 0.000 0.096
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4277 0.36457 0.280 0.000 0.720 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4936 0.58645 0.000 0.672 0.012 0.316
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.2704 0.68643 0.876 0.000 0.000 0.124
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.7009 -0.09434 0.000 0.440 0.116 0.444
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4728 0.56357 0.752 0.000 0.216 0.032
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5512 -0.10824 0.488 0.000 0.016 0.496
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4492 0.61178 0.020 0.028 0.812 0.140
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5161 0.42818 0.300 0.000 0.676 0.024
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.7501 0.19045 0.004 0.492 0.172 0.332
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.7253 0.29658 0.172 0.000 0.520 0.308
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5494 0.59018 0.076 0.000 0.716 0.208
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5230 0.56957 0.008 0.672 0.048 0.264 0.008
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 5 0.6792 0.26850 0.228 0.000 0.300 0.008 0.464
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5301 0.50052 0.120 0.192 0.004 0.684 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3318 0.60949 0.180 0.000 0.000 0.012 0.808
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.6639 0.21680 0.008 0.472 0.180 0.340 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5027 0.60355 0.008 0.704 0.048 0.232 0.008
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2580 0.59610 0.892 0.000 0.000 0.044 0.064
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.3807 0.55548 0.240 0.000 0.000 0.012 0.748
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4045 0.29298 0.644 0.000 0.000 0.000 0.356
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4814 0.12218 0.568 0.000 0.004 0.016 0.412
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.6113 0.43350 0.004 0.584 0.180 0.232 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5168 0.13805 0.452 0.000 0.040 0.508 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5229 0.09991 0.548 0.000 0.048 0.404 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4943 0.60698 0.008 0.704 0.040 0.240 0.008
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.6579 0.29411 0.168 0.032 0.220 0.580 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4743 0.53234 0.000 0.124 0.772 0.040 0.064
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0703 0.74108 0.000 0.976 0.000 0.024 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4938 0.54159 0.000 0.084 0.768 0.084 0.064
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0794 0.74073 0.000 0.972 0.000 0.028 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.6121 0.39737 0.044 0.020 0.240 0.648 0.048
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7423 0.46346 0.104 0.088 0.160 0.600 0.048
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4944 0.40188 0.020 0.032 0.236 0.708 0.004
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.5932 0.31216 0.008 0.000 0.536 0.088 0.368
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.6676 0.11253 0.200 0.000 0.484 0.008 0.308
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.6362 0.30739 0.264 0.000 0.176 0.552 0.008
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2142 0.72425 0.004 0.920 0.028 0.048 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.6625 0.54351 0.164 0.000 0.112 0.100 0.624
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.3154 0.64854 0.104 0.000 0.012 0.024 0.860
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4225 0.27147 0.632 0.000 0.000 0.004 0.364
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.6094 0.34266 0.004 0.552 0.132 0.312 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.4996 0.61271 0.100 0.000 0.092 0.048 0.760
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2136 0.72984 0.000 0.904 0.008 0.088 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5620 0.44514 0.660 0.000 0.064 0.244 0.032
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3480 0.43745 0.752 0.000 0.000 0.000 0.248
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4326 0.67303 0.008 0.780 0.040 0.164 0.008
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 5 0.6778 0.24678 0.216 0.000 0.316 0.008 0.460
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3421 0.49840 0.000 0.004 0.816 0.016 0.164
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.8016 0.33609 0.216 0.000 0.168 0.168 0.448
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.3061 0.55125 0.844 0.000 0.000 0.020 0.136
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4670 0.06804 0.548 0.000 0.004 0.008 0.440
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.3558 0.69532 0.020 0.816 0.008 0.156 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.4341 0.18147 0.592 0.000 0.004 0.404 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2513 0.72015 0.000 0.876 0.008 0.116 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3966 0.63682 0.004 0.784 0.036 0.176 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2300 0.60416 0.908 0.000 0.000 0.052 0.040
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.7305 0.11616 0.008 0.320 0.188 0.456 0.028
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.3722 0.49201 0.004 0.000 0.176 0.024 0.796
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.5506 0.48817 0.008 0.616 0.048 0.320 0.008
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.6873 0.15949 0.008 0.312 0.188 0.484 0.008
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.4581 0.65406 0.008 0.760 0.048 0.176 0.008
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.5117 0.52229 0.000 0.160 0.736 0.040 0.064
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.3086 0.50635 0.816 0.000 0.000 0.004 0.180
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4359 0.15813 0.584 0.000 0.000 0.004 0.412
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1507 0.61587 0.012 0.000 0.024 0.012 0.952
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.3777 0.59401 0.192 0.000 0.004 0.020 0.784
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2446 0.60181 0.900 0.000 0.000 0.056 0.044
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.6289 0.51127 0.108 0.040 0.216 0.632 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3312 0.56172 0.000 0.020 0.864 0.048 0.068
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.7027 0.16486 0.016 0.096 0.372 0.480 0.036
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.6418 -0.11831 0.016 0.084 0.440 0.452 0.008
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.2588 0.60107 0.892 0.000 0.000 0.060 0.048
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.1372 0.74196 0.004 0.956 0.016 0.024 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 5 0.3999 0.38716 0.344 0.000 0.000 0.000 0.656
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.5594 0.60102 0.152 0.000 0.084 0.056 0.708
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 5 0.6926 0.22602 0.256 0.000 0.312 0.008 0.424
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2341 0.72571 0.020 0.912 0.056 0.012 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.3632 0.66366 0.004 0.800 0.020 0.176 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.6399 0.11889 0.040 0.380 0.072 0.508 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.2376 0.60027 0.904 0.000 0.000 0.044 0.052
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.4016 0.51581 0.272 0.000 0.000 0.012 0.716
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.3210 0.48100 0.788 0.000 0.000 0.212 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4045 0.29298 0.644 0.000 0.000 0.000 0.356
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4583 0.53089 0.000 0.084 0.776 0.120 0.020
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.4449 -0.02992 0.512 0.000 0.004 0.484 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.5081 0.49860 0.000 0.136 0.720 0.136 0.008
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.5658 0.32384 0.076 0.300 0.012 0.612 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.6170 0.51484 0.092 0.144 0.096 0.668 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.6434 0.15795 0.012 0.048 0.472 0.432 0.036
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.5208 0.49989 0.720 0.000 0.068 0.180 0.032
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4045 0.29298 0.644 0.000 0.000 0.000 0.356
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.5109 0.60180 0.172 0.000 0.052 0.044 0.732
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.3927 0.55621 0.000 0.044 0.832 0.048 0.076
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.6428 0.14834 0.156 0.000 0.516 0.008 0.320
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 3 0.7913 0.20926 0.072 0.000 0.348 0.272 0.308
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.4227 0.36509 0.000 0.000 0.692 0.016 0.292
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.3218 0.63858 0.128 0.000 0.004 0.024 0.844
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.2124 0.72870 0.020 0.924 0.044 0.012 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.7223 0.12221 0.328 0.012 0.272 0.384 0.004
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.4912 0.61873 0.008 0.720 0.048 0.216 0.008
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.6680 0.51290 0.128 0.000 0.124 0.124 0.624
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.5270 0.47583 0.692 0.004 0.004 0.096 0.204
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.7115 0.48593 0.096 0.160 0.132 0.600 0.012
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.3675 0.71099 0.008 0.840 0.044 0.100 0.008
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.5321 0.49716 0.008 0.048 0.692 0.232 0.020
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.6880 0.45524 0.108 0.012 0.208 0.604 0.068
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.4398 0.57499 0.780 0.000 0.008 0.100 0.112
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.2569 0.59650 0.892 0.000 0.000 0.040 0.068
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.7044 0.49156 0.200 0.000 0.096 0.132 0.572
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.6107 0.26959 0.048 0.032 0.344 0.568 0.008
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.5591 0.24648 0.588 0.000 0.032 0.348 0.032
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#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.7021 0.27819 0.020 0.000 0.456 0.308 0.216
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.6584 0.52779 0.104 0.076 0.188 0.628 0.004
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.3340 0.55120 0.000 0.012 0.856 0.088 0.044
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.6519 0.29470 0.112 0.020 0.528 0.336 0.004
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.5853 0.43369 0.004 0.000 0.624 0.188 0.184
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.5275 0.55855 0.008 0.664 0.048 0.272 0.008
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.6467 0.44959 0.184 0.120 0.068 0.628 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.6810 0.32326 0.008 0.500 0.320 0.160 0.012
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.6799 0.32269 0.008 0.000 0.464 0.232 0.296
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.7881 0.23707 0.156 0.000 0.132 0.448 0.264
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.5995 0.17010 0.016 0.072 0.512 0.400 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.3714 0.51148 0.000 0.000 0.812 0.056 0.132
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.7048 0.49314 0.108 0.112 0.160 0.608 0.012
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.4251 0.33747 0.672 0.000 0.012 0.316 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.4750 0.56112 0.040 0.712 0.236 0.012 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.8071 0.21829 0.304 0.000 0.108 0.212 0.376
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.6281 0.00779 0.020 0.088 0.420 0.472 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.2813 0.57031 0.868 0.000 0.000 0.024 0.108
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.6359 0.29504 0.036 0.000 0.284 0.580 0.100
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1408 0.74104 0.000 0.948 0.008 0.044 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.5719 0.03854 0.008 0.408 0.064 0.520 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.7304 0.16369 0.036 0.000 0.404 0.360 0.200
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4637 0.54432 0.000 0.088 0.788 0.060 0.064
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.6405 0.37987 0.164 0.000 0.612 0.036 0.188
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.7070 0.28797 0.016 0.000 0.428 0.248 0.308
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.3527 0.66651 0.004 0.820 0.028 0.148 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1731 0.73305 0.008 0.940 0.040 0.012 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.6425 0.07054 0.140 0.000 0.480 0.008 0.372
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.6806 0.40726 0.088 0.244 0.092 0.576 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.3644 0.56256 0.000 0.032 0.848 0.052 0.068
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.2670 0.60575 0.888 0.000 0.004 0.080 0.028
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.4832 0.62477 0.008 0.720 0.040 0.224 0.008
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.7096 0.35715 0.092 0.000 0.184 0.156 0.568
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.6705 0.19736 0.008 0.460 0.128 0.392 0.012
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.7092 0.46352 0.128 0.016 0.188 0.596 0.072
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.4045 0.29298 0.644 0.000 0.000 0.000 0.356
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5169 0.47715 0.672 0.000 0.012 0.260 0.056
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.6753 0.06361 0.012 0.120 0.436 0.420 0.012
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.7006 0.07579 0.040 0.160 0.296 0.504 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0932 0.74096 0.004 0.972 0.004 0.020 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3636 0.40323 0.728 0.000 0.000 0.000 0.272
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1704 0.73845 0.000 0.928 0.004 0.068 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0794 0.74073 0.000 0.972 0.000 0.028 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.5467 0.47106 0.052 0.004 0.660 0.264 0.020
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6028 0.24276 0.612 0.000 0.188 0.008 0.192
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.3489 0.58361 0.208 0.000 0.004 0.004 0.784
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6237 0.16955 0.052 0.056 0.328 0.564 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.5772 0.37470 0.120 0.296 0.000 0.584 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.5034 0.37347 0.348 0.020 0.016 0.616 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.5757 0.30133 0.004 0.088 0.304 0.600 0.004
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.6785 0.39550 0.020 0.192 0.204 0.572 0.012
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6036 0.40677 0.000 0.580 0.208 0.212 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1869 0.73775 0.008 0.936 0.028 0.028 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.6630 0.16258 0.208 0.000 0.504 0.008 0.280
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.5154 0.52363 0.000 0.164 0.732 0.040 0.064
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.7611 0.15898 0.180 0.084 0.268 0.468 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.7162 -0.04036 0.056 0.020 0.388 0.464 0.072
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.2166 0.58245 0.004 0.000 0.072 0.012 0.912
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5543 0.50783 0.212 0.004 0.104 0.672 0.008
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.5309 0.59164 0.008 0.688 0.068 0.228 0.008
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2580 0.59677 0.892 0.000 0.000 0.044 0.064
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.6701 0.21186 0.008 0.000 0.424 0.180 0.388
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.4210 0.59840 0.184 0.000 0.016 0.028 0.772
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6532 0.34472 0.156 0.016 0.564 0.260 0.004
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.4291 0.10974 0.536 0.000 0.000 0.000 0.464
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2270 0.72651 0.020 0.916 0.052 0.012 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.4178 0.45923 0.292 0.000 0.004 0.008 0.696
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2124 0.60450 0.916 0.000 0.000 0.056 0.028
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4835 0.58949 0.004 0.724 0.084 0.188 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0932 0.74096 0.004 0.972 0.004 0.020 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6612 0.43524 0.176 0.000 0.228 0.568 0.028
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2006 0.73349 0.000 0.916 0.012 0.072 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3650 0.53112 0.796 0.000 0.000 0.028 0.176
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4765 0.53736 0.000 0.108 0.776 0.052 0.064
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.6182 0.49712 0.116 0.000 0.656 0.168 0.060
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4990 0.22959 0.600 0.000 0.040 0.360 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3882 0.64243 0.000 0.756 0.020 0.224 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6676 0.14209 0.004 0.432 0.200 0.364 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.5126 0.47164 0.024 0.000 0.176 0.076 0.724
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3328 0.68342 0.004 0.812 0.008 0.176 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4060 0.28550 0.640 0.000 0.000 0.000 0.360
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4816 0.08008 0.008 0.000 0.500 0.008 0.484
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.5313 -0.11133 0.004 0.452 0.040 0.504 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4150 0.23033 0.612 0.000 0.000 0.000 0.388
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.7217 0.09363 0.028 0.324 0.220 0.428 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.4497 0.63346 0.116 0.000 0.064 0.032 0.788
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.6033 0.52905 0.664 0.000 0.044 0.140 0.152
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4687 0.55617 0.000 0.044 0.780 0.108 0.068
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.6469 0.22204 0.172 0.000 0.544 0.012 0.272
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.7044 0.32917 0.016 0.212 0.244 0.516 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.6852 0.27135 0.012 0.000 0.468 0.300 0.220
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5530 0.52909 0.060 0.000 0.720 0.120 0.100
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4076 -0.08181 0.000 0.540 0.008 0.000 0.000 0.452
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5185 0.45458 0.328 0.000 0.564 0.000 0.108 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6422 0.21868 0.024 0.492 0.036 0.352 0.000 0.096
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4688 0.48142 0.288 0.000 0.064 0.004 0.644 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.4871 0.29981 0.000 0.024 0.036 0.616 0.000 0.324
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4095 -0.16602 0.000 0.512 0.008 0.000 0.000 0.480
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2665 0.73707 0.868 0.016 0.012 0.104 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.5024 0.19155 0.440 0.000 0.052 0.008 0.500 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2308 0.67691 0.892 0.000 0.040 0.000 0.068 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2537 0.66317 0.872 0.000 0.032 0.000 0.096 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.5133 0.08672 0.000 0.020 0.044 0.524 0.000 0.412
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5508 0.31403 0.200 0.212 0.004 0.584 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.5093 0.07751 0.388 0.084 0.000 0.528 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3860 -0.12525 0.000 0.528 0.000 0.000 0.000 0.472
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3293 0.49709 0.008 0.052 0.048 0.860 0.028 0.004
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4901 0.60543 0.000 0.040 0.748 0.124 0.036 0.052
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.1151 0.73101 0.000 0.032 0.000 0.012 0.000 0.956
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4515 0.59826 0.000 0.020 0.760 0.148 0.036 0.036
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.1297 0.72888 0.000 0.040 0.000 0.012 0.000 0.948
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.5030 0.49679 0.008 0.724 0.036 0.084 0.144 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2773 0.56855 0.004 0.884 0.008 0.008 0.060 0.036
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.6078 0.17446 0.000 0.304 0.088 0.548 0.056 0.004
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.5017 0.36903 0.000 0.004 0.232 0.120 0.644 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3555 0.60603 0.184 0.000 0.776 0.000 0.040 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.4839 0.42977 0.116 0.108 0.000 0.728 0.048 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.2585 0.70326 0.000 0.012 0.024 0.084 0.000 0.880
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.4253 0.66274 0.100 0.100 0.016 0.008 0.776 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.2747 0.64449 0.108 0.004 0.028 0.000 0.860 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2750 0.66579 0.868 0.000 0.048 0.004 0.080 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.5020 0.31313 0.000 0.028 0.044 0.616 0.000 0.312
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.3362 0.66878 0.088 0.052 0.016 0.004 0.840 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.2595 0.66731 0.000 0.160 0.000 0.004 0.000 0.836
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5155 0.31500 0.508 0.024 0.008 0.436 0.024 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2484 0.71052 0.896 0.000 0.024 0.036 0.044 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.3899 0.37054 0.000 0.404 0.000 0.004 0.000 0.592
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.5025 0.50028 0.284 0.000 0.608 0.000 0.108 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4971 0.56395 0.000 0.044 0.716 0.080 0.156 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.5195 0.64003 0.112 0.148 0.028 0.012 0.700 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.2976 0.73475 0.844 0.012 0.000 0.124 0.020 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3337 0.62179 0.824 0.000 0.064 0.004 0.108 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 6 0.3538 0.68159 0.000 0.108 0.016 0.048 0.004 0.824
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.6339 0.15655 0.296 0.264 0.008 0.428 0.004 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 6 0.2838 0.63806 0.000 0.188 0.000 0.004 0.000 0.808
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.4938 0.33373 0.000 0.024 0.036 0.344 0.000 0.596
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3019 0.72462 0.840 0.020 0.000 0.128 0.012 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4978 0.45444 0.000 0.728 0.016 0.036 0.076 0.144
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.2932 0.57403 0.016 0.000 0.164 0.000 0.820 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3934 0.13288 0.000 0.616 0.008 0.000 0.000 0.376
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6324 0.38238 0.000 0.580 0.044 0.244 0.028 0.104
#> 36B2E208-FF01-4249-92C3-BE77D426691B 6 0.4722 0.20022 0.000 0.476 0.012 0.024 0.000 0.488
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4668 0.60254 0.000 0.016 0.756 0.128 0.036 0.064
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2811 0.73062 0.876 0.008 0.012 0.076 0.028 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.2812 0.65110 0.856 0.000 0.048 0.000 0.096 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.4111 0.52346 0.084 0.000 0.176 0.000 0.740 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.3752 0.60515 0.200 0.000 0.036 0.004 0.760 0.000
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#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3003 0.56965 0.016 0.000 0.812 0.000 0.172 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.6561 0.12363 0.000 0.308 0.040 0.448 0.000 0.204
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.2660 0.66208 0.868 0.000 0.048 0.000 0.084 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.4181 0.48907 0.000 0.020 0.044 0.760 0.004 0.172
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.4157 0.64367 0.088 0.000 0.072 0.052 0.788 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5406 0.39489 0.512 0.016 0.016 0.416 0.040 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4166 0.59509 0.000 0.008 0.772 0.156 0.040 0.024
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.2868 0.62973 0.112 0.004 0.852 0.000 0.032 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4962 0.47132 0.000 0.712 0.016 0.180 0.024 0.068
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.6463 0.46064 0.000 0.192 0.112 0.136 0.560 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4037 0.60171 0.008 0.016 0.768 0.176 0.032 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.907 0.962 0.5014 0.499 0.499
#> 3 3 0.744 0.779 0.900 0.3074 0.756 0.551
#> 4 4 0.661 0.726 0.855 0.1427 0.805 0.504
#> 5 5 0.691 0.665 0.800 0.0599 0.892 0.613
#> 6 6 0.799 0.754 0.866 0.0436 0.923 0.659
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.95644 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.96081 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.95644 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.96081 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.95644 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.95644 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.96081 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.96081 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.96081 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.96081 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.95644 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7219 0.73663 0.200 0.800
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.9795 0.26754 0.416 0.584
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.95644 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.95644 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.9358 0.47908 0.352 0.648
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.95644 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7219 0.74630 0.200 0.800
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.95644 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.95644 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.95644 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.95644 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.96081 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.96081 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5059 0.85219 0.888 0.112
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.95644 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.96081 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.96081 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.96081 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.95644 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.96081 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.95644 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.96081 1.000 0.000
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#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.95644 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.96081 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.96081 1.000 0.000
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#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.96081 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.96081 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.95644 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.96081 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.95644 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.95644 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.96081 1.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.95644 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.96081 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.95644 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.95644 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.95644 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.7219 0.74630 0.200 0.800
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.96081 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.96081 1.000 0.000
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#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.96081 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.95644 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.9710 0.36355 0.400 0.600
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.95644 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.0000 0.95644 0.000 1.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.96081 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.95644 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.96081 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.96081 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.96081 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.95644 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.95644 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.95644 0.000 1.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.96081 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.96081 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.7219 0.74408 0.800 0.200
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.96081 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0000 0.95644 0.000 1.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9608 0.39076 0.616 0.384
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.1414 0.93991 0.020 0.980
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.95644 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.95644 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.9775 0.33878 0.412 0.588
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.96081 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.96081 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.96081 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.9833 0.29649 0.424 0.576
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.96081 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.96081 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.96081 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.96081 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.95644 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.96081 1.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.95644 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.96081 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.6531 0.78704 0.832 0.168
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.95644 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.95644 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.9710 0.36355 0.400 0.600
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.95644 0.000 1.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.96081 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.96081 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.96081 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.0000 0.95644 0.000 1.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.7219 0.74408 0.800 0.200
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0000 0.96081 1.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.96081 1.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.95644 0.000 1.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.96081 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.0000 0.95644 0.000 1.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.0000 0.96081 1.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.0000 0.95644 0.000 1.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.9661 0.38419 0.392 0.608
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0000 0.96081 1.000 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.7219 0.73796 0.800 0.200
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.0000 0.95644 0.000 1.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.95644 0.000 1.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.96081 1.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.95644 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0000 0.96081 1.000 0.000
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#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.95644 0.000 1.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.96081 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.95644 0.000 1.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.95644 0.000 1.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.96081 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.96081 1.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.6623 0.77582 0.172 0.828
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0000 0.96081 1.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.96081 1.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.95644 0.000 1.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.9686 0.37217 0.604 0.396
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#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.9996 -0.00997 0.512 0.488
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#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.7219 0.74408 0.800 0.200
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#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.95644 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.95644 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.96081 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.96081 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.96081 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.95644 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.95644 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.3274 0.90334 0.060 0.940
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.95644 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.95644 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.95644 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.95644 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.96081 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.7219 0.74630 0.200 0.800
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0000 0.95644 0.000 1.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.4022 0.88713 0.920 0.080
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#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7219 0.73663 0.200 0.800
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.95644 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.96081 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.96081 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.96081 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.96081 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.96081 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.95644 0.000 1.000
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#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.96081 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.95644 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.95644 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.96081 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.95644 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.96081 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.8499 0.62897 0.276 0.724
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.96081 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1633 0.94098 0.976 0.024
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.95644 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.95644 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.96081 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.95644 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.96081 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.96081 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.95644 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.96081 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.95644 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.96081 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.96081 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.7219 0.73796 0.800 0.200
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.96081 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.95644 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.7219 0.73796 0.800 0.200
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.96081 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9532 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5138 0.6504 0.252 0.000 0.748
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9532 0.000 1.000 0.000
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#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.0000 0.9532 0.000 1.000 0.000
#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.0747 0.8698 0.984 0.000 0.016
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0892 0.9485 0.000 0.980 0.020
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0892 0.9485 0.000 0.980 0.020
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.0892 0.9485 0.000 0.980 0.020
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 3 0.5138 0.6504 0.252 0.000 0.748
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 3 0.6204 0.1121 0.424 0.000 0.576
#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.0892 0.7766 0.020 0.000 0.980
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 3 0.0892 0.7766 0.020 0.000 0.980
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0000 0.8810 1.000 0.000 0.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.2711 0.8105 0.912 0.000 0.088
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 3 0.0892 0.7766 0.020 0.000 0.980
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.0892 0.7766 0.020 0.000 0.980
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0000 0.9532 0.000 1.000 0.000
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0000 0.9532 0.000 1.000 0.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.4842 0.6824 0.000 0.776 0.224
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0892 0.8657 0.980 0.020 0.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.0892 0.7766 0.020 0.000 0.980
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0983 0.8670 0.980 0.016 0.004
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.0000 0.8810 1.000 0.000 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.4750 0.7105 0.000 0.784 0.216
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.0000 0.9532 0.000 1.000 0.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.8810 1.000 0.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.8810 1.000 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 3 0.6192 0.1255 0.420 0.000 0.580
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.6045 0.3962 0.000 0.380 0.620
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0892 0.9485 0.000 0.980 0.020
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.4842 0.6639 0.224 0.000 0.776
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0747 0.9499 0.000 0.984 0.016
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.5138 0.6504 0.252 0.000 0.748
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.0892 0.7766 0.020 0.000 0.980
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.5948 0.5097 0.640 0.000 0.360
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0747 0.9499 0.000 0.984 0.016
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0000 0.8810 1.000 0.000 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.9532 0.000 1.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.9532 0.000 1.000 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.9532 0.000 1.000 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.0892 0.8665 0.980 0.000 0.020
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.0892 0.8665 0.980 0.000 0.020
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0892 0.7766 0.020 0.000 0.980
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0892 0.9485 0.000 0.980 0.020
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.8810 1.000 0.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0892 0.7766 0.020 0.000 0.980
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0892 0.7766 0.020 0.000 0.980
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.9532 0.000 1.000 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.8810 1.000 0.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.8810 1.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0592 0.8728 0.988 0.000 0.012
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.5650 0.5784 0.312 0.000 0.688
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.9532 0.000 1.000 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0747 0.9499 0.000 0.984 0.016
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.6026 0.4834 0.624 0.000 0.376
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.1860 0.8432 0.948 0.000 0.052
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.0747 0.7756 0.016 0.000 0.984
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.9532 0.000 1.000 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.1643 0.7600 0.000 0.044 0.956
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.6045 0.4512 0.380 0.000 0.620
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0000 0.7706 0.000 0.000 1.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.9532 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0892 0.9485 0.000 0.980 0.020
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0424 0.9520 0.000 0.992 0.008
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0892 0.7766 0.020 0.000 0.980
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.6045 0.4774 0.620 0.000 0.380
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.6295 0.0650 0.000 0.528 0.472
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0892 0.7766 0.020 0.000 0.980
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0000 0.9532 0.000 1.000 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0000 0.8810 1.000 0.000 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.8689 0.3964 0.204 0.596 0.200
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.5988 0.4972 0.632 0.000 0.368
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0892 0.9485 0.000 0.980 0.020
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.8810 1.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.2804 0.7431 0.060 0.016 0.924
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0237 0.9528 0.000 0.996 0.004
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0892 0.9485 0.000 0.980 0.020
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0892 0.7766 0.020 0.000 0.980
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.6045 0.3962 0.000 0.380 0.620
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5178 0.6463 0.256 0.000 0.744
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0892 0.7766 0.020 0.000 0.980
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0892 0.9485 0.000 0.980 0.020
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0747 0.9499 0.000 0.984 0.016
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4702 0.6830 0.212 0.000 0.788
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.9532 0.000 1.000 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.5926 0.4444 0.000 0.356 0.644
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.8810 1.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9532 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0892 0.7766 0.020 0.000 0.980
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9532 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.5681 0.6438 0.016 0.748 0.236
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.8810 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.8810 1.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.4291 0.7656 0.000 0.820 0.180
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0892 0.9485 0.000 0.980 0.020
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0424 0.9520 0.000 0.992 0.008
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.8810 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0237 0.9528 0.000 0.996 0.004
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9532 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.3941 0.7101 0.156 0.000 0.844
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6235 -0.0207 0.564 0.000 0.436
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.6045 0.4774 0.620 0.000 0.380
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.5178 0.6414 0.000 0.744 0.256
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0237 0.9528 0.000 0.996 0.004
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.6224 0.5708 0.296 0.688 0.016
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9532 0.000 1.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.9532 0.000 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0892 0.9485 0.000 0.980 0.020
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0424 0.9520 0.000 0.992 0.008
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5138 0.6504 0.252 0.000 0.748
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6045 0.3962 0.000 0.380 0.620
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.4750 0.7105 0.000 0.784 0.216
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0000 0.7706 0.000 0.000 1.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0892 0.7766 0.020 0.000 0.980
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.5939 0.6624 0.748 0.028 0.224
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9532 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.8810 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0892 0.7766 0.020 0.000 0.980
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.6045 0.4774 0.620 0.000 0.380
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6045 0.4512 0.380 0.000 0.620
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.8810 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0747 0.9499 0.000 0.984 0.016
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.6274 0.2803 0.456 0.000 0.544
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.8810 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0892 0.9485 0.000 0.980 0.020
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0424 0.9520 0.000 0.992 0.008
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6045 0.4774 0.620 0.000 0.380
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9532 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8810 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.6045 0.3962 0.000 0.380 0.620
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4887 0.6631 0.228 0.000 0.772
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.8810 1.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9532 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0892 0.9485 0.000 0.980 0.020
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0892 0.7766 0.020 0.000 0.980
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9532 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8810 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0892 0.7766 0.020 0.000 0.980
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0237 0.9528 0.000 0.996 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8810 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0892 0.9485 0.000 0.980 0.020
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.0892 0.7766 0.020 0.000 0.980
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.8810 1.000 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4555 0.6738 0.000 0.200 0.800
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5058 0.6576 0.244 0.000 0.756
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9532 0.000 1.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0892 0.7766 0.020 0.000 0.980
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4887 0.6600 0.228 0.000 0.772
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2973 0.76214 0.000 0.144 0.000 0.856
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 3 0.4855 0.43209 0.400 0.000 0.600 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.3444 0.79846 0.000 0.184 0.000 0.816
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 3 0.4933 0.36597 0.432 0.000 0.568 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3219 0.68811 0.836 0.000 0.164 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5410 0.69452 0.728 0.080 0.000 0.192
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.2926 0.83298 0.896 0.056 0.000 0.048
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.3610 0.67198 0.000 0.800 0.000 0.200
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.6264 0.47490 0.000 0.560 0.376 0.064
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.5000 0.27657 0.000 0.496 0.000 0.504
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.4328 0.66943 0.000 0.748 0.244 0.008
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.4790 0.57788 0.000 0.380 0.000 0.620
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.0000 0.81407 0.000 0.000 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.0707 0.80627 0.000 0.000 0.020 0.980
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3649 0.71375 0.000 0.204 0.000 0.796
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0336 0.79427 0.000 0.008 0.992 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6542 0.44346 0.620 0.128 0.252 0.000
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#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 4 0.4967 0.44030 0.000 0.452 0.000 0.548
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.3764 0.59957 0.784 0.000 0.216 0.000
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 4 0.0000 0.81407 0.000 0.000 0.000 1.000
#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.6066 0.66008 0.692 0.116 0.004 0.188
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 3 0.3688 0.69963 0.208 0.000 0.792 0.000
#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.0707 0.79130 0.000 0.020 0.980 0.000
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.2704 0.75100 0.876 0.000 0.124 0.000
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.1356 0.79500 0.032 0.008 0.960 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 4 0.0188 0.81509 0.000 0.004 0.000 0.996
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 4 0.1637 0.78966 0.000 0.000 0.060 0.940
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0469 0.88298 0.988 0.000 0.000 0.012
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.0336 0.79427 0.000 0.008 0.992 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.3439 0.81542 0.868 0.048 0.000 0.084
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.1629 0.86635 0.952 0.024 0.000 0.024
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.2081 0.80131 0.000 0.916 0.000 0.084
#> 93429F04-8404-4E8C-B654-9D2216BA432C 4 0.3907 0.67370 0.000 0.232 0.000 0.768
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0817 0.87745 0.976 0.000 0.000 0.024
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 3 0.3873 0.68995 0.228 0.000 0.772 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.3444 0.72327 0.000 0.816 0.184 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.5252 0.73032 0.080 0.776 0.128 0.016
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.4776 0.09037 0.000 0.624 0.000 0.376
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.0921 0.79695 0.028 0.000 0.972 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.4955 0.05127 0.556 0.000 0.444 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.3444 0.76212 0.816 0.000 0.000 0.184
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 4 0.3486 0.79617 0.000 0.188 0.000 0.812
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.1792 0.81807 0.000 0.068 0.000 0.932
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 4 0.3486 0.79617 0.000 0.188 0.000 0.812
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.5332 0.70357 0.736 0.080 0.000 0.184
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.3498 0.73806 0.832 0.160 0.000 0.008
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0188 0.79619 0.004 0.000 0.996 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0188 0.79619 0.004 0.000 0.996 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0188 0.79619 0.004 0.000 0.996 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.0817 0.81850 0.000 0.024 0.000 0.976
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.1042 0.87508 0.972 0.020 0.000 0.008
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.4594 0.60915 0.280 0.008 0.712 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.1792 0.80131 0.000 0.068 0.000 0.932
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.1940 0.80472 0.000 0.924 0.000 0.076
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 3 0.4933 0.36597 0.432 0.000 0.568 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.2760 0.74469 0.872 0.000 0.128 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.0469 0.81505 0.000 0.012 0.000 0.988
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.4669 0.64080 0.000 0.052 0.780 0.168
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.7358 0.17184 0.160 0.448 0.392 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.2704 0.77321 0.000 0.876 0.000 0.124
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.5508 0.23556 0.020 0.000 0.408 0.572
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.3925 0.74175 0.000 0.808 0.176 0.016
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0707 0.79130 0.000 0.020 0.980 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.0000 0.81407 0.000 0.000 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.3400 0.76543 0.820 0.000 0.000 0.180
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.2494 0.79385 0.048 0.916 0.000 0.036
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 3 0.7187 0.03103 0.424 0.000 0.440 0.136
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.1118 0.81447 0.000 0.964 0.000 0.036
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.4088 0.65040 0.004 0.000 0.764 0.232
#> A2007795-C728-4688-B199-AE89500011D2 2 0.3942 0.63444 0.000 0.764 0.000 0.236
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.5298 0.67402 0.000 0.708 0.244 0.048
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.1211 0.81663 0.000 0.960 0.000 0.040
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4204 0.69917 0.192 0.020 0.788 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0469 0.81505 0.000 0.012 0.000 0.988
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.6197 0.42930 0.000 0.544 0.400 0.056
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0188 0.79619 0.004 0.000 0.996 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.3400 0.80026 0.000 0.180 0.000 0.820
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.3873 0.63917 0.000 0.000 0.228 0.772
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1940 0.80307 0.000 0.924 0.000 0.076
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.2589 0.77157 0.000 0.884 0.000 0.116
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.4713 0.61796 0.000 0.360 0.000 0.640
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.5220 0.38269 0.008 0.568 0.424 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.5161 0.20515 0.592 0.008 0.400 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 3 0.4925 0.37301 0.428 0.000 0.572 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.5147 0.68816 0.000 0.740 0.060 0.200
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.3975 0.66407 0.000 0.240 0.000 0.760
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.6404 0.54094 0.136 0.220 0.000 0.644
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 4 0.4040 0.76066 0.000 0.248 0.000 0.752
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.3444 0.79846 0.000 0.184 0.000 0.816
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2011 0.80168 0.000 0.920 0.000 0.080
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4737 0.64011 0.252 0.020 0.728 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.4888 0.69423 0.000 0.740 0.224 0.036
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0779 0.82012 0.000 0.980 0.004 0.016
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.4916 0.43600 0.000 0.576 0.424 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5733 0.60053 0.060 0.012 0.216 0.712
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 4 0.3486 0.79617 0.000 0.188 0.000 0.812
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.4898 0.39086 0.416 0.000 0.584 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.6646 0.54247 0.156 0.620 0.224 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2216 0.79714 0.000 0.908 0.000 0.092
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.4992 0.32935 0.476 0.000 0.524 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2081 0.79963 0.000 0.916 0.000 0.084
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.7248 0.32894 0.284 0.000 0.532 0.184
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.3569 0.78979 0.000 0.196 0.000 0.804
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.6110 0.49168 0.000 0.576 0.368 0.056
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4744 0.65079 0.240 0.024 0.736 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0188 0.88620 0.996 0.000 0.000 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.1302 0.81994 0.000 0.044 0.000 0.956
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0592 0.81499 0.000 0.016 0.000 0.984
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0707 0.79130 0.000 0.020 0.980 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4454 0.72385 0.000 0.308 0.000 0.692
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.88677 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0707 0.82095 0.000 0.980 0.000 0.020
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.1022 0.79717 0.032 0.000 0.968 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0188 0.88462 0.996 0.000 0.004 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.4888 0.41547 0.000 0.588 0.412 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4675 0.64902 0.244 0.020 0.736 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.3486 0.79617 0.000 0.188 0.000 0.812
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.79567 0.000 0.000 1.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4956 0.65167 0.232 0.036 0.732 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3586 0.6122 0.000 0.736 0.000 0.264 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3819 0.7198 0.228 0.000 0.756 0.000 0.016
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6375 0.3185 0.004 0.536 0.080 0.352 0.028
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3772 0.7501 0.172 0.000 0.036 0.000 0.792
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0727 0.7972 0.000 0.012 0.004 0.980 0.004
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.3586 0.6122 0.000 0.736 0.000 0.264 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0794 0.8335 0.972 0.000 0.028 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4150 0.7022 0.216 0.000 0.036 0.000 0.748
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1041 0.8315 0.964 0.000 0.032 0.000 0.004
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1750 0.8151 0.936 0.000 0.036 0.000 0.028
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0486 0.8000 0.000 0.004 0.004 0.988 0.004
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.8687 0.2541 0.380 0.264 0.212 0.116 0.028
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#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 4 0.2179 0.7303 0.000 0.112 0.000 0.888 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4455 0.5164 0.704 0.000 0.036 0.000 0.260
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0609 0.8365 0.980 0.000 0.020 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.0486 0.8000 0.000 0.004 0.004 0.988 0.004
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.1341 0.7803 0.000 0.056 0.000 0.944 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.4100 0.6842 0.004 0.160 0.052 0.000 0.784
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4074 0.5108 0.000 0.636 0.000 0.364 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0955 0.8328 0.968 0.000 0.028 0.000 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3607 0.6613 0.000 0.004 0.752 0.244 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3597 0.7415 0.180 0.000 0.800 0.008 0.012
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.2377 0.8035 0.872 0.000 0.128 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3476 0.6173 0.000 0.816 0.020 0.160 0.004
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0740 0.7979 0.000 0.008 0.008 0.980 0.004
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0880 0.8799 0.000 0.000 0.032 0.000 0.968
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4410 0.5949 0.000 0.776 0.036 0.160 0.028
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1041 0.8315 0.964 0.000 0.032 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3596 0.6775 0.016 0.000 0.784 0.000 0.200
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.1485 0.7874 0.000 0.032 0.020 0.948 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1124 0.8292 0.960 0.000 0.036 0.000 0.004
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.1173 0.7918 0.000 0.012 0.020 0.964 0.004
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3301 0.8110 0.080 0.000 0.072 0.000 0.848
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1894 0.8342 0.920 0.000 0.072 0.000 0.008
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3779 0.6698 0.000 0.000 0.752 0.236 0.012
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3562 0.7384 0.196 0.000 0.788 0.000 0.016
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3636 0.6053 0.000 0.728 0.000 0.272 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.1410 0.8668 0.000 0.000 0.060 0.000 0.940
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.3642 0.7518 0.144 0.000 0.820 0.020 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3795 0.562242 0.364 0.000 0.632 0.004 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3482 0.633834 0.000 0.000 0.000 0.684 0.000 0.316
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3924 0.667492 0.252 0.000 0.016 0.012 0.720 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0717 0.900990 0.000 0.000 0.016 0.008 0.000 0.976
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0260 0.851698 0.992 0.000 0.008 0.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4207 0.588242 0.308 0.000 0.016 0.012 0.664 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.0547 0.901390 0.000 0.000 0.020 0.000 0.000 0.980
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.1148 0.717862 0.004 0.000 0.016 0.960 0.000 0.020
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4344 0.490562 0.568 0.000 0.008 0.412 0.000 0.012
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3671 0.598461 0.000 0.000 0.036 0.756 0.000 0.208
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.0713 0.898602 0.000 0.028 0.000 0.000 0.000 0.972
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.1074 0.894963 0.000 0.028 0.000 0.012 0.000 0.960
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0520 0.922561 0.000 0.984 0.000 0.008 0.008 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0458 0.921657 0.000 0.984 0.000 0.016 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4638 0.536411 0.000 0.000 0.040 0.588 0.004 0.368
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3867 0.529247 0.000 0.000 0.660 0.012 0.328 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.2838 0.755797 0.188 0.000 0.808 0.004 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.5914 0.409667 0.280 0.000 0.524 0.184 0.000 0.012
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.0458 0.901732 0.000 0.000 0.016 0.000 0.000 0.984
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0622 0.888749 0.000 0.000 0.008 0.012 0.980 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.0806 0.896796 0.000 0.000 0.008 0.020 0.000 0.972
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2491 0.776331 0.000 0.836 0.000 0.000 0.000 0.164
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.3717 0.670373 0.708 0.000 0.016 0.276 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0622 0.850993 0.980 0.000 0.012 0.008 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1610 0.863425 0.000 0.916 0.000 0.000 0.000 0.084
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.3595 0.656499 0.288 0.000 0.704 0.008 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2631 0.739539 0.000 0.000 0.820 0.000 0.180 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0363 0.851550 0.988 0.000 0.000 0.012 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0146 0.850429 0.996 0.000 0.000 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.3620 0.591524 0.000 0.000 0.000 0.648 0.000 0.352
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.2945 0.575608 0.156 0.000 0.020 0.824 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2135 0.821931 0.000 0.872 0.000 0.000 0.000 0.128
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.0458 0.901732 0.000 0.000 0.016 0.000 0.000 0.984
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0146 0.852554 0.996 0.000 0.000 0.004 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.0820 0.886706 0.000 0.000 0.016 0.012 0.972 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.3288 0.642352 0.000 0.276 0.000 0.000 0.000 0.724
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0146 0.852554 0.996 0.000 0.000 0.004 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.0820 0.886706 0.000 0.000 0.016 0.012 0.972 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.2415 0.835234 0.084 0.000 0.016 0.012 0.888 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0146 0.852554 0.996 0.000 0.000 0.004 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.3841 0.401287 0.000 0.380 0.004 0.616 0.000 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0790 0.812150 0.000 0.000 0.968 0.000 0.000 0.032
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 6 0.0632 0.901575 0.000 0.000 0.024 0.000 0.000 0.976
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0405 0.852489 0.988 0.000 0.008 0.004 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 6 0.3052 0.729418 0.000 0.216 0.004 0.000 0.000 0.780
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4619 0.189646 0.576 0.000 0.024 0.012 0.388 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.3684 0.553286 0.372 0.000 0.628 0.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.3703 0.781526 0.000 0.108 0.104 0.000 0.000 0.788
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.0632 0.892082 0.000 0.000 0.000 0.024 0.000 0.976
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 6 0.0935 0.893231 0.000 0.000 0.004 0.032 0.000 0.964
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.4440 0.458804 0.376 0.000 0.016 0.012 0.596 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.4091 0.291760 0.520 0.000 0.008 0.472 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.1196 0.810174 0.000 0.008 0.952 0.000 0.000 0.040
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.1092 0.713455 0.020 0.000 0.020 0.960 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3714 0.603250 0.000 0.004 0.000 0.656 0.000 0.340
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.4681 0.662757 0.000 0.100 0.000 0.668 0.000 0.232
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 6 0.3164 0.787689 0.000 0.000 0.044 0.004 0.120 0.832
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0914 0.848967 0.968 0.000 0.016 0.016 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0508 0.889561 0.000 0.000 0.004 0.012 0.984 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0865 0.811978 0.000 0.000 0.964 0.000 0.000 0.036
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.1806 0.810312 0.088 0.000 0.908 0.004 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.1075 0.808196 0.000 0.000 0.952 0.000 0.048 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.1605 0.871051 0.032 0.000 0.016 0.012 0.940 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 6 0.2358 0.844073 0.000 0.108 0.016 0.000 0.000 0.876
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 3 0.6028 0.370404 0.200 0.000 0.500 0.288 0.000 0.012
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.4995 0.115123 0.440 0.000 0.028 0.508 0.024 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0865 0.906824 0.000 0.964 0.000 0.036 0.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.4076 0.436952 0.000 0.000 0.016 0.620 0.364 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0508 0.851217 0.984 0.000 0.012 0.004 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.6364 0.191401 0.000 0.004 0.144 0.440 0.032 0.380
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.4248 0.484825 0.248 0.000 0.032 0.708 0.004 0.008
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0458 0.885310 0.000 0.000 0.016 0.000 0.984 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0146 0.852554 0.996 0.000 0.000 0.004 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 6 0.0820 0.902407 0.000 0.012 0.016 0.000 0.000 0.972
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.1349 0.815841 0.056 0.000 0.940 0.004 0.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 6 0.0622 0.899419 0.000 0.000 0.008 0.012 0.000 0.980
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.3817 0.358036 0.000 0.000 0.568 0.000 0.432 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 6 0.0692 0.900843 0.000 0.000 0.020 0.004 0.000 0.976
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.4405 0.553960 0.604 0.000 0.020 0.368 0.000 0.008
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.0790 0.907407 0.000 0.968 0.000 0.000 0.032 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 6 0.4140 0.692949 0.000 0.000 0.152 0.104 0.000 0.744
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.2003 0.830993 0.000 0.884 0.000 0.000 0.000 0.116
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 5 0.0146 0.889702 0.000 0.000 0.004 0.000 0.996 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.5320 0.600119 0.252 0.000 0.616 0.012 0.120 0.000
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#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.3733 0.657781 0.000 0.000 0.004 0.700 0.008 0.288
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 6 0.1088 0.900845 0.000 0.024 0.016 0.000 0.000 0.960
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.4474 0.489521 0.360 0.000 0.020 0.012 0.608 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.0363 0.887255 0.000 0.000 0.012 0.000 0.988 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.5262 0.668182 0.000 0.132 0.004 0.668 0.020 0.176
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.1196 0.804328 0.000 0.040 0.952 0.000 0.008 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.1477 0.815969 0.048 0.000 0.940 0.004 0.000 0.008
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.3860 -0.051413 0.000 0.000 0.472 0.000 0.528 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 6 0.1556 0.863552 0.000 0.000 0.000 0.080 0.000 0.920
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 6 0.3923 0.452172 0.000 0.372 0.008 0.000 0.000 0.620
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.0363 0.887255 0.000 0.000 0.012 0.000 0.988 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.2823 0.669395 0.000 0.000 0.000 0.204 0.796 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 6 0.2882 0.783037 0.000 0.000 0.180 0.008 0.000 0.812
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.1334 0.813633 0.020 0.000 0.948 0.000 0.032 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0146 0.928555 0.000 0.996 0.000 0.004 0.000 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.3934 0.263918 0.304 0.000 0.020 0.676 0.000 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.6380 0.563066 0.104 0.096 0.592 0.012 0.000 0.196
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.2762 0.681715 0.000 0.000 0.000 0.196 0.804 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 6 0.2830 0.804448 0.000 0.000 0.144 0.020 0.000 0.836
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0146 0.852554 0.996 0.000 0.000 0.004 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0717 0.882555 0.000 0.008 0.016 0.000 0.976 0.000
#> A2007795-C728-4688-B199-AE89500011D2 6 0.2340 0.807281 0.000 0.148 0.000 0.000 0.000 0.852
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 6 0.0935 0.892360 0.000 0.000 0.004 0.032 0.000 0.964
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.1387 0.813667 0.068 0.000 0.932 0.000 0.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 6 0.0622 0.898474 0.000 0.000 0.008 0.012 0.000 0.980
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.1003 0.901548 0.000 0.020 0.016 0.000 0.000 0.964
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.1701 0.813000 0.072 0.000 0.920 0.008 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.5085 0.608969 0.000 0.208 0.004 0.644 0.000 0.144
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.3236 0.753326 0.796 0.000 0.024 0.180 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0146 0.928748 0.000 0.996 0.000 0.000 0.000 0.004
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.3878 0.473473 0.000 0.004 0.004 0.644 0.348 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0146 0.851801 0.996 0.000 0.004 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.2135 0.791804 0.872 0.000 0.000 0.128 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.1074 0.898894 0.000 0.000 0.028 0.000 0.012 0.960
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 6 0.1492 0.887587 0.000 0.000 0.024 0.036 0.000 0.940
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.0858 0.899059 0.000 0.028 0.004 0.000 0.000 0.968
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.1003 0.895737 0.000 0.020 0.000 0.016 0.000 0.964
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.0713 0.898602 0.000 0.028 0.000 0.000 0.000 0.972
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.1082 0.808657 0.000 0.000 0.956 0.040 0.004 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.5145 -0.119863 0.484 0.000 0.432 0.084 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.4014 0.648165 0.268 0.000 0.016 0.012 0.704 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 6 0.6243 0.228131 0.000 0.312 0.216 0.016 0.000 0.456
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2793 0.708588 0.000 0.000 0.000 0.800 0.000 0.200
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0820 0.720747 0.000 0.000 0.016 0.972 0.000 0.012
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 6 0.1787 0.885727 0.000 0.032 0.016 0.020 0.000 0.932
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.0458 0.901732 0.000 0.000 0.016 0.000 0.000 0.984
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.1074 0.899535 0.000 0.028 0.012 0.000 0.000 0.960
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.1556 0.812170 0.080 0.000 0.920 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> 4F501635-545A-479A-A95E-12C4AC30BA50 6 0.2266 0.829270 0.000 0.000 0.012 0.108 0.000 0.880
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 6 0.5197 0.440151 0.000 0.000 0.040 0.040 0.324 0.596
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0725 0.887609 0.000 0.000 0.012 0.012 0.976 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.2520 0.683933 0.000 0.000 0.004 0.844 0.152 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0622 0.850557 0.980 0.000 0.012 0.008 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0000 0.890924 0.000 0.000 0.000 0.000 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2841 0.797998 0.128 0.000 0.012 0.012 0.848 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.1966 0.815587 0.024 0.000 0.924 0.028 0.000 0.024
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1542 0.834998 0.944 0.000 0.024 0.016 0.016 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.2605 0.839595 0.000 0.108 0.028 0.000 0.000 0.864
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1922 0.817294 0.924 0.000 0.024 0.012 0.040 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0547 0.849499 0.980 0.000 0.000 0.020 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.0405 0.900540 0.000 0.000 0.008 0.004 0.000 0.988
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.0972 0.899424 0.000 0.028 0.008 0.000 0.000 0.964
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.4748 -0.000409 0.000 0.000 0.048 0.448 0.504 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3244 0.626505 0.000 0.732 0.000 0.000 0.000 0.268
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0363 0.851650 0.988 0.000 0.012 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0937 0.811172 0.000 0.000 0.960 0.000 0.000 0.040
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.1492 0.811308 0.024 0.000 0.940 0.036 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.3489 0.662658 0.708 0.000 0.004 0.288 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.4674 0.577929 0.000 0.060 0.000 0.608 0.000 0.332
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.0820 0.900294 0.000 0.000 0.016 0.012 0.000 0.972
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.0622 0.888617 0.000 0.000 0.012 0.008 0.980 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.4034 0.604701 0.000 0.020 0.000 0.652 0.000 0.328
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0405 0.850347 0.988 0.000 0.008 0.004 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1542 0.808177 0.004 0.000 0.936 0.008 0.052 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.1074 0.890845 0.000 0.012 0.000 0.028 0.000 0.960
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.852333 1.000 0.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 6 0.1492 0.887305 0.000 0.000 0.024 0.036 0.000 0.940
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.2867 0.826004 0.076 0.000 0.040 0.016 0.868 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2307 0.823512 0.896 0.000 0.032 0.068 0.004 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0865 0.811978 0.000 0.000 0.964 0.000 0.000 0.036
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.1387 0.813667 0.068 0.000 0.932 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.930241 0.000 1.000 0.000 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.2003 0.819146 0.000 0.000 0.116 0.000 0.884 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.1007 0.815696 0.044 0.000 0.956 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.378 0.666 0.864 0.4882 0.507 0.507
#> 3 3 0.461 0.536 0.769 0.3501 0.699 0.474
#> 4 4 0.543 0.617 0.790 0.1229 0.759 0.418
#> 5 5 0.632 0.663 0.781 0.0632 0.853 0.520
#> 6 6 0.643 0.602 0.767 0.0245 0.976 0.890
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.84566 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.79504 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.84566 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.79504 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.84566 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.84566 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.8661 0.59750 0.712 0.288
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.79504 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.5737 0.73287 0.864 0.136
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.79504 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.84566 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.9552 0.27340 0.376 0.624
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#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.79504 1.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0000 0.84566 0.000 1.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.9608 0.46014 0.616 0.384
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.84566 0.000 1.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.84566 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.84566 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.9460 0.29751 0.364 0.636
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.9661 0.22284 0.392 0.608
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.79504 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.84566 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.5842 0.73025 0.860 0.140
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.9963 0.07986 0.536 0.464
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.79504 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.84566 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.8016 0.63025 0.756 0.244
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.5842 0.73025 0.860 0.140
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.9954 0.00805 0.460 0.540
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.79504 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.84566 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0000 0.84566 0.000 1.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.79504 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.79504 1.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.9983 0.12024 0.476 0.524
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.84566 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.9248 0.47212 0.340 0.660
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.8499 0.61572 0.724 0.276
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.8861 0.53614 0.304 0.696
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.84566 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.84566 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.6048 0.74528 0.148 0.852
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9963 0.07986 0.536 0.464
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.9129 0.51424 0.672 0.328
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.6048 0.74529 0.148 0.852
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0376 0.79338 0.996 0.004
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.9815 0.12668 0.420 0.580
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.9954 0.00805 0.460 0.540
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.9795 0.14706 0.416 0.584
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.79504 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.6247 0.74136 0.156 0.844
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.5737 0.73287 0.864 0.136
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.8713 0.57522 0.292 0.708
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.84566 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.84566 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.7299 0.70185 0.204 0.796
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.8713 0.55301 0.292 0.708
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.0000 0.79504 1.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.9963 0.07986 0.536 0.464
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.84566 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.84566 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.79504 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.84566 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9248 0.47217 0.340 0.660
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.8909 0.56938 0.692 0.308
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.84566 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.8081 0.57383 0.752 0.248
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0672 0.84231 0.008 0.992
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.6887 0.71470 0.184 0.816
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.5842 0.73025 0.860 0.140
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.3114 0.77657 0.944 0.056
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.6048 0.74528 0.148 0.852
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0672 0.84234 0.008 0.992
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.84566 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1184 0.79028 0.984 0.016
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.84566 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.84566 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.9933 0.06996 0.548 0.452
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.79504 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.79504 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.9909 0.05113 0.444 0.556
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.84566 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.1843 0.83265 0.028 0.972
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.5519 0.76170 0.128 0.872
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1843 0.83165 0.028 0.972
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.1184 0.83839 0.016 0.984
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.84566 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.79504 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.8763 0.54599 0.296 0.704
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.9909 0.05113 0.444 0.556
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.6531 0.73304 0.168 0.832
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.79504 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.3584 0.80570 0.068 0.932
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.84566 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.8661 0.59750 0.712 0.288
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.9963 0.07986 0.536 0.464
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.79504 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9944 0.16460 0.456 0.544
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.79504 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.84566 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.79504 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.9000 0.55957 0.684 0.316
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.84566 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.84566 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.7139 0.70984 0.196 0.804
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.84566 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.79504 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.9044 0.50248 0.320 0.680
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.3733 0.76110 0.928 0.072
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.7528 0.68507 0.784 0.216
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.84566 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.84566 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.9963 0.07986 0.536 0.464
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.84566 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.79504 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1414 0.78603 0.980 0.020
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.84566 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.79504 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.84566 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0938 0.79056 0.988 0.012
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3879 0.75464 0.924 0.076
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.9393 0.44227 0.356 0.644
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.79504 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.9460 0.27712 0.364 0.636
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9977 0.05290 0.528 0.472
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.79504 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.8164 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.6008 0.7367 0.628 0.000 0.372
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.6267 0.1606 0.000 0.548 0.452
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3686 0.6579 0.860 0.000 0.140
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5291 0.6737 0.000 0.732 0.268
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.8164 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.9146 0.6051 0.472 0.148 0.380
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5760 0.7292 0.672 0.000 0.328
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.6026 0.7356 0.624 0.000 0.376
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.6008 0.7367 0.628 0.000 0.372
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4974 0.6873 0.000 0.764 0.236
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 3 0.2947 0.3116 0.060 0.020 0.920
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 3 0.6148 0.2104 0.076 0.148 0.776
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.8164 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.8286 0.6104 0.308 0.104 0.588
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.9243 0.4756 0.208 0.264 0.528
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.8164 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.8733 0.5654 0.260 0.160 0.580
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.8164 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 3 0.9252 0.5850 0.372 0.160 0.468
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 3 0.9715 0.5375 0.380 0.220 0.400
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.7279 0.6334 0.376 0.036 0.588
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.6721 0.6299 0.380 0.016 0.604
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.6045 0.7356 0.620 0.000 0.380
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.6814 0.6323 0.372 0.020 0.608
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.4399 0.7219 0.000 0.812 0.188
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.3091 0.5794 0.912 0.016 0.072
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.5681 1.000 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.6026 0.7356 0.624 0.000 0.376
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.1964 0.7960 0.000 0.944 0.056
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0747 0.5572 0.984 0.000 0.016
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3752 0.7448 0.000 0.856 0.144
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.6244 0.7088 0.560 0.000 0.440
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6062 0.7337 0.616 0.000 0.384
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.8164 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.6008 0.7367 0.628 0.000 0.372
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.7250 0.6211 0.396 0.032 0.572
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.6629 -0.2846 0.624 0.016 0.360
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.6244 0.7088 0.560 0.000 0.440
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.6008 0.7367 0.628 0.000 0.372
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.1411 0.8074 0.000 0.964 0.036
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 3 0.8635 0.5502 0.440 0.100 0.460
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.8164 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2537 0.8025 0.000 0.920 0.080
#> E6AF8360-3A04-41E9-97D3-871067377F76 3 0.9191 -0.5618 0.420 0.148 0.432
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.6880 0.6216 0.108 0.736 0.156
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.2297 0.5260 0.944 0.020 0.036
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0237 0.8163 0.000 0.996 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1411 0.8130 0.000 0.964 0.036
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0237 0.8154 0.000 0.996 0.004
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.7699 0.2039 0.052 0.388 0.560
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.6045 0.7347 0.620 0.000 0.380
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.6008 0.7367 0.628 0.000 0.372
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.5681 1.000 0.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5785 0.7193 0.696 0.004 0.300
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.6079 0.7324 0.612 0.000 0.388
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 3 0.7263 0.6335 0.372 0.036 0.592
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.6832 0.6308 0.376 0.020 0.604
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.7624 0.2079 0.368 0.580 0.052
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.8435 0.5830 0.268 0.132 0.600
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.9154 0.6021 0.468 0.148 0.384
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3816 0.7361 0.000 0.852 0.148
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.2625 0.6130 0.916 0.000 0.084
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.3445 0.4274 0.896 0.016 0.088
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.6008 0.7367 0.628 0.000 0.372
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.4575 0.7299 0.004 0.812 0.184
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#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.8675 0.1120 0.104 0.476 0.420
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.6952 0.6310 0.376 0.024 0.600
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.9342 -0.5088 0.484 0.180 0.336
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.8379 0.5862 0.268 0.128 0.604
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.2165 0.5316 0.936 0.000 0.064
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.4514 0.6865 0.012 0.832 0.156
#> E9061D61-4774-464E-ABE4-EB15CD889141 3 0.6266 0.2122 0.076 0.156 0.768
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 1 0.9638 -0.5114 0.420 0.208 0.372
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.1643 0.5462 0.956 0.000 0.044
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.8616 0.5775 0.264 0.148 0.588
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.6140 0.7260 0.596 0.000 0.404
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.6952 0.6336 0.376 0.024 0.600
#> A2007795-C728-4688-B199-AE89500011D2 2 0.3482 0.7494 0.000 0.872 0.128
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.6280 0.1598 0.000 0.540 0.460
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.6704 0.6304 0.376 0.016 0.608
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.8109 0.2883 0.080 0.352 0.568
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6008 0.7243 0.628 0.000 0.372
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.6566 0.6302 0.376 0.012 0.612
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.1529 0.8124 0.000 0.960 0.040
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.3482 0.7494 0.000 0.872 0.128
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.1163 0.5640 0.972 0.000 0.028
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2261 0.8005 0.000 0.932 0.068
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.7379 0.6276 0.376 0.040 0.584
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 3 0.9187 -0.5570 0.412 0.148 0.440
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.8164 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.6848 0.6142 0.416 0.016 0.568
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.3129 0.7496 0.088 0.904 0.008
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.7656 0.6308 0.376 0.052 0.572
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.6026 0.7356 0.624 0.000 0.376
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.6192 0.7233 0.580 0.000 0.420
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.7841 0.2478 0.064 0.360 0.576
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 3 0.8460 0.5815 0.264 0.136 0.600
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.8164 0.000 1.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.6026 0.7356 0.624 0.000 0.376
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1289 0.8138 0.000 0.968 0.032
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.8164 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6192 0.5881 0.420 0.000 0.580
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6126 0.7280 0.600 0.000 0.400
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.5882 0.7362 0.652 0.000 0.348
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.6148 0.2104 0.076 0.148 0.776
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.3192 0.7862 0.000 0.888 0.112
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 3 0.9527 0.5232 0.300 0.220 0.480
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.8117 0.2722 0.076 0.372 0.552
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.8550 0.5271 0.176 0.216 0.608
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.6280 0.0342 0.000 0.460 0.540
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2878 0.7788 0.000 0.904 0.096
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.6008 0.7367 0.628 0.000 0.372
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.8143 0.2751 0.080 0.360 0.560
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.6266 0.2122 0.076 0.156 0.768
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.7175 0.6338 0.376 0.032 0.592
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.5681 1.000 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 3 0.7158 0.6339 0.372 0.032 0.596
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3619 0.7447 0.000 0.864 0.136
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.9161 0.5988 0.464 0.148 0.388
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.7250 0.6211 0.396 0.032 0.572
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.2878 0.4872 0.904 0.000 0.096
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.7107 0.3963 0.196 0.092 0.712
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.6192 0.7218 0.580 0.000 0.420
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0747 0.8100 0.000 0.984 0.016
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.6008 0.7367 0.628 0.000 0.372
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.9191 0.5636 0.428 0.148 0.424
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1860 0.7981 0.000 0.948 0.052
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1964 0.7986 0.000 0.944 0.056
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 3 0.6832 0.6338 0.376 0.020 0.604
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.8164 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.6140 0.7296 0.596 0.000 0.404
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.9355 0.5244 0.252 0.232 0.516
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.3116 0.4509 0.892 0.000 0.108
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.4291 0.1186 0.152 0.008 0.840
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1964 0.8044 0.000 0.944 0.056
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5216 0.6596 0.000 0.740 0.260
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.6798 0.6205 0.400 0.016 0.584
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.8164 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.6026 0.7356 0.624 0.000 0.376
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.1031 0.5518 0.976 0.000 0.024
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.6095 0.3311 0.000 0.608 0.392
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.6008 0.7367 0.628 0.000 0.372
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.6307 0.2500 0.000 0.512 0.488
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6008 -0.2865 0.628 0.000 0.372
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 3 0.6286 0.5655 0.464 0.000 0.536
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.8673 0.5736 0.272 0.148 0.580
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.6095 0.7325 0.608 0.000 0.392
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1529 0.8050 0.000 0.960 0.040
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.6910 0.6224 0.396 0.020 0.584
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.4887 0.6224 0.772 0.000 0.228
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.1389 0.73563 0.952 0.000 0.048 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0336 0.72987 0.000 0.000 0.008 0.992
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.3219 0.67247 0.836 0.000 0.164 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.3925 0.79452 0.000 0.808 0.016 0.176
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4907 0.02959 0.580 0.000 0.000 0.420
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.2530 0.71471 0.888 0.000 0.112 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4855 0.72837 0.000 0.712 0.020 0.268
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2593 0.76140 0.104 0.000 0.004 0.892
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.4018 0.73109 0.224 0.000 0.004 0.772
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3123 0.62408 0.000 0.000 0.156 0.844
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4562 0.63404 0.000 0.152 0.792 0.056
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3831 0.65678 0.000 0.004 0.792 0.204
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.5010 0.49848 0.000 0.024 0.276 0.700
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7036 0.21150 0.008 0.100 0.368 0.524
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4955 0.08442 0.000 0.000 0.444 0.556
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.1389 0.70206 0.000 0.000 0.952 0.048
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.3726 0.64889 0.788 0.000 0.212 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 4 0.5138 0.24051 0.008 0.000 0.392 0.600
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2334 0.83962 0.000 0.908 0.004 0.088
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4994 0.25894 0.520 0.000 0.480 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4998 0.23909 0.512 0.000 0.488 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.2647 0.72079 0.000 0.120 0.000 0.880
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.5165 0.23856 0.512 0.000 0.484 0.004
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0657 0.85675 0.000 0.984 0.004 0.012
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.4564 0.61591 0.328 0.000 0.000 0.672
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2081 0.70747 0.916 0.000 0.000 0.084
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.2647 0.81603 0.000 0.880 0.000 0.120
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.1389 0.73563 0.952 0.000 0.048 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2469 0.71289 0.000 0.000 0.892 0.108
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 3 0.6557 -0.02930 0.448 0.000 0.476 0.076
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4406 0.43514 0.700 0.000 0.000 0.300
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.1637 0.85388 0.000 0.940 0.000 0.060
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.5006 0.72846 0.104 0.000 0.124 0.772
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.2345 0.84196 0.000 0.900 0.000 0.100
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.5458 0.70603 0.236 0.000 0.060 0.704
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.3074 0.56125 0.152 0.000 0.848 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1022 0.85272 0.000 0.968 0.000 0.032
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.6202 0.32148 0.000 0.312 0.612 0.076
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4866 0.42889 0.596 0.000 0.404 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4730 0.47796 0.636 0.000 0.364 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2530 0.68931 0.888 0.000 0.000 0.112
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.4134 0.51438 0.000 0.000 0.260 0.740
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.1867 0.70817 0.000 0.000 0.928 0.072
#> F043185A-D4D2-4503-93FA-A7B7DA684290 3 0.4817 0.35187 0.000 0.388 0.612 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.4123 0.67419 0.000 0.008 0.772 0.220
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4985 -0.24194 0.532 0.000 0.000 0.468
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0592 0.85801 0.000 0.984 0.000 0.016
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.7858 0.08968 0.396 0.000 0.288 0.316
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 3 0.6011 -0.15480 0.476 0.000 0.484 0.040
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.4205 0.77066 0.008 0.804 0.016 0.172
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.6551 0.62134 0.000 0.624 0.136 0.240
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.1557 0.73442 0.000 0.056 0.000 0.944
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.4830 0.02060 0.608 0.000 0.000 0.392
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3801 0.62789 0.780 0.000 0.220 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4040 0.71617 0.248 0.000 0.000 0.752
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.6516 0.32048 0.000 0.332 0.576 0.092
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.3024 0.75703 0.148 0.000 0.000 0.852
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.7105 0.41838 0.000 0.196 0.564 0.240
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.4428 0.73787 0.000 0.720 0.004 0.276
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.2469 0.73404 0.000 0.108 0.000 0.892
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 3 0.4799 0.65387 0.000 0.032 0.744 0.224
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4888 0.12227 0.588 0.000 0.000 0.412
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 3 0.6008 -0.11823 0.464 0.000 0.496 0.040
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#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.7015 0.43636 0.264 0.000 0.568 0.168
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.6295 0.61667 0.000 0.656 0.132 0.212
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.2469 0.71282 0.000 0.000 0.892 0.108
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.7688 0.33249 0.232 0.000 0.328 0.440
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.2654 0.71379 0.004 0.000 0.888 0.108
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.0188 0.73154 0.000 0.000 0.004 0.996
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.3081 0.82054 0.000 0.888 0.048 0.064
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.2799 0.71289 0.008 0.000 0.884 0.108
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 3 0.6203 0.27489 0.068 0.000 0.592 0.340
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.4406 0.59530 0.000 0.000 0.700 0.300
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.3791 0.54228 0.200 0.000 0.796 0.004
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.4741 0.55484 0.004 0.328 0.000 0.668
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.4072 0.71371 0.252 0.000 0.000 0.748
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 1 0.9184 -0.14904 0.352 0.076 0.328 0.244
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.6332 0.24088 0.488 0.000 0.452 0.060
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.3528 0.57292 0.000 0.000 0.192 0.808
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0336 0.74943 0.992 0.000 0.000 0.008
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.4040 0.63020 0.000 0.000 0.752 0.248
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0336 0.85744 0.000 0.992 0.000 0.008
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.1118 0.71676 0.000 0.000 0.036 0.964
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.3024 0.70947 0.000 0.000 0.852 0.148
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.6323 0.36479 0.000 0.272 0.628 0.100
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.5979 0.53864 0.652 0.000 0.272 0.076
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.2546 0.71263 0.008 0.000 0.900 0.092
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.4535 0.68831 0.000 0.704 0.004 0.292
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4304 0.43337 0.284 0.000 0.716 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.3808 0.78056 0.000 0.812 0.012 0.176
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.1792 0.70792 0.000 0.000 0.932 0.068
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.3907 0.72563 0.232 0.000 0.000 0.768
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0188 0.85655 0.000 0.996 0.000 0.004
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.1545 0.69823 0.008 0.000 0.952 0.040
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 3 0.4989 0.17382 0.000 0.000 0.528 0.472
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5596 0.53790 0.696 0.000 0.068 0.236
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5792 0.66006 0.000 0.708 0.168 0.124
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.3764 0.54492 0.000 0.000 0.216 0.784
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.1474 0.73450 0.948 0.000 0.000 0.052
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.3837 0.76979 0.000 0.776 0.000 0.224
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0921 0.85800 0.000 0.972 0.000 0.028
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.4711 0.65078 0.064 0.000 0.784 0.152
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1302 0.73760 0.956 0.000 0.000 0.044
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1940 0.72252 0.924 0.000 0.076 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.3105 0.75902 0.140 0.000 0.004 0.856
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.1474 0.73528 0.000 0.052 0.000 0.948
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.1022 0.73274 0.000 0.000 0.032 0.968
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.7250 0.46080 0.000 0.544 0.220 0.236
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 4 0.7051 -0.06823 0.004 0.104 0.436 0.456
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5972 0.67792 0.000 0.692 0.132 0.176
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0188 0.85648 0.000 0.996 0.000 0.004
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.2197 0.72911 0.916 0.000 0.080 0.004
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6148 0.38797 0.000 0.280 0.636 0.084
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.3945 0.73554 0.216 0.000 0.004 0.780
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.4933 0.29554 0.000 0.000 0.568 0.432
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.4981 -0.17929 0.464 0.000 0.536 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.4679 0.49700 0.000 0.000 0.352 0.648
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.85580 0.000 1.000 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.4730 0.10911 0.636 0.000 0.000 0.364
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.2799 0.71289 0.008 0.000 0.884 0.108
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5167 0.22898 0.508 0.000 0.488 0.004
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4136 0.70693 0.196 0.000 0.016 0.788
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5369 0.61233 0.744 0.000 0.112 0.144
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2469 0.82582 0.000 0.892 0.000 0.108
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.4406 0.67492 0.300 0.000 0.000 0.700
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4998 0.21590 0.000 0.512 0.000 0.488
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0707 0.85809 0.000 0.980 0.000 0.020
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4933 0.06470 0.000 0.000 0.432 0.568
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0336 0.85718 0.000 0.992 0.000 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5339 0.61152 0.744 0.000 0.156 0.100
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4605 0.65230 0.000 0.072 0.796 0.132
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4662 0.58590 0.092 0.000 0.796 0.112
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.4792 0.63992 0.312 0.000 0.008 0.680
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1824 0.84215 0.000 0.936 0.004 0.060
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5636 0.66331 0.000 0.648 0.044 0.308
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.1635 0.69970 0.008 0.000 0.948 0.044
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2814 0.81052 0.000 0.868 0.000 0.132
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3539 0.55996 0.176 0.000 0.820 0.004
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.1902 0.73809 0.000 0.064 0.004 0.932
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.75131 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2408 0.68339 0.000 0.104 0.000 0.896
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.6015 0.42722 0.268 0.000 0.652 0.080
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.7540 0.27157 0.204 0.000 0.328 0.468
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3708 0.70099 0.000 0.020 0.832 0.148
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.4522 0.48114 0.680 0.000 0.320 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4948 0.11508 0.000 0.560 0.000 0.440
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.2859 0.71261 0.008 0.000 0.880 0.112
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4391 0.47428 0.252 0.000 0.740 0.008
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5699 0.57715 0.220 0.000 0.624 0.156 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5237 0.54654 0.000 0.008 0.056 0.644 0.292
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2131 0.62607 0.920 0.000 0.056 0.008 0.016
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.6055 0.52965 0.000 0.608 0.060 0.048 0.284
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4302 -0.15610 0.480 0.000 0.000 0.520 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1701 0.64274 0.936 0.000 0.048 0.016 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3039 0.70728 0.808 0.000 0.000 0.192 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5734 0.71478 0.000 0.688 0.148 0.036 0.128
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2116 0.75543 0.028 0.000 0.008 0.924 0.040
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.1671 0.73613 0.076 0.000 0.000 0.924 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.2124 0.73823 0.000 0.004 0.000 0.096 0.900
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4595 0.61718 0.000 0.088 0.740 0.000 0.172
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0865 0.88192 0.000 0.972 0.024 0.000 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3632 0.59658 0.000 0.004 0.800 0.020 0.176
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0955 0.88179 0.000 0.968 0.028 0.000 0.004
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.3214 0.73446 0.004 0.020 0.008 0.112 0.856
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.7920 0.44690 0.048 0.180 0.164 0.536 0.072
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.1168 0.75792 0.008 0.000 0.000 0.032 0.960
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.5532 0.55821 0.156 0.000 0.196 0.000 0.648
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5375 0.61583 0.176 0.000 0.668 0.156 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.4447 0.70247 0.008 0.000 0.140 0.080 0.772
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3752 0.79346 0.000 0.804 0.048 0.000 0.148
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4832 0.51905 0.712 0.000 0.200 0.000 0.088
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4933 0.51231 0.704 0.000 0.200 0.000 0.096
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4340 0.69893 0.000 0.060 0.148 0.780 0.012
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4933 0.51231 0.704 0.000 0.200 0.000 0.096
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2170 0.84887 0.004 0.904 0.004 0.000 0.088
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.2408 0.72516 0.092 0.000 0.000 0.892 0.016
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3932 0.58806 0.672 0.000 0.000 0.328 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.1200 0.88234 0.000 0.964 0.016 0.008 0.012
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.5673 0.58208 0.216 0.000 0.628 0.156 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.2971 0.70419 0.008 0.000 0.156 0.000 0.836
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.6342 0.23416 0.356 0.000 0.168 0.000 0.476
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4192 0.53539 0.596 0.000 0.000 0.404 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.4396 0.78682 0.000 0.772 0.152 0.068 0.008
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.2921 0.73192 0.028 0.000 0.020 0.884 0.068
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0898 0.88191 0.000 0.972 0.020 0.000 0.008
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.4072 0.79238 0.000 0.792 0.152 0.048 0.008
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.3159 0.70851 0.088 0.000 0.056 0.856 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0740 0.87891 0.004 0.980 0.008 0.000 0.008
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.5815 0.28352 0.356 0.000 0.540 0.000 0.104
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.1928 0.86080 0.004 0.920 0.004 0.000 0.072
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4355 0.60875 0.000 0.076 0.760 0.000 0.164
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4964 0.52560 0.700 0.000 0.204 0.000 0.096
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4609 0.57866 0.756 0.000 0.172 0.016 0.056
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.3857 0.60648 0.688 0.000 0.000 0.312 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.2054 0.74878 0.008 0.004 0.000 0.072 0.916
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4151 0.51806 0.004 0.000 0.652 0.000 0.344
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4522 0.65221 0.004 0.772 0.124 0.004 0.096
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.0693 0.75805 0.000 0.008 0.000 0.012 0.980
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.4114 0.28439 0.376 0.000 0.000 0.624 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0566 0.88166 0.004 0.984 0.012 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.6958 0.31613 0.192 0.000 0.144 0.580 0.084
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#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 5 0.0486 0.75612 0.004 0.004 0.004 0.000 0.988
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 4 0.1792 0.73222 0.084 0.000 0.000 0.916 0.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.4803 0.55379 0.184 0.000 0.720 0.000 0.096
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 4 0.1408 0.75033 0.044 0.000 0.008 0.948 0.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 4 0.2124 0.74454 0.012 0.000 0.020 0.924 0.044
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.2471 0.82794 0.000 0.864 0.000 0.000 0.136
#> 93429F04-8404-4E8C-B654-9D2216BA432C 5 0.1549 0.75746 0.000 0.016 0.000 0.040 0.944
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 4 0.2074 0.72212 0.104 0.000 0.000 0.896 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.5091 0.69736 0.712 0.000 0.056 0.208 0.024
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.7315 0.60092 0.540 0.000 0.172 0.192 0.096
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 5 0.4244 0.68518 0.000 0.008 0.132 0.072 0.788
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.5985 0.60298 0.000 0.204 0.148 0.632 0.016
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 1 0.7432 0.32922 0.540 0.032 0.228 0.036 0.164
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 5 0.3857 0.72345 0.000 0.052 0.028 0.088 0.832
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.5646 0.58610 0.212 0.000 0.632 0.156 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.3370 0.59019 0.824 0.000 0.148 0.028 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.3504 0.59541 0.816 0.000 0.160 0.008 0.016
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.7905 0.19305 0.004 0.444 0.136 0.124 0.292
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.1750 0.75614 0.036 0.000 0.000 0.936 0.028
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.4168 0.61364 0.004 0.284 0.004 0.704 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0451 0.88252 0.000 0.988 0.008 0.000 0.004
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.3160 0.73825 0.000 0.004 0.116 0.852 0.028
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 4 0.3887 0.72382 0.004 0.004 0.152 0.804 0.036
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.3471 0.58883 0.836 0.000 0.072 0.000 0.092
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.6817 0.58878 0.000 0.584 0.148 0.064 0.204
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.3109 0.70692 0.800 0.000 0.000 0.200 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.2798 0.71394 0.008 0.000 0.140 0.000 0.852
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.4933 0.51231 0.704 0.000 0.200 0.000 0.096
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.3768 0.66568 0.000 0.008 0.004 0.760 0.228
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 4 0.3134 0.71419 0.096 0.000 0.028 0.864 0.012
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.4227 0.47896 0.580 0.000 0.000 0.420 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 4 0.1671 0.73613 0.076 0.000 0.000 0.924 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.6072 0.49593 0.252 0.000 0.568 0.180 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 5 0.2569 0.73866 0.000 0.068 0.000 0.040 0.892
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 5 0.7346 0.32530 0.004 0.328 0.136 0.060 0.472
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.1251 0.63920 0.956 0.000 0.036 0.008 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.3003 0.70759 0.812 0.000 0.000 0.188 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 5 0.2909 0.71123 0.012 0.000 0.140 0.000 0.848
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 5 0.2801 0.73360 0.004 0.084 0.004 0.024 0.884
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 5 0.3612 0.53608 0.008 0.000 0.228 0.000 0.764
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.2230 0.71489 0.116 0.000 0.000 0.884 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.3163 0.69749 0.012 0.000 0.164 0.000 0.824
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.4173 0.70429 0.000 0.004 0.148 0.784 0.064
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 5 0.4567 0.18638 0.004 0.448 0.004 0.000 0.544
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.3013 0.70103 0.008 0.000 0.160 0.000 0.832
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.6983 0.43221 0.240 0.004 0.200 0.028 0.528
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 5 0.1329 0.75498 0.000 0.008 0.004 0.032 0.956
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.4109 0.67612 0.020 0.000 0.784 0.172 0.024
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.4505 0.55368 0.008 0.328 0.004 0.656 0.004
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.3526 0.75209 0.072 0.000 0.096 0.832 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 5 0.8168 0.37511 0.200 0.032 0.240 0.068 0.460
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.5944 0.48641 0.672 0.000 0.184 0.080 0.064
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 5 0.1924 0.74932 0.000 0.008 0.004 0.064 0.924
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.3210 0.70707 0.788 0.000 0.000 0.212 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0579 0.75581 0.008 0.000 0.008 0.000 0.984
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0404 0.88274 0.000 0.988 0.000 0.000 0.012
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.5994 0.55057 0.000 0.008 0.148 0.608 0.236
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.2017 0.74030 0.008 0.000 0.080 0.000 0.912
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4524 0.50548 0.000 0.020 0.644 0.000 0.336
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.4986 0.61734 0.104 0.000 0.716 0.176 0.004
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.4298 0.67233 0.052 0.000 0.168 0.008 0.772
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.5480 0.74500 0.000 0.712 0.152 0.096 0.040
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.2536 0.84150 0.000 0.868 0.128 0.000 0.004
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4305 0.67377 0.044 0.000 0.784 0.152 0.020
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.5161 0.48442 0.004 0.596 0.004 0.032 0.364
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.3635 0.59449 0.004 0.000 0.748 0.000 0.248
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.1792 0.73222 0.084 0.000 0.000 0.916 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0290 0.88179 0.000 0.992 0.000 0.000 0.008
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.5931 0.50183 0.204 0.000 0.200 0.000 0.596
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0727 0.87934 0.004 0.980 0.004 0.000 0.012
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.4074 0.70053 0.044 0.004 0.144 0.008 0.800
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.5939 0.60177 0.576 0.000 0.000 0.276 0.148
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 5 0.2011 0.73559 0.004 0.088 0.000 0.000 0.908
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 5 0.2692 0.73339 0.000 0.008 0.016 0.092 0.884
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0865 0.88192 0.000 0.972 0.024 0.000 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3395 0.69943 0.764 0.000 0.000 0.236 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.4386 0.81191 0.000 0.800 0.068 0.096 0.036
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0865 0.88192 0.000 0.972 0.024 0.000 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.5237 0.60849 0.012 0.000 0.272 0.056 0.660
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4490 0.69770 0.724 0.000 0.000 0.224 0.052
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1364 0.63931 0.952 0.000 0.036 0.012 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.1484 0.75748 0.008 0.000 0.048 0.944 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.4140 0.70318 0.000 0.048 0.148 0.792 0.012
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3676 0.66006 0.004 0.004 0.000 0.760 0.232
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.1364 0.75543 0.000 0.036 0.000 0.012 0.952
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.4991 0.65547 0.004 0.176 0.004 0.092 0.724
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 5 0.6206 0.55867 0.000 0.228 0.128 0.028 0.616
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.1605 0.87867 0.004 0.944 0.040 0.000 0.012
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.5625 0.59232 0.204 0.000 0.636 0.160 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4333 0.59535 0.000 0.048 0.740 0.000 0.212
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.4139 0.74719 0.084 0.000 0.132 0.784 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.0451 0.75539 0.008 0.000 0.004 0.000 0.988
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.4930 0.52995 0.220 0.000 0.696 0.000 0.084
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.5559 0.63456 0.200 0.000 0.036 0.076 0.688
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0486 0.87899 0.004 0.988 0.004 0.000 0.004
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.4256 0.08759 0.436 0.000 0.000 0.564 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.2909 0.71121 0.012 0.000 0.140 0.000 0.848
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5526 0.44315 0.648 0.000 0.200 0.000 0.152
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.6320 0.49962 0.012 0.004 0.144 0.584 0.256
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5439 0.66586 0.652 0.000 0.100 0.244 0.004
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3934 0.80350 0.000 0.792 0.168 0.032 0.008
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.3455 0.70827 0.784 0.000 0.000 0.208 0.008
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.2773 0.67425 0.164 0.000 0.000 0.836 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6398 0.43642 0.000 0.540 0.148 0.300 0.012
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0771 0.88226 0.000 0.976 0.020 0.000 0.004
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.6452 0.34737 0.008 0.000 0.152 0.500 0.340
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0451 0.88259 0.000 0.988 0.004 0.000 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5463 0.66067 0.648 0.000 0.100 0.248 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4140 0.61287 0.000 0.048 0.792 0.012 0.148
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4204 0.65326 0.028 0.000 0.808 0.060 0.104
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.4309 0.63814 0.084 0.000 0.000 0.768 0.148
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3387 0.76222 0.004 0.796 0.004 0.000 0.196
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6819 0.53471 0.000 0.560 0.148 0.048 0.244
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.5761 0.52938 0.184 0.000 0.196 0.000 0.620
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2027 0.87529 0.000 0.928 0.040 0.024 0.008
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.3177 0.70788 0.792 0.000 0.000 0.208 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4541 0.68451 0.096 0.000 0.788 0.084 0.032
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4404 0.70607 0.000 0.040 0.144 0.784 0.032
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3039 0.70728 0.808 0.000 0.000 0.192 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.5356 0.69194 0.000 0.044 0.148 0.724 0.084
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.8008 0.08091 0.128 0.000 0.164 0.308 0.400
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5072 0.56388 0.020 0.000 0.132 0.736 0.112
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.3086 0.65366 0.000 0.004 0.180 0.000 0.816
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5408 0.61321 0.180 0.000 0.664 0.156 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4672 0.14145 0.004 0.568 0.004 0.420 0.004
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0451 0.75539 0.008 0.000 0.004 0.000 0.988
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4181 0.66880 0.032 0.000 0.780 0.172 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0865 0.7734 0.000 0.964 0.000 0.000 0.000 0.036
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3390 0.6385 0.296 0.000 0.704 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.5484 0.3912 0.000 0.008 0.000 0.596 0.232 0.164
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4848 0.5999 0.684 0.000 0.184 0.000 0.008 0.124
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5272 0.2916 0.000 0.584 0.000 0.140 0.276 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0865 0.7734 0.000 0.964 0.000 0.000 0.000 0.036
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4792 0.4490 0.672 0.000 0.000 0.148 0.000 0.180
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4238 0.6206 0.728 0.000 0.180 0.000 0.000 0.092
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.6821 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0260 0.6819 0.992 0.000 0.008 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4767 0.5151 0.000 0.676 0.000 0.156 0.168 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.3190 0.7582 0.136 0.000 0.000 0.820 0.044 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.2969 0.7415 0.224 0.000 0.000 0.776 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0865 0.7734 0.000 0.964 0.000 0.000 0.000 0.036
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 5 0.1398 0.7160 0.000 0.008 0.000 0.052 0.940 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4807 0.5124 0.000 0.100 0.704 0.020 0.176 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.2163 0.7756 0.000 0.892 0.000 0.008 0.004 0.096
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4530 0.5165 0.000 0.000 0.704 0.136 0.160 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2070 0.7752 0.000 0.892 0.000 0.008 0.000 0.100
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#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2491 0.6538 0.000 0.000 0.000 0.836 0.000 0.164
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.4977 0.5905 0.000 0.000 0.000 0.648 0.188 0.164
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.1152 0.7164 0.000 0.044 0.000 0.004 0.952 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.5116 0.5046 0.000 0.204 0.000 0.084 0.676 0.036
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 5 0.4884 0.4757 0.000 0.220 0.000 0.128 0.652 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2520 0.7672 0.000 0.844 0.000 0.000 0.004 0.152
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3448 0.6485 0.280 0.000 0.716 0.004 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4331 0.5128 0.000 0.024 0.700 0.024 0.252 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.2178 0.7510 0.132 0.000 0.000 0.868 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.0146 0.7234 0.000 0.000 0.004 0.000 0.996 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.4347 0.3872 0.036 0.000 0.756 0.000 0.056 0.152
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.6487 0.3114 0.000 0.000 0.164 0.060 0.508 0.268
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0865 0.7734 0.000 0.964 0.000 0.000 0.000 0.036
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.4977 0.2632 0.648 0.000 0.000 0.188 0.000 0.164
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.2445 0.6859 0.000 0.004 0.120 0.000 0.868 0.008
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.7015 0.4539 0.440 0.000 0.292 0.000 0.116 0.152
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.3704 0.5601 0.016 0.008 0.000 0.744 0.232 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2734 0.6609 0.872 0.000 0.088 0.020 0.000 0.020
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.4863 0.4052 0.000 0.412 0.000 0.060 0.000 0.528
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0405 0.6825 0.988 0.000 0.008 0.000 0.000 0.004
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 4 0.3774 0.5684 0.408 0.000 0.000 0.592 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4128 0.1412 0.000 0.504 0.000 0.488 0.004 0.004
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.2070 0.7752 0.000 0.892 0.000 0.008 0.000 0.100
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.5356 0.4553 0.000 0.000 0.128 0.580 0.288 0.004
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0146 0.7843 0.000 0.996 0.000 0.000 0.004 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2734 0.6580 0.872 0.000 0.088 0.020 0.000 0.020
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.5136 0.5123 0.000 0.060 0.704 0.116 0.120 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4990 0.5464 0.048 0.000 0.708 0.176 0.064 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 4 0.5307 0.6391 0.256 0.000 0.000 0.588 0.156 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3352 0.6443 0.000 0.792 0.000 0.000 0.176 0.032
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5533 0.2287 0.000 0.544 0.000 0.172 0.284 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.4897 0.4659 0.000 0.000 0.292 0.000 0.616 0.092
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4281 0.5585 0.000 0.704 0.000 0.068 0.000 0.228
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0146 0.6820 0.996 0.000 0.004 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2311 0.6783 0.104 0.000 0.880 0.000 0.016 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.1049 0.7136 0.000 0.032 0.000 0.960 0.008 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0458 0.6820 0.984 0.000 0.000 0.000 0.000 0.016
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2511 0.6964 0.000 0.056 0.000 0.880 0.064 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.8095 0.0579 0.304 0.000 0.132 0.112 0.368 0.084
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5938 0.6389 0.176 0.000 0.120 0.628 0.072 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 5 0.2135 0.6643 0.000 0.000 0.128 0.000 0.872 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3266 0.6562 0.272 0.000 0.728 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4157 0.0731 0.000 0.544 0.000 0.444 0.000 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0146 0.7234 0.000 0.000 0.004 0.000 0.996 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.3000 0.6796 0.156 0.000 0.824 0.016 0.004 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.430 0.834 0.878 0.4087 0.614 0.614
#> 3 3 0.499 0.730 0.852 0.4842 0.578 0.409
#> 4 4 0.642 0.794 0.869 0.1635 0.816 0.575
#> 5 5 0.668 0.656 0.798 0.0867 0.896 0.665
#> 6 6 0.657 0.541 0.713 0.0397 0.906 0.643
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3733 0.8709 0.072 0.928
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 2 0.8081 0.7849 0.248 0.752
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.9909 -0.0583 0.556 0.444
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.1414 0.8620 0.020 0.980
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.9000 0.7157 0.316 0.684
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1843 0.8621 0.028 0.972
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0938 0.9375 0.988 0.012
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.5294 0.8611 0.880 0.120
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1184 0.9402 0.984 0.016
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.2603 0.8656 0.044 0.956
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.8386 0.7717 0.268 0.732
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1633 0.9370 0.976 0.024
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.1414 0.9389 0.980 0.020
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3733 0.8709 0.072 0.928
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4298 0.8968 0.912 0.088
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.4298 0.8700 0.088 0.912
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.5519 0.8702 0.128 0.872
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.4562 0.8701 0.096 0.904
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.5737 0.8684 0.136 0.864
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3733 0.8720 0.072 0.928
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1843 0.8640 0.028 0.972
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.4815 0.8738 0.104 0.896
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.4431 0.8703 0.092 0.908
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 2 0.7950 0.7840 0.240 0.760
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.8763 0.7617 0.296 0.704
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.7950 0.7933 0.240 0.760
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0938 0.8593 0.012 0.988
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.0938 0.8593 0.012 0.988
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1184 0.9402 0.984 0.016
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.9209 0.7031 0.336 0.664
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.0938 0.8593 0.012 0.988
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3733 0.8709 0.072 0.928
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.1184 0.9402 0.984 0.016
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1184 0.9402 0.984 0.016
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.3733 0.8709 0.072 0.928
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 2 0.7950 0.7865 0.240 0.760
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.4431 0.8676 0.092 0.908
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.1843 0.8664 0.028 0.972
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1184 0.9402 0.984 0.016
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1184 0.9402 0.984 0.016
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.9866 0.4976 0.432 0.568
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1843 0.9352 0.972 0.028
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.4022 0.8741 0.080 0.920
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.9129 0.7088 0.328 0.672
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.8608 0.7687 0.284 0.716
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1414 0.8635 0.020 0.980
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 2 0.1843 0.8670 0.028 0.972
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.3879 0.8703 0.076 0.924
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.2948 0.8738 0.052 0.948
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3584 0.8710 0.068 0.932
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.4161 0.8690 0.084 0.916
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.8763 0.7617 0.296 0.704
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.8327 0.6154 0.736 0.264
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 2 0.2778 0.8690 0.048 0.952
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 1.0000 0.1508 0.496 0.504
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0938 0.9375 0.988 0.012
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.3733 0.8711 0.072 0.928
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.4161 0.8690 0.084 0.916
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.1633 0.8655 0.024 0.976
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.5294 0.8710 0.120 0.880
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0938 0.9375 0.988 0.012
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5294 0.8728 0.120 0.880
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3879 0.9024 0.924 0.076
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.0938 0.8593 0.012 0.988
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 2 0.8207 0.7796 0.256 0.744
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.7745 0.8143 0.228 0.772
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.8763 0.7464 0.296 0.704
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.6712 0.7502 0.824 0.176
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0938 0.9375 0.988 0.012
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3584 0.9072 0.932 0.068
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.1633 0.9352 0.976 0.024
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1184 0.9402 0.984 0.016
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.4022 0.8702 0.080 0.920
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.1843 0.9352 0.972 0.028
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.4298 0.8700 0.088 0.912
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.9000 0.7241 0.316 0.684
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.5629 0.8699 0.132 0.868
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.5294 0.8710 0.120 0.880
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#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.8144 0.5852 0.748 0.252
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.7376 0.8301 0.208 0.792
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.5519 0.8702 0.128 0.872
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.8713 0.7549 0.292 0.708
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 2 0.9850 0.4928 0.428 0.572
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.2603 0.8712 0.044 0.956
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.8661 0.7644 0.288 0.712
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.3733 0.9051 0.928 0.072
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.2423 0.9326 0.960 0.040
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.3114 0.8750 0.056 0.944
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1843 0.8655 0.028 0.972
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5294 0.8710 0.120 0.880
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.5059 0.8731 0.112 0.888
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 2 0.8327 0.7771 0.264 0.736
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.4161 0.8690 0.084 0.916
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.9522 0.6441 0.372 0.628
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.7056 0.8416 0.192 0.808
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 2 0.0938 0.8595 0.012 0.988
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7674 0.8084 0.224 0.776
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1843 0.8621 0.028 0.972
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1184 0.9402 0.984 0.016
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.0672 0.8588 0.008 0.992
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.0938 0.8593 0.012 0.988
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.9129 0.7104 0.328 0.672
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1184 0.9402 0.984 0.016
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.7950 0.8050 0.240 0.760
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.9358 0.3421 0.648 0.352
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.1184 0.9402 0.984 0.016
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.9209 0.7031 0.336 0.664
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.5519 0.8702 0.128 0.872
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.5294 0.8730 0.120 0.880
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4022 0.8741 0.080 0.920
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1633 0.9373 0.976 0.024
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.4298 0.8700 0.088 0.912
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.9044 0.7141 0.320 0.680
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.9129 0.3698 0.672 0.328
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3879 0.8722 0.076 0.924
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.9209 0.7031 0.336 0.664
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.4022 0.8724 0.080 0.920
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.8909 0.7343 0.308 0.692
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1184 0.9402 0.984 0.016
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 2 0.4431 0.8676 0.092 0.908
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.8909 0.7314 0.308 0.692
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4815 0.8708 0.896 0.104
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.9129 0.6984 0.328 0.672
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.6712 0.8551 0.176 0.824
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3274 0.9143 0.940 0.060
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.4690 0.8687 0.100 0.900
#> AB642383-1611-4355-B03C-08D42FF4676C 2 0.6048 0.8609 0.148 0.852
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3584 0.8710 0.068 0.932
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.0672 0.8615 0.008 0.992
#> EE118E80-F125-4655-8845-56A9CBBA0680 2 0.7299 0.8178 0.204 0.796
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.7793 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5442 0.7626 0.132 0.056 0.812
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.0237 0.8755 0.996 0.004 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.6297 0.7347 0.060 0.756 0.184
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.5339 0.8174 0.824 0.080 0.096
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0424 0.7803 0.000 0.992 0.008
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.8762 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4994 0.7499 0.816 0.024 0.160
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8762 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.4195 0.7617 0.136 0.852 0.012
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.5915 0.7976 0.792 0.080 0.128
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0000 0.8762 1.000 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.8762 1.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.7793 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4807 0.8291 0.848 0.060 0.092
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.2448 0.8328 0.000 0.076 0.924
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.6673 0.3738 0.344 0.636 0.020
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.2584 0.8352 0.008 0.064 0.928
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.6973 0.1434 0.416 0.564 0.020
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3406 0.7860 0.068 0.904 0.028
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.2261 0.7776 0.068 0.932 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7739 0.5043 0.268 0.644 0.088
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2261 0.8347 0.000 0.068 0.932
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5471 0.7655 0.128 0.060 0.812
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3141 0.8437 0.912 0.068 0.020
#> C6AD4922-9981-4493-9F33-87A449B6EE55 1 0.6460 0.7762 0.764 0.124 0.112
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.5722 0.7662 0.068 0.800 0.132
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.5791 0.7608 0.060 0.792 0.148
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.8762 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 1 0.4652 0.8288 0.856 0.080 0.064
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.5791 0.7608 0.060 0.792 0.148
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0424 0.7787 0.000 0.992 0.008
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0424 0.8754 0.992 0.008 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.8762 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0592 0.7778 0.000 0.988 0.012
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4179 0.8047 0.072 0.052 0.876
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1860 0.8356 0.000 0.052 0.948
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.5656 0.7684 0.068 0.804 0.128
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.8762 1.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.8762 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 1 0.2383 0.8629 0.940 0.044 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0237 0.8756 0.996 0.000 0.004
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0237 0.7792 0.000 0.996 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 1 0.4925 0.8251 0.844 0.080 0.076
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.6280 0.0207 0.540 0.460 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1643 0.7878 0.000 0.956 0.044
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.6267 0.1652 0.000 0.452 0.548
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0424 0.7817 0.008 0.992 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.2625 0.7817 0.000 0.916 0.084
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0592 0.7778 0.000 0.988 0.012
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.1860 0.8356 0.000 0.052 0.948
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4883 0.7058 0.788 0.208 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1163 0.8711 0.972 0.028 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.6247 0.3730 0.004 0.376 0.620
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.7027 0.6547 0.724 0.104 0.172
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.8762 1.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4384 0.7876 0.068 0.868 0.064
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.1964 0.8355 0.000 0.056 0.944
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.2356 0.7860 0.000 0.928 0.072
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.9638 0.0508 0.420 0.372 0.208
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.8762 1.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.2066 0.7595 0.000 0.940 0.060
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3715 0.8052 0.868 0.004 0.128
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.5667 0.7656 0.060 0.800 0.140
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.6398 0.7157 0.192 0.060 0.748
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.9106 0.2682 0.180 0.536 0.284
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 1 0.4662 0.8159 0.844 0.124 0.032
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.3649 0.8400 0.896 0.068 0.036
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.8762 1.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3340 0.8128 0.880 0.000 0.120
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.8762 1.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.8762 1.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.3412 0.7988 0.000 0.124 0.876
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0000 0.8762 1.000 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.3500 0.8163 0.004 0.116 0.880
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 0.3918 0.8303 0.868 0.120 0.012
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.4974 0.6365 0.236 0.764 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.7918 0.6296 0.660 0.136 0.204
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1182 0.8728 0.976 0.012 0.012
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.8762 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 2 0.5722 0.7662 0.068 0.800 0.132
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.2066 0.8349 0.000 0.060 0.940
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.2599 0.8338 0.016 0.052 0.932
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 2 0.8030 0.6188 0.204 0.652 0.144
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.2066 0.8349 0.000 0.060 0.940
#> E435C03F-0277-49C1-83EF-19452082723E 2 0.7605 0.6708 0.124 0.684 0.192
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.7699 0.2819 0.388 0.560 0.052
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.3713 0.8418 0.892 0.076 0.032
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0424 0.7803 0.000 0.992 0.008
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.5667 0.7656 0.060 0.800 0.140
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.0237 0.8755 0.996 0.000 0.004
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.2261 0.7776 0.068 0.932 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0892 0.7792 0.000 0.980 0.020
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.7113 0.6981 0.168 0.112 0.720
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.5377 0.7761 0.068 0.820 0.112
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.1964 0.8563 0.944 0.056 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.8762 1.000 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 2 0.5722 0.7662 0.068 0.800 0.132
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.8082 0.5225 0.608 0.296 0.096
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.0892 0.8726 0.980 0.000 0.020
#> E3A5FB64-EB24-4A24-9B79-539012C57711 2 0.3983 0.7675 0.004 0.852 0.144
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0237 0.8752 0.996 0.004 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 1 0.5285 0.7958 0.812 0.148 0.040
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.2584 0.8366 0.008 0.064 0.928
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.6295 0.6960 0.728 0.236 0.036
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.6225 0.2216 0.000 0.432 0.568
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 1 0.5416 0.8141 0.820 0.080 0.100
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.1860 0.8356 0.000 0.052 0.948
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0000 0.8762 1.000 0.000 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 2 0.2550 0.7906 0.040 0.936 0.024
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.5780 0.8025 0.800 0.080 0.120
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.2796 0.7821 0.000 0.908 0.092
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0592 0.8745 0.988 0.012 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0237 0.7792 0.000 0.996 0.004
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.6858 0.6628 0.728 0.084 0.188
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.1964 0.8361 0.000 0.056 0.944
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0424 0.7803 0.000 0.992 0.008
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.7912 0.1882 0.536 0.060 0.404
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0829 0.7786 0.004 0.984 0.012
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.1031 0.7852 0.000 0.976 0.024
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.5603 0.7589 0.136 0.060 0.804
#> 55788408-50CF-4518-8A82-1D94AEA7444E 2 0.6372 0.7373 0.068 0.756 0.176
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 1 0.4821 0.7908 0.848 0.088 0.064
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#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.5010 0.8249 0.840 0.076 0.084
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.8762 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.9304 0.2449 0.300 0.508 0.192
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4563 0.8105 0.852 0.036 0.112
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.8762 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.4836 0.8262 0.848 0.080 0.072
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.4371 0.7146 0.108 0.860 0.032
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.7860 0.4531 0.628 0.284 0.088
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0592 0.7778 0.000 0.988 0.012
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8762 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.1964 0.8354 0.000 0.056 0.944
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.7804 0.6363 0.664 0.120 0.216
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0983 0.8733 0.980 0.016 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0747 0.7848 0.000 0.984 0.016
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.4925 0.8251 0.844 0.080 0.076
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.6880 0.6025 0.036 0.660 0.304
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.5268 0.7236 0.776 0.212 0.012
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8762 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1860 0.8356 0.000 0.052 0.948
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.4128 0.8207 0.856 0.132 0.012
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.5560 0.4946 0.700 0.300 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.5096 0.8223 0.836 0.080 0.084
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.6678 0.6702 0.728 0.064 0.208
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1860 0.8612 0.948 0.000 0.052
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2400 0.8362 0.004 0.064 0.932
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3856 0.8254 0.040 0.072 0.888
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0592 0.7778 0.000 0.988 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.3784 0.7737 0.004 0.864 0.132
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4379 0.8080 0.072 0.060 0.868
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.0336 0.8368 0.000 0.008 0.000 0.992
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.5698 0.8119 0.104 0.064 0.768 0.064
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.0921 0.9154 0.972 0.028 0.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 4 0.3791 0.8012 0.000 0.004 0.200 0.796
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1302 0.8021 0.044 0.956 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3962 0.7872 0.820 0.028 0.152 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 4 0.1362 0.8400 0.020 0.004 0.012 0.964
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.1302 0.8021 0.044 0.956 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0707 0.9162 0.980 0.020 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0592 0.9172 0.984 0.016 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.2149 0.8059 0.000 0.088 0.000 0.912
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4978 0.4500 0.612 0.384 0.004 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.2542 0.8476 0.000 0.084 0.904 0.012
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.3688 0.7598 0.000 0.792 0.000 0.208
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3105 0.8130 0.000 0.140 0.856 0.004
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.3626 0.7781 0.004 0.812 0.000 0.184
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.0000 0.8379 0.000 0.000 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.6094 0.7081 0.112 0.112 0.040 0.736
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2413 0.8588 0.000 0.020 0.916 0.064
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.5950 0.8022 0.072 0.112 0.752 0.064
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5423 0.7190 0.740 0.116 0.000 0.144
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.2282 0.8234 0.024 0.924 0.000 0.052
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 4 0.3355 0.8190 0.000 0.004 0.160 0.836
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 4 0.3751 0.8015 0.000 0.004 0.196 0.800
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.2973 0.7634 0.144 0.856 0.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 4 0.3710 0.8040 0.000 0.004 0.192 0.804
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.1792 0.8186 0.000 0.068 0.000 0.932
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0707 0.9176 0.980 0.020 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.2973 0.7575 0.000 0.144 0.000 0.856
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4427 0.8524 0.032 0.084 0.836 0.048
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1576 0.8606 0.000 0.004 0.948 0.048
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 4 0.2831 0.8310 0.000 0.004 0.120 0.876
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 1 0.3056 0.8665 0.888 0.072 0.000 0.040
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.1302 0.9096 0.956 0.044 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.3074 0.7487 0.000 0.152 0.000 0.848
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.1389 0.8017 0.048 0.952 0.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.4431 0.5907 0.304 0.000 0.000 0.696
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 4 0.0336 0.8376 0.000 0.008 0.000 0.992
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 4 0.4134 0.7541 0.000 0.000 0.260 0.740
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3333 0.8220 0.000 0.088 0.040 0.872
#> 36B2E208-FF01-4249-92C3-BE77D426691B 4 0.1557 0.8220 0.000 0.056 0.000 0.944
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.2401 0.8478 0.000 0.092 0.904 0.004
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 4 0.4998 0.1328 0.488 0.000 0.000 0.512
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.3157 0.7863 0.852 0.004 0.000 0.144
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 4 0.4103 0.7650 0.000 0.000 0.256 0.744
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.7243 0.5425 0.640 0.044 0.140 0.176
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.0592 0.8377 0.000 0.016 0.000 0.984
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.1489 0.8572 0.000 0.044 0.952 0.004
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.0000 0.8379 0.000 0.000 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.4106 0.8076 0.024 0.852 0.052 0.072
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 4 0.4661 0.3531 0.000 0.348 0.000 0.652
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3858 0.8409 0.844 0.100 0.056 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 4 0.3668 0.8060 0.000 0.004 0.188 0.808
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.6277 0.7808 0.132 0.064 0.728 0.076
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.5453 0.4845 0.008 0.620 0.012 0.360
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.2830 0.8239 0.040 0.900 0.000 0.060
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.3688 0.7371 0.792 0.208 0.000 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3691 0.8484 0.856 0.076 0.068 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0188 0.9151 0.996 0.004 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.2844 0.8691 0.000 0.048 0.900 0.052
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0817 0.9161 0.976 0.024 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.3778 0.8529 0.000 0.100 0.848 0.052
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 0.4188 0.7992 0.824 0.064 0.000 0.112
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.4713 0.6761 0.172 0.052 0.000 0.776
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.4884 0.7976 0.048 0.816 0.072 0.064
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.1211 0.9121 0.960 0.040 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 4 0.3539 0.8123 0.000 0.004 0.176 0.820
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.1305 0.8546 0.000 0.036 0.960 0.004
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.3329 0.8701 0.004 0.072 0.880 0.044
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.5371 0.7598 0.080 0.000 0.188 0.732
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0376 0.8453 0.000 0.004 0.992 0.004
#> E435C03F-0277-49C1-83EF-19452082723E 4 0.3831 0.7986 0.000 0.004 0.204 0.792
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.3182 0.7948 0.004 0.860 0.004 0.132
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.4277 0.6260 0.280 0.720 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 4 0.3668 0.8060 0.000 0.004 0.188 0.808
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.1209 0.9133 0.964 0.032 0.004 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.1042 0.8331 0.008 0.020 0.000 0.972
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 4 0.1389 0.8253 0.000 0.048 0.000 0.952
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.6701 0.2890 0.016 0.572 0.348 0.064
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 4 0.2831 0.8290 0.000 0.004 0.120 0.876
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.2413 0.8688 0.916 0.020 0.000 0.064
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 4 0.3583 0.8104 0.000 0.004 0.180 0.816
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.8003 0.1281 0.388 0.120 0.040 0.452
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.2401 0.8819 0.904 0.092 0.004 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 4 0.3539 0.8119 0.000 0.004 0.176 0.820
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.2908 0.8234 0.040 0.896 0.000 0.064
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.3474 0.8627 0.000 0.068 0.868 0.064
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.2722 0.8239 0.032 0.904 0.000 0.064
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 4 0.4761 0.6769 0.000 0.004 0.332 0.664
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.1302 0.8021 0.044 0.956 0.000 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.3117 0.8570 0.000 0.092 0.880 0.028
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.1398 0.9107 0.956 0.040 0.004 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 4 0.0336 0.8376 0.000 0.008 0.000 0.992
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.1576 0.8008 0.048 0.948 0.004 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 4 0.2644 0.8294 0.000 0.060 0.032 0.908
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0592 0.9114 0.984 0.000 0.000 0.016
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.2345 0.7975 0.000 0.100 0.000 0.900
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.7093 0.5196 0.644 0.032 0.160 0.164
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.1557 0.8574 0.000 0.000 0.944 0.056
#> 810FC459-F77D-462D-90B7-E77C1FD43981 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.6906 0.4505 0.368 0.004 0.528 0.100
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.3486 0.7186 0.000 0.188 0.000 0.812
#> DFADB933-D083-4175-88A6-72086FD5115E 4 0.0000 0.8379 0.000 0.000 0.000 1.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.5474 0.7762 0.160 0.020 0.756 0.064
#> 55788408-50CF-4518-8A82-1D94AEA7444E 4 0.3791 0.8012 0.000 0.004 0.200 0.796
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 1 0.4083 0.8321 0.832 0.100 0.000 0.068
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 4 0.3765 0.8094 0.004 0.004 0.180 0.812
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0469 0.9174 0.988 0.012 0.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.3617 0.7974 0.000 0.860 0.064 0.076
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 4 0.0336 0.8376 0.000 0.008 0.000 0.992
#> FE330797-5A40-45A8-98DF-43A33369E90F 4 0.0927 0.8407 0.000 0.008 0.016 0.976
#> DAD951A3-C22E-42F0-BB02-854413DDC351 4 0.0524 0.8370 0.004 0.008 0.000 0.988
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 4 0.6696 0.1613 0.000 0.428 0.088 0.484
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.1824 0.8573 0.000 0.004 0.936 0.060
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.4269 0.8599 0.044 0.060 0.848 0.048
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 1 0.0779 0.9176 0.980 0.016 0.000 0.004
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.2983 0.8230 0.040 0.892 0.000 0.068
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#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4814 0.6135 0.000 0.676 0.008 0.316
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.6081 0.7987 0.088 0.108 0.744 0.060
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.2401 0.8478 0.000 0.092 0.904 0.004
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.3975 0.6759 0.240 0.760 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.5235 0.7954 0.088 0.796 0.056 0.060
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 4 0.4193 0.7538 0.000 0.000 0.268 0.732
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6507 -0.0664 0.468 0.052 0.008 0.472
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0469 0.9174 0.988 0.012 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.3668 0.8060 0.000 0.004 0.188 0.808
#> C20F209A-2102-4502-80FA-17AF04601987 4 0.3710 0.8040 0.000 0.004 0.192 0.804
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.2654 0.7707 0.108 0.888 0.000 0.004
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0657 0.9175 0.984 0.012 0.004 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.2922 0.8130 0.008 0.884 0.004 0.104
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.6310 0.6605 0.692 0.112 0.180 0.016
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1940 0.7987 0.076 0.924 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.3486 0.7755 0.000 0.812 0.000 0.188
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.7062 0.0396 0.448 0.052 0.032 0.468
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.3444 0.7189 0.000 0.184 0.000 0.816
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0188 0.9164 0.996 0.004 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.2401 0.8478 0.000 0.092 0.904 0.004
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.4264 0.7960 0.052 0.848 0.060 0.040
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1389 0.8873 0.952 0.000 0.000 0.048
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.2868 0.7736 0.000 0.136 0.000 0.864
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.1389 0.8017 0.048 0.952 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 4 0.4018 0.7858 0.000 0.004 0.224 0.772
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.5140 0.7306 0.760 0.096 0.000 0.144
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9152 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1398 0.8607 0.000 0.004 0.956 0.040
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.6315 0.4289 0.396 0.540 0.000 0.064
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0921 0.9036 0.972 0.000 0.000 0.028
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.1902 0.7939 0.064 0.932 0.004 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.8783 0.3286 0.516 0.144 0.200 0.140
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3208 0.8354 0.848 0.148 0.004 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4514 0.8297 0.000 0.136 0.800 0.064
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3725 0.8695 0.024 0.052 0.872 0.052
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.0188 0.8374 0.000 0.004 0.000 0.996
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.3450 0.8186 0.000 0.008 0.156 0.836
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.5250 0.7701 0.004 0.192 0.744 0.060
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 5 0.4307 0.3692 0.000 0.500 0.000 0.000 0.500
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3584 0.8013 0.132 0.000 0.828 0.012 0.028
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.2374 0.8764 0.912 0.016 0.020 0.052 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0609 0.6701 0.000 0.000 0.020 0.000 0.980
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0000 0.7424 0.000 0.000 0.000 1.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 5 0.4242 0.5222 0.000 0.428 0.000 0.000 0.572
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4023 0.7911 0.800 0.004 0.048 0.004 0.144
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0324 0.8914 0.992 0.004 0.004 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.3441 0.6704 0.024 0.148 0.004 0.000 0.824
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0290 0.7427 0.000 0.000 0.008 0.992 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.2722 0.8479 0.868 0.008 0.004 0.120 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.1455 0.8900 0.952 0.008 0.008 0.032 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3333 0.5538 0.000 0.788 0.000 0.004 0.208
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4109 0.5018 0.260 0.008 0.008 0.724 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.2053 0.8508 0.000 0.016 0.928 0.016 0.040
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.5176 -0.1756 0.000 0.560 0.036 0.400 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.2411 0.8345 0.004 0.008 0.912 0.052 0.024
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.5345 -0.2731 0.000 0.520 0.036 0.436 0.008
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.4138 0.5770 0.000 0.384 0.000 0.000 0.616
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 5 0.3966 0.6168 0.000 0.336 0.000 0.000 0.664
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7347 0.4243 0.180 0.572 0.068 0.020 0.160
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.2193 0.8620 0.000 0.000 0.900 0.008 0.092
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.3234 0.8170 0.092 0.000 0.856 0.048 0.004
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3232 0.8550 0.864 0.000 0.016 0.084 0.036
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.1043 0.7403 0.000 0.000 0.040 0.960 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.1478 0.6909 0.000 0.064 0.000 0.000 0.936
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0510 0.6712 0.000 0.000 0.016 0.000 0.984
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0451 0.8912 0.988 0.008 0.004 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.1251 0.7389 0.036 0.000 0.008 0.956 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0162 0.6727 0.000 0.000 0.004 0.000 0.996
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3196 0.5769 0.000 0.804 0.000 0.004 0.192
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0865 0.8913 0.972 0.004 0.000 0.024 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0324 0.8914 0.992 0.004 0.004 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.2798 0.6232 0.000 0.852 0.000 0.008 0.140
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.2941 0.8457 0.064 0.000 0.884 0.020 0.032
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2286 0.8607 0.000 0.000 0.888 0.004 0.108
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.2536 0.6906 0.000 0.128 0.004 0.000 0.868
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0486 0.8917 0.988 0.004 0.004 0.000 0.004
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0451 0.8912 0.988 0.008 0.004 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 1 0.5487 0.6309 0.664 0.248 0.024 0.064 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0771 0.8927 0.976 0.004 0.000 0.020 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.2660 0.6280 0.000 0.864 0.000 0.008 0.128
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.0324 0.7435 0.004 0.000 0.004 0.992 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3826 0.6621 0.752 0.000 0.004 0.008 0.236
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 5 0.4030 0.6047 0.000 0.352 0.000 0.000 0.648
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.0609 0.6680 0.000 0.000 0.020 0.000 0.980
#> 69595C5D-6655-4065-8943-90045A2B2478 5 0.4302 0.4211 0.000 0.480 0.000 0.000 0.520
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.4605 0.5071 0.000 0.692 0.032 0.004 0.272
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3662 0.4904 0.000 0.744 0.000 0.004 0.252
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.1988 0.8527 0.000 0.008 0.928 0.016 0.048
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.2694 0.8115 0.864 0.000 0.004 0.004 0.128
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1285 0.8869 0.956 0.004 0.004 0.000 0.036
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1478 0.6580 0.000 0.000 0.064 0.000 0.936
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4855 0.6791 0.708 0.004 0.052 0.004 0.232
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.4590 0.5094 0.000 0.420 0.012 0.000 0.568
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.2302 0.8602 0.000 0.008 0.904 0.008 0.080
#> F043185A-D4D2-4503-93FA-A7B7DA684290 5 0.4235 0.5277 0.000 0.424 0.000 0.000 0.576
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.6485 0.5452 0.000 0.284 0.112 0.568 0.036
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3641 0.6297 0.000 0.844 0.020 0.060 0.076
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3719 0.8467 0.852 0.008 0.064 0.032 0.044
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0703 0.6836 0.000 0.024 0.000 0.000 0.976
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.3943 0.7678 0.164 0.000 0.796 0.020 0.020
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 4 0.6510 0.3177 0.008 0.428 0.072 0.464 0.028
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4591 0.5748 0.004 0.324 0.012 0.656 0.004
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.3234 0.6688 0.144 0.008 0.012 0.836 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3005 0.8596 0.884 0.004 0.048 0.012 0.052
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0898 0.8911 0.972 0.020 0.008 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0451 0.8912 0.988 0.008 0.004 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.2131 0.8558 0.000 0.008 0.920 0.016 0.056
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0932 0.8924 0.972 0.004 0.004 0.020 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.2027 0.8468 0.000 0.008 0.928 0.024 0.040
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 0.6743 0.1885 0.468 0.420 0.036 0.048 0.028
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.3217 0.6308 0.020 0.864 0.016 0.004 0.096
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.3495 0.6992 0.000 0.008 0.120 0.836 0.036
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2488 0.8520 0.872 0.000 0.004 0.124 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0162 0.8913 0.996 0.000 0.004 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0880 0.6858 0.000 0.032 0.000 0.000 0.968
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.2237 0.8605 0.000 0.008 0.904 0.004 0.084
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.2733 0.8656 0.016 0.000 0.888 0.016 0.080
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.5310 0.3521 0.264 0.080 0.004 0.000 0.652
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.2753 0.8555 0.000 0.008 0.856 0.000 0.136
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.1403 0.6565 0.024 0.000 0.024 0.000 0.952
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 4 0.5947 0.3227 0.008 0.460 0.040 0.472 0.020
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 4 0.2389 0.6991 0.116 0.000 0.004 0.880 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 5 0.4256 0.5097 0.000 0.436 0.000 0.000 0.564
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.1197 0.6886 0.000 0.048 0.000 0.000 0.952
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.1116 0.8919 0.964 0.004 0.004 0.028 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 5 0.4291 0.4618 0.000 0.464 0.000 0.000 0.536
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.3455 0.5653 0.000 0.784 0.000 0.008 0.208
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 4 0.3741 0.4720 0.004 0.000 0.264 0.732 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.4127 0.6182 0.000 0.312 0.008 0.000 0.680
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.1153 0.8888 0.964 0.000 0.004 0.008 0.024
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0324 0.8914 0.992 0.004 0.004 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.1544 0.6913 0.000 0.068 0.000 0.000 0.932
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.7367 0.4438 0.576 0.220 0.048 0.052 0.104
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.3362 0.8207 0.824 0.008 0.012 0.156 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0771 0.6831 0.000 0.020 0.004 0.000 0.976
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0486 0.8918 0.988 0.004 0.004 0.000 0.004
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 4 0.2879 0.7224 0.004 0.096 0.020 0.876 0.004
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.2438 0.8593 0.000 0.000 0.900 0.040 0.060
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.4783 0.5457 0.004 0.348 0.016 0.628 0.004
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.0510 0.6659 0.000 0.000 0.016 0.000 0.984
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.0162 0.7432 0.004 0.000 0.000 0.996 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.2131 0.8554 0.000 0.008 0.920 0.016 0.056
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.3509 0.7824 0.792 0.008 0.004 0.196 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.3586 0.6488 0.000 0.264 0.000 0.000 0.736
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.0579 0.7420 0.008 0.000 0.008 0.984 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.4268 0.4913 0.000 0.708 0.016 0.004 0.272
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0613 0.8920 0.984 0.000 0.004 0.004 0.008
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#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.4461 0.6788 0.000 0.032 0.136 0.784 0.048
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2732 0.8488 0.000 0.000 0.840 0.000 0.160
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 5 0.4182 0.5597 0.000 0.400 0.000 0.000 0.600
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.2517 0.8589 0.884 0.008 0.004 0.104 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 4 0.8626 0.1294 0.020 0.296 0.172 0.368 0.144
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.3160 0.6781 0.000 0.188 0.004 0.000 0.808
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.3828 0.7078 0.004 0.100 0.060 0.828 0.008
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.3969 0.6326 0.000 0.304 0.004 0.000 0.692
#> A2007795-C728-4688-B199-AE89500011D2 2 0.3831 0.6318 0.000 0.812 0.044 0.008 0.136
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.2624 0.6968 0.116 0.000 0.012 0.872 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.5254 0.4632 0.028 0.340 0.020 0.000 0.612
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.2047 0.8482 0.000 0.012 0.928 0.020 0.040
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5716 0.7501 0.136 0.020 0.724 0.052 0.068
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.1357 0.6900 0.000 0.048 0.004 0.000 0.948
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.0451 0.7431 0.008 0.000 0.004 0.988 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.5636 0.4965 0.000 0.368 0.064 0.560 0.008
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.2352 0.8620 0.004 0.000 0.896 0.008 0.092
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4798 -0.0305 0.000 0.576 0.016 0.004 0.404
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.1913 0.8508 0.000 0.008 0.932 0.016 0.044
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1329 0.8899 0.956 0.008 0.004 0.032 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.3452 0.4938 0.000 0.756 0.000 0.000 0.244
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0510 0.6813 0.000 0.016 0.000 0.000 0.984
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 5 0.4283 0.4714 0.000 0.456 0.000 0.000 0.544
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.3876 0.6259 0.000 0.316 0.000 0.000 0.684
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0613 0.8916 0.984 0.008 0.004 0.004 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0960 0.8914 0.972 0.000 0.004 0.008 0.016
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.7173 0.3340 0.000 0.568 0.128 0.172 0.132
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.0404 0.7428 0.000 0.000 0.012 0.988 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.5599 0.3833 0.000 0.448 0.052 0.492 0.008
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0613 0.8920 0.984 0.000 0.004 0.004 0.008
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.5199 0.4588 0.000 0.412 0.036 0.548 0.004
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4525 0.4532 0.000 0.764 0.036 0.172 0.028
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.3053 0.6314 0.008 0.000 0.164 0.828 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1670 0.8853 0.936 0.000 0.000 0.052 0.012
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.2438 0.6154 0.060 0.000 0.040 0.000 0.900
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.5813 0.3807 0.380 0.064 0.008 0.544 0.004
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.2102 0.8786 0.916 0.004 0.012 0.068 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.2463 0.8669 0.888 0.008 0.004 0.100 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4661 0.3989 0.000 0.656 0.032 0.000 0.312
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.4235 0.5289 0.000 0.424 0.000 0.000 0.576
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.5759 0.5385 0.000 0.328 0.068 0.588 0.016
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.5504 0.4127 0.000 0.700 0.076 0.184 0.040
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3691 0.7880 0.076 0.000 0.820 0.104 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.2011 0.8494 0.000 0.008 0.928 0.020 0.044
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.1894 0.7225 0.072 0.000 0.008 0.920 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.5598 0.6023 0.168 0.000 0.120 0.688 0.024
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.0794 0.6655 0.000 0.000 0.028 0.000 0.972
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.7429 0.1069 0.448 0.236 0.028 0.008 0.280
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 5 0.4268 0.4952 0.000 0.444 0.000 0.000 0.556
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0324 0.8917 0.992 0.000 0.004 0.004 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0955 0.6838 0.000 0.028 0.004 0.000 0.968
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.0451 0.6769 0.000 0.004 0.008 0.000 0.988
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.0510 0.7424 0.016 0.000 0.000 0.984 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0854 0.8923 0.976 0.004 0.008 0.012 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 4 0.5785 0.3900 0.008 0.432 0.036 0.508 0.016
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5020 0.7371 0.744 0.004 0.168 0.040 0.044
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.0566 0.7430 0.012 0.000 0.004 0.984 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.5465 0.1661 0.000 0.644 0.056 0.280 0.020
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.6234 0.5637 0.656 0.140 0.036 0.008 0.160
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.2942 0.6311 0.000 0.856 0.008 0.008 0.128
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0324 0.8913 0.992 0.004 0.004 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.2053 0.8508 0.000 0.016 0.928 0.016 0.040
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.2563 0.6810 0.008 0.000 0.120 0.872 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0960 0.8929 0.972 0.000 0.004 0.016 0.008
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3611 0.6199 0.000 0.812 0.028 0.004 0.156
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0162 0.7432 0.004 0.000 0.000 0.996 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.2233 0.6280 0.004 0.000 0.104 0.000 0.892
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.4944 0.3293 0.240 0.708 0.024 0.016 0.012
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0613 0.8916 0.984 0.008 0.004 0.004 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2329 0.8558 0.000 0.000 0.876 0.000 0.124
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.7189 0.3866 0.244 0.304 0.016 0.432 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1991 0.8662 0.916 0.004 0.004 0.000 0.076
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0000 0.7424 0.000 0.000 0.000 1.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5495 0.6887 0.700 0.000 0.152 0.024 0.124
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3678 0.8041 0.804 0.008 0.020 0.168 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.1836 0.8465 0.000 0.000 0.932 0.032 0.036
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.3348 0.8635 0.032 0.004 0.864 0.020 0.080
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4294 -0.2691 0.000 0.532 0.000 0.000 0.468
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3513 0.6798 0.000 0.180 0.020 0.000 0.800
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.2746 0.8190 0.008 0.000 0.872 0.112 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.1556 0.58883 0.000 0.920 0.000 0.000 0.000 0.080
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3316 0.79225 0.100 0.000 0.844 0.012 0.020 0.024
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.7221 0.44023 0.468 0.024 0.012 0.040 0.188 0.268
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4524 0.88943 0.024 0.452 0.004 0.000 0.520 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0976 0.73242 0.000 0.008 0.016 0.968 0.000 0.008
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0909 0.59161 0.000 0.968 0.000 0.012 0.000 0.020
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0260 0.81193 0.992 0.000 0.000 0.000 0.000 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3894 0.74593 0.800 0.004 0.048 0.004 0.128 0.016
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0520 0.81248 0.984 0.000 0.000 0.000 0.008 0.008
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.4524 -0.58999 0.040 0.584 0.000 0.000 0.376 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0935 0.72590 0.000 0.000 0.004 0.964 0.000 0.032
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5639 0.67439 0.676 0.012 0.024 0.184 0.080 0.024
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3885 0.79323 0.828 0.012 0.024 0.056 0.068 0.012
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3756 0.16171 0.000 0.600 0.000 0.000 0.000 0.400
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.4033 0.61957 0.112 0.012 0.028 0.800 0.048 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.3464 0.81246 0.000 0.016 0.848 0.028 0.060 0.048
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 6 0.4513 0.53336 0.000 0.052 0.008 0.264 0.000 0.676
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3634 0.80412 0.000 0.004 0.832 0.060 0.056 0.048
#> 479B4832-82DB-4176-9D24-D588F2903617 6 0.4127 0.51716 0.000 0.036 0.000 0.284 0.000 0.680
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.1413 0.56186 0.004 0.948 0.000 0.008 0.036 0.004
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1010 0.55583 0.000 0.960 0.000 0.000 0.036 0.004
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7527 -0.13805 0.136 0.404 0.064 0.020 0.024 0.352
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.1863 0.83467 0.000 0.000 0.920 0.016 0.060 0.004
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.2622 0.80543 0.056 0.000 0.892 0.020 0.008 0.024
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4068 0.78856 0.816 0.044 0.016 0.056 0.004 0.064
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.2358 0.68214 0.000 0.000 0.016 0.876 0.000 0.108
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.4755 -0.79632 0.024 0.512 0.004 0.000 0.452 0.008
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.4527 0.88961 0.024 0.456 0.004 0.000 0.516 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2066 0.80350 0.904 0.000 0.000 0.000 0.072 0.024
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.1652 0.72942 0.004 0.012 0.016 0.944 0.004 0.020
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.4527 0.88961 0.024 0.456 0.004 0.000 0.516 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3789 0.10068 0.000 0.584 0.000 0.000 0.000 0.416
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.2782 0.80689 0.888 0.012 0.020 0.004 0.056 0.020
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1321 0.81277 0.952 0.000 0.004 0.000 0.024 0.020
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.4179 -0.10056 0.000 0.516 0.000 0.000 0.012 0.472
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.2302 0.82243 0.036 0.000 0.912 0.012 0.024 0.016
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2808 0.83216 0.000 0.012 0.860 0.004 0.112 0.012
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.4620 -0.46187 0.024 0.620 0.004 0.000 0.340 0.012
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0405 0.81216 0.988 0.000 0.000 0.000 0.004 0.008
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0972 0.81229 0.964 0.000 0.000 0.000 0.028 0.008
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 6 0.7608 -0.13560 0.292 0.020 0.016 0.044 0.272 0.356
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.2087 0.81456 0.924 0.012 0.036 0.012 0.004 0.012
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 6 0.4264 0.12682 0.000 0.488 0.000 0.000 0.016 0.496
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.0603 0.72739 0.000 0.000 0.004 0.980 0.000 0.016
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.5268 0.37228 0.616 0.280 0.000 0.004 0.088 0.012
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.1053 0.57506 0.000 0.964 0.000 0.012 0.020 0.004
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.4791 0.85765 0.000 0.436 0.052 0.000 0.512 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0713 0.59179 0.000 0.972 0.000 0.000 0.000 0.028
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.4935 0.24913 0.000 0.592 0.028 0.012 0.012 0.356
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3954 0.24107 0.000 0.636 0.000 0.012 0.000 0.352
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.3371 0.81436 0.000 0.004 0.848 0.040 0.064 0.044
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4086 0.67932 0.776 0.140 0.000 0.008 0.068 0.008
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1599 0.80559 0.940 0.028 0.000 0.000 0.024 0.008
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.5408 0.79548 0.000 0.412 0.100 0.000 0.484 0.004
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.5962 0.61283 0.668 0.120 0.068 0.004 0.116 0.024
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0260 0.81193 0.992 0.000 0.000 0.000 0.000 0.008
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0891 0.58595 0.000 0.968 0.000 0.008 0.000 0.024
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.3233 0.82269 0.000 0.004 0.848 0.020 0.092 0.036
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.1434 0.59077 0.000 0.948 0.000 0.012 0.012 0.028
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.5729 0.03384 0.000 0.016 0.116 0.512 0.000 0.356
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0622 0.81406 0.980 0.000 0.000 0.000 0.012 0.008
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 6 0.4810 0.51586 0.000 0.292 0.008 0.064 0.000 0.636
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4218 0.77449 0.796 0.000 0.076 0.016 0.080 0.032
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.4536 0.87251 0.024 0.476 0.004 0.000 0.496 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.3500 0.76570 0.124 0.000 0.824 0.012 0.016 0.024
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.5795 0.37892 0.000 0.068 0.044 0.408 0.000 0.480
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.3998 0.26000 0.000 0.000 0.004 0.492 0.000 0.504
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#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 4 0.2199 0.68791 0.000 0.000 0.020 0.892 0.000 0.088
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 4 0.3263 0.60706 0.000 0.004 0.020 0.800 0.000 0.176
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 6 0.4631 0.34626 0.000 0.004 0.032 0.428 0.000 0.536
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 3 0.2905 0.80322 0.072 0.000 0.872 0.028 0.004 0.024
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 5 0.4851 0.86441 0.024 0.472 0.004 0.000 0.488 0.012
#> 976924B0-5799-4AC9-804F-78C8568037CA 5 0.5067 0.84068 0.000 0.452 0.048 0.000 0.488 0.012
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 5 0.4529 0.87584 0.000 0.460 0.032 0.000 0.508 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0363 0.81189 0.988 0.000 0.000 0.000 0.000 0.012
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.3776 0.79012 0.824 0.000 0.068 0.008 0.064 0.036
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 5 0.4463 0.87791 0.000 0.456 0.028 0.000 0.516 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.4348 0.74265 0.128 0.000 0.752 0.000 0.104 0.016
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.1729 0.55291 0.000 0.936 0.004 0.012 0.036 0.012
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0653 0.58344 0.000 0.980 0.000 0.012 0.004 0.004
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.1476 0.56139 0.004 0.948 0.000 0.008 0.028 0.012
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.1766 0.81227 0.940 0.012 0.004 0.016 0.008 0.020
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.2234 0.82377 0.000 0.000 0.872 0.000 0.124 0.004
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.3322 0.80500 0.860 0.012 0.008 0.036 0.064 0.020
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.2800 0.80635 0.884 0.012 0.036 0.052 0.000 0.016
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 6 0.6973 0.22149 0.000 0.016 0.368 0.172 0.048 0.396
#> 93429F04-8404-4E8C-B654-9D2216BA432C 1 0.8073 0.31865 0.416 0.128 0.016 0.032 0.168 0.240
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0984 0.81443 0.968 0.012 0.000 0.000 0.012 0.008
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.3522 0.79836 0.848 0.000 0.048 0.032 0.048 0.024
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 5 0.4845 0.88187 0.024 0.456 0.004 0.000 0.504 0.012
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 4 0.1074 0.73160 0.000 0.012 0.028 0.960 0.000 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.1691 0.72753 0.028 0.012 0.012 0.940 0.000 0.008
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.7494 0.26448 0.012 0.248 0.472 0.096 0.020 0.152
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.4284 0.49811 0.008 0.028 0.008 0.708 0.000 0.248
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.5174 0.75544 0.088 0.056 0.712 0.008 0.136 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.4397 0.39426 0.000 0.008 0.528 0.000 0.452 0.012
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.5783 0.35500 0.560 0.116 0.020 0.000 0.300 0.004
#> 6D711561-D549-44C7-885F-F3B846DB130C 6 0.4656 0.31750 0.004 0.012 0.008 0.448 0.004 0.524
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.1993 0.80868 0.928 0.012 0.000 0.020 0.020 0.020
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.1297 0.59425 0.000 0.948 0.000 0.012 0.000 0.040
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0547 0.59047 0.000 0.980 0.000 0.000 0.000 0.020
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 6 0.4177 0.20551 0.000 0.468 0.000 0.000 0.012 0.520
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.5705 0.67797 0.672 0.012 0.032 0.184 0.080 0.020
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.6536 0.34563 0.488 0.012 0.036 0.364 0.080 0.020
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.6243 0.40269 0.000 0.212 0.320 0.000 0.452 0.016
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.0692 0.72603 0.000 0.000 0.004 0.976 0.000 0.020
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.1003 0.81100 0.964 0.000 0.000 0.000 0.020 0.016
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 5 0.7131 0.53753 0.140 0.372 0.072 0.000 0.396 0.020
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.4456 0.87731 0.000 0.448 0.028 0.000 0.524 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.4477 0.44711 0.004 0.676 0.008 0.016 0.012 0.284
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.5883 0.68542 0.672 0.012 0.048 0.164 0.080 0.024
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0984 0.81281 0.968 0.012 0.000 0.000 0.012 0.008
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.5837 0.65975 0.660 0.012 0.032 0.192 0.080 0.024
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.3644 0.75756 0.144 0.000 0.804 0.004 0.016 0.032
#> B58BFFE5-4390-4791-8385-A04A35CA1149 6 0.7942 -0.04125 0.256 0.148 0.012 0.004 0.268 0.312
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 6 0.4344 0.36955 0.000 0.016 0.004 0.424 0.000 0.556
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.4196 0.72552 0.776 0.000 0.076 0.004 0.124 0.020
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 2 0.5903 -0.53743 0.220 0.452 0.000 0.000 0.328 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.6131 0.09848 0.020 0.644 0.116 0.012 0.164 0.044
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.1555 0.58492 0.000 0.940 0.008 0.000 0.012 0.040
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.4957 0.69201 0.000 0.104 0.700 0.004 0.172 0.020
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 4 0.3372 0.68053 0.080 0.012 0.036 0.848 0.000 0.024
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.5827 0.16740 0.000 0.644 0.112 0.012 0.180 0.052
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0632 0.59132 0.000 0.976 0.000 0.000 0.000 0.024
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.5269 0.33598 0.328 0.012 0.020 0.604 0.012 0.024
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.4437 0.48735 0.000 0.780 0.092 0.012 0.048 0.068
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 2 0.4929 -0.57362 0.004 0.564 0.016 0.008 0.392 0.016
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.3191 0.29221 0.012 0.812 0.000 0.000 0.164 0.012
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.4564 0.58130 0.000 0.016 0.136 0.740 0.004 0.104
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2377 0.83250 0.000 0.008 0.892 0.000 0.076 0.024
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0405 0.58528 0.000 0.988 0.000 0.008 0.000 0.004
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.5302 0.72730 0.724 0.012 0.036 0.128 0.080 0.020
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 4 0.8105 -0.18889 0.016 0.176 0.200 0.328 0.008 0.272
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.4107 -0.12530 0.024 0.708 0.000 0.000 0.256 0.012
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.4744 0.47109 0.000 0.028 0.052 0.688 0.000 0.232
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0146 0.81180 0.996 0.000 0.000 0.000 0.000 0.004
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.3101 0.45719 0.012 0.856 0.020 0.000 0.096 0.016
#> A2007795-C728-4688-B199-AE89500011D2 6 0.4497 0.24558 0.000 0.440 0.016 0.004 0.004 0.536
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.2237 0.72055 0.028 0.012 0.016 0.920 0.008 0.016
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.6317 0.34549 0.028 0.640 0.056 0.012 0.152 0.112
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.3472 0.81019 0.000 0.008 0.844 0.032 0.060 0.056
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5563 0.72003 0.160 0.036 0.700 0.036 0.056 0.012
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 2 0.4639 -0.61416 0.012 0.572 0.008 0.000 0.396 0.012
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.0993 0.72656 0.000 0.000 0.012 0.964 0.000 0.024
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.4338 0.37250 0.000 0.004 0.016 0.420 0.000 0.560
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.1668 0.83441 0.004 0.000 0.928 0.000 0.060 0.008
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.2888 0.56492 0.000 0.852 0.000 0.000 0.056 0.092
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.3333 0.81671 0.000 0.004 0.848 0.028 0.072 0.048
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.3269 0.79851 0.860 0.004 0.028 0.016 0.072 0.020
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.3515 0.34890 0.000 0.676 0.000 0.000 0.000 0.324
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.4312 0.86910 0.012 0.476 0.004 0.000 0.508 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0993 0.59288 0.000 0.964 0.000 0.012 0.000 0.024
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.1785 0.53682 0.000 0.928 0.016 0.000 0.048 0.008
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1850 0.80870 0.924 0.000 0.008 0.000 0.052 0.016
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1476 0.81333 0.948 0.028 0.004 0.012 0.000 0.008
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.6815 0.50714 0.000 0.140 0.120 0.180 0.012 0.548
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.1138 0.73170 0.000 0.012 0.024 0.960 0.000 0.004
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.4382 0.48676 0.000 0.020 0.012 0.332 0.000 0.636
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0622 0.81361 0.980 0.000 0.008 0.000 0.000 0.012
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.4171 0.44046 0.000 0.012 0.004 0.380 0.000 0.604
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.5202 0.56203 0.000 0.156 0.008 0.140 0.016 0.680
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 4 0.3608 0.56088 0.000 0.012 0.248 0.736 0.000 0.004
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4113 0.79156 0.824 0.048 0.048 0.028 0.016 0.036
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.5559 0.76927 0.092 0.380 0.016 0.000 0.512 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.6000 0.39418 0.164 0.024 0.008 0.600 0.004 0.200
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.7527 0.51454 0.492 0.024 0.020 0.088 0.144 0.232
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.5286 0.75219 0.744 0.024 0.032 0.096 0.036 0.068
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4380 0.38145 0.000 0.652 0.024 0.012 0.000 0.312
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0725 0.58769 0.000 0.976 0.000 0.012 0.000 0.012
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.5199 -0.23332 0.000 0.016 0.052 0.468 0.000 0.464
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.5135 0.56178 0.000 0.148 0.016 0.140 0.008 0.688
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.3332 0.76577 0.044 0.000 0.832 0.108 0.000 0.016
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.3371 0.81436 0.000 0.004 0.848 0.040 0.064 0.044
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.2162 0.72225 0.020 0.012 0.020 0.924 0.008 0.016
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.5169 0.60773 0.088 0.012 0.112 0.736 0.020 0.032
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.4570 0.86870 0.000 0.436 0.036 0.000 0.528 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.7762 0.06904 0.236 0.400 0.024 0.000 0.132 0.208
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1434 0.59404 0.000 0.940 0.000 0.012 0.000 0.048
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.1313 0.81421 0.952 0.000 0.016 0.000 0.028 0.004
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.4631 -0.77194 0.012 0.516 0.008 0.000 0.456 0.008
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.4850 0.87495 0.024 0.468 0.004 0.000 0.492 0.012
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.1894 0.72637 0.016 0.012 0.040 0.928 0.004 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1151 0.81538 0.956 0.000 0.032 0.000 0.000 0.012
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.4924 0.35380 0.000 0.020 0.028 0.440 0.000 0.512
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5322 0.69267 0.688 0.000 0.168 0.016 0.100 0.028
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.81181 1.000 0.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.1007 0.73153 0.000 0.004 0.016 0.968 0.004 0.008
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.4887 0.54647 0.000 0.068 0.012 0.232 0.008 0.680
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.5808 0.51510 0.612 0.264 0.060 0.000 0.028 0.036
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.4157 0.26013 0.000 0.444 0.000 0.000 0.012 0.544
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0146 0.81180 0.996 0.000 0.000 0.000 0.000 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.3440 0.81531 0.000 0.012 0.848 0.032 0.064 0.044
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.3013 0.65320 0.000 0.012 0.152 0.828 0.004 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1893 0.81243 0.932 0.012 0.004 0.032 0.004 0.016
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4260 -0.08781 0.000 0.512 0.000 0.000 0.016 0.472
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.0862 0.73253 0.000 0.008 0.016 0.972 0.000 0.004
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.6511 0.70143 0.028 0.380 0.136 0.000 0.440 0.016
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 6 0.6433 0.25835 0.100 0.060 0.008 0.008 0.264 0.560
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2630 0.80158 0.888 0.000 0.020 0.004 0.064 0.024
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.2402 0.82871 0.000 0.000 0.868 0.000 0.120 0.012
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.6103 0.28953 0.112 0.012 0.008 0.372 0.008 0.488
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3706 0.69954 0.796 0.096 0.000 0.000 0.104 0.004
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.1053 0.73322 0.000 0.012 0.020 0.964 0.004 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4925 0.68428 0.716 0.000 0.164 0.008 0.084 0.028
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5735 0.70815 0.692 0.012 0.044 0.148 0.072 0.032
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2862 0.81833 0.000 0.016 0.884 0.028 0.028 0.044
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.2684 0.83679 0.024 0.008 0.896 0.020 0.044 0.008
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2572 0.56794 0.000 0.852 0.000 0.012 0.000 0.136
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.4686 -0.00471 0.004 0.692 0.028 0.008 0.248 0.020
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.2076 0.81526 0.012 0.000 0.912 0.060 0.000 0.016
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.802 0.887 0.953 0.5005 0.500 0.500
#> 3 3 0.622 0.764 0.882 0.3065 0.683 0.452
#> 4 4 0.546 0.627 0.787 0.1334 0.805 0.510
#> 5 5 0.761 0.750 0.871 0.0734 0.841 0.490
#> 6 6 0.712 0.668 0.820 0.0380 0.907 0.607
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.93664 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.96314 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.93664 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.96314 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.93664 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.93664 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.96314 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.96314 1.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.96314 1.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.96314 1.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.93664 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.7453 0.72430 0.212 0.788
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.8016 0.67218 0.756 0.244
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.93664 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0672 0.93117 0.008 0.992
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 2 0.7376 0.73916 0.208 0.792
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.93664 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 2 0.7219 0.74914 0.200 0.800
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.93664 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4298 0.88413 0.912 0.088
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.93664 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.93664 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.96314 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.96314 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.9922 0.24473 0.448 0.552
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.93664 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.96314 1.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.96314 1.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.96314 1.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.93664 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.96314 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.93664 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.96314 1.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.96314 1.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.93664 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.96314 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.7219 0.74914 0.200 0.800
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.96314 1.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.96314 1.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.96314 1.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.93664 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.96314 1.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.93664 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.93664 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.96314 1.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.93664 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.96314 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.93664 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.93664 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.93664 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 2 0.0000 0.93664 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.96314 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.96314 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.96314 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.96314 1.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.96314 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.93664 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 2 0.9710 0.38000 0.400 0.600
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.9909 0.25870 0.444 0.556
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.0000 0.93664 0.000 1.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.96314 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.93664 0.000 1.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.96314 1.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.96314 1.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.96314 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.93664 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.93664 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.93664 0.000 1.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.96314 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.96314 1.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.3584 0.90042 0.932 0.068
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.96314 1.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.0000 0.93664 0.000 1.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.9393 0.43132 0.644 0.356
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.0000 0.93664 0.000 1.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.93664 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.93664 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.1184 0.92572 0.016 0.984
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.96314 1.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.96314 1.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.96314 1.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 2 0.8386 0.65210 0.268 0.732
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.5408 0.83653 0.876 0.124
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.96314 1.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0376 0.96001 0.996 0.004
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.96314 1.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.93664 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.6048 0.80528 0.852 0.148
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.93664 0.000 1.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.96314 1.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.9000 0.54898 0.316 0.684
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.93664 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.93664 0.000 1.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 2 0.7219 0.74914 0.200 0.800
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.93664 0.000 1.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.96314 1.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.96314 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.96314 1.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.1414 0.94686 0.980 0.020
#> 60A51C36-7423-4C84-8034-325DE57046BE 2 0.9608 0.39698 0.384 0.616
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0000 0.96314 1.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.96314 1.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.93664 0.000 1.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 1 0.0000 0.96314 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.0000 0.93664 0.000 1.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 1 0.0000 0.96314 1.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.0000 0.93664 0.000 1.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 2 0.0000 0.93664 0.000 1.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 2 0.9580 0.41768 0.380 0.620
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.5294 0.84161 0.880 0.120
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.0000 0.93664 0.000 1.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.0000 0.93664 0.000 1.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.96314 1.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.93664 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0000 0.96314 1.000 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 1 0.0000 0.96314 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0000 0.93664 0.000 1.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.0000 0.96314 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.93664 0.000 1.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0000 0.93664 0.000 1.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 1 0.0000 0.96314 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.96314 1.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.9608 0.39764 0.384 0.616
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0000 0.96314 1.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.96314 1.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.93664 0.000 1.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.1843 0.93979 0.972 0.028
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.0376 0.96002 0.996 0.004
#> DAD951A3-C22E-42F0-BB02-854413DDC351 2 0.0000 0.93664 0.000 1.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.0000 0.93664 0.000 1.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 1 0.0000 0.96314 1.000 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 1 0.0000 0.96314 1.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0000 0.93664 0.000 1.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.0000 0.93664 0.000 1.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0000 0.93664 0.000 1.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0000 0.93664 0.000 1.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.0000 0.93664 0.000 1.000
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.0000 0.96314 1.000 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.0000 0.93664 0.000 1.000
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 2 0.1633 0.91999 0.024 0.976
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0000 0.93664 0.000 1.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0000 0.96314 1.000 0.000
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#> 92C9DF6D-4C78-4193-8DF4-0ACC49C63AF2 1 0.0000 0.96314 1.000 0.000
#> 12178D82-CADF-49AD-BC2F-3956CB321EE9 1 0.2603 0.92588 0.956 0.044
#> 0EAC1C1B-4B84-479B-A8E9-DC7ED4D3E0F3 1 0.0000 0.96314 1.000 0.000
#> 362DEA8E-F338-42D8-AA20-21F3B5AF72C3 2 0.0000 0.93664 0.000 1.000
#> 9CC24423-CCFA-475B-84CC-5A884048222C 2 0.0000 0.93664 0.000 1.000
#> E2625C62-2ABA-4670-A186-A7C03D69DD58 1 0.0000 0.96314 1.000 0.000
#> FCA5BADD-A6B2-4602-9B8F-0CD760E0AC2A 2 0.0000 0.93664 0.000 1.000
#> 36A4A073-CB26-4A65-8E47-A61F29929BDC 1 0.1633 0.94338 0.976 0.024
#> BB6D222E-585A-4C3E-ADD2-1B2BD5281F50 2 0.0000 0.93664 0.000 1.000
#> 55CFCA9F-0704-4948-BFB3-9027DE73E4BC 1 0.0000 0.96314 1.000 0.000
#> 3A052FCB-69B1-4699-BE22-19A835E6D102 2 0.0000 0.93664 0.000 1.000
#> 90AAB588-049D-4C56-B024-97831990F7CB 2 0.0000 0.93664 0.000 1.000
#> 75858032-A88A-4851-BCE5-66831D649D57 2 0.2603 0.90410 0.044 0.956
#> EA5B09C5-A45D-44BC-8477-DAF6B0DD79C7 2 0.0000 0.93664 0.000 1.000
#> 8026EF80-8CFB-4A62-9C72-BB5B50BDECFE 1 0.0000 0.96314 1.000 0.000
#> C1D05156-9AA7-48FD-9C3C-8894F9025D29 2 0.0000 0.93664 0.000 1.000
#> D3AEFD54-52E3-4761-898B-F05A5B6BA198 2 0.7376 0.73948 0.208 0.792
#> 33FAC29F-D146-454C-AE5D-07DF7C191DFC 2 0.9635 0.41182 0.388 0.612
#> E3E13B94-9335-4B34-9975-ECA99EB1BCBE 1 0.0000 0.96314 1.000 0.000
#> 2E1AC099-CE43-4605-BDFD-FA71DE8EAE44 2 0.0000 0.93664 0.000 1.000
#> 1D7B591B-8382-47C9-8555-64B7E96965BC 2 0.0000 0.93664 0.000 1.000
#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.0000 0.93664 0.000 1.000
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.0000 0.93664 0.000 1.000
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.0000 0.93664 0.000 1.000
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.0000 0.96314 1.000 0.000
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.0000 0.93664 0.000 1.000
#> 4C838D35-B667-46DA-836F-068453D254DA 2 0.8267 0.65236 0.260 0.740
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0000 0.93664 0.000 1.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0000 0.93664 0.000 1.000
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.0000 0.93664 0.000 1.000
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.0000 0.96314 1.000 0.000
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 1 0.0000 0.96314 1.000 0.000
#> 976924B0-5799-4AC9-804F-78C8568037CA 1 0.0000 0.96314 1.000 0.000
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.0000 0.96314 1.000 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0000 0.96314 1.000 0.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.0000 0.96314 1.000 0.000
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0000 0.96314 1.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0000 0.96314 1.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0000 0.93664 0.000 1.000
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0000 0.93664 0.000 1.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 1 1.0000 -0.00732 0.504 0.496
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.6801 0.76082 0.820 0.180
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0000 0.96314 1.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.2043 0.93728 0.968 0.032
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.0000 0.96314 1.000 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.0000 0.93664 0.000 1.000
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.0000 0.93664 0.000 1.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.96314 1.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.96314 1.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.96314 1.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.0000 0.93664 0.000 1.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0000 0.93664 0.000 1.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.0000 0.93664 0.000 1.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.93664 0.000 1.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0000 0.96314 1.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.96314 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0000 0.96314 1.000 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0000 0.93664 0.000 1.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.7139 0.73734 0.804 0.196
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.93664 0.000 1.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.93664 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.93664 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.0672 0.93120 0.008 0.992
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.0000 0.93664 0.000 1.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.96314 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.93664 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0000 0.96314 1.000 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.0000 0.96314 1.000 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.96314 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.93664 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.96314 1.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.96314 1.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0000 0.96314 1.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.96314 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.93664 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0000 0.93664 0.000 1.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.96314 1.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.96314 1.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.9998 -0.03695 0.508 0.492
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.93664 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.9988 0.13645 0.480 0.520
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.6148 0.80049 0.848 0.152
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.9922 0.11919 0.552 0.448
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.93664 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.93664 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.93664 0.000 1.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.0000 0.96314 1.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.2948 0.91693 0.948 0.052
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.7453 0.73408 0.212 0.788
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.96314 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.7950 0.68623 0.240 0.760
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.4562 0.85871 0.096 0.904
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0000 0.93664 0.000 1.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0000 0.96314 1.000 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.93664 0.000 1.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0000 0.96314 1.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.0000 0.96314 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.93664 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.93664 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.0376 0.96001 0.996 0.004
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 2 0.7219 0.74914 0.200 0.800
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.2603 0.92484 0.956 0.044
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.0000 0.96314 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.93664 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.93664 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.96314 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.93664 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 2 0.9710 0.38000 0.400 0.600
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.96314 1.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.93664 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.96314 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.93664 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.93664 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.96314 1.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.96314 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.93664 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.93664 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.93664 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.96314 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.93664 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.93664 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.9608 0.33889 0.616 0.384
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.96314 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.96314 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.9988 0.01112 0.520 0.480
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.93664 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0376 0.93391 0.004 0.996
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.93664 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.93664 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.93664 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.93664 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.96314 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 2 0.2423 0.90803 0.040 0.960
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.2778 0.90152 0.048 0.952
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.3879 0.87805 0.076 0.924
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.96314 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.9993 0.08634 0.484 0.516
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.93664 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.96314 1.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0938 0.95352 0.988 0.012
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.96314 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.8813 0.59722 0.300 0.700
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.96314 1.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.93664 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.96314 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.96314 1.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.93664 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.93664 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.96314 1.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.93664 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.96314 1.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 2 0.7219 0.74914 0.200 0.800
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.96314 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.96314 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.93664 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.93664 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.96314 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.93664 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.96314 1.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.96314 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.93664 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.96314 1.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.93664 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.96314 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.96314 1.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 2 0.7299 0.74425 0.204 0.796
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.96314 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1633 0.92016 0.024 0.976
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0000 0.96314 1.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.96314 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.93654 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4346 0.74605 0.184 0.000 0.816
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.4750 0.70843 0.216 0.784 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.5905 0.60167 0.648 0.000 0.352
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0892 0.92745 0.020 0.980 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.93654 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0237 0.83364 0.996 0.000 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4750 0.73147 0.784 0.000 0.216
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0592 0.83238 0.988 0.000 0.012
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.5016 0.71586 0.760 0.000 0.240
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0424 0.93370 0.008 0.992 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0237 0.83254 0.996 0.004 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.83349 1.000 0.000 0.000
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#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.0000 0.79381 0.000 0.000 1.000
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 3 0.0000 0.79381 0.000 0.000 1.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0237 0.83364 0.996 0.000 0.004
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.1163 0.82743 0.972 0.000 0.028
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 3 0.0000 0.79381 0.000 0.000 1.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.1289 0.79325 0.032 0.000 0.968
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.7653 0.58390 0.140 0.684 0.176
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.5926 0.38125 0.356 0.644 0.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 1 0.8550 0.59626 0.608 0.176 0.216
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.0475 0.83351 0.992 0.004 0.004
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.0000 0.79381 0.000 0.000 1.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0000 0.83349 1.000 0.000 0.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.0000 0.83349 1.000 0.000 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.0424 0.93203 0.000 0.992 0.008
#> 93429F04-8404-4E8C-B654-9D2216BA432C 1 0.6280 0.23427 0.540 0.460 0.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0000 0.83349 1.000 0.000 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.0000 0.83349 1.000 0.000 0.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 3 0.2356 0.75370 0.072 0.000 0.928
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.5253 0.71145 0.020 0.792 0.188
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0892 0.92745 0.020 0.980 0.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.0000 0.93654 0.000 1.000 0.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.93654 0.000 1.000 0.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.4291 0.74812 0.180 0.000 0.820
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.0424 0.79180 0.008 0.000 0.992
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.4605 0.73799 0.796 0.000 0.204
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0237 0.93525 0.004 0.996 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0424 0.83322 0.992 0.000 0.008
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.93654 0.000 1.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0424 0.93276 0.008 0.992 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.93654 0.000 1.000 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.0592 0.82939 0.988 0.012 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.5926 0.48545 0.356 0.644 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0424 0.79180 0.008 0.000 0.992
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0424 0.93370 0.008 0.992 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0424 0.83322 0.992 0.000 0.008
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0000 0.79381 0.000 0.000 1.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0000 0.79381 0.000 0.000 1.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0424 0.93276 0.008 0.992 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0000 0.83349 1.000 0.000 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0592 0.83238 0.988 0.000 0.012
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0000 0.83349 1.000 0.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.4654 0.73138 0.208 0.000 0.792
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.5397 0.62676 0.720 0.280 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0000 0.93654 0.000 1.000 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.5650 0.64956 0.688 0.000 0.312
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.2066 0.81435 0.940 0.000 0.060
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.6252 0.30158 0.000 0.444 0.556
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 1 0.6168 0.38782 0.588 0.412 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.0747 0.79338 0.000 0.016 0.984
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.6673 0.71912 0.200 0.068 0.732
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0424 0.79380 0.000 0.008 0.992
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.93654 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.1031 0.92456 0.024 0.976 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0000 0.93654 0.000 1.000 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.79381 0.000 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.4974 0.71673 0.764 0.000 0.236
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.5754 0.61641 0.004 0.296 0.700
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2537 0.78645 0.000 0.080 0.920
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 1 0.6379 0.48696 0.624 0.368 0.008
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0237 0.83254 0.996 0.004 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.0000 0.93654 0.000 1.000 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.4654 0.73545 0.792 0.000 0.208
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.93654 0.000 1.000 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0237 0.83364 0.996 0.000 0.004
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6168 0.50891 0.588 0.000 0.412
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.93654 0.000 1.000 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.1411 0.91604 0.036 0.964 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.3325 0.76821 0.020 0.076 0.904
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.5397 0.64214 0.000 0.280 0.720
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5793 0.76627 0.116 0.084 0.800
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.79381 0.000 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0424 0.93370 0.008 0.992 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.93654 0.000 1.000 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.3752 0.76474 0.144 0.000 0.856
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.5905 0.40049 0.352 0.648 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4796 0.71169 0.000 0.220 0.780
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.83349 1.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.93654 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.3482 0.69807 0.128 0.000 0.872
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.93654 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.7603 0.67190 0.688 0.140 0.172
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0237 0.83364 0.996 0.000 0.004
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0424 0.83320 0.992 0.000 0.008
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.93654 0.000 1.000 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.1289 0.91814 0.032 0.968 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.93654 0.000 1.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0592 0.83238 0.988 0.000 0.012
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.93654 0.000 1.000 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.93654 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.6470 0.74832 0.148 0.092 0.760
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.6126 0.50633 0.400 0.000 0.600
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.5529 0.66615 0.704 0.000 0.296
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.8745 0.44535 0.120 0.356 0.524
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.4605 0.74393 0.204 0.796 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.1753 0.81431 0.952 0.048 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.93654 0.000 1.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.93654 0.000 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.93654 0.000 1.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.93654 0.000 1.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4555 0.73788 0.200 0.000 0.800
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.6168 0.39856 0.000 0.412 0.588
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.5171 0.69615 0.204 0.784 0.012
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.1267 0.92381 0.024 0.972 0.004
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.79381 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.5346 0.75327 0.808 0.040 0.152
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.93654 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.83349 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0424 0.79346 0.000 0.008 0.992
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.5948 0.59001 0.640 0.000 0.360
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.7546 0.15256 0.044 0.560 0.396
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0747 0.83114 0.984 0.000 0.016
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.93654 0.000 1.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.5327 0.67305 0.272 0.000 0.728
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0424 0.83322 0.992 0.000 0.008
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0424 0.93370 0.008 0.992 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.93654 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.7138 0.70064 0.720 0.120 0.160
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.93654 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0592 0.83238 0.988 0.000 0.012
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.5560 0.61429 0.000 0.300 0.700
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4605 0.73693 0.204 0.000 0.796
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0237 0.83364 0.996 0.000 0.004
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.93654 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.1031 0.92347 0.024 0.976 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.79381 0.000 0.000 1.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0424 0.93324 0.008 0.992 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1031 0.82805 0.976 0.000 0.024
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.79381 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0592 0.93216 0.012 0.988 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1289 0.82695 0.968 0.000 0.032
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.1860 0.89972 0.052 0.948 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.3038 0.77870 0.104 0.000 0.896
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5497 0.42139 0.708 0.000 0.292
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.5859 0.54076 0.000 0.344 0.656
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4994 0.75881 0.160 0.024 0.816
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0424 0.93220 0.000 0.992 0.008
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.79381 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4861 0.74924 0.180 0.012 0.808
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2011 0.77593 0.000 0.920 0.000 0.080
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4669 0.67687 0.200 0.000 0.764 0.036
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.7053 0.45211 0.356 0.512 0.132 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 4 0.1902 0.70228 0.064 0.000 0.004 0.932
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.6854 0.59324 0.172 0.596 0.232 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.3123 0.71312 0.000 0.844 0.000 0.156
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2345 0.79332 0.900 0.000 0.000 0.100
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 4 0.4543 0.34406 0.324 0.000 0.000 0.676
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3718 0.76537 0.820 0.000 0.012 0.168
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 4 0.4319 0.54838 0.228 0.012 0.000 0.760
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.6259 0.63680 0.116 0.652 0.232 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3668 0.69085 0.808 0.004 0.188 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.1151 0.78022 0.968 0.000 0.024 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.1557 0.78781 0.000 0.944 0.000 0.056
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.7099 0.38090 0.552 0.168 0.280 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4123 0.64575 0.000 0.220 0.772 0.008
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1509 0.79804 0.020 0.960 0.008 0.012
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.3764 0.66944 0.000 0.172 0.816 0.012
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.1297 0.79680 0.020 0.964 0.016 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 4 0.4072 0.59086 0.000 0.252 0.000 0.748
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.4164 0.58014 0.000 0.264 0.000 0.736
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7798 0.62014 0.120 0.620 0.136 0.124
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3610 0.64807 0.000 0.000 0.800 0.200
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4540 0.67955 0.196 0.000 0.772 0.032
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.6633 0.58174 0.120 0.680 0.172 0.028
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.5956 0.65989 0.100 0.680 0.220 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 4 0.1059 0.72076 0.016 0.012 0.000 0.972
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 4 0.1661 0.70509 0.004 0.000 0.052 0.944
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4364 0.75134 0.816 0.000 0.092 0.092
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.4756 0.71963 0.176 0.772 0.052 0.000
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#> 4C838D35-B667-46DA-836F-068453D254DA 1 0.4089 0.67068 0.780 0.004 0.212 0.004
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.3707 0.75445 0.028 0.840 0.132 0.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.5458 0.68954 0.076 0.720 0.204 0.000
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.4741 0.69911 0.028 0.744 0.228 0.000
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 3 0.4446 0.68019 0.196 0.000 0.776 0.028
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 4 0.1302 0.70981 0.000 0.000 0.044 0.956
#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.4406 0.56080 0.000 0.000 0.700 0.300
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 4 0.4855 0.18305 0.000 0.000 0.400 0.600
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.3123 0.77485 0.844 0.000 0.000 0.156
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 1 0.4106 0.76140 0.832 0.000 0.084 0.084
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 4 0.4193 0.47857 0.000 0.000 0.268 0.732
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.3942 0.62669 0.000 0.000 0.764 0.236
#> F3285881-878E-4190-BB96-9A2303C76346 4 0.3266 0.65769 0.000 0.168 0.000 0.832
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 4 0.4817 0.38828 0.000 0.388 0.000 0.612
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 4 0.1302 0.71830 0.000 0.044 0.000 0.956
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 1 0.4088 0.76207 0.808 0.008 0.012 0.172
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.4072 0.61321 0.000 0.000 0.748 0.252
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0672 0.78240 0.984 0.000 0.008 0.008
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.4669 0.69948 0.772 0.008 0.196 0.024
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.1576 0.78835 0.000 0.948 0.048 0.004
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.8832 0.47092 0.264 0.452 0.216 0.068
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.1489 0.79079 0.952 0.000 0.004 0.044
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.3638 0.75784 0.848 0.000 0.120 0.032
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 4 0.2589 0.66570 0.000 0.000 0.116 0.884
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.5759 0.35882 0.080 0.232 0.688 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.7558 0.44026 0.296 0.480 0.224 0.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.1837 0.79494 0.000 0.944 0.028 0.028
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.4776 0.72366 0.164 0.776 0.060 0.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.5022 0.68185 0.188 0.016 0.764 0.032
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.4888 0.38120 0.000 0.000 0.588 0.412
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 4 0.4356 0.41010 0.292 0.000 0.000 0.708
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.1489 0.79008 0.004 0.952 0.044 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.2868 0.78375 0.864 0.000 0.000 0.136
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.1637 0.78631 0.000 0.940 0.000 0.060
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.3356 0.69773 0.000 0.824 0.000 0.176
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.1474 0.78907 0.000 0.948 0.000 0.052
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.3852 0.68464 0.800 0.008 0.192 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.4655 0.65258 0.760 0.032 0.208 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.4981 0.25341 0.000 0.000 0.536 0.464
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.6790 0.59804 0.168 0.604 0.228 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.3444 0.75631 0.816 0.000 0.000 0.184
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 4 0.4941 0.07413 0.000 0.000 0.436 0.564
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 4 0.4382 0.42962 0.000 0.000 0.296 0.704
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.1902 0.78624 0.000 0.932 0.004 0.064
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.3172 0.71695 0.840 0.000 0.160 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.3933 0.74190 0.792 0.000 0.008 0.200
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.2921 0.72914 0.860 0.000 0.140 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.4690 0.61025 0.276 0.000 0.712 0.012
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.9816 0.32701 0.240 0.348 0.204 0.208
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.0921 0.79214 0.000 0.972 0.028 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 4 0.5155 -0.16889 0.468 0.000 0.004 0.528
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 4 0.4936 0.25281 0.372 0.000 0.004 0.624
#> BDDB8226-723E-426F-973F-59D14E9EEB06 4 0.7020 0.30355 0.000 0.136 0.332 0.532
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.5226 0.51247 0.008 0.276 0.020 0.696
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.5604 0.65667 0.000 0.116 0.724 0.160
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.4355 0.67144 0.212 0.012 0.772 0.004
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 4 0.6253 0.18764 0.000 0.064 0.372 0.564
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.3610 0.66204 0.000 0.800 0.000 0.200
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.7142 0.47674 0.324 0.524 0.152 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.1970 0.78996 0.000 0.932 0.008 0.060
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 4 0.4948 0.06001 0.000 0.000 0.440 0.560
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.1452 0.71827 0.008 0.036 0.000 0.956
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.2578 0.66285 0.000 0.052 0.912 0.036
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.5079 0.67280 0.004 0.156 0.768 0.072
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.4543 0.48726 0.000 0.324 0.000 0.676
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.3710 0.68827 0.804 0.004 0.192 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.1624 0.79568 0.000 0.952 0.028 0.020
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 4 0.1888 0.71610 0.044 0.016 0.000 0.940
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.5716 0.61406 0.068 0.680 0.252 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.3208 0.77867 0.848 0.000 0.004 0.148
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 4 0.0592 0.71905 0.000 0.000 0.016 0.984
#> A2007795-C728-4688-B199-AE89500011D2 2 0.1398 0.79275 0.000 0.956 0.004 0.040
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.7385 0.41344 0.340 0.484 0.176 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 4 0.4720 0.47190 0.000 0.016 0.264 0.720
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.4019 0.65851 0.000 0.196 0.792 0.012
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.5252 0.69482 0.128 0.080 0.776 0.016
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 4 0.3400 0.60321 0.000 0.000 0.180 0.820
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.6353 0.63936 0.140 0.652 0.208 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.3108 0.76932 0.016 0.872 0.112 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.4938 0.68531 0.148 0.000 0.772 0.080
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4673 0.64190 0.008 0.748 0.012 0.232
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.4284 0.65738 0.000 0.200 0.780 0.020
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1297 0.78405 0.964 0.000 0.020 0.016
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.1557 0.78781 0.000 0.944 0.000 0.056
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 4 0.1389 0.70780 0.000 0.000 0.048 0.952
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.3486 0.67629 0.000 0.812 0.000 0.188
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.2207 0.71325 0.004 0.056 0.012 0.928
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.2924 0.79318 0.884 0.000 0.016 0.100
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.3529 0.77594 0.836 0.000 0.012 0.152
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5123 0.68794 0.044 0.724 0.232 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.7310 0.52849 0.212 0.532 0.256 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1174 0.79427 0.012 0.968 0.020 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3577 0.77288 0.832 0.000 0.012 0.156
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1284 0.79324 0.012 0.964 0.024 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.2210 0.79910 0.020 0.936 0.016 0.028
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0779 0.66234 0.000 0.016 0.980 0.004
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.4989 -0.03650 0.528 0.000 0.472 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 4 0.2466 0.68655 0.096 0.000 0.004 0.900
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.5615 0.66914 0.188 0.096 0.716 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 1 0.6781 0.43892 0.608 0.180 0.212 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.5576 0.60719 0.716 0.068 0.212 0.004
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.2706 0.79038 0.000 0.900 0.020 0.080
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.2408 0.76144 0.000 0.896 0.000 0.104
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.3806 0.74631 0.020 0.824 0.156 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2196 0.79947 0.016 0.936 0.032 0.016
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.4529 0.68104 0.196 0.004 0.776 0.024
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.4328 0.62875 0.000 0.244 0.748 0.008
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.4916 0.58604 0.760 0.056 0.184 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.7404 0.53861 0.204 0.540 0.252 0.004
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 4 0.4961 0.02867 0.000 0.000 0.448 0.552
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.6869 0.53274 0.128 0.040 0.160 0.672
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1557 0.78781 0.000 0.944 0.000 0.056
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2224 0.78594 0.928 0.000 0.040 0.032
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 4 0.4748 0.47086 0.000 0.016 0.268 0.716
#> C20F209A-2102-4502-80FA-17AF04601987 4 0.1109 0.71898 0.028 0.000 0.004 0.968
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.6158 0.29963 0.272 0.088 0.640 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3808 0.75990 0.812 0.000 0.012 0.176
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1590 0.79508 0.008 0.956 0.028 0.008
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.6929 0.11788 0.444 0.000 0.448 0.108
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3300 0.77986 0.848 0.000 0.008 0.144
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.4824 0.72775 0.144 0.780 0.076 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1139 0.79740 0.008 0.972 0.008 0.012
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.2795 0.69114 0.088 0.004 0.012 0.896
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1389 0.79009 0.000 0.952 0.000 0.048
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3539 0.76337 0.820 0.000 0.004 0.176
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4011 0.65178 0.000 0.208 0.784 0.008
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.1114 0.66721 0.016 0.008 0.972 0.004
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.3542 0.78663 0.852 0.000 0.028 0.120
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.2021 0.78916 0.000 0.932 0.012 0.056
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.7035 0.56581 0.184 0.572 0.244 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.4998 0.15387 0.000 0.000 0.512 0.488
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3411 0.78943 0.064 0.880 0.008 0.048
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4093 0.75526 0.832 0.000 0.096 0.072
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.3942 0.62669 0.000 0.000 0.764 0.236
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1520 0.79427 0.020 0.956 0.024 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4699 0.58996 0.676 0.000 0.004 0.320
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.7437 0.50638 0.240 0.512 0.248 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.3837 0.63529 0.000 0.000 0.776 0.224
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.4122 0.68552 0.760 0.000 0.236 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.3498 0.66879 0.000 0.160 0.832 0.008
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.5026 0.69088 0.168 0.028 0.776 0.028
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1890 0.78609 0.000 0.936 0.008 0.056
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 4 0.4585 0.36556 0.000 0.000 0.332 0.668
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4526 0.69419 0.160 0.016 0.800 0.024
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0162 0.87235 0.000 0.996 0.000 0.000 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3074 0.71416 0.196 0.000 0.804 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3079 0.82154 0.064 0.044 0.016 0.876 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0162 0.85560 0.000 0.000 0.000 0.004 0.996
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.0671 0.81635 0.000 0.016 0.004 0.980 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0162 0.87235 0.000 0.996 0.000 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.1012 0.89363 0.968 0.000 0.000 0.020 0.012
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.0865 0.84868 0.024 0.000 0.000 0.004 0.972
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.90732 1.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1992 0.86265 0.924 0.044 0.000 0.000 0.032
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.0671 0.81668 0.000 0.016 0.004 0.980 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2127 0.80978 0.108 0.000 0.000 0.892 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0703 0.89772 0.976 0.000 0.000 0.024 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0290 0.87358 0.000 0.992 0.008 0.000 0.000
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#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.90732 1.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6158 0.21154 0.000 0.480 0.136 0.384 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1386 0.87100 0.000 0.952 0.016 0.032 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.2597 0.81542 0.004 0.000 0.040 0.060 0.896
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0566 0.87389 0.000 0.984 0.012 0.004 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0703 0.89734 0.976 0.000 0.000 0.000 0.024
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0510 0.83067 0.000 0.016 0.984 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.1386 0.83042 0.000 0.000 0.952 0.032 0.016
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0404 0.90462 0.988 0.000 0.012 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.1179 0.86942 0.000 0.964 0.004 0.016 0.016
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.3081 0.74058 0.000 0.012 0.156 0.832 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.4367 0.29952 0.000 0.000 0.416 0.004 0.580
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.2046 0.84482 0.016 0.916 0.000 0.068 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0162 0.90675 0.996 0.000 0.004 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.1270 0.82256 0.000 0.000 0.948 0.000 0.052
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.1518 0.86953 0.004 0.944 0.048 0.004 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0162 0.90660 0.996 0.000 0.000 0.000 0.004
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0486 0.81685 0.004 0.004 0.004 0.988 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.3081 0.75123 0.000 0.000 0.832 0.012 0.156
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.5648 0.63985 0.104 0.000 0.196 0.676 0.024
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0451 0.83283 0.000 0.004 0.988 0.008 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0290 0.83214 0.000 0.008 0.992 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0794 0.87430 0.000 0.972 0.028 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3861 0.60191 0.000 0.000 0.284 0.004 0.712
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0162 0.83254 0.000 0.004 0.996 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2581 0.7211 0.000 0.856 0.000 0.000 0.016 0.128
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.3699 0.4688 0.336 0.000 0.660 0.000 0.000 0.004
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3998 0.7119 0.048 0.128 0.000 0.788 0.000 0.036
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0405 0.8506 0.000 0.000 0.000 0.004 0.988 0.008
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.3014 0.6416 0.000 0.000 0.012 0.184 0.000 0.804
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2147 0.7403 0.000 0.896 0.000 0.000 0.020 0.084
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.5173 0.1696 0.544 0.048 0.004 0.392 0.008 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.1930 0.8369 0.000 0.000 0.000 0.036 0.916 0.048
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0405 0.8718 0.988 0.004 0.000 0.000 0.008 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.4307 0.5719 0.000 0.000 0.072 0.704 0.000 0.224
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.2623 0.7230 0.132 0.000 0.000 0.852 0.000 0.016
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3290 0.6093 0.744 0.004 0.000 0.252 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0547 0.7486 0.000 0.980 0.000 0.000 0.000 0.020
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.0972 0.7359 0.000 0.000 0.008 0.964 0.000 0.028
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.1152 0.8061 0.000 0.044 0.952 0.000 0.000 0.004
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1649 0.7423 0.000 0.936 0.016 0.008 0.000 0.040
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0405 0.8173 0.000 0.008 0.988 0.000 0.000 0.004
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.2680 0.7347 0.000 0.880 0.012 0.060 0.000 0.048
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.3758 0.5148 0.000 0.668 0.008 0.000 0.324 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.4331 0.2651 0.004 0.540 0.004 0.000 0.444 0.008
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.4117 0.6466 0.000 0.016 0.044 0.748 0.192 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.4718 0.7006 0.000 0.000 0.720 0.032 0.172 0.076
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.1858 0.7810 0.092 0.000 0.904 0.000 0.000 0.004
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6244 0.4874 0.616 0.096 0.052 0.036 0.000 0.200
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.3023 0.6998 0.000 0.032 0.000 0.140 0.000 0.828
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.0260 0.8495 0.000 0.008 0.000 0.000 0.992 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0146 0.8508 0.000 0.000 0.000 0.004 0.996 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0632 0.8681 0.976 0.000 0.000 0.000 0.000 0.024
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.6243 0.1034 0.004 0.400 0.116 0.444 0.000 0.036
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.0000 0.8507 0.000 0.000 0.000 0.000 1.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2100 0.7310 0.000 0.884 0.000 0.000 0.004 0.112
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.4770 0.5815 0.264 0.000 0.652 0.080 0.000 0.004
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0520 0.7456 0.000 0.984 0.008 0.000 0.000 0.008
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.2609 0.7732 0.096 0.000 0.868 0.000 0.000 0.036
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.5509 0.3154 0.000 0.000 0.496 0.000 0.136 0.368
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.0146 0.8503 0.000 0.004 0.000 0.000 0.996 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1010 0.8625 0.960 0.000 0.000 0.004 0.000 0.036
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.2065 0.7309 0.000 0.032 0.004 0.912 0.000 0.052
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.4230 0.6501 0.224 0.004 0.000 0.716 0.056 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0146 0.7478 0.000 0.996 0.000 0.000 0.000 0.004
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.2562 0.6589 0.000 0.000 0.000 0.172 0.000 0.828
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.1556 0.8305 0.920 0.080 0.000 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 5 0.4807 -0.0720 0.000 0.464 0.000 0.000 0.484 0.052
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.4066 0.3639 0.000 0.000 0.392 0.000 0.596 0.012
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.1320 0.7494 0.000 0.948 0.000 0.000 0.016 0.036
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.4560 0.6536 0.000 0.124 0.000 0.020 0.120 0.736
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1616 0.7425 0.000 0.932 0.048 0.000 0.000 0.020
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.3795 0.4363 0.000 0.004 0.632 0.000 0.000 0.364
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0146 0.8729 0.996 0.000 0.000 0.000 0.000 0.004
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.3946 0.7237 0.000 0.000 0.164 0.004 0.764 0.068
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.0777 0.8497 0.000 0.000 0.000 0.024 0.972 0.004
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0146 0.8727 0.996 0.004 0.000 0.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 5 0.2333 0.7693 0.000 0.120 0.004 0.000 0.872 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0603 0.8192 0.000 0.000 0.980 0.000 0.016 0.004
#> F043185A-D4D2-4503-93FA-A7B7DA684290 5 0.6238 -0.0423 0.000 0.392 0.048 0.000 0.448 0.112
#> B730E9AD-DA24-46A3-BE56-A89447421C09 4 0.5315 0.5345 0.000 0.000 0.140 0.660 0.028 0.172
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.3874 0.4622 0.000 0.636 0.008 0.000 0.000 0.356
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.2608 0.7153 0.000 0.000 0.000 0.872 0.080 0.048
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.0146 0.8503 0.000 0.004 0.000 0.000 0.996 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.3445 0.6413 0.732 0.000 0.260 0.000 0.000 0.008
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.4009 0.4350 0.000 0.632 0.008 0.004 0.000 0.356
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.2404 0.7086 0.000 0.016 0.000 0.872 0.000 0.112
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.5550 0.2561 0.428 0.000 0.060 0.480 0.000 0.032
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0291 0.8723 0.992 0.004 0.000 0.004 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 5 0.4710 0.6462 0.020 0.000 0.000 0.208 0.700 0.072
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.2774 0.7814 0.000 0.040 0.872 0.000 0.012 0.076
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.3265 0.6248 0.748 0.000 0.000 0.248 0.000 0.004
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.3431 0.6328 0.000 0.228 0.756 0.000 0.000 0.016
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.5348 0.3954 0.012 0.592 0.000 0.292 0.000 0.104
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.2145 0.7389 0.016 0.916 0.000 0.020 0.044 0.004
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 6 0.6736 0.1331 0.000 0.000 0.208 0.312 0.052 0.428
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.2711 0.8164 0.872 0.000 0.056 0.004 0.000 0.068
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.0436 0.8505 0.000 0.004 0.004 0.004 0.988 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.1007 0.8121 0.000 0.000 0.956 0.000 0.000 0.044
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.1225 0.8158 0.012 0.000 0.952 0.000 0.000 0.036
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 5 0.3445 0.7972 0.000 0.000 0.096 0.036 0.832 0.036
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0508 0.8191 0.000 0.000 0.984 0.000 0.012 0.004
#> E435C03F-0277-49C1-83EF-19452082723E 5 0.2190 0.8365 0.000 0.000 0.008 0.040 0.908 0.044
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.3805 0.4971 0.000 0.664 0.004 0.004 0.000 0.328
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.2979 0.7940 0.840 0.000 0.116 0.000 0.000 0.044
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.3141 0.6723 0.000 0.788 0.000 0.000 0.012 0.200
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.0146 0.8505 0.000 0.004 0.000 0.000 0.996 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.2304 0.7448 0.024 0.012 0.004 0.916 0.020 0.024
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.4175 0.6873 0.020 0.784 0.004 0.004 0.124 0.064
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.1923 0.7311 0.000 0.916 0.064 0.004 0.000 0.016
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.0436 0.8182 0.000 0.004 0.988 0.004 0.000 0.004
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.0291 0.8500 0.000 0.004 0.000 0.000 0.992 0.004
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.2326 0.8275 0.888 0.008 0.092 0.000 0.000 0.012
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.1606 0.8499 0.932 0.004 0.000 0.056 0.000 0.008
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.0291 0.8508 0.000 0.004 0.000 0.004 0.992 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.5934 0.1272 0.000 0.016 0.396 0.496 0.052 0.040
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.0405 0.7384 0.000 0.000 0.000 0.988 0.004 0.008
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.1588 0.8352 0.000 0.000 0.072 0.000 0.924 0.004
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.4507 0.3967 0.000 0.596 0.020 0.012 0.000 0.372
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0692 0.8196 0.004 0.000 0.976 0.000 0.020 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 4 0.7152 0.3097 0.000 0.200 0.168 0.460 0.000 0.172
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 5 0.4018 0.3334 0.000 0.000 0.412 0.000 0.580 0.008
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.5346 0.3449 0.000 0.000 0.128 0.548 0.000 0.324
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.1471 0.8074 0.000 0.000 0.932 0.000 0.004 0.064
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.2350 0.7363 0.076 0.000 0.000 0.888 0.000 0.036
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.4709 0.1181 0.000 0.412 0.000 0.000 0.540 0.048
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 3 0.5042 0.4133 0.000 0.000 0.576 0.332 0.000 0.092
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.3279 0.6851 0.000 0.796 0.028 0.000 0.000 0.176
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0260 0.8720 0.992 0.000 0.008 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.2838 0.6855 0.000 0.808 0.000 0.000 0.004 0.188
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 4 0.4014 0.5556 0.000 0.000 0.012 0.704 0.268 0.016
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.3602 0.7478 0.000 0.000 0.792 0.000 0.136 0.072
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.1518 0.7510 0.000 0.944 0.008 0.000 0.024 0.024
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 1 0.2706 0.8026 0.860 0.000 0.104 0.000 0.000 0.036
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.3636 0.5382 0.000 0.676 0.000 0.000 0.004 0.320
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#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.3172 0.7294 0.148 0.000 0.816 0.000 0.000 0.036
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.4368 0.5461 0.000 0.000 0.296 0.000 0.656 0.048
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.2250 0.7403 0.000 0.896 0.000 0.000 0.040 0.064
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.4558 0.6667 0.032 0.168 0.028 0.748 0.000 0.024
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 6 0.2712 0.7107 0.000 0.108 0.012 0.000 0.016 0.864
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 5 0.3261 0.7137 0.000 0.000 0.204 0.000 0.780 0.016
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.2243 0.7820 0.000 0.112 0.004 0.004 0.880 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.2518 0.7971 0.000 0.000 0.880 0.092 0.016 0.012
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.1151 0.8174 0.000 0.000 0.956 0.000 0.032 0.012
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.5175 0.6323 0.060 0.700 0.000 0.000 0.116 0.124
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.2357 0.7287 0.116 0.000 0.000 0.872 0.000 0.012
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.2979 0.7018 0.000 0.852 0.088 0.004 0.000 0.056
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.2040 0.8043 0.004 0.084 0.004 0.004 0.904 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 3 0.6470 0.1408 0.000 0.224 0.440 0.308 0.000 0.028
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0146 0.8727 0.996 0.004 0.000 0.000 0.000 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.0291 0.8508 0.000 0.004 0.000 0.004 0.992 0.000
#> A2007795-C728-4688-B199-AE89500011D2 6 0.2520 0.6884 0.000 0.152 0.004 0.000 0.000 0.844
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.3791 0.7315 0.044 0.076 0.024 0.828 0.000 0.028
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.1982 0.8289 0.000 0.000 0.068 0.004 0.912 0.016
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0405 0.8173 0.000 0.008 0.988 0.000 0.000 0.004
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.3731 0.6114 0.020 0.240 0.736 0.000 0.000 0.004
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.0935 0.8485 0.000 0.000 0.032 0.004 0.964 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.5163 0.5539 0.000 0.216 0.076 0.668 0.000 0.040
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.2442 0.7313 0.000 0.068 0.000 0.048 0.000 0.884
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0363 0.8196 0.000 0.000 0.988 0.000 0.012 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.4283 0.5074 0.000 0.656 0.004 0.016 0.316 0.008
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0291 0.8175 0.000 0.004 0.992 0.000 0.000 0.004
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.3320 0.6683 0.212 0.000 0.000 0.772 0.000 0.016
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0603 0.7491 0.000 0.980 0.000 0.000 0.004 0.016
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.0146 0.8508 0.000 0.000 0.000 0.004 0.996 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2685 0.7329 0.000 0.868 0.000 0.000 0.072 0.060
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.1697 0.8318 0.004 0.036 0.004 0.000 0.936 0.020
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0260 0.8722 0.992 0.000 0.000 0.000 0.000 0.008
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1003 0.8673 0.964 0.016 0.020 0.000 0.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.4209 0.6039 0.000 0.000 0.000 0.160 0.104 0.736
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.0858 0.7364 0.000 0.000 0.000 0.968 0.004 0.028
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 6 0.3971 0.1046 0.000 0.448 0.004 0.000 0.000 0.548
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0146 0.8729 0.996 0.000 0.000 0.000 0.000 0.004
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1692 0.7372 0.000 0.932 0.048 0.008 0.000 0.012
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 6 0.4509 0.0883 0.000 0.436 0.000 0.032 0.000 0.532
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.3708 0.7599 0.000 0.000 0.800 0.112 0.008 0.080
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.1700 0.8364 0.916 0.000 0.080 0.000 0.000 0.004
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.1297 0.8457 0.000 0.000 0.000 0.012 0.948 0.040
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.3727 0.3932 0.612 0.000 0.388 0.000 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2136 0.7383 0.048 0.000 0.000 0.904 0.000 0.048
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.1168 0.7377 0.016 0.000 0.000 0.956 0.000 0.028
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.1605 0.8437 0.000 0.016 0.044 0.004 0.936 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.1398 0.7402 0.000 0.940 0.052 0.000 0.000 0.008
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.2787 0.7187 0.000 0.012 0.044 0.072 0.000 0.872
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 6 0.2361 0.7264 0.000 0.088 0.000 0.028 0.000 0.884
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0436 0.8182 0.000 0.004 0.988 0.004 0.000 0.004
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0790 0.8155 0.000 0.000 0.968 0.000 0.000 0.032
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.1007 0.8590 0.956 0.000 0.044 0.000 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.4190 0.5931 0.000 0.000 0.012 0.724 0.040 0.224
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 5 0.2979 0.7367 0.000 0.000 0.188 0.004 0.804 0.004
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.4148 0.6031 0.008 0.012 0.004 0.240 0.724 0.012
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.4076 0.2893 0.000 0.564 0.004 0.000 0.004 0.428
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0363 0.8708 0.988 0.000 0.000 0.012 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.2531 0.7904 0.000 0.000 0.132 0.000 0.856 0.012
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.0632 0.8451 0.000 0.024 0.000 0.000 0.976 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.4825 0.2829 0.000 0.012 0.560 0.392 0.000 0.036
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5637 0.5166 0.640 0.016 0.004 0.124 0.204 0.012
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3705 0.6039 0.000 0.740 0.020 0.004 0.000 0.236
#> 21385544-2FC4-4EB8-AF55-1C046216E189 3 0.7181 0.4848 0.252 0.000 0.504 0.044 0.120 0.080
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0146 0.8727 0.996 0.004 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6184 0.3498 0.000 0.560 0.180 0.212 0.000 0.048
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.2378 0.6886 0.000 0.152 0.000 0.000 0.000 0.848
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 4 0.4262 0.2092 0.000 0.012 0.000 0.560 0.424 0.004
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4103 0.2461 0.000 0.544 0.004 0.000 0.004 0.448
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0951 0.8652 0.968 0.020 0.000 0.008 0.004 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.1010 0.8099 0.000 0.036 0.960 0.000 0.000 0.004
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.3183 0.7748 0.000 0.000 0.828 0.112 0.000 0.060
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4976 0.2501 0.000 0.536 0.004 0.000 0.060 0.400
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.4229 0.5914 0.000 0.000 0.220 0.712 0.000 0.068
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3568 0.6984 0.000 0.000 0.212 0.008 0.764 0.016
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.3577 0.6836 0.012 0.792 0.004 0.020 0.000 0.172
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1340 0.8583 0.948 0.000 0.004 0.008 0.000 0.040
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0858 0.8187 0.000 0.000 0.968 0.000 0.028 0.004
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2296 0.7320 0.052 0.908 0.012 0.008 0.000 0.020
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8732 1.000 0.000 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0865 0.7324 0.000 0.000 0.000 0.964 0.000 0.036
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.3909 0.7391 0.000 0.000 0.772 0.060 0.160 0.008
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 4 0.2631 0.7224 0.000 0.000 0.044 0.880 0.008 0.068
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0837 0.8177 0.000 0.004 0.972 0.020 0.000 0.004
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0436 0.8179 0.004 0.004 0.988 0.000 0.000 0.004
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.1890 0.7460 0.000 0.916 0.024 0.000 0.000 0.060
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.2772 0.7525 0.000 0.000 0.180 0.004 0.816 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0551 0.8179 0.000 0.004 0.984 0.004 0.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.200 0.531 0.745 0.3968 0.522 0.522
#> 3 3 0.346 0.675 0.829 0.4578 0.584 0.393
#> 4 4 0.398 0.515 0.748 0.1911 0.843 0.644
#> 5 5 0.479 0.505 0.725 0.0726 0.895 0.677
#> 6 6 0.513 0.482 0.701 0.0313 0.967 0.875
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0376 0.7014 0.004 0.996
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.6480 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.7000 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.9993 0.0373 0.484 0.516
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.9996 0.1293 0.512 0.488
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.7883 0.6363 0.236 0.764
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.7000 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.9977 0.0960 0.472 0.528
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.9866 0.2544 0.432 0.568
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.9954 0.1510 0.460 0.540
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.9963 0.2306 0.536 0.464
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.5519 0.6988 0.128 0.872
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.6887 0.6755 0.184 0.816
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.2778 0.7056 0.048 0.952
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.8499 0.5907 0.276 0.724
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.0000 0.6480 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.7000 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.0000 0.6480 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.7000 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.9996 0.1065 0.512 0.488
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.7000 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.7528 0.6576 0.216 0.784
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#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.9815 0.3621 0.580 0.420
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.4298 0.6640 0.912 0.088
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.4690 0.7048 0.100 0.900
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 2 0.8861 0.5530 0.304 0.696
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 2 0.8713 0.5748 0.292 0.708
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.8443 0.6031 0.272 0.728
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.6480 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0376 0.7014 0.004 0.996
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 1 0.9608 0.4594 0.616 0.384
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 2 0.9909 0.2115 0.444 0.556
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 2 0.9993 0.0375 0.484 0.516
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.9795 0.3803 0.584 0.416
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.7000 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 1 0.5178 0.6619 0.884 0.116
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.9775 0.3915 0.588 0.412
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.6623 0.6458 0.828 0.172
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0376 0.7014 0.004 0.996
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.6343 0.6878 0.160 0.840
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 1 0.9815 0.3802 0.580 0.420
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.9552 0.4682 0.624 0.376
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.0672 0.7022 0.008 0.992
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.9775 0.3915 0.588 0.412
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0672 0.6508 0.992 0.008
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.7056 0.6718 0.192 0.808
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.0000 0.7000 0.000 1.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 1 0.9775 0.4014 0.588 0.412
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.0672 0.7022 0.008 0.992
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.9996 0.1065 0.512 0.488
#> 93E69515-4C47-4E68-8842-818DE0E369E2 2 0.9754 0.3300 0.408 0.592
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.9896 0.2073 0.440 0.560
#> A2007795-C728-4688-B199-AE89500011D2 2 0.8555 0.5854 0.280 0.720
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.4690 0.7047 0.100 0.900
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.9754 0.4013 0.592 0.408
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 1 0.0000 0.6480 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.4815 0.6637 0.896 0.104
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.9552 0.4700 0.624 0.376
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.7000 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.7000 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.6480 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.7000 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.0000 0.6480 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.8144 0.6167 0.252 0.748
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.7000 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.9815 0.3590 0.580 0.420
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.5946 0.6888 0.144 0.856
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.1843 0.7053 0.028 0.972
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 2 0.9850 0.2665 0.428 0.572
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.8661 0.5744 0.712 0.288
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 1 0.9732 0.4176 0.596 0.404
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.8267 0.6167 0.260 0.740
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.7000 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.3879 0.6649 0.924 0.076
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.7745 0.6451 0.228 0.772
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.7000 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.4022 0.6647 0.920 0.080
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.2948 0.6623 0.948 0.052
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.9988 0.0581 0.480 0.520
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.9944 0.2631 0.544 0.456
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.7000 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.7000 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.9896 0.2073 0.440 0.560
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.9491 0.4909 0.632 0.368
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 1 0.9552 0.4770 0.624 0.376
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.7000 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.6480 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 1 0.0000 0.6480 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.9775 0.3915 0.588 0.412
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.9710 0.4267 0.600 0.400
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0672 0.6508 0.992 0.008
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0672 0.7022 0.008 0.992
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 1 0.9710 0.4274 0.600 0.400
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0000 0.7000 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.6801 0.6423 0.820 0.180
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.9710 0.4196 0.600 0.400
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.9323 0.5148 0.652 0.348
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.9944 0.1662 0.456 0.544
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.9087 0.5031 0.324 0.676
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.9993 0.0357 0.484 0.516
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.9358 0.4714 0.352 0.648
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.8207 0.6194 0.256 0.744
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.7000 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.9608 0.3890 0.384 0.616
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6623 0.6779 0.172 0.828
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.9686 0.3615 0.396 0.604
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.6480 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.6048 0.6548 0.852 0.148
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.8661 0.5744 0.712 0.288
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.7000 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.8443 0.6034 0.272 0.728
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5629 0.6583 0.868 0.132
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.7000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.9977 0.0960 0.472 0.528
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.6480 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.8713 0.5762 0.292 0.708
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.9833 0.2815 0.424 0.576
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.8144 0.6253 0.252 0.748
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.9580 0.4631 0.620 0.380
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.9993 0.0396 0.484 0.516
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.6480 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.6480 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.9775 0.3215 0.412 0.588
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.9661 0.4371 0.608 0.392
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.6480 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3267 0.81047 0.116 0.884 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.91247 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.2537 0.82181 0.080 0.920 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2772 0.76754 0.916 0.080 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.4586 0.76606 0.856 0.096 0.048
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 1 0.6045 0.39444 0.620 0.380 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0237 0.82367 0.004 0.996 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.2711 0.76429 0.912 0.088 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3482 0.74971 0.872 0.128 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2959 0.76023 0.900 0.100 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.4087 0.77127 0.880 0.068 0.052
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.6235 0.26790 0.436 0.564 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6267 0.18719 0.548 0.452 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4887 0.71812 0.228 0.772 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.5529 0.58384 0.704 0.296 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.91247 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.1289 0.82597 0.032 0.968 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.91247 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.82340 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.3045 0.77474 0.916 0.064 0.020
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0237 0.82477 0.004 0.996 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.6330 0.34944 0.600 0.396 0.004
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.6307 0.00775 0.512 0.000 0.488
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.91247 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3415 0.76045 0.900 0.020 0.080
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.3340 0.80939 0.120 0.880 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.5621 0.58231 0.692 0.308 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.2446 0.77089 0.936 0.052 0.012
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.2878 0.76302 0.904 0.096 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 1 0.6225 0.25296 0.568 0.432 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.2269 0.77145 0.944 0.040 0.016
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5948 0.52128 0.360 0.640 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.2443 0.77121 0.940 0.032 0.028
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.5327 0.62705 0.728 0.272 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.2878 0.81869 0.096 0.904 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.91247 0.000 0.000 1.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.91247 0.000 0.000 1.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4062 0.73373 0.836 0.164 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.2959 0.76023 0.900 0.100 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3921 0.74793 0.872 0.016 0.112
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.82340 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.6299 0.11854 0.476 0.524 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.82340 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3340 0.80939 0.120 0.880 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.5178 0.64492 0.744 0.256 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.5254 0.62400 0.736 0.264 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.6280 0.16307 0.460 0.000 0.540
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.4796 0.72746 0.220 0.780 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 1 0.5835 0.49720 0.660 0.340 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 1 0.5363 0.60771 0.724 0.276 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.91247 0.000 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.3310 0.77003 0.908 0.028 0.064
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.4750 0.63032 0.784 0.000 0.216
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.6307 0.01211 0.512 0.000 0.488
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.2625 0.76506 0.916 0.084 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0237 0.82367 0.004 0.996 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.6045 0.44151 0.380 0.620 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.91247 0.000 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.4453 0.74202 0.836 0.152 0.012
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.5012 0.64207 0.788 0.008 0.204
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0237 0.82367 0.004 0.996 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.4712 0.73950 0.848 0.044 0.108
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4931 0.67557 0.768 0.232 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.2625 0.76632 0.916 0.084 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4121 0.76103 0.168 0.000 0.832
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 1 0.4544 0.75241 0.860 0.056 0.084
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.5678 0.58496 0.316 0.684 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.6062 0.43815 0.384 0.616 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 2 0.0237 0.82367 0.004 0.996 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.5016 0.66986 0.760 0.240 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.0237 0.82367 0.004 0.996 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.3482 0.74971 0.872 0.128 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4887 0.68737 0.228 0.000 0.772
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.0237 0.82367 0.004 0.996 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 1 0.6111 0.30796 0.604 0.000 0.396
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.2878 0.81716 0.096 0.904 0.000
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#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.3045 0.77474 0.916 0.064 0.020
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.4121 0.73073 0.832 0.168 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.3845 0.76112 0.872 0.116 0.012
#> A2007795-C728-4688-B199-AE89500011D2 1 0.5733 0.52959 0.676 0.324 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.6062 0.43815 0.384 0.616 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.2804 0.76428 0.924 0.016 0.060
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.91247 0.000 0.000 1.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6225 0.20051 0.568 0.000 0.432
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.3528 0.75084 0.892 0.016 0.092
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.1411 0.82612 0.036 0.964 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.3619 0.80019 0.136 0.864 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.91247 0.000 0.000 1.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.82340 0.000 1.000 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.91247 0.000 0.000 1.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.6008 0.44128 0.628 0.372 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.2796 0.81987 0.092 0.908 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.3083 0.77074 0.916 0.024 0.060
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.6204 0.34298 0.424 0.576 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.4654 0.73496 0.208 0.792 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.3619 0.74624 0.864 0.136 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.4861 0.67853 0.808 0.012 0.180
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 1 0.3590 0.76442 0.896 0.028 0.076
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.5982 0.50915 0.668 0.328 0.004
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.1964 0.82600 0.056 0.944 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.6095 0.29776 0.608 0.000 0.392
#> C5102A81-265F-4CD9-9B6C-390348FB690C 1 0.6215 0.26318 0.572 0.428 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.82340 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.6305 0.02085 0.516 0.000 0.484
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.6244 0.23959 0.440 0.000 0.560
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.2860 0.76663 0.912 0.084 0.004
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.3484 0.77335 0.904 0.048 0.048
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.82340 0.000 1.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.82340 0.000 1.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.3845 0.76112 0.872 0.116 0.012
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.4324 0.74151 0.860 0.028 0.112
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 1 0.4563 0.73854 0.852 0.036 0.112
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.2261 0.82498 0.068 0.932 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.91247 0.000 0.000 1.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.91247 0.000 0.000 1.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.2846 0.76406 0.924 0.020 0.056
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.3590 0.75947 0.896 0.028 0.076
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2261 0.86513 0.068 0.000 0.932
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.3412 0.80482 0.124 0.876 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 1 0.4399 0.75003 0.864 0.044 0.092
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0237 0.82367 0.004 0.996 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.5465 0.52207 0.712 0.000 0.288
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3141 0.76491 0.912 0.020 0.068
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.3682 0.73381 0.876 0.008 0.116
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3038 0.75960 0.896 0.104 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 1 0.5553 0.61793 0.724 0.272 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.2448 0.76799 0.924 0.076 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.4931 0.67311 0.768 0.232 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.6026 0.42667 0.624 0.376 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.1529 0.82638 0.040 0.960 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.4842 0.69597 0.776 0.224 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6295 0.16235 0.472 0.528 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4178 0.72616 0.828 0.172 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.91247 0.000 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.5650 0.47419 0.688 0.000 0.312
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4861 0.67853 0.808 0.012 0.180
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0237 0.82466 0.004 0.996 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.5873 0.54346 0.684 0.312 0.004
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5810 0.42308 0.664 0.000 0.336
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.82340 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2711 0.76455 0.912 0.088 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.91247 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.5845 0.56921 0.688 0.308 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.3686 0.74375 0.860 0.140 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.6057 0.48518 0.656 0.340 0.004
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.3670 0.75445 0.888 0.020 0.092
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.2448 0.76696 0.924 0.076 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.91247 0.000 0.000 1.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.91247 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.4514 0.73919 0.832 0.156 0.012
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.3415 0.76045 0.900 0.020 0.080
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.91247 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.4149 0.77018 0.152 0.036 0.000 0.812
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3105 0.79406 0.120 0.012 0.000 0.868
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1389 0.56390 0.952 0.048 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5564 0.51751 0.224 0.720 0.024 0.032
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 1 0.7878 0.18748 0.376 0.340 0.000 0.284
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.1211 0.80674 0.040 0.000 0.000 0.960
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0817 0.57090 0.976 0.024 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1284 0.58155 0.964 0.012 0.000 0.024
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0927 0.57614 0.976 0.016 0.000 0.008
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5235 0.53005 0.232 0.728 0.024 0.016
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.6209 -0.09142 0.492 0.052 0.000 0.456
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6249 0.30875 0.592 0.072 0.000 0.336
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.6096 0.68083 0.184 0.136 0.000 0.680
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4079 0.54944 0.800 0.020 0.000 0.180
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.2124 0.79151 0.008 0.068 0.000 0.924
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.5522 0.31808 0.648 0.324 0.016 0.012
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.1398 0.80927 0.040 0.004 0.000 0.956
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.6837 0.38933 0.576 0.112 0.004 0.308
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.7732 0.18676 0.228 0.392 0.380 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.5987 0.00319 0.520 0.440 0.040 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.4426 0.76342 0.092 0.096 0.000 0.812
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4426 0.53424 0.772 0.024 0.000 0.204
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.2466 0.53915 0.900 0.096 0.004 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0895 0.57510 0.976 0.020 0.000 0.004
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 1 0.7850 0.21428 0.388 0.272 0.000 0.340
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.2831 0.52255 0.876 0.120 0.004 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.7159 0.48639 0.180 0.272 0.000 0.548
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4319 0.44000 0.760 0.228 0.012 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3647 0.56023 0.832 0.016 0.000 0.152
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.4171 0.77593 0.084 0.088 0.000 0.828
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.1743 0.58369 0.940 0.004 0.000 0.056
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0927 0.57614 0.976 0.016 0.000 0.008
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.5599 0.28973 0.700 0.228 0.072 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5894 0.04405 0.536 0.036 0.000 0.428
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4426 0.76342 0.092 0.096 0.000 0.812
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3907 0.56865 0.828 0.032 0.000 0.140
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.7510 0.18096 0.436 0.380 0.000 0.184
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.7521 0.00106 0.188 0.368 0.444 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.5358 0.66684 0.252 0.048 0.000 0.700
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 1 0.7761 0.17083 0.388 0.376 0.000 0.236
#> 36B2E208-FF01-4249-92C3-BE77D426691B 1 0.7550 0.18943 0.436 0.372 0.000 0.192
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.5558 0.22505 0.608 0.364 0.028 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.7106 -0.12347 0.528 0.324 0.148 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.7811 -0.19890 0.252 0.368 0.380 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1118 0.56912 0.964 0.036 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.6507 0.32870 0.404 0.076 0.000 0.520
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.6856 0.33651 0.568 0.328 0.008 0.096
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.6157 0.55849 0.232 0.660 0.108 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.2546 0.57036 0.092 0.900 0.008 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3108 0.57123 0.872 0.016 0.000 0.112
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.1398 0.57177 0.956 0.040 0.000 0.004
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4931 0.68386 0.092 0.132 0.776 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.3123 0.55896 0.156 0.844 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.6382 0.48072 0.340 0.080 0.000 0.580
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.6360 0.30375 0.420 0.064 0.000 0.516
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3224 0.56913 0.864 0.016 0.000 0.120
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1284 0.58155 0.964 0.012 0.000 0.024
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.5672 0.59416 0.100 0.188 0.712 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.7355 0.40944 0.204 0.520 0.276 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3390 0.78704 0.132 0.016 0.000 0.852
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.3390 0.78704 0.132 0.016 0.000 0.852
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.5978 0.24386 0.424 0.540 0.032 0.004
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.5113 0.38034 0.704 0.264 0.032 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0804 0.57662 0.980 0.012 0.000 0.008
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.1489 0.57035 0.952 0.044 0.000 0.004
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.5536 0.41648 0.680 0.280 0.008 0.032
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.2101 0.56823 0.928 0.060 0.000 0.012
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.6719 0.30837 0.204 0.616 0.000 0.180
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.6393 -0.16952 0.480 0.456 0.064 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.4486 0.53470 0.188 0.784 0.008 0.020
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.3988 0.48601 0.820 0.156 0.020 0.004
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#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.5586 0.01346 0.528 0.452 0.020 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2500 0.83163 0.044 0.040 0.916 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 1 0.6324 0.30016 0.584 0.076 0.000 0.340
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.1211 0.80674 0.040 0.000 0.000 0.960
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.3123 0.55896 0.156 0.844 0.000 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 4 0.3300 0.78268 0.144 0.008 0.000 0.848
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.5522 0.31808 0.648 0.324 0.016 0.012
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.1975 0.58099 0.936 0.016 0.000 0.048
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6356 0.40139 0.612 0.308 0.004 0.076
#> A2007795-C728-4688-B199-AE89500011D2 2 0.7697 -0.10824 0.376 0.404 0.000 0.220
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.6360 0.30375 0.420 0.064 0.000 0.516
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.5760 -0.01758 0.524 0.448 0.028 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 2 0.7762 0.35344 0.256 0.428 0.316 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.6071 -0.04311 0.504 0.452 0.044 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.2489 0.79233 0.020 0.068 0.000 0.912
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.5000 0.74033 0.100 0.128 0.000 0.772
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.4661 0.48579 0.728 0.016 0.000 0.256
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.4104 0.77782 0.080 0.088 0.000 0.832
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.5022 0.40024 0.736 0.220 0.044 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.7574 0.33943 0.248 0.268 0.000 0.484
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.4963 0.64878 0.284 0.020 0.000 0.696
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1174 0.57885 0.968 0.012 0.000 0.020
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.7009 -0.17343 0.488 0.392 0.120 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.5925 0.17844 0.452 0.512 0.036 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.7519 0.36613 0.496 0.256 0.000 0.248
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.3082 0.78874 0.032 0.084 0.000 0.884
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 2 0.7416 0.43280 0.240 0.516 0.244 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 1 0.7841 0.23454 0.396 0.272 0.000 0.332
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.7746 0.19960 0.232 0.392 0.376 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.7502 0.03900 0.188 0.356 0.456 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1118 0.56780 0.964 0.036 0.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.6258 0.12017 0.524 0.432 0.016 0.028
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.6356 0.40139 0.612 0.308 0.004 0.076
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.6209 0.24305 0.456 0.492 0.052 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5052 0.53583 0.244 0.720 0.036 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.3047 0.77660 0.012 0.116 0.000 0.872
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.5581 0.02170 0.532 0.448 0.020 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.5784 0.27667 0.412 0.556 0.032 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2500 0.83163 0.044 0.040 0.916 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.4121 0.75805 0.184 0.020 0.000 0.796
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.3142 0.56897 0.132 0.860 0.008 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.1302 0.80725 0.044 0.000 0.000 0.956
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.7463 0.42224 0.364 0.456 0.180 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4446 0.40993 0.776 0.196 0.028 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.6417 -0.04268 0.540 0.388 0.072 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0804 0.57696 0.980 0.012 0.000 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.6719 0.30837 0.204 0.616 0.000 0.180
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1389 0.56384 0.952 0.048 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3485 0.57719 0.856 0.028 0.000 0.116
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.7748 0.28405 0.440 0.280 0.000 0.280
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.2197 0.78777 0.004 0.080 0.000 0.916
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.3659 0.57611 0.840 0.024 0.000 0.136
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.7785 0.18331 0.288 0.284 0.000 0.428
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2060 0.58106 0.932 0.016 0.000 0.052
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.7252 0.48123 0.292 0.528 0.180 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.7002 -0.16316 0.492 0.388 0.120 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0524 0.80447 0.008 0.004 0.000 0.988
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.7551 0.34165 0.484 0.288 0.000 0.228
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.7493 0.43897 0.320 0.480 0.200 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.80131 0.000 0.000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1209 0.57204 0.964 0.032 0.000 0.004
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.7480 0.37991 0.528 0.256 0.004 0.212
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1510 0.58116 0.956 0.016 0.000 0.028
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.7519 0.36390 0.496 0.248 0.000 0.256
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5102 0.36084 0.732 0.220 0.048 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1576 0.56718 0.948 0.048 0.000 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0188 0.88214 0.000 0.004 0.996 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.88377 0.000 0.000 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.6840 0.33873 0.572 0.324 0.008 0.096
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.5987 0.00319 0.520 0.440 0.040 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.88377 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.5236 0.6902 0.120 0.184 0.000 0.692 0.004
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3992 0.7475 0.124 0.080 0.000 0.796 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1831 0.6068 0.920 0.004 0.000 0.000 0.076
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5386 0.4077 0.088 0.676 0.000 0.012 0.224
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.6804 0.2854 0.304 0.488 0.000 0.192 0.016
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.1357 0.7736 0.048 0.000 0.000 0.948 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1408 0.6160 0.948 0.008 0.000 0.000 0.044
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1564 0.6150 0.948 0.024 0.000 0.004 0.024
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0794 0.6161 0.972 0.000 0.000 0.000 0.028
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5684 0.3774 0.100 0.640 0.000 0.012 0.248
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.6433 0.0751 0.480 0.160 0.000 0.356 0.004
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6183 0.3649 0.580 0.160 0.000 0.252 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.6033 0.5491 0.132 0.296 0.000 0.568 0.004
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.3888 0.5533 0.804 0.076 0.000 0.120 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.3005 0.7339 0.008 0.124 0.000 0.856 0.012
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0566 0.7614 0.000 0.004 0.000 0.984 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6504 0.2886 0.536 0.236 0.000 0.008 0.220
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.2075 0.7778 0.032 0.040 0.000 0.924 0.004
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.6801 0.3337 0.540 0.208 0.000 0.224 0.028
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4989 0.5969 0.056 0.032 0.176 0.000 0.736
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6739 -0.0697 0.392 0.260 0.000 0.000 0.348
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.4829 0.6419 0.032 0.272 0.000 0.684 0.012
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4376 0.5373 0.768 0.048 0.000 0.172 0.012
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.3061 0.5742 0.844 0.020 0.000 0.000 0.136
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1597 0.6166 0.940 0.012 0.000 0.000 0.048
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.7448 0.2035 0.320 0.392 0.000 0.252 0.036
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.3409 0.5581 0.816 0.024 0.000 0.000 0.160
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.6144 -0.2022 0.100 0.456 0.000 0.436 0.008
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5251 0.4489 0.680 0.136 0.000 0.000 0.184
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3410 0.5720 0.840 0.068 0.000 0.092 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.4783 0.6693 0.036 0.252 0.000 0.700 0.012
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.2338 0.6136 0.916 0.032 0.000 0.036 0.016
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0794 0.6161 0.972 0.000 0.000 0.000 0.028
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4768 0.2158 0.592 0.024 0.000 0.000 0.384
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0510 0.7619 0.000 0.000 0.000 0.984 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5964 0.2086 0.536 0.124 0.000 0.340 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0566 0.7614 0.000 0.004 0.000 0.984 0.012
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4829 0.6419 0.032 0.272 0.000 0.684 0.012
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4244 0.5742 0.800 0.084 0.000 0.100 0.016
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.7061 0.2620 0.376 0.448 0.000 0.128 0.048
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.4652 0.4748 0.032 0.008 0.260 0.000 0.700
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.6175 0.5715 0.228 0.192 0.000 0.576 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6755 0.2978 0.320 0.496 0.000 0.164 0.020
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.7056 0.2713 0.368 0.452 0.000 0.136 0.044
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.6326 0.1897 0.512 0.188 0.000 0.000 0.300
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.5033 0.3217 0.400 0.028 0.004 0.000 0.568
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.4548 0.5963 0.076 0.004 0.168 0.000 0.752
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1544 0.6130 0.932 0.000 0.000 0.000 0.068
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.6763 0.2228 0.364 0.220 0.000 0.412 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.7128 0.1693 0.496 0.308 0.000 0.056 0.140
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.5260 0.3633 0.064 0.332 0.000 0.000 0.604
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.4437 0.2843 0.020 0.664 0.000 0.000 0.316
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.2797 0.5894 0.880 0.060 0.000 0.060 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.1956 0.6140 0.916 0.008 0.000 0.000 0.076
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4419 0.5654 0.020 0.000 0.668 0.000 0.312
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.3999 0.3048 0.020 0.740 0.000 0.000 0.240
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.6666 0.3861 0.300 0.224 0.000 0.472 0.004
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.6742 0.2081 0.388 0.188 0.000 0.416 0.008
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.2992 0.5845 0.868 0.064 0.000 0.068 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.1564 0.6150 0.948 0.024 0.000 0.004 0.024
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4581 0.4542 0.004 0.012 0.624 0.000 0.360
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
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#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.3999 0.3048 0.020 0.740 0.000 0.000 0.240
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.6719 0.2258 0.384 0.184 0.000 0.424 0.008
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.2732 0.8214 0.000 0.000 0.840 0.000 0.160
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.1121 0.9234 0.000 0.000 0.956 0.000 0.044
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.3631 0.5842 0.840 0.068 0.000 0.080 0.012
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.5535 0.3198 0.108 0.620 0.000 0.000 0.272
#> 4BF521F6-7804-49BA-8C56-28E253531628 4 0.2570 0.7597 0.108 0.008 0.000 0.880 0.004
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.4238 0.4259 0.052 0.756 0.000 0.000 0.192
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.1914 0.7779 0.032 0.032 0.000 0.932 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 4 0.5959 0.5554 0.124 0.296 0.000 0.576 0.004
#> 82964248-7145-4D55-9634-DC0173F2FA5A 4 0.6059 0.2687 0.412 0.120 0.000 0.468 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.5450 0.4264 0.652 0.132 0.000 0.216 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 5 0.2990 0.6211 0.080 0.012 0.032 0.000 0.876
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.3882 0.7100 0.012 0.200 0.000 0.776 0.012
#> F79C78B6-421E-4634-A403-4EC822299308 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.4240 0.4866 0.736 0.036 0.000 0.000 0.228
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 5 0.3353 0.6268 0.104 0.020 0.024 0.000 0.852
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.6698 0.2393 0.384 0.180 0.000 0.428 0.008
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.3354 0.5723 0.844 0.068 0.000 0.088 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.4634 0.5291 0.752 0.100 0.000 0.144 0.004
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.4610 0.5371 0.760 0.092 0.000 0.140 0.008
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.4724 0.7250 0.148 0.104 0.000 0.744 0.004
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.4437 0.2843 0.020 0.664 0.000 0.000 0.316
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.1668 0.6130 0.940 0.032 0.000 0.000 0.028
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.1792 0.6062 0.916 0.000 0.000 0.000 0.084
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.6718 0.0137 0.420 0.272 0.000 0.000 0.308
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.0162 0.7656 0.000 0.000 0.000 0.996 0.004
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 5 0.4890 0.6014 0.032 0.088 0.120 0.000 0.760
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.6712 -0.0116 0.416 0.260 0.000 0.000 0.324
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 5 0.4866 0.5794 0.148 0.116 0.004 0.000 0.732
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.4225 0.7467 0.112 0.096 0.000 0.788 0.004
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.6679 0.2453 0.492 0.212 0.000 0.288 0.008
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.5091 0.3572 0.088 0.676 0.000 0.000 0.236
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.6080 0.1725 0.528 0.140 0.000 0.000 0.332
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.4593 0.7144 0.184 0.080 0.000 0.736 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.6728 -0.0137 0.412 0.268 0.000 0.000 0.320
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.2966 0.8317 0.016 0.000 0.848 0.000 0.136
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 1 0.6141 0.3546 0.576 0.172 0.000 0.248 0.004
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.1357 0.7736 0.048 0.000 0.000 0.948 0.004
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.3999 0.3048 0.020 0.740 0.000 0.000 0.240
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 4 0.3123 0.7420 0.160 0.012 0.000 0.828 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.6504 0.2886 0.536 0.236 0.000 0.008 0.220
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.2445 0.6066 0.908 0.056 0.000 0.020 0.016
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.6814 0.3639 0.568 0.232 0.000 0.052 0.148
#> A2007795-C728-4688-B199-AE89500011D2 2 0.6543 0.3901 0.280 0.552 0.000 0.144 0.024
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.6723 0.1998 0.392 0.184 0.000 0.416 0.008
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.6728 -0.0735 0.404 0.260 0.000 0.000 0.336
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 5 0.5298 0.6147 0.092 0.044 0.132 0.000 0.732
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.6738 -0.1217 0.376 0.256 0.000 0.000 0.368
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3669 0.7212 0.012 0.176 0.000 0.800 0.012
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 4 0.4686 0.5978 0.016 0.332 0.000 0.644 0.008
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0162 0.7656 0.000 0.000 0.000 0.996 0.004
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.4555 0.4994 0.732 0.068 0.000 0.200 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.4731 0.6751 0.036 0.244 0.000 0.708 0.012
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.5331 0.3781 0.640 0.092 0.000 0.000 0.268
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.6585 -0.0165 0.180 0.440 0.000 0.376 0.004
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.5811 0.5818 0.264 0.140 0.000 0.596 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.1549 0.6104 0.944 0.040 0.000 0.000 0.016
#> DDC71530-38B7-483F-83DC-1BCC550719C3 5 0.6284 0.3025 0.372 0.136 0.004 0.000 0.488
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 5 0.6825 0.0713 0.336 0.324 0.000 0.000 0.340
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.7143 0.0606 0.456 0.332 0.000 0.176 0.036
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.3699 0.7087 0.008 0.204 0.000 0.780 0.008
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 5 0.1862 0.6099 0.048 0.016 0.004 0.000 0.932
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.7446 0.1908 0.328 0.388 0.000 0.248 0.036
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0566 0.7614 0.000 0.004 0.000 0.984 0.012
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.4916 0.5989 0.056 0.032 0.168 0.000 0.744
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 5 0.5519 0.4496 0.040 0.036 0.280 0.000 0.644
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1478 0.6117 0.936 0.000 0.000 0.000 0.064
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.7062 0.1250 0.432 0.304 0.000 0.016 0.248
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0290 0.7650 0.000 0.000 0.000 0.992 0.008
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0162 0.7656 0.000 0.000 0.000 0.996 0.004
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.6814 0.3639 0.568 0.232 0.000 0.052 0.148
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.6758 0.2399 0.336 0.272 0.000 0.000 0.392
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.6243 0.0628 0.148 0.472 0.000 0.000 0.380
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.3796 0.6895 0.008 0.216 0.000 0.768 0.008
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.6712 -0.0116 0.416 0.260 0.000 0.000 0.324
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.6806 0.0750 0.296 0.352 0.000 0.000 0.352
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2966 0.8317 0.016 0.000 0.848 0.000 0.136
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.4747 0.7030 0.196 0.084 0.000 0.720 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.4800 0.3332 0.052 0.676 0.000 0.000 0.272
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.1430 0.7740 0.052 0.000 0.000 0.944 0.004
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.5090 0.5672 0.172 0.116 0.004 0.000 0.708
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4338 0.4136 0.696 0.024 0.000 0.000 0.280
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.6274 0.1853 0.424 0.148 0.000 0.000 0.428
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1041 0.6169 0.964 0.004 0.000 0.000 0.032
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3197 0.4513 0.024 0.868 0.000 0.080 0.028
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1943 0.6072 0.924 0.020 0.000 0.000 0.056
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3854 0.5881 0.828 0.080 0.000 0.076 0.016
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.7414 0.1398 0.372 0.376 0.000 0.212 0.040
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.3252 0.7215 0.008 0.156 0.000 0.828 0.008
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.3495 0.5954 0.844 0.024 0.000 0.108 0.024
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6793 0.1591 0.212 0.448 0.000 0.332 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2395 0.6106 0.912 0.048 0.000 0.024 0.016
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.3558 0.6164 0.108 0.064 0.000 0.000 0.828
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.6277 0.3123 0.368 0.136 0.004 0.000 0.492
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.1569 0.7697 0.012 0.032 0.000 0.948 0.008
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.7208 -0.0372 0.424 0.368 0.000 0.168 0.040
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3255 0.6178 0.136 0.012 0.012 0.000 0.840
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0290 0.7650 0.000 0.000 0.000 0.992 0.008
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1628 0.6157 0.936 0.008 0.000 0.000 0.056
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.7343 0.1109 0.480 0.296 0.000 0.160 0.064
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1630 0.6128 0.944 0.036 0.000 0.004 0.016
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.7189 0.0614 0.448 0.332 0.000 0.184 0.036
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4805 0.3498 0.648 0.040 0.000 0.000 0.312
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1830 0.6131 0.924 0.008 0.000 0.000 0.068
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0290 0.9402 0.000 0.000 0.992 0.000 0.008
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.7150 0.1545 0.488 0.316 0.000 0.056 0.140
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6739 -0.0697 0.392 0.260 0.000 0.000 0.348
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.9436 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.6177 0.605172 0.088 0.212 0.000 0.584 0.000 0.116
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4873 0.691685 0.104 0.112 0.000 0.728 0.000 0.056
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1590 0.586739 0.936 0.008 0.000 0.000 0.048 0.008
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.4267 0.298152 0.052 0.040 0.000 0.004 0.128 0.776
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 6 0.7303 0.296059 0.264 0.156 0.000 0.132 0.008 0.440
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.1225 0.721533 0.036 0.012 0.000 0.952 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1275 0.592978 0.956 0.016 0.000 0.000 0.016 0.012
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1598 0.591655 0.940 0.040 0.000 0.004 0.008 0.008
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0653 0.593068 0.980 0.004 0.000 0.000 0.004 0.012
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.4070 0.317521 0.064 0.016 0.000 0.004 0.136 0.780
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.6963 0.140620 0.436 0.176 0.000 0.296 0.000 0.092
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6755 0.369274 0.528 0.164 0.000 0.204 0.004 0.100
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.7025 0.459280 0.100 0.212 0.000 0.452 0.000 0.236
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4430 0.536393 0.752 0.120 0.000 0.104 0.000 0.024
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.4007 0.652936 0.004 0.128 0.000 0.776 0.004 0.088
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.1555 0.695880 0.000 0.060 0.000 0.932 0.004 0.004
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6100 0.186340 0.512 0.012 0.000 0.008 0.164 0.304
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.2607 0.727868 0.028 0.056 0.000 0.888 0.000 0.028
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.7220 0.300960 0.496 0.128 0.000 0.168 0.016 0.192
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.4656 0.627669 0.056 0.004 0.172 0.000 0.732 0.036
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.6383 -0.062614 0.388 0.016 0.000 0.000 0.240 0.356
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.5789 0.501765 0.008 0.264 0.000 0.540 0.000 0.188
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4528 0.525587 0.744 0.064 0.000 0.160 0.004 0.028
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.2926 0.563499 0.852 0.012 0.000 0.000 0.112 0.024
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1700 0.591317 0.936 0.028 0.000 0.000 0.024 0.012
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.7424 0.238437 0.280 0.144 0.000 0.176 0.004 0.396
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#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.6292 -0.016203 0.404 0.012 0.000 0.000 0.236 0.348
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 6 0.6202 0.216135 0.288 0.012 0.000 0.000 0.240 0.460
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2704 0.816011 0.016 0.000 0.844 0.000 0.140 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5519 0.647826 0.168 0.124 0.000 0.656 0.000 0.052
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 6 0.3277 0.222300 0.024 0.020 0.000 0.000 0.128 0.828
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.1297 0.722081 0.040 0.012 0.000 0.948 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.5356 0.548212 0.168 0.008 0.004 0.000 0.636 0.184
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4366 0.444763 0.708 0.012 0.000 0.000 0.232 0.048
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.6184 -0.102310 0.412 0.012 0.000 0.000 0.376 0.200
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0881 0.593664 0.972 0.008 0.000 0.000 0.012 0.008
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.4873 0.798670 0.000 0.652 0.000 0.032 0.040 0.276
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1798 0.588791 0.932 0.020 0.000 0.000 0.028 0.020
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3876 0.566010 0.808 0.080 0.000 0.068 0.000 0.044
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.7233 0.201235 0.324 0.128 0.000 0.144 0.004 0.400
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.4750 0.618150 0.004 0.172 0.000 0.700 0.004 0.120
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.3931 0.573949 0.812 0.044 0.000 0.096 0.012 0.036
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.7388 0.205193 0.172 0.180 0.000 0.248 0.000 0.400
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.2345 0.587960 0.896 0.072 0.000 0.016 0.000 0.016
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.3866 0.646357 0.104 0.012 0.000 0.000 0.792 0.092
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.6145 0.210953 0.368 0.012 0.000 0.000 0.428 0.192
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.2492 0.706524 0.008 0.080 0.000 0.888 0.004 0.020
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.6796 0.089532 0.380 0.084 0.000 0.120 0.004 0.412
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.3336 0.640459 0.132 0.004 0.008 0.000 0.824 0.032
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0363 0.710180 0.000 0.012 0.000 0.988 0.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1434 0.590701 0.948 0.012 0.000 0.000 0.028 0.012
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.7211 0.049273 0.432 0.092 0.000 0.120 0.024 0.332
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1462 0.590836 0.936 0.056 0.000 0.000 0.000 0.008
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.7032 -0.002366 0.400 0.108 0.000 0.128 0.004 0.360
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4872 0.387028 0.652 0.012 0.000 0.000 0.264 0.072
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1679 0.589616 0.936 0.012 0.000 0.000 0.036 0.016
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0260 0.932927 0.000 0.000 0.992 0.000 0.008 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.936568 0.000 0.000 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.6549 0.029159 0.456 0.048 0.000 0.028 0.080 0.388
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.6383 -0.062614 0.388 0.016 0.000 0.000 0.240 0.356
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.936568 0.000 0.000 1.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.987 0.946 0.980 0.3902 0.613 0.613
#> 3 3 0.924 0.907 0.961 0.5464 0.608 0.442
#> 4 4 0.670 0.468 0.766 0.2030 0.796 0.536
#> 5 5 0.736 0.742 0.859 0.0843 0.813 0.444
#> 6 6 0.681 0.511 0.708 0.0407 0.894 0.564
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
#> attr(,"optional")
#> [1] 2
There is also optional best \(k\) = 2 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9834 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9664 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9834 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.0000 0.9834 0.000 1.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9834 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9834 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.9834 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.0000 0.9834 0.000 1.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.0000 0.9834 0.000 1.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.0000 0.9834 0.000 1.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9834 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.9834 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.0000 0.9834 0.000 1.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9834 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.9834 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.0000 0.9664 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9834 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.0000 0.9664 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9834 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.9834 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9834 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9834 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9664 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9664 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.3733 0.9092 0.072 0.928
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9834 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0000 0.9834 0.000 1.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.0000 0.9834 0.000 1.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 2 0.0000 0.9834 0.000 1.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9834 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 1.0000 -0.0165 0.496 0.504
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9834 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.0000 0.9834 0.000 1.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 2 0.0000 0.9834 0.000 1.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9834 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9664 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.9664 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.0000 0.9834 0.000 1.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 2 0.0000 0.9834 0.000 1.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3114 0.9146 0.944 0.056
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9834 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.0000 0.9834 0.000 1.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9834 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9834 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.0000 0.9834 0.000 1.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9834 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9664 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9834 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9834 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9834 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 1 0.0000 0.9664 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.6531 0.7878 0.168 0.832
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9664 1.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.9664 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 0.0000 0.9834 0.000 1.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0000 0.9834 0.000 1.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0000 0.9834 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.0000 0.9664 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9834 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.0000 0.9664 1.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0000 0.9834 0.000 1.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.0000 0.9664 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 2 0.0000 0.9834 0.000 1.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.0000 0.9834 0.000 1.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.9664 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.9834 0.000 1.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9834 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.9834 0.000 1.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 2 0.0000 0.9834 0.000 1.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 2 0.0000 0.9834 0.000 1.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.0000 0.9834 0.000 1.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 2 0.0000 0.9834 0.000 1.000
#> 26635F72-F34D-4543-908F-484441832E9E 1 0.0000 0.9664 1.000 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.0000 0.9834 0.000 1.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 1 0.0000 0.9664 1.000 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.9834 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9834 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.0000 0.9834 0.000 1.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 2 0.0000 0.9834 0.000 1.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 2 0.0000 0.9834 0.000 1.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 2 0.0000 0.9834 0.000 1.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.0000 0.9664 1.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.0000 0.9664 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 2 0.0000 0.9834 0.000 1.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.9664 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 2 0.0000 0.9834 0.000 1.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.9834 0.000 1.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.9661 0.3394 0.392 0.608
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.9834 0.000 1.000
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#> C20F209A-2102-4502-80FA-17AF04601987 1 0.9661 0.3688 0.608 0.392
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.2043 0.9520 0.032 0.968
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.0000 0.9834 0.000 1.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9834 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.0000 0.9834 0.000 1.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.0000 0.9834 0.000 1.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9834 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9834 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.0000 0.9834 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9834 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.0000 0.9834 0.000 1.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.9664 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9664 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9664 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9834 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9834 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.9664 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9834 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.0000 0.9834 0.000 1.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9664 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9834 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.0000 0.9834 0.000 1.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9834 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.9635 0.3789 0.612 0.388
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.0000 0.9834 0.000 1.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.9664 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9664 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9834 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.9933 0.1527 0.452 0.548
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9664 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0747 0.93366 0.016 0.984 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.99611 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.93553 0.000 1.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0747 0.95442 0.984 0.016 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.0000 0.95417 1.000 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0747 0.93366 0.016 0.984 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.93553 0.000 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0747 0.95442 0.984 0.016 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0747 0.95442 0.984 0.016 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0747 0.95442 0.984 0.016 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.0000 0.95417 1.000 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.93553 0.000 1.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0747 0.95442 0.984 0.016 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0747 0.93366 0.016 0.984 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.5678 0.53022 0.316 0.684 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.99611 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0747 0.93366 0.016 0.984 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.99611 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0747 0.93366 0.016 0.984 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0237 0.95462 0.996 0.004 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.93553 0.000 1.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.0237 0.95462 0.996 0.004 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.99611 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.99611 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0000 0.95417 1.000 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0747 0.93366 0.016 0.984 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0747 0.95442 0.984 0.016 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0747 0.95442 0.984 0.016 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0747 0.95442 0.984 0.016 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.3879 0.78953 0.152 0.848 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0747 0.95442 0.984 0.016 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0892 0.93135 0.020 0.980 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0747 0.95442 0.984 0.016 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6154 0.31569 0.592 0.408 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0747 0.93366 0.016 0.984 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.99611 0.000 0.000 1.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.99611 0.000 0.000 1.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0747 0.95442 0.984 0.016 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0747 0.95442 0.984 0.016 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0747 0.95442 0.984 0.016 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0747 0.93366 0.016 0.984 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0892 0.95241 0.980 0.020 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0747 0.93366 0.016 0.984 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0747 0.93366 0.016 0.984 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0747 0.95442 0.984 0.016 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.0000 0.95417 1.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.99611 0.000 0.000 1.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0747 0.93366 0.016 0.984 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 1 0.6045 0.35722 0.620 0.380 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 1 0.0000 0.95417 1.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.99611 0.000 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0747 0.95442 0.984 0.016 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0747 0.95029 0.984 0.000 0.016
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0000 0.99611 0.000 0.000 1.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0747 0.95442 0.984 0.016 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0000 0.93553 0.000 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.0000 0.95417 1.000 0.000 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.99611 0.000 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.0000 0.95417 1.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.0000 0.95417 1.000 0.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0000 0.93553 0.000 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.0000 0.95417 1.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.5706 0.53138 0.680 0.320 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0747 0.95442 0.984 0.016 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.0000 0.99611 0.000 0.000 1.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 1 0.0000 0.95417 1.000 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0747 0.93366 0.016 0.984 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0747 0.93366 0.016 0.984 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 2 0.0000 0.93553 0.000 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.6180 0.29263 0.584 0.416 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.0000 0.93553 0.000 1.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0747 0.95442 0.984 0.016 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.0000 0.99611 0.000 0.000 1.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.0000 0.93553 0.000 1.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.0000 0.99611 0.000 0.000 1.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0747 0.93366 0.016 0.984 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0747 0.93366 0.016 0.984 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.0000 0.95417 1.000 0.000 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0747 0.95442 0.984 0.016 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0747 0.95442 0.984 0.016 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0747 0.95442 0.984 0.016 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.99611 0.000 0.000 1.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.99611 0.000 0.000 1.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0747 0.95442 0.984 0.016 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.99611 0.000 0.000 1.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0747 0.95442 0.984 0.016 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0747 0.93366 0.016 0.984 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.95417 1.000 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 1 0.0000 0.95417 1.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0747 0.95442 0.984 0.016 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.0000 0.93553 0.000 1.000 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.93553 0.000 1.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 1 0.0000 0.95417 1.000 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.0000 0.99611 0.000 0.000 1.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.4702 0.69102 0.212 0.788 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0747 0.95442 0.984 0.016 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 2 0.0000 0.93553 0.000 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0747 0.95442 0.984 0.016 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.0747 0.95442 0.984 0.016 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 2 0.0000 0.93553 0.000 1.000 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0747 0.95029 0.984 0.000 0.016
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.6180 0.29263 0.584 0.416 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 1 0.4931 0.67526 0.768 0.232 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.99611 0.000 0.000 1.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.0000 0.95417 1.000 0.000 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.99611 0.000 0.000 1.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 1 0.0000 0.95417 1.000 0.000 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0000 0.99611 0.000 0.000 1.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.1289 0.94416 0.968 0.032 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.0747 0.95029 0.984 0.000 0.016
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.0000 0.95417 1.000 0.000 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 1 0.0000 0.95417 1.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0747 0.95029 0.984 0.000 0.016
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0747 0.93366 0.016 0.984 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0747 0.95442 0.984 0.016 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.99611 0.000 0.000 1.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 1 0.0000 0.95417 1.000 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.0000 0.99611 0.000 0.000 1.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0747 0.93366 0.016 0.984 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 1 0.0000 0.95417 1.000 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.99611 0.000 0.000 1.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0747 0.95442 0.984 0.016 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.0000 0.93553 0.000 1.000 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0237 0.95462 0.996 0.004 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0747 0.95442 0.984 0.016 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 1 0.5905 0.45038 0.648 0.000 0.352
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.0747 0.95442 0.984 0.016 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.0747 0.95442 0.984 0.016 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 1 0.0000 0.95417 1.000 0.000 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 1 0.0000 0.95417 1.000 0.000 0.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.0000 0.99611 0.000 0.000 1.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.0000 0.99611 0.000 0.000 1.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 2 0.0000 0.93553 0.000 1.000 0.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 1 0.0000 0.95417 1.000 0.000 0.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 2 0.0747 0.93366 0.016 0.984 0.000
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 1 0.2878 0.86347 0.904 0.096 0.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 1 0.0000 0.95417 1.000 0.000 0.000
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.6180 0.29263 0.584 0.416 0.000
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 1 0.0000 0.95417 1.000 0.000 0.000
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 1 0.0747 0.95029 0.984 0.000 0.016
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 2 0.0747 0.93366 0.016 0.984 0.000
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0747 0.95029 0.984 0.000 0.016
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0747 0.95442 0.984 0.016 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.0747 0.95442 0.984 0.016 0.000
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#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0747 0.95442 0.984 0.016 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.4750 0.70156 0.784 0.216 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0747 0.95442 0.984 0.016 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0747 0.95442 0.984 0.016 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.99611 0.000 0.000 1.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.99611 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.0000 0.95417 1.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0237 0.95462 0.996 0.004 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.99611 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.7370 0.09890 0.000 0.160 0.412 0.428
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1716 0.59506 0.936 0.000 0.064 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.6430 0.68152 0.068 0.504 0.428 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.6792 0.65973 0.000 0.476 0.428 0.096
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.1474 0.83038 0.000 0.000 0.052 0.948
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3074 0.56154 0.848 0.000 0.152 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4948 0.35467 0.560 0.000 0.440 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.3219 0.55451 0.836 0.000 0.164 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.6071 0.35414 0.452 0.504 0.044 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5679 0.33356 0.016 0.004 0.484 0.496
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.5165 0.31429 0.512 0.004 0.484 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.7343 0.10111 0.000 0.156 0.416 0.428
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 3 0.7393 -0.31220 0.392 0.016 0.484 0.108
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.5256 0.44306 0.700 0.040 0.260 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.0188 0.85500 0.000 0.000 0.004 0.996
#> FE853F93-5273-434D-8021-E084F9494E05 3 0.7323 -0.53852 0.164 0.352 0.484 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.6694 0.59683 0.092 0.392 0.516 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1792 0.56381 0.932 0.068 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.7146 0.63222 0.000 0.456 0.412 0.132
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1716 0.59506 0.936 0.000 0.064 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4277 0.47921 0.720 0.000 0.280 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.6319 0.67917 0.000 0.504 0.436 0.060
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.59524 1.000 0.000 0.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.6430 0.67964 0.000 0.504 0.428 0.068
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0188 0.59576 0.996 0.000 0.004 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.5279 0.44356 0.000 0.012 0.400 0.588
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.2814 0.57064 0.868 0.000 0.132 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.1474 0.59509 0.948 0.000 0.052 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0817 0.84848 0.000 0.024 0.000 0.976
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.7151 0.62660 0.000 0.448 0.420 0.132
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.7002 0.40682 0.388 0.492 0.120 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.6792 0.65973 0.000 0.476 0.428 0.096
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6319 0.67917 0.000 0.504 0.436 0.060
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.6430 0.68152 0.068 0.504 0.428 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0921 0.58677 0.972 0.028 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.59524 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.7013 0.56931 0.128 0.356 0.516 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1792 0.59425 0.932 0.000 0.068 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.1474 0.83038 0.000 0.000 0.052 0.948
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 3 0.6082 -0.65561 0.044 0.476 0.480 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.5396 -0.22307 0.524 0.464 0.012 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.4999 -0.25429 0.508 0.492 0.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.1474 0.83038 0.000 0.000 0.052 0.948
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.5000 0.26675 0.496 0.504 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.3975 0.50775 0.760 0.000 0.240 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.5931 0.34381 0.460 0.504 0.036 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.6792 0.65973 0.000 0.476 0.428 0.096
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.4916 0.41512 0.000 0.000 0.424 0.576
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.1474 0.83038 0.000 0.000 0.052 0.948
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.0707 0.84906 0.000 0.000 0.020 0.980
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.6885 0.58048 0.112 0.372 0.516 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.4713 0.09101 0.640 0.360 0.000 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0188 0.59576 0.996 0.000 0.004 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.3688 0.53018 0.792 0.000 0.208 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.2281 0.58575 0.904 0.000 0.096 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.4994 0.32069 0.520 0.000 0.480 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.1716 0.59506 0.936 0.000 0.064 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.6430 0.67964 0.000 0.504 0.428 0.068
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.1474 0.57456 0.948 0.052 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.5931 0.34381 0.460 0.504 0.036 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.1302 0.57938 0.956 0.044 0.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.0469 0.85128 0.000 0.012 0.000 0.988
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 1 0.4999 -0.25429 0.508 0.492 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 3 0.8156 -0.25316 0.048 0.132 0.484 0.336
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0188 0.59434 0.996 0.004 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.1474 0.83038 0.000 0.000 0.052 0.948
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.4989 0.31984 0.528 0.000 0.472 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.1637 0.56976 0.940 0.060 0.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.6748 0.68594 0.044 0.504 0.428 0.024
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.4941 -0.12300 0.564 0.436 0.000 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.6430 0.68152 0.068 0.504 0.428 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.5704 0.29968 0.496 0.008 0.484 0.012
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.1637 0.56976 0.940 0.060 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.4961 -0.15288 0.552 0.448 0.000 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.5604 0.31066 0.476 0.504 0.020 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0188 0.59434 0.996 0.004 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 1 0.4999 -0.25429 0.508 0.492 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> DFADB933-D083-4175-88A6-72086FD5115E 1 0.7215 -0.11764 0.500 0.348 0.152 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.1474 0.59509 0.948 0.000 0.052 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.0188 0.85500 0.000 0.000 0.004 0.996
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.1557 0.57241 0.944 0.056 0.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.1867 0.59337 0.928 0.000 0.072 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.5168 0.26906 0.492 0.504 0.004 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.5607 0.29116 0.496 0.020 0.484 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.4072 0.49656 0.748 0.000 0.252 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 1 0.4567 0.28866 0.716 0.276 0.008 0.000
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.7388 0.50382 0.304 0.504 0.192 0.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.5931 0.34381 0.460 0.504 0.036 0.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.6635 0.68477 0.048 0.504 0.432 0.016
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.5931 0.34381 0.460 0.504 0.036 0.000
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.5937 0.32244 0.472 0.492 0.036 0.000
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 1 0.4761 0.05850 0.628 0.372 0.000 0.000
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 3 0.7424 -0.30739 0.000 0.168 0.424 0.408
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0921 0.58677 0.972 0.028 0.000 0.000
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.0707 0.59638 0.980 0.000 0.020 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.1637 0.59521 0.940 0.000 0.060 0.000
#> C827E9E0-907E-412C-91ED-6C7D5D34FF6D 1 0.4992 -0.22123 0.524 0.476 0.000 0.000
#> 30314913-97C1-4EFD-98CE-BFF1C006E1BC 1 0.1716 0.59506 0.936 0.000 0.064 0.000
#> F93110D3-D250-4BBE-A9FF-35D759DB7E61 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 310CAB62-626D-418C-A256-B91A7D312DEB 1 0.5781 0.29209 0.488 0.000 0.484 0.028
#> A017FC0A-3FE9-4C46-B71A-F079EB7D18D3 4 0.4994 0.36951 0.000 0.000 0.480 0.520
#> F4BFC324-A340-4CA3-9719-EA049C7315B6 1 0.4996 0.31933 0.516 0.000 0.484 0.000
#> 5206C997-CCAE-463E-9902-C60ADA86E632 1 0.7204 0.07347 0.512 0.156 0.332 0.000
#> AC2D5D97-6FBD-4E61-A023-644F26549D04 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 41F0988E-3BF0-4733-98B3-863B7D11B521 3 0.7365 -0.31781 0.400 0.020 0.484 0.096
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#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.6792 0.65973 0.000 0.476 0.428 0.096
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.5407 0.31038 0.504 0.000 0.484 0.012
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.1389 0.57674 0.952 0.048 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1637 0.56976 0.940 0.060 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0469 0.85228 0.000 0.012 0.000 0.988
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6430 0.68152 0.068 0.504 0.428 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0921 0.58677 0.972 0.028 0.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.85582 0.000 0.000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.3486 0.54190 0.812 0.000 0.188 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.6430 0.68152 0.068 0.504 0.428 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4948 0.35467 0.560 0.000 0.440 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.6540 0.63535 0.036 0.476 0.468 0.020
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0188 0.59576 0.996 0.000 0.004 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.3688 0.53016 0.792 0.000 0.208 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.4996 0.65782 0.000 0.484 0.516 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.7307 0.40855 0.376 0.468 0.156 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.1557 0.57224 0.944 0.056 0.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.4996 0.65782 0.000 0.484 0.516 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3012 0.80033 0.124 0.852 0.000 0.024 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0162 0.87154 0.004 0.000 0.000 0.996 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4756 0.59590 0.668 0.044 0.000 0.000 0.288
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1408 0.81797 0.008 0.948 0.000 0.000 0.044
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.2329 0.80925 0.124 0.876 0.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.3336 0.77672 0.228 0.000 0.000 0.772 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0794 0.77940 0.972 0.028 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.2516 0.75937 0.000 0.860 0.000 0.000 0.140
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3058 0.70085 0.860 0.096 0.000 0.044 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.3197 0.78990 0.140 0.836 0.000 0.024 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.1907 0.75317 0.928 0.044 0.000 0.028 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.1043 0.86270 0.000 0.040 0.000 0.960 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.5894 0.43114 0.532 0.112 0.000 0.000 0.356
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.3143 0.79464 0.204 0.000 0.000 0.796 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.4978 -0.22655 0.496 0.476 0.000 0.000 0.028
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.3596 0.64578 0.000 0.016 0.200 0.000 0.784
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.1522 0.84860 0.012 0.044 0.000 0.000 0.944
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.1410 0.82800 0.060 0.940 0.000 0.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0162 0.78302 0.996 0.004 0.000 0.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4756 0.59590 0.668 0.044 0.000 0.000 0.288
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4668 0.61379 0.684 0.044 0.000 0.000 0.272
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.2723 0.81259 0.124 0.864 0.000 0.000 0.012
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.2446 0.83583 0.056 0.044 0.000 0.000 0.900
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1410 0.82800 0.060 0.940 0.000 0.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 5 0.4495 0.58662 0.244 0.044 0.000 0.000 0.712
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0162 0.78257 0.996 0.004 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.5759 0.43145 0.128 0.276 0.000 0.596 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0162 0.78302 0.996 0.004 0.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.4797 0.48426 0.296 0.044 0.000 0.000 0.660
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.1251 0.86146 0.000 0.036 0.000 0.956 0.008
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0609 0.77772 0.980 0.020 0.000 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.1671 0.82592 0.076 0.924 0.000 0.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.2278 0.79906 0.032 0.908 0.000 0.000 0.060
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.4746 -0.06741 0.000 0.016 0.480 0.000 0.504
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.2329 0.80925 0.124 0.876 0.000 0.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.2723 0.81259 0.124 0.864 0.000 0.000 0.012
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1408 0.81797 0.008 0.948 0.000 0.000 0.044
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 5 0.2304 0.83980 0.048 0.044 0.000 0.000 0.908
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.1270 0.83791 0.052 0.000 0.000 0.000 0.948
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.3098 0.71908 0.000 0.016 0.148 0.000 0.836
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.3395 0.76974 0.236 0.000 0.000 0.764 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.3531 0.80265 0.148 0.816 0.000 0.000 0.036
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4430 0.59857 0.036 0.708 0.000 0.000 0.256
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.3305 0.63511 0.000 0.224 0.000 0.000 0.776
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.3366 0.77321 0.232 0.000 0.000 0.768 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 5 0.4294 0.01826 0.000 0.468 0.000 0.000 0.532
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0162 0.78257 0.996 0.004 0.000 0.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4712 0.61684 0.684 0.048 0.000 0.000 0.268
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.2966 0.85374 0.000 0.016 0.848 0.000 0.136
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.2674 0.75605 0.004 0.856 0.000 0.000 0.140
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.2179 0.81477 0.112 0.888 0.000 0.000 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.5941 0.52464 0.332 0.124 0.000 0.544 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.3395 0.76974 0.236 0.000 0.000 0.764 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0162 0.78257 0.996 0.004 0.000 0.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.3039 0.80228 0.192 0.000 0.000 0.808 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0162 0.78302 0.996 0.004 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.1701 0.93328 0.000 0.016 0.936 0.000 0.048
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.2773 0.81730 0.164 0.000 0.000 0.836 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 5 0.4348 0.42430 0.000 0.016 0.316 0.000 0.668
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.0324 0.87195 0.004 0.004 0.000 0.992 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.1628 0.84710 0.008 0.056 0.000 0.000 0.936
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 5 0.3882 0.71660 0.168 0.044 0.000 0.000 0.788
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.4302 0.66536 0.744 0.048 0.000 0.000 0.208
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4756 0.59590 0.668 0.044 0.000 0.000 0.288
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1410 0.82800 0.060 0.940 0.000 0.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 5 0.1522 0.84860 0.012 0.044 0.000 0.000 0.944
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.2674 0.75605 0.004 0.856 0.000 0.000 0.140
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.1725 0.84799 0.020 0.044 0.000 0.000 0.936
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.0290 0.86982 0.000 0.000 0.000 0.992 0.008
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.0162 0.87154 0.004 0.000 0.000 0.996 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 5 0.4256 0.16080 0.000 0.436 0.000 0.000 0.564
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.3011 0.84933 0.000 0.016 0.844 0.000 0.140
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.4735 0.39915 0.672 0.284 0.000 0.044 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 5 0.2946 0.81108 0.088 0.044 0.000 0.000 0.868
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.3661 0.72432 0.276 0.000 0.000 0.724 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.4431 0.66796 0.732 0.052 0.000 0.000 0.216
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.0162 0.87171 0.004 0.000 0.000 0.996 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.0579 0.84474 0.008 0.008 0.000 0.000 0.984
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0404 0.78110 0.988 0.012 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.1809 0.82941 0.060 0.928 0.000 0.000 0.012
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 5 0.1502 0.84698 0.004 0.056 0.000 0.000 0.940
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.1408 0.81797 0.008 0.948 0.000 0.000 0.044
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.1893 0.75361 0.928 0.048 0.000 0.024 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.0290 0.84666 0.008 0.000 0.000 0.000 0.992
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 5 0.0510 0.84421 0.000 0.016 0.000 0.000 0.984
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.2674 0.75605 0.004 0.856 0.000 0.000 0.140
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 5 0.1121 0.83884 0.044 0.000 0.000 0.000 0.956
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.1043 0.86270 0.000 0.040 0.000 0.960 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0693 0.78279 0.980 0.008 0.000 0.000 0.012
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 5 0.3766 0.62111 0.004 0.268 0.000 0.000 0.728
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.6000 0.30319 0.132 0.540 0.000 0.000 0.328
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 5 0.4854 0.45607 0.308 0.044 0.000 0.000 0.648
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.3074 0.79990 0.196 0.000 0.000 0.804 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 5 0.1818 0.84593 0.024 0.044 0.000 0.000 0.932
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.4756 0.59590 0.668 0.044 0.000 0.000 0.288
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.4297 0.15853 0.000 0.528 0.000 0.000 0.472
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.4668 0.61336 0.684 0.044 0.000 0.000 0.272
#> DAD951A3-C22E-42F0-BB02-854413DDC351 5 0.5056 0.38346 0.044 0.360 0.000 0.000 0.596
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.1270 0.81365 0.000 0.948 0.000 0.000 0.052
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
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#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0162 0.78257 0.996 0.004 0.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.1124 0.86479 0.004 0.036 0.000 0.960 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.2376 0.83812 0.052 0.044 0.000 0.000 0.904
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.2329 0.80925 0.124 0.876 0.000 0.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.5989 0.48530 0.336 0.128 0.000 0.536 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0162 0.78302 0.996 0.004 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 5 0.2304 0.83980 0.048 0.044 0.000 0.000 0.908
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.4450 -0.00959 0.004 0.508 0.000 0.000 0.488
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.1893 0.81121 0.024 0.928 0.000 0.000 0.048
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.2813 0.74896 0.000 0.168 0.000 0.832 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 5 0.2153 0.84310 0.040 0.044 0.000 0.000 0.916
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.1942 0.82940 0.068 0.920 0.000 0.000 0.012
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.4366 0.41890 0.000 0.016 0.320 0.000 0.664
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 5 0.4366 0.41890 0.000 0.016 0.320 0.000 0.664
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.4854 0.56347 0.648 0.044 0.000 0.000 0.308
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 5 0.1484 0.84856 0.008 0.048 0.000 0.000 0.944
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0000 0.87179 0.000 0.000 0.000 1.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0000 0.87179 0.000 0.000 0.000 1.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.4367 0.28483 0.004 0.416 0.000 0.000 0.580
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.0771 0.84943 0.004 0.020 0.000 0.000 0.976
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4449 0.00416 0.004 0.512 0.000 0.000 0.484
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.2690 0.76328 0.000 0.156 0.000 0.844 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 5 0.1484 0.84856 0.008 0.048 0.000 0.000 0.944
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.1557 0.84787 0.008 0.052 0.000 0.000 0.940
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5233 0.63135 0.288 0.076 0.000 0.636 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 5 0.4268 0.20918 0.000 0.444 0.000 0.000 0.556
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.3336 0.77672 0.228 0.000 0.000 0.772 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0290 0.84666 0.008 0.000 0.000 0.000 0.992
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2376 0.83795 0.052 0.044 0.000 0.000 0.904
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.2514 0.83333 0.060 0.044 0.000 0.000 0.896
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.2149 0.76507 0.916 0.048 0.000 0.000 0.036
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.1410 0.82800 0.060 0.940 0.000 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4756 0.59590 0.668 0.044 0.000 0.000 0.288
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1809 0.82941 0.060 0.928 0.000 0.000 0.012
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.2561 0.77706 0.000 0.144 0.000 0.856 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1671 0.82592 0.076 0.924 0.000 0.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0290 0.78249 0.992 0.008 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.0798 0.84185 0.008 0.016 0.000 0.000 0.976
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.1444 0.84964 0.012 0.040 0.000 0.000 0.948
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0963 0.86409 0.000 0.036 0.000 0.964 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.1444 0.81976 0.012 0.948 0.000 0.000 0.040
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.1626 0.83275 0.044 0.016 0.000 0.000 0.940
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0290 0.87035 0.000 0.008 0.000 0.992 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4735 0.60111 0.672 0.044 0.000 0.000 0.284
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2426 0.82891 0.064 0.900 0.000 0.000 0.036
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0162 0.78302 0.996 0.004 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.3123 0.79001 0.160 0.828 0.000 0.000 0.012
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.2376 0.83795 0.052 0.044 0.000 0.000 0.904
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.4713 0.60537 0.676 0.044 0.000 0.000 0.280
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0510 0.96223 0.000 0.016 0.984 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4111 0.72655 0.092 0.788 0.000 0.000 0.120
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.1522 0.84860 0.012 0.044 0.000 0.000 0.944
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.96490 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4403 -0.05187 0.008 0.520 0.000 0.012 0.000 0.460
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.1285 0.77121 0.000 0.052 0.000 0.944 0.000 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1714 0.65733 0.908 0.000 0.000 0.000 0.092 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.0881 0.61959 0.008 0.012 0.000 0.000 0.008 0.972
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 6 0.4225 0.13610 0.008 0.480 0.000 0.004 0.000 0.508
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4915 0.57733 0.072 0.320 0.000 0.604 0.000 0.004
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1918 0.66212 0.904 0.008 0.000 0.000 0.088 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1327 0.63275 0.936 0.064 0.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1663 0.65983 0.912 0.000 0.000 0.000 0.088 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.1503 0.62281 0.016 0.008 0.000 0.000 0.032 0.944
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.3983 0.46156 0.208 0.736 0.000 0.056 0.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.3351 0.44812 0.712 0.288 0.000 0.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.4296 0.00529 0.008 0.544 0.000 0.008 0.000 0.440
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.3925 0.28860 0.332 0.656 0.000 0.008 0.004 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.2531 0.72468 0.000 0.132 0.000 0.856 0.000 0.012
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.2121 0.74719 0.000 0.096 0.000 0.892 0.000 0.012
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.6649 0.16889 0.528 0.104 0.000 0.000 0.156 0.212
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.4782 0.57384 0.056 0.340 0.000 0.600 0.000 0.004
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.5562 0.25142 0.132 0.520 0.000 0.000 0.004 0.344
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.3030 0.59173 0.000 0.056 0.092 0.000 0.848 0.004
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.5611 0.54114 0.232 0.000 0.000 0.000 0.544 0.224
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.3820 0.38612 0.004 0.332 0.000 0.004 0.000 0.660
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.2631 0.54138 0.820 0.180 0.000 0.000 0.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1714 0.65733 0.908 0.000 0.000 0.000 0.092 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1913 0.66511 0.908 0.012 0.000 0.000 0.080 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.4214 0.18166 0.008 0.460 0.000 0.000 0.004 0.528
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4844 -0.17589 0.504 0.000 0.000 0.000 0.440 0.056
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.3489 0.43035 0.004 0.288 0.000 0.000 0.000 0.708
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4809 0.28789 0.652 0.000 0.000 0.000 0.240 0.108
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3890 0.27584 0.596 0.400 0.000 0.000 0.000 0.004
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5476 0.29008 0.008 0.580 0.000 0.276 0.000 0.136
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.2594 0.90532 0.000 0.056 0.880 0.000 0.060 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.2527 0.55395 0.832 0.168 0.000 0.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.1663 0.65983 0.912 0.000 0.000 0.000 0.088 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3373 0.44479 0.744 0.000 0.000 0.000 0.248 0.008
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.2515 0.74532 0.008 0.104 0.000 0.876 0.004 0.008
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3869 0.05377 0.500 0.500 0.000 0.000 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.1970 0.75076 0.000 0.092 0.000 0.900 0.000 0.008
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.4098 0.25599 0.004 0.444 0.000 0.004 0.000 0.548
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3198 0.46701 0.740 0.260 0.000 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 6 0.3757 0.61558 0.024 0.120 0.000 0.000 0.052 0.804
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.3878 0.48342 0.000 0.056 0.176 0.000 0.764 0.004
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.4227 -0.10955 0.008 0.500 0.000 0.004 0.000 0.488
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.4211 0.18986 0.008 0.456 0.000 0.000 0.004 0.532
#> 36B2E208-FF01-4249-92C3-BE77D426691B 6 0.2884 0.58915 0.008 0.164 0.000 0.000 0.004 0.824
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 5 0.5336 0.55732 0.256 0.000 0.000 0.000 0.584 0.160
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.3405 0.52352 0.272 0.000 0.000 0.000 0.724 0.004
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.2767 0.61414 0.000 0.056 0.072 0.000 0.868 0.004
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1663 0.65983 0.912 0.000 0.000 0.000 0.088 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.5060 0.55140 0.080 0.336 0.000 0.580 0.000 0.004
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 6 0.4315 0.09771 0.012 0.488 0.000 0.000 0.004 0.496
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 6 0.6771 0.34560 0.216 0.104 0.000 0.000 0.172 0.508
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.4116 0.35639 0.012 0.000 0.000 0.000 0.572 0.416
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.4962 0.57328 0.076 0.320 0.000 0.600 0.000 0.004
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 6 0.3828 0.10833 0.000 0.000 0.000 0.000 0.440 0.560
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3797 0.24186 0.580 0.420 0.000 0.000 0.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.1610 0.66132 0.916 0.000 0.000 0.000 0.084 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 5 0.4829 0.08259 0.000 0.056 0.356 0.000 0.584 0.004
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 6 0.1777 0.61730 0.024 0.004 0.000 0.000 0.044 0.928
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.4227 -0.12894 0.008 0.500 0.000 0.004 0.000 0.488
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.2894 0.49045 0.004 0.852 0.000 0.108 0.000 0.036
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.5021 0.56406 0.080 0.324 0.000 0.592 0.000 0.004
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3937 0.23444 0.572 0.424 0.000 0.000 0.000 0.004
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4713 0.59091 0.056 0.320 0.000 0.620 0.000 0.004
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.3050 0.49004 0.764 0.236 0.000 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4870 0.47127 0.000 0.056 0.568 0.000 0.372 0.004
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4602 0.59690 0.048 0.320 0.000 0.628 0.000 0.004
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 5 0.3127 0.57347 0.000 0.056 0.100 0.000 0.840 0.004
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.2450 0.75656 0.000 0.116 0.000 0.868 0.000 0.016
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.1908 0.77043 0.000 0.096 0.000 0.900 0.000 0.004
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.5946 0.42304 0.208 0.004 0.000 0.000 0.476 0.312
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4874 0.25790 0.640 0.000 0.000 0.000 0.252 0.108
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.2019 0.66306 0.900 0.012 0.000 0.000 0.088 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.1858 0.65462 0.904 0.000 0.000 0.000 0.092 0.004
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.2471 0.90917 0.000 0.052 0.888 0.000 0.056 0.004
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#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 5 0.4161 0.38864 0.008 0.008 0.000 0.000 0.612 0.372
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.3900 0.40684 0.008 0.760 0.000 0.044 0.000 0.188
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#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.3367 0.67016 0.104 0.000 0.000 0.000 0.816 0.080
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3791 0.60245 0.000 0.236 0.000 0.732 0.000 0.032
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.3351 0.42246 0.000 0.288 0.000 0.000 0.000 0.712
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
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#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 6 0.4224 0.14894 0.008 0.476 0.000 0.004 0.000 0.512
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.4688 0.15768 0.060 0.636 0.000 0.300 0.000 0.004
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#> DDC71530-38B7-483F-83DC-1BCC550719C3 5 0.4711 0.56373 0.280 0.000 0.000 0.000 0.640 0.080
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.5529 0.40843 0.120 0.040 0.000 0.000 0.200 0.640
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#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.3878 0.41039 0.004 0.348 0.000 0.000 0.004 0.644
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#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.4002 0.61908 0.000 0.188 0.000 0.744 0.000 0.068
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 5 0.6031 0.46885 0.268 0.004 0.000 0.000 0.468 0.260
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.5908 0.42890 0.200 0.004 0.000 0.000 0.484 0.312
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2594 0.90548 0.000 0.056 0.880 0.000 0.060 0.004
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.4794 0.07691 0.060 0.608 0.000 0.328 0.000 0.004
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 6 0.4093 0.08574 0.012 0.000 0.000 0.000 0.404 0.584
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.4915 0.57733 0.072 0.320 0.000 0.604 0.000 0.004
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.0622 0.68495 0.008 0.000 0.000 0.000 0.980 0.012
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.4856 -0.25451 0.472 0.000 0.000 0.000 0.472 0.056
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.5267 0.03757 0.560 0.000 0.000 0.000 0.320 0.120
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0790 0.64764 0.968 0.032 0.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.3043 0.49395 0.008 0.200 0.000 0.000 0.000 0.792
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1663 0.65983 0.912 0.000 0.000 0.000 0.088 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3782 0.25725 0.588 0.412 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.3805 0.43785 0.004 0.328 0.000 0.000 0.004 0.664
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.3861 0.63361 0.000 0.184 0.000 0.756 0.000 0.060
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.3782 0.25859 0.588 0.412 0.000 0.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.4082 0.28015 0.004 0.432 0.000 0.004 0.000 0.560
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3607 0.35189 0.652 0.348 0.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.0405 0.68428 0.004 0.000 0.000 0.000 0.988 0.008
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.3943 0.64856 0.156 0.000 0.000 0.000 0.760 0.084
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.2357 0.73871 0.000 0.116 0.000 0.872 0.000 0.012
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.2734 0.59642 0.008 0.148 0.000 0.000 0.004 0.840
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.1411 0.67933 0.060 0.000 0.000 0.000 0.936 0.004
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.1644 0.75779 0.000 0.076 0.000 0.920 0.000 0.004
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.2019 0.66306 0.900 0.012 0.000 0.000 0.088 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.3789 0.44160 0.004 0.324 0.000 0.000 0.004 0.668
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.2300 0.57258 0.856 0.144 0.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.4461 -0.04202 0.020 0.512 0.000 0.000 0.004 0.464
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.4534 0.25023 0.472 0.000 0.000 0.000 0.496 0.032
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1967 0.66428 0.904 0.012 0.000 0.000 0.084 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2532 0.90745 0.000 0.052 0.884 0.000 0.060 0.004
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.94406 0.000 0.000 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 6 0.6622 0.42225 0.220 0.124 0.000 0.000 0.124 0.532
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.5253 0.57449 0.228 0.000 0.000 0.000 0.604 0.168
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.94406 0.000 0.000 1.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.962 0.985 0.4997 0.501 0.501
#> 3 3 0.845 0.832 0.932 0.2942 0.794 0.610
#> 4 4 0.876 0.878 0.949 0.1120 0.831 0.576
#> 5 5 0.836 0.836 0.923 0.0825 0.859 0.560
#> 6 6 0.779 0.678 0.826 0.0344 0.955 0.803
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.98532 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.98319 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.98532 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.98319 1.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.98532 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.98532 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.98532 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1184 0.96863 0.984 0.016
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.0000 0.98532 0.000 1.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0376 0.97963 0.996 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.9460 0.43075 0.636 0.364
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.98532 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.0000 0.98532 0.000 1.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.98532 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.98532 0.000 1.000
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#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.98532 0.000 1.000
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#> 8BEFCFB5-B379-430F-8B94-5E4E6C50B706 2 0.0000 0.98532 0.000 1.000
#> 7C920F29-C20E-464D-90DC-3B953B96F663 2 0.0000 0.98532 0.000 1.000
#> 23077FD7-F6AE-4336-A1CD-30A0E34F24C2 2 0.0000 0.98532 0.000 1.000
#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 1 0.0000 0.98319 1.000 0.000
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.0000 0.98532 0.000 1.000
#> 4C838D35-B667-46DA-836F-068453D254DA 2 0.0000 0.98532 0.000 1.000
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 1 0.0000 0.98319 1.000 0.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0000 0.98532 0.000 1.000
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 1 0.9661 0.35882 0.608 0.392
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.0000 0.98319 1.000 0.000
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 2 0.8144 0.66401 0.252 0.748
#> 976924B0-5799-4AC9-804F-78C8568037CA 1 0.0000 0.98319 1.000 0.000
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.0000 0.98319 1.000 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 2 0.0000 0.98532 0.000 1.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 2 0.7950 0.68397 0.240 0.760
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.0000 0.98319 1.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 1 0.0000 0.98319 1.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0000 0.98532 0.000 1.000
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0000 0.98532 0.000 1.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.0000 0.98532 0.000 1.000
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 2 0.0000 0.98532 0.000 1.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.0000 0.98319 1.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 2 0.0000 0.98532 0.000 1.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 2 0.0000 0.98532 0.000 1.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 1 0.0000 0.98319 1.000 0.000
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.0000 0.98532 0.000 1.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 2 0.0000 0.98532 0.000 1.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 2 0.0000 0.98532 0.000 1.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.0000 0.98319 1.000 0.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 1 0.0000 0.98319 1.000 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0000 0.98532 0.000 1.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 1 0.0000 0.98319 1.000 0.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.98532 0.000 1.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 1 0.0000 0.98319 1.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.0000 0.98319 1.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 2 0.0000 0.98532 0.000 1.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 1 0.0000 0.98319 1.000 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 2 0.0000 0.98532 0.000 1.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 1 0.0000 0.98319 1.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.98532 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.98532 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.0000 0.98532 0.000 1.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.0000 0.98532 0.000 1.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.0000 0.98319 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.98532 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 2 0.0000 0.98532 0.000 1.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.0000 0.98319 1.000 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.0000 0.98319 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.98532 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 2 0.0000 0.98532 0.000 1.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 2 0.0000 0.98532 0.000 1.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.0000 0.98532 0.000 1.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.98319 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.98532 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 1 0.0000 0.98319 1.000 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 2 0.3431 0.92208 0.064 0.936
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.98319 1.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.0000 0.98319 1.000 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.98532 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 1 0.0000 0.98319 1.000 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.0000 0.98319 1.000 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.0000 0.98319 1.000 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.98532 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.98532 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 1 0.0000 0.98319 1.000 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.0000 0.98319 1.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.0000 0.98532 0.000 1.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.0000 0.98319 1.000 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.0000 0.98319 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0000 0.98532 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.0000 0.98532 0.000 1.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 1 0.0000 0.98319 1.000 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.0000 0.98532 0.000 1.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.1184 0.97050 0.016 0.984
#> 93E69515-4C47-4E68-8842-818DE0E369E2 2 0.0000 0.98532 0.000 1.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.0000 0.98319 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.98532 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.98532 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.0000 0.98319 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 1 0.0000 0.98319 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.0000 0.98319 1.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.0000 0.98319 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.98532 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.98532 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.98319 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.98532 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.0000 0.98319 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.0000 0.98532 0.000 1.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.98532 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0000 0.98319 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.98532 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.98532 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 2 0.0000 0.98532 0.000 1.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.0000 0.98319 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 1 0.0000 0.98319 1.000 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.98532 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.98532 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.0000 0.98319 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.98532 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.98532 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.98319 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.98319 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.98319 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.0000 0.98319 1.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.98532 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.98532 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.0000 0.98319 1.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.0000 0.98319 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 1 0.0000 0.98319 1.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.98532 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.98319 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 1 0.0000 0.98319 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.0000 0.98319 1.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.0000 0.98319 1.000 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.98319 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0000 0.98532 0.000 1.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 1 0.0000 0.98319 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0000 0.98532 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.98319 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.98319 1.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.98319 1.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.5842 0.83236 0.140 0.860
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.98532 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.98319 1.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.0000 0.98532 0.000 1.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.98532 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.98532 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.0000 0.98532 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.98532 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.0000 0.98532 0.000 1.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.98319 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.98319 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.98319 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.98532 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.98532 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.98319 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.98532 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4562 0.88481 0.904 0.096
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.98319 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.98532 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.5178 0.86256 0.116 0.884
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.98532 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.98319 1.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 1.0000 0.00657 0.504 0.496
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.98319 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.98319 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.8327 0.63970 0.264 0.736
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0000 0.98319 1.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.98319 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.913 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.961 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0237 0.912 0.004 0.996 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0424 0.855 0.992 0.000 0.008
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0237 0.912 0.004 0.996 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.913 0.000 1.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.6111 0.455 0.604 0.396 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0237 0.858 0.996 0.000 0.004
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0237 0.859 0.996 0.004 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0237 0.858 0.996 0.000 0.004
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.6421 0.159 0.004 0.572 0.424
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.3686 0.765 0.140 0.860 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.6111 0.455 0.604 0.396 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.913 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.6168 0.198 0.412 0.588 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.961 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.913 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.961 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.913 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.8802 0.550 0.584 0.200 0.216
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.1163 0.896 0.028 0.972 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.913 0.000 1.000 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.961 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.961 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.0000 0.961 0.000 0.000 1.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0237 0.912 0.004 0.996 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0237 0.859 0.996 0.004 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0237 0.858 0.996 0.000 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0237 0.859 0.996 0.004 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.913 0.000 1.000 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.0000 0.961 0.000 0.000 1.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0237 0.912 0.004 0.996 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.3816 0.794 0.148 0.000 0.852
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#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.913 0.000 1.000 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.913 0.000 1.000 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.0892 0.903 0.020 0.980 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.6168 0.198 0.412 0.588 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0000 0.961 0.000 0.000 1.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.913 0.000 1.000 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.6111 0.455 0.604 0.396 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0000 0.961 0.000 0.000 1.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0000 0.961 0.000 0.000 1.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.913 0.000 1.000 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.0237 0.859 0.996 0.004 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0237 0.859 0.996 0.004 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0237 0.859 0.996 0.004 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0000 0.961 0.000 0.000 1.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0237 0.912 0.004 0.996 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 3 0.0000 0.961 0.000 0.000 1.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0237 0.859 0.996 0.004 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0237 0.858 0.996 0.000 0.004
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.0000 0.961 0.000 0.000 1.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0237 0.912 0.004 0.996 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.0000 0.961 0.000 0.000 1.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.0000 0.961 0.000 0.000 1.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0000 0.961 0.000 0.000 1.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.913 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.913 0.000 1.000 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 3 0.0000 0.961 0.000 0.000 1.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.961 0.000 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.6168 0.198 0.412 0.588 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.0000 0.961 0.000 0.000 1.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0000 0.961 0.000 0.000 1.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0237 0.912 0.004 0.996 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.6168 0.198 0.412 0.588 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.0000 0.961 0.000 0.000 1.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.6111 0.455 0.604 0.396 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.1585 0.891 0.028 0.964 0.008
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0237 0.859 0.996 0.004 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.0000 0.961 0.000 0.000 1.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0237 0.912 0.004 0.996 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.913 0.000 1.000 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.961 0.000 0.000 1.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.961 0.000 0.000 1.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.0000 0.961 0.000 0.000 1.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.961 0.000 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.913 0.000 1.000 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0237 0.912 0.004 0.996 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.961 0.000 0.000 1.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0237 0.912 0.004 0.996 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.961 0.000 0.000 1.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0237 0.859 0.996 0.004 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.913 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0000 0.961 0.000 0.000 1.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.913 0.000 1.000 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0892 0.903 0.020 0.980 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0237 0.859 0.996 0.004 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 3 0.0000 0.961 0.000 0.000 1.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 3 0.0000 0.961 0.000 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0237 0.912 0.004 0.996 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.913 0.000 1.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 3 0.0000 0.961 0.000 0.000 1.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0237 0.912 0.004 0.996 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.913 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0000 0.961 0.000 0.000 1.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.0000 0.961 0.000 0.000 1.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0424 0.855 0.992 0.000 0.008
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.0000 0.961 0.000 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0237 0.912 0.004 0.996 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0892 0.903 0.020 0.980 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.0000 0.961 0.000 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.0000 0.961 0.000 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 3 0.0000 0.961 0.000 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.913 0.000 1.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.961 0.000 0.000 1.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.961 0.000 0.000 1.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.0000 0.961 0.000 0.000 1.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0000 0.961 0.000 0.000 1.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.961 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0892 0.903 0.020 0.980 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 3 0.0000 0.961 0.000 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.6111 0.455 0.604 0.396 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.961 0.000 0.000 1.000
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.0000 0.961 0.000 0.000 1.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.0000 0.961 0.000 0.000 1.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0237 0.859 0.996 0.004 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0237 0.912 0.004 0.996 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0424 0.855 0.992 0.000 0.008
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.1529 0.841 0.960 0.040 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0237 0.912 0.004 0.996 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.913 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0237 0.859 0.996 0.004 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0237 0.912 0.004 0.996 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0237 0.859 0.996 0.004 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.961 0.000 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.0000 0.961 0.000 0.000 1.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.0000 0.961 0.000 0.000 1.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.913 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0237 0.912 0.004 0.996 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.961 0.000 0.000 1.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.913 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0237 0.859 0.996 0.004 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.961 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0237 0.912 0.004 0.996 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0237 0.859 0.996 0.004 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.913 0.000 1.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.0000 0.961 0.000 0.000 1.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0237 0.858 0.996 0.000 0.004
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.961 0.000 0.000 1.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.961 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.2229 0.859 0.012 0.944 0.044
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.961 0.000 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.961 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.3528 0.7641 0.000 0.192 0.000 0.808
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.4996 0.1369 0.000 0.484 0.000 0.516
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 4 0.1474 0.9021 0.052 0.000 0.000 0.948
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.3486 0.7690 0.000 0.188 0.000 0.812
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.3528 0.7641 0.000 0.192 0.000 0.808
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4745 0.7338 0.756 0.036 0.000 0.208
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.2921 0.8089 0.860 0.000 0.000 0.140
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4843 0.3951 0.000 0.396 0.000 0.604
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 3 0.4477 0.5593 0.312 0.000 0.688 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 3 0.4989 0.1436 0.472 0.000 0.528 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.3311 0.7362 0.000 0.828 0.000 0.172
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4040 0.7102 0.752 0.000 0.000 0.248
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.3528 0.7641 0.000 0.192 0.000 0.808
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3688 0.7432 0.000 0.208 0.000 0.792
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 3 0.4382 0.5893 0.296 0.000 0.704 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0469 0.9155 0.000 0.988 0.012 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.0000 0.9493 0.000 0.000 0.000 1.000
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#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.3569 0.7590 0.000 0.196 0.000 0.804
#> F79C78B6-421E-4634-A403-4EC822299308 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.3528 0.7704 0.808 0.000 0.000 0.192
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.3486 0.7738 0.812 0.000 0.000 0.188
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.4134 0.6931 0.740 0.000 0.000 0.260
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.4830 0.3941 0.000 0.608 0.392 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 3 0.2345 0.8555 0.000 0.100 0.900 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.4881 0.6710 0.048 0.756 0.000 0.196
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.3610 0.7629 0.800 0.000 0.000 0.200
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.3486 0.7690 0.000 0.188 0.000 0.812
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.3528 0.7704 0.808 0.000 0.000 0.192
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.4855 0.3854 0.000 0.400 0.000 0.600
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.4804 0.4136 0.000 0.616 0.384 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.4977 0.2158 0.000 0.460 0.000 0.540
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0707 0.9090 0.000 0.980 0.000 0.020
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 3 0.0469 0.9473 0.000 0.012 0.988 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.4855 0.3740 0.000 0.600 0.400 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.4866 0.3752 0.000 0.404 0.000 0.596
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 3 0.2011 0.8793 0.000 0.080 0.920 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 3 0.4382 0.5893 0.296 0.000 0.704 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 3 0.4713 0.4579 0.360 0.000 0.640 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3942 0.7252 0.764 0.000 0.000 0.236
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.4855 0.3854 0.000 0.400 0.000 0.600
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.4981 0.2288 0.536 0.000 0.000 0.464
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0469 0.9151 0.000 0.988 0.000 0.012
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0000 0.9493 0.000 0.000 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 3 0.4866 0.3495 0.404 0.000 0.596 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.8991 1.000 0.000 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9237 0.000 1.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.9578 0.000 0.000 1.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.9578 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3143 0.787109 0.204 0.000 0.000 0.796 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 5 0.2280 0.793549 0.120 0.000 0.000 0.000 0.880
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.2929 0.689801 0.820 0.000 0.000 0.180 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.884116 1.000 0.000 0.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.5216 0.608167 0.092 0.008 0.000 0.208 0.692
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.3876 0.675046 0.316 0.000 0.000 0.684 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.0162 0.876477 0.004 0.000 0.000 0.996 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 4 0.2648 0.736754 0.000 0.152 0.000 0.848 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.3424 0.681644 0.760 0.000 0.000 0.000 0.240
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.2605 0.786060 0.000 0.000 0.148 0.000 0.852
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 4 0.4210 0.201316 0.000 0.412 0.000 0.588 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 5 0.3242 0.721551 0.000 0.000 0.216 0.000 0.784
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3586 0.647154 0.736 0.000 0.000 0.000 0.264
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.4030 0.403997 0.352 0.000 0.000 0.000 0.648
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2690 0.777091 0.844 0.000 0.000 0.000 0.156
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.4030 0.524271 0.000 0.000 0.352 0.000 0.648
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#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> 976924B0-5799-4AC9-804F-78C8568037CA 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 2343975A-0AB3-448E-A633-4B433B1DF960 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 5 0.0404 0.888573 0.012 0.000 0.000 0.000 0.988
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> F3285881-878E-4190-BB96-9A2303C76346 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 4 0.0162 0.876477 0.004 0.000 0.000 0.996 0.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 4 0.3508 0.748302 0.252 0.000 0.000 0.748 0.000
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 5 0.4227 0.181498 0.420 0.000 0.000 0.000 0.580
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 1 0.0000 0.884116 1.000 0.000 0.000 0.000 0.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 1 0.3636 0.508279 0.728 0.000 0.000 0.272 0.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.4304 0.120566 0.000 0.516 0.484 0.000 0.000
#> 93429F04-8404-4E8C-B654-9D2216BA432C 1 0.4235 0.023022 0.576 0.000 0.000 0.424 0.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 1 0.4242 0.338228 0.572 0.000 0.000 0.000 0.428
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 5 0.3305 0.712959 0.000 0.000 0.224 0.000 0.776
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 3 0.3561 0.621837 0.000 0.260 0.740 0.000 0.000
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.3074 0.737164 0.804 0.000 0.000 0.000 0.196
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.0000 0.877424 0.000 1.000 0.000 0.000 0.000
#> 1501020D-0CDC-48B4-8756-33099804FEC6 4 0.0290 0.875711 0.008 0.000 0.000 0.992 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.0880 0.869816 0.968 0.000 0.000 0.032 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 3 0.1732 0.890003 0.000 0.000 0.920 0.000 0.080
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 4 0.0162 0.876477 0.004 0.000 0.000 0.996 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.1965 0.827274 0.904 0.000 0.000 0.000 0.096
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.3074 0.737164 0.804 0.000 0.000 0.000 0.196
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0000 0.884116 1.000 0.000 0.000 0.000 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 4 0.3143 0.787109 0.204 0.000 0.000 0.796 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 3 0.3561 0.621814 0.000 0.260 0.740 0.000 0.000
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 5 0.0703 0.882295 0.024 0.000 0.000 0.000 0.976
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 4 0.3395 0.762381 0.236 0.000 0.000 0.764 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.3143 0.713041 0.000 0.796 0.204 0.000 0.000
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.0609 0.877771 0.980 0.000 0.000 0.020 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 4 0.0609 0.872018 0.020 0.000 0.000 0.980 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.0703 0.875372 0.976 0.000 0.000 0.024 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.3395 0.680651 0.000 0.764 0.236 0.000 0.000
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.3430 0.727655 0.012 0.152 0.000 0.824 0.012
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.2377 0.801954 0.872 0.000 0.000 0.000 0.128
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 3 0.3336 0.682332 0.000 0.000 0.772 0.000 0.228
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0162 0.875854 0.000 0.996 0.000 0.004 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0510 0.868899 0.000 0.984 0.000 0.016 0.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.3074 0.792360 0.196 0.000 0.000 0.804 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.1851 0.832905 0.912 0.000 0.000 0.000 0.088
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 3 0.3796 0.550916 0.000 0.000 0.700 0.000 0.300
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.3774 0.703532 0.296 0.000 0.000 0.704 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.3774 0.595523 0.704 0.000 0.000 0.000 0.296
#> DDC71530-38B7-483F-83DC-1BCC550719C3 3 0.0162 0.967134 0.000 0.000 0.996 0.000 0.004
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.3210 0.705583 0.000 0.788 0.212 0.000 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.4307 -0.057825 0.000 0.496 0.000 0.504 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.2605 0.741530 0.000 0.148 0.000 0.852 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.0000 0.892215 0.000 0.000 0.000 0.000 1.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.3143 0.787109 0.204 0.000 0.000 0.796 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3774 0.703532 0.296 0.000 0.000 0.704 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.4114 0.443451 0.000 0.624 0.376 0.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.3210 0.705583 0.000 0.788 0.212 0.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.3774 0.703532 0.296 0.000 0.000 0.704 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.4126 0.433828 0.000 0.620 0.380 0.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0162 0.885016 0.996 0.000 0.000 0.004 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.3586 0.665450 0.000 0.000 0.264 0.000 0.736
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.4030 0.526864 0.000 0.000 0.352 0.000 0.648
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0162 0.875854 0.000 0.996 0.000 0.004 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.884116 1.000 0.000 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.3895 0.542826 0.000 0.680 0.000 0.320 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.884116 1.000 0.000 0.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.0510 0.867970 0.000 0.016 0.000 0.984 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3707 0.615169 0.716 0.000 0.000 0.000 0.284
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.3730 0.596916 0.000 0.712 0.000 0.288 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.0162 0.874925 0.000 0.004 0.000 0.996 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.1732 0.839829 0.080 0.000 0.000 0.000 0.920
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.0000 0.877128 0.000 0.000 0.000 1.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3177 0.729585 0.000 0.000 0.208 0.000 0.792
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.0162 0.891968 0.004 0.000 0.000 0.000 0.996
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0162 0.875533 0.000 0.996 0.000 0.000 0.004
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.970534 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 4 0.1556 0.67516 0.000 0.080 0.000 0.920 0.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3101 0.72591 0.244 0.000 0.000 0.756 0.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.0260 0.77375 0.000 0.008 0.000 0.000 0.992 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.3684 0.26662 0.000 0.372 0.000 0.000 0.000 0.628
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.3899 -0.13739 0.000 0.404 0.000 0.592 0.000 0.004
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0865 0.74866 0.964 0.000 0.000 0.036 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.2494 0.76870 0.016 0.120 0.000 0.000 0.864 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 5 0.6043 0.24486 0.320 0.268 0.000 0.000 0.412 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.0000 0.77299 0.000 0.000 0.000 0.000 1.000 0.000
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#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.4500 0.59599 0.000 0.688 0.000 0.224 0.000 0.088
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.3309 0.30002 0.000 0.280 0.000 0.720 0.000 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.4218 0.58271 0.000 0.556 0.000 0.428 0.000 0.016
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0632 0.72559 0.000 0.024 0.000 0.976 0.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.0000 0.77299 0.000 0.000 0.000 0.000 1.000 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.2378 0.81534 0.000 0.152 0.848 0.000 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.3076 0.72818 0.240 0.000 0.000 0.760 0.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3266 0.70326 0.272 0.000 0.000 0.728 0.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 6 0.2402 0.67124 0.000 0.004 0.140 0.000 0.000 0.856
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.2868 0.69912 0.000 0.132 0.028 0.000 0.000 0.840
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.2178 0.61142 0.000 0.132 0.000 0.868 0.000 0.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 3 0.2595 0.80207 0.000 0.160 0.836 0.000 0.000 0.004
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 3 0.2581 0.82749 0.000 0.120 0.860 0.000 0.000 0.020
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.3244 0.70783 0.268 0.000 0.000 0.732 0.000 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 6 0.2092 0.68455 0.000 0.000 0.124 0.000 0.000 0.876
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0865 0.74866 0.964 0.000 0.000 0.036 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2631 0.67746 0.000 0.000 0.180 0.000 0.820 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.5956 0.42826 0.000 0.224 0.356 0.000 0.420 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.2831 0.76368 0.024 0.136 0.000 0.000 0.840 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.3592 0.48117 0.000 0.240 0.000 0.020 0.000 0.740
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.4151 0.70495 0.040 0.276 0.000 0.000 0.684 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.2945 0.72617 0.824 0.156 0.000 0.020 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.5112 0.63785 0.000 0.592 0.000 0.296 0.000 0.112
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.2378 0.58126 0.000 0.152 0.000 0.848 0.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.2664 0.70630 0.816 0.184 0.000 0.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.4067 0.55896 0.000 0.548 0.000 0.444 0.000 0.008
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3848 0.64900 0.736 0.224 0.000 0.000 0.040 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.0632 0.72559 0.000 0.024 0.000 0.976 0.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.4746 0.61068 0.000 0.668 0.000 0.216 0.000 0.116
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.1556 0.74937 0.080 0.000 0.000 0.920 0.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 5 0.4151 0.70495 0.040 0.276 0.000 0.000 0.684 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 4 0.4709 -0.33189 0.000 0.412 0.000 0.540 0.000 0.048
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.4094 0.70169 0.180 0.080 0.000 0.000 0.740 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.3706 -0.01061 0.000 0.380 0.000 0.620 0.000 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3259 0.66056 0.000 0.012 0.216 0.000 0.772 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.4151 0.70495 0.040 0.276 0.000 0.000 0.684 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.3528 0.31981 0.000 0.700 0.000 0.004 0.000 0.296
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 3 0.0000 0.94975 0.000 0.000 1.000 0.000 0.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.94975 0.000 0.000 1.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.731 0.901 0.953 0.4055 0.582 0.582
#> 3 3 0.805 0.902 0.954 0.4339 0.579 0.410
#> 4 4 0.595 0.562 0.802 0.1858 0.781 0.523
#> 5 5 0.640 0.629 0.782 0.1037 0.781 0.407
#> 6 6 0.677 0.610 0.806 0.0504 0.862 0.528
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.965 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.902 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.965 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.7883 0.680 0.236 0.764
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0376 0.965 0.004 0.996
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.965 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.965 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.0376 0.965 0.004 0.996
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.0376 0.965 0.004 0.996
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.0376 0.965 0.004 0.996
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0376 0.965 0.004 0.996
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.965 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.0376 0.965 0.004 0.996
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.965 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0376 0.965 0.004 0.996
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.0000 0.902 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.965 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.0000 0.902 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.965 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0376 0.965 0.004 0.996
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.965 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0376 0.965 0.004 0.996
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.902 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.902 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.8144 0.653 0.252 0.748
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.965 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0376 0.965 0.004 0.996
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.3274 0.913 0.060 0.940
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 2 0.0376 0.965 0.004 0.996
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.965 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.8555 0.700 0.720 0.280
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.965 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.8144 0.653 0.252 0.748
#> 72BCF7F5-3826-4289-B0C7-505678481099 2 0.0376 0.965 0.004 0.996
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.965 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.902 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.902 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.0376 0.965 0.004 0.996
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 2 0.0376 0.965 0.004 0.996
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.8499 0.706 0.724 0.276
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.965 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.0376 0.965 0.004 0.996
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.965 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.965 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.0376 0.965 0.004 0.996
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0376 0.965 0.004 0.996
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.902 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.965 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.965 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0376 0.965 0.004 0.996
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 1 0.0000 0.902 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.8144 0.653 0.252 0.748
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.7453 0.765 0.788 0.212
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.902 1.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 0.0376 0.965 0.004 0.996
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0000 0.965 0.000 1.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.0376 0.965 0.004 0.996
#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.0000 0.902 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4298 0.882 0.088 0.912
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.8499 0.706 0.724 0.276
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0000 0.965 0.000 1.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.0000 0.902 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 2 0.0376 0.965 0.004 0.996
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.0376 0.965 0.004 0.996
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 1 0.0000 0.902 1.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0376 0.965 0.004 0.996
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.965 0.000 1.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.965 0.000 1.000
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#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.965 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.965 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.902 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.0000 0.902 1.000 0.000
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.8144 0.653 0.252 0.748
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.9866 0.354 0.568 0.432
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.965 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.965 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0376 0.965 0.004 0.996
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.8499 0.706 0.724 0.276
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 1 0.8499 0.706 0.724 0.276
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.965 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.902 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 1 0.0000 0.902 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.8144 0.653 0.252 0.748
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.7883 0.680 0.236 0.764
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.902 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0000 0.965 0.000 1.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 1 0.8499 0.706 0.724 0.276
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0000 0.965 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.0000 0.902 1.000 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.9795 0.400 0.584 0.416
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.8327 0.630 0.264 0.736
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.0376 0.965 0.004 0.996
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0376 0.965 0.004 0.996
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.7950 0.673 0.240 0.760
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.0376 0.965 0.004 0.996
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.965 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.965 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.0376 0.965 0.004 0.996
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.965 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.0376 0.965 0.004 0.996
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.902 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.902 1.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.8499 0.706 0.724 0.276
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.965 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0376 0.965 0.004 0.996
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.902 1.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.965 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.0376 0.965 0.004 0.996
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.902 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0376 0.965 0.004 0.996
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.0376 0.965 0.004 0.996
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0376 0.965 0.004 0.996
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.8499 0.706 0.724 0.276
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.0376 0.965 0.004 0.996
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.902 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.902 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0376 0.965 0.004 0.996
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.8499 0.706 0.724 0.276
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.902 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9663 0.000 1.000 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.9993 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9663 0.000 1.000 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9207 1.000 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 1 0.4750 0.7723 0.784 0.216 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.1031 0.9427 0.024 0.976 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.9663 0.000 1.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9207 1.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4796 0.7688 0.780 0.220 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9207 1.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 1 0.4452 0.7940 0.808 0.192 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.9663 0.000 1.000 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4796 0.7688 0.780 0.220 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9663 0.000 1.000 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4750 0.7730 0.784 0.216 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.9993 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9663 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.9993 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9663 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0000 0.9207 1.000 0.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9663 0.000 1.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.4750 0.7730 0.784 0.216 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.1031 0.9056 0.976 0.000 0.024
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.9993 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0000 0.9207 1.000 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9663 0.000 1.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0237 0.9194 0.996 0.004 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9207 1.000 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9207 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0592 0.9550 0.012 0.988 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9207 1.000 0.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.1031 0.9427 0.024 0.976 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9207 1.000 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.5810 0.5893 0.664 0.336 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9663 0.000 1.000 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.9993 0.000 0.000 1.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0000 0.9993 0.000 0.000 1.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0237 0.9194 0.996 0.004 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9207 1.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9207 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9663 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.4796 0.7688 0.780 0.220 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9663 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9663 0.000 1.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.4796 0.7688 0.780 0.220 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.0000 0.9207 1.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.6260 0.1547 0.552 0.000 0.448
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9663 0.000 1.000 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 1 0.6111 0.4578 0.604 0.396 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 1 0.4750 0.7723 0.784 0.216 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.9993 0.000 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9207 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9207 1.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.1031 0.9056 0.976 0.000 0.024
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9207 1.000 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0000 0.9663 0.000 1.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.4796 0.7688 0.780 0.220 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.9993 0.000 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.0000 0.9207 1.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.0000 0.9207 1.000 0.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0000 0.9663 0.000 1.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.0000 0.9207 1.000 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4974 0.7493 0.764 0.236 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0237 0.9194 0.996 0.004 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.0000 0.9993 0.000 0.000 1.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 1 0.0237 0.9194 0.996 0.004 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9663 0.000 1.000 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 2 0.0000 0.9663 0.000 1.000 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 2 0.0000 0.9663 0.000 1.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.4931 0.7078 0.768 0.232 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.0000 0.9663 0.000 1.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4796 0.7688 0.780 0.220 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.0000 0.9993 0.000 0.000 1.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 2 0.0000 0.9663 0.000 1.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 1 0.1643 0.8909 0.956 0.000 0.044
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 2 0.0000 0.9663 0.000 1.000 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 2 0.0000 0.9663 0.000 1.000 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.0000 0.9207 1.000 0.000 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9207 1.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9207 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0237 0.9194 0.996 0.004 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.9993 0.000 0.000 1.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.9993 0.000 0.000 1.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.9207 1.000 0.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.9993 0.000 0.000 1.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9207 1.000 0.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0592 0.9549 0.012 0.988 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.0000 0.9207 1.000 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 1 0.0000 0.9207 1.000 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.9207 1.000 0.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.0000 0.9663 0.000 1.000 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 2 0.0000 0.9663 0.000 1.000 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 1 0.0000 0.9207 1.000 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.0000 0.9993 0.000 0.000 1.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.5058 0.7390 0.756 0.244 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.9207 1.000 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 2 0.0000 0.9663 0.000 1.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0237 0.9194 0.996 0.004 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.0000 0.9207 1.000 0.000 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 2 0.0000 0.9663 0.000 1.000 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0000 0.9207 1.000 0.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.5397 0.6869 0.720 0.280 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 1 0.6111 0.4578 0.604 0.396 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.9993 0.000 0.000 1.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.0000 0.9207 1.000 0.000 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.9993 0.000 0.000 1.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 1 0.4750 0.7723 0.784 0.216 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0000 0.9993 0.000 0.000 1.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.4796 0.7688 0.780 0.220 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.0000 0.9207 1.000 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.0000 0.9207 1.000 0.000 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 1 0.0000 0.9207 1.000 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.9207 1.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.9663 0.000 1.000 0.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.0237 0.9194 0.996 0.004 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.9993 0.000 0.000 1.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 1 0.0000 0.9207 1.000 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.0000 0.9993 0.000 0.000 1.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 2 0.0000 0.9663 0.000 1.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 1 0.0000 0.9207 1.000 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.9993 0.000 0.000 1.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.0000 0.9207 1.000 0.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 2 0.0000 0.9663 0.000 1.000 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.0000 0.9207 1.000 0.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.0000 0.9207 1.000 0.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 1 0.0747 0.9111 0.984 0.000 0.016
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.4796 0.7688 0.780 0.220 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.0000 0.9207 1.000 0.000 0.000
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#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.9993 0.000 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.9207 1.000 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0000 0.9207 1.000 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9663 0.000 1.000 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 1 0.4750 0.7723 0.784 0.216 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0892 0.9084 0.980 0.000 0.020
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9663 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9207 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.9993 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.4796 0.7688 0.780 0.220 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0237 0.9194 0.996 0.004 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.4796 0.7688 0.780 0.220 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9207 1.000 0.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9207 1.000 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.9993 0.000 0.000 1.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.9993 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.0000 0.9207 1.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0000 0.9207 1.000 0.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.9993 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4992 -0.48411 0.000 0.524 0.000 0.476
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2281 0.87816 0.000 0.096 0.000 0.904
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.4730 0.37668 0.636 0.364 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.1867 0.54240 0.072 0.928 0.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.56792 0.000 1.000 0.000 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4955 0.26777 0.556 0.444 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.5167 0.41363 0.340 0.644 0.000 0.016
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4961 0.25660 0.552 0.448 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.3356 0.45581 0.176 0.824 0.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 4 0.5047 0.68811 0.016 0.316 0.000 0.668
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.4819 0.40996 0.344 0.652 0.000 0.004
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.3873 0.84176 0.000 0.228 0.000 0.772
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.4973 0.40441 0.348 0.644 0.000 0.008
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.1716 0.87705 0.000 0.064 0.000 0.936
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0592 0.86850 0.000 0.016 0.000 0.984
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4967 0.25587 0.548 0.452 0.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.3172 0.86773 0.000 0.160 0.000 0.840
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.4837 0.40287 0.348 0.648 0.000 0.004
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.4925 0.30359 0.572 0.428 0.000 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.4730 -0.19757 0.000 0.636 0.000 0.364
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.5168 -0.05627 0.492 0.504 0.000 0.004
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.4804 0.35427 0.616 0.384 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4941 0.28962 0.564 0.436 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0336 0.56727 0.000 0.992 0.000 0.008
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1474 0.60484 0.948 0.052 0.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.4817 -0.17275 0.000 0.612 0.000 0.388
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4916 0.30923 0.576 0.424 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 2 0.5213 0.42639 0.328 0.652 0.000 0.020
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.4661 0.72271 0.000 0.348 0.000 0.652
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1474 0.89343 0.052 0.000 0.948 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.5168 -0.05627 0.492 0.504 0.000 0.004
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4941 0.28962 0.564 0.436 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.2345 0.57771 0.900 0.100 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0592 0.86850 0.000 0.016 0.000 0.984
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.4819 0.40996 0.344 0.652 0.000 0.004
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0592 0.86850 0.000 0.016 0.000 0.984
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.4985 -0.42321 0.000 0.532 0.000 0.468
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.5213 0.42639 0.328 0.652 0.000 0.020
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.4948 0.05689 0.440 0.560 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.2081 0.52887 0.916 0.000 0.084 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.4331 0.37419 0.000 0.712 0.000 0.288
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0188 0.56828 0.000 0.996 0.000 0.004
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.1557 0.55071 0.056 0.944 0.000 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4564 0.39308 0.672 0.328 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.4948 0.27808 0.560 0.440 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.0817 0.87503 0.000 0.024 0.000 0.976
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 2 0.4819 0.40996 0.344 0.652 0.000 0.004
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.4972 0.00934 0.456 0.544 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 1 0.0336 0.60588 0.992 0.008 0.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 1 0.4746 0.20815 0.632 0.368 0.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 2 0.5213 0.42639 0.328 0.652 0.000 0.020
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4994 0.14696 0.520 0.480 0.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4941 0.58881 0.436 0.000 0.564 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 1 0.4866 0.29624 0.596 0.404 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4713 0.63677 0.000 0.360 0.000 0.640
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.3873 0.84176 0.000 0.228 0.000 0.772
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.0336 0.87212 0.000 0.008 0.000 0.992
#> 40424A8F-CE23-436B-8F65-4919F90F6691 2 0.6794 0.32298 0.372 0.524 0.000 0.104
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 2 0.5213 0.42639 0.328 0.652 0.000 0.020
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4925 0.59639 0.428 0.000 0.572 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 1 0.0336 0.60133 0.992 0.000 0.008 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3266 0.86737 0.000 0.168 0.000 0.832
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.3219 0.86607 0.000 0.164 0.000 0.836
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.4967 0.25692 0.548 0.452 0.000 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4933 0.29742 0.568 0.432 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4999 0.09976 0.508 0.492 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.4948 0.27808 0.560 0.440 0.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.5126 0.26179 0.552 0.444 0.000 0.004
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.4925 0.29874 0.572 0.428 0.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.4761 -0.21901 0.000 0.628 0.000 0.372
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.4643 0.37724 0.656 0.344 0.000 0.000
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.3726 0.40562 0.212 0.788 0.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.3837 0.50420 0.776 0.224 0.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.3649 0.84970 0.000 0.204 0.000 0.796
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 1 0.3266 0.46977 0.832 0.168 0.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4941 0.58881 0.436 0.000 0.564 0.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.4122 0.51775 0.236 0.760 0.000 0.004
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.4925 0.30227 0.572 0.428 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.1867 0.87914 0.000 0.072 0.000 0.928
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 2 0.5168 -0.05627 0.492 0.504 0.000 0.004
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.4967 0.25587 0.548 0.452 0.000 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 2 0.4737 0.50433 0.252 0.728 0.000 0.020
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0188 0.56828 0.000 0.996 0.000 0.004
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.1637 0.60343 0.940 0.060 0.000 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.1716 0.54714 0.064 0.936 0.000 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.3873 0.77132 0.228 0.000 0.772 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 2 0.4819 0.40996 0.344 0.652 0.000 0.004
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 1 0.0336 0.60588 0.992 0.008 0.000 0.000
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.3801 0.39527 0.220 0.780 0.000 0.000
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.2973 0.87200 0.000 0.144 0.000 0.856
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 2 0.5168 -0.05627 0.492 0.504 0.000 0.004
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 1 0.3486 0.50318 0.812 0.188 0.000 0.000
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.0592 0.86850 0.000 0.016 0.000 0.984
#> DFADB933-D083-4175-88A6-72086FD5115E 1 0.4967 0.25587 0.548 0.452 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.4790 0.35969 0.620 0.380 0.000 0.000
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.0817 0.87547 0.000 0.024 0.000 0.976
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.4855 0.33989 0.600 0.400 0.000 0.000
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.4941 0.28962 0.564 0.436 0.000 0.000
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 1 0.4679 0.21336 0.648 0.352 0.000 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 2 0.3942 0.51662 0.236 0.764 0.000 0.000
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.4967 0.25587 0.548 0.452 0.000 0.000
#> DAD951A3-C22E-42F0-BB02-854413DDC351 1 0.5105 0.28993 0.564 0.432 0.000 0.004
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 2 0.3444 0.45966 0.184 0.816 0.000 0.000
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 2 0.3801 0.39527 0.220 0.780 0.000 0.000
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 4 0.0592 0.86850 0.000 0.016 0.000 0.984
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 2 0.0000 0.56792 0.000 1.000 0.000 0.000
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 2 0.4713 0.22653 0.360 0.640 0.000 0.000
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 2 0.5736 0.42726 0.328 0.628 0.000 0.044
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 2 0.3649 0.43150 0.204 0.796 0.000 0.000
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 4 0.3907 0.83989 0.000 0.232 0.000 0.768
#> CD44A5FC-A723-4409-AE30-732ECF05AE1B 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> 1BAFAC88-7372-41F9-965F-EFF1A2179E01 1 0.1474 0.60484 0.948 0.052 0.000 0.000
#> 846FECEB-E9B1-4E42-B5C6-8793C52A3DB6 1 0.4790 0.36061 0.620 0.380 0.000 0.000
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#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.4888 0.32413 0.588 0.412 0.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.5000 0.06660 0.500 0.500 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.56792 0.000 1.000 0.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4933 0.29742 0.568 0.432 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.5213 0.42639 0.328 0.652 0.000 0.020
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0524 0.56754 0.008 0.988 0.000 0.004
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.3975 0.78921 0.000 0.240 0.000 0.760
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.4819 0.40996 0.344 0.652 0.000 0.004
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.1557 0.54366 0.000 0.944 0.000 0.056
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.5004 0.30875 0.392 0.604 0.000 0.004
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0592 0.60762 0.984 0.016 0.000 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.1940 0.87789 0.000 0.076 0.000 0.924
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.1302 0.55630 0.044 0.956 0.000 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.0000 0.60695 1.000 0.000 0.000 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.86989 0.000 0.000 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4941 0.28962 0.564 0.436 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0188 0.56828 0.000 0.996 0.000 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.5000 -0.07846 0.500 0.500 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0188 0.56828 0.000 0.996 0.000 0.004
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.1557 0.60402 0.944 0.056 0.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.4941 0.28962 0.564 0.436 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.92424 0.000 0.000 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.4967 0.02193 0.452 0.548 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.1557 0.60402 0.944 0.056 0.000 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.92424 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 1 0.5198 0.63226 0.688 0.148 0.000 0.164 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.4283 0.24392 0.456 0.000 0.000 0.544 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.5049 0.52869 0.060 0.644 0.000 0.000 0.296
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.4678 0.32822 0.224 0.712 0.000 0.000 0.064
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 1 0.5504 0.43846 0.488 0.448 0.000 0.000 0.064
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4060 0.64017 0.360 0.000 0.000 0.640 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.5087 0.53377 0.064 0.644 0.000 0.000 0.292
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.2124 0.64749 0.900 0.004 0.000 0.000 0.096
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.5124 0.53545 0.068 0.644 0.000 0.000 0.288
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.1478 0.66218 0.000 0.936 0.000 0.000 0.064
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1410 0.68072 0.940 0.000 0.000 0.060 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.2127 0.66726 0.892 0.108 0.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 1 0.3210 0.62741 0.788 0.000 0.000 0.212 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.0162 0.69303 0.996 0.004 0.000 0.000 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.1544 0.78368 0.068 0.000 0.000 0.932 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0290 0.68555 0.008 0.992 0.000 0.000 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.3730 0.30044 0.712 0.000 0.000 0.288 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.4157 0.66284 0.716 0.264 0.000 0.020 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.3752 0.54858 0.000 0.708 0.000 0.000 0.292
#> C6AD4922-9981-4493-9F33-87A449B6EE55 1 0.7159 0.51029 0.532 0.168 0.000 0.236 0.064
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.3999 0.51486 0.344 0.656 0.000 0.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 2 0.6176 0.40286 0.172 0.540 0.000 0.000 0.288
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 1 0.3398 0.67945 0.780 0.216 0.000 0.000 0.004
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.4256 0.31889 0.000 0.564 0.000 0.000 0.436
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 1 0.7281 0.53591 0.516 0.224 0.000 0.196 0.064
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.69372 1.000 0.000 0.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 1 0.4049 0.65545 0.780 0.056 0.000 0.164 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3274 0.77019 0.000 0.000 0.780 0.000 0.220
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.4201 0.45325 0.408 0.592 0.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 2 0.5087 0.53377 0.064 0.644 0.000 0.000 0.292
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.5435 0.00875 0.060 0.428 0.000 0.000 0.512
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.69372 1.000 0.000 0.000 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 1 0.6356 0.59034 0.628 0.104 0.000 0.208 0.060
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0162 0.69417 0.996 0.004 0.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0162 0.68496 0.004 0.996 0.000 0.000 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> 69595C5D-6655-4065-8943-90045A2B2478 1 0.4350 0.54718 0.588 0.408 0.000 0.004 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 1 0.4151 0.61913 0.652 0.344 0.000 0.000 0.004
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.5067 0.14296 0.288 0.648 0.000 0.000 0.064
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.4278 0.27451 0.000 0.548 0.000 0.000 0.452
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.4204 0.68123 0.048 0.196 0.000 0.000 0.756
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4297 -0.28455 0.528 0.000 0.000 0.472 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.5091 0.57615 0.584 0.372 0.000 0.044 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.4150 0.11180 0.000 0.612 0.000 0.000 0.388
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.4060 0.64017 0.360 0.000 0.000 0.640 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 5 0.4235 0.20565 0.000 0.424 0.000 0.000 0.576
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.69372 1.000 0.000 0.000 0.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.4235 0.50830 0.008 0.656 0.000 0.000 0.336
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 5 0.1478 0.77986 0.000 0.000 0.064 0.000 0.936
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 1 0.5462 0.61095 0.652 0.136 0.000 0.212 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.3210 0.62741 0.788 0.000 0.000 0.212 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.4101 0.62593 0.372 0.000 0.000 0.628 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.1410 0.66335 0.940 0.060 0.000 0.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4060 0.64017 0.360 0.000 0.000 0.640 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0162 0.69417 0.996 0.004 0.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 5 0.4045 0.21798 0.000 0.000 0.356 0.000 0.644
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4060 0.64017 0.360 0.000 0.000 0.640 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.4273 0.30264 0.448 0.000 0.000 0.552 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 1 0.4150 0.29762 0.612 0.000 0.000 0.388 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 2 0.5087 0.53377 0.064 0.644 0.000 0.000 0.292
#> F4F647DC-C630-429C-AD49-ADA43B652781 2 0.5067 0.53532 0.064 0.648 0.000 0.000 0.288
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.2329 0.87524 0.000 0.000 0.876 0.000 0.124
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 2 0.2074 0.67386 0.104 0.896 0.000 0.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 2 0.4508 0.50599 0.020 0.648 0.000 0.000 0.332
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 1 0.4367 0.53444 0.580 0.416 0.000 0.000 0.004
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 2 0.2514 0.67328 0.060 0.896 0.000 0.000 0.044
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1478 0.66218 0.000 0.936 0.000 0.000 0.064
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 2 0.4030 0.48824 0.000 0.648 0.000 0.000 0.352
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.3730 0.69145 0.288 0.000 0.000 0.712 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 1 0.3242 0.62331 0.784 0.000 0.000 0.216 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.4249 -0.05562 0.000 0.568 0.000 0.000 0.432
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 5 0.1478 0.77986 0.000 0.000 0.064 0.000 0.936
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.3424 0.67176 0.760 0.240 0.000 0.000 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.4297 -0.40108 0.528 0.000 0.000 0.472 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 2 0.4302 0.29179 0.480 0.520 0.000 0.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 2 0.1478 0.68142 0.064 0.936 0.000 0.000 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.4015 0.65029 0.348 0.000 0.000 0.652 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.1851 0.82291 0.000 0.088 0.000 0.000 0.912
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.69372 1.000 0.000 0.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 1 0.5478 0.47861 0.516 0.420 0.000 0.000 0.064
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.2020 0.63950 0.000 0.900 0.000 0.000 0.100
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.5509 -0.40081 0.464 0.472 0.000 0.000 0.064
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.3661 0.68521 0.000 0.000 0.724 0.000 0.276
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0162 0.69514 0.996 0.004 0.000 0.000 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 5 0.3074 0.72468 0.000 0.196 0.000 0.000 0.804
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 5 0.4060 0.45744 0.000 0.360 0.000 0.000 0.640
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 2 0.1478 0.66218 0.000 0.936 0.000 0.000 0.064
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 5 0.4170 0.68736 0.048 0.192 0.000 0.000 0.760
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.3496 0.64083 0.200 0.000 0.000 0.788 0.012
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 2 0.4060 0.49832 0.360 0.640 0.000 0.000 0.000
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 2 0.0162 0.68448 0.000 0.996 0.000 0.000 0.004
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.0290 0.95712 0.000 0.000 0.992 0.000 0.008
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> DFADB933-D083-4175-88A6-72086FD5115E 2 0.0162 0.68496 0.004 0.996 0.000 0.000 0.000
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 2 0.5068 0.52379 0.060 0.640 0.000 0.000 0.300
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.4256 0.52837 0.436 0.000 0.000 0.564 0.000
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 2 0.1732 0.66919 0.000 0.920 0.000 0.000 0.080
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 2 0.5254 0.53903 0.084 0.644 0.000 0.000 0.272
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#> 2ED9F780-A4D9-442E-8742-725183DEAC99 1 0.4242 0.37716 0.572 0.000 0.000 0.428 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 1 0.7484 0.46288 0.476 0.216 0.000 0.244 0.064
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0000 0.69372 1.000 0.000 0.000 0.000 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 1 0.3913 0.52511 0.676 0.000 0.000 0.324 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 2 0.4030 0.48824 0.000 0.648 0.000 0.000 0.352
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 1 0.4047 0.62917 0.676 0.320 0.000 0.000 0.004
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.1544 0.68016 0.932 0.000 0.000 0.068 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0290 0.69317 0.992 0.008 0.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.4150 0.42778 0.000 0.612 0.000 0.000 0.388
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0609 0.68219 0.020 0.980 0.000 0.000 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.4190 0.62902 0.172 0.000 0.000 0.768 0.060
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 2 0.4297 0.22050 0.000 0.528 0.000 0.000 0.472
#> C5102A81-265F-4CD9-9B6C-390348FB690C 1 0.4375 0.52983 0.576 0.420 0.000 0.000 0.004
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.5104 0.51296 0.060 0.632 0.000 0.000 0.308
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.3966 0.49177 0.000 0.336 0.000 0.000 0.664
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.1544 0.66164 0.000 0.932 0.000 0.000 0.068
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.3825 0.67855 0.136 0.000 0.000 0.804 0.060
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0162 0.68586 0.004 0.996 0.000 0.000 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.0000 0.68511 0.000 1.000 0.000 0.000 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.1608 0.91577 0.000 0.000 0.928 0.000 0.072
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.3274 0.62057 0.780 0.000 0.000 0.220 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.4138 0.09141 0.000 0.616 0.000 0.000 0.384
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.4060 0.64017 0.360 0.000 0.000 0.640 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.1544 0.83491 0.000 0.068 0.000 0.000 0.932
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.4891 0.51413 0.044 0.640 0.000 0.000 0.316
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.5029 0.53331 0.060 0.648 0.000 0.000 0.292
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.5581 0.53058 0.224 0.636 0.000 0.000 0.140
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 1 0.4434 0.47832 0.536 0.460 0.000 0.000 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.5304 0.51702 0.080 0.628 0.000 0.000 0.292
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0162 0.69417 0.996 0.004 0.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 1 0.5478 0.47861 0.516 0.420 0.000 0.000 0.064
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.2863 0.75159 0.064 0.000 0.000 0.876 0.060
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0162 0.69417 0.996 0.004 0.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 1 0.5341 0.57160 0.580 0.356 0.000 0.000 0.064
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1410 0.66335 0.940 0.060 0.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.4138 0.43567 0.000 0.616 0.000 0.000 0.384
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.1341 0.78952 0.056 0.000 0.000 0.944 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.4983 0.19474 0.272 0.664 0.000 0.000 0.064
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.1478 0.83646 0.000 0.064 0.000 0.000 0.936
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.80324 0.000 0.000 0.000 1.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.5525 0.50856 0.100 0.612 0.000 0.000 0.288
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.4375 0.52983 0.576 0.420 0.000 0.000 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.5923 0.47970 0.288 0.572 0.000 0.000 0.140
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.3398 0.67945 0.780 0.216 0.000 0.000 0.004
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.5285 0.43225 0.060 0.584 0.000 0.000 0.356
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.4288 0.52113 0.324 0.664 0.000 0.000 0.012
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.1121 0.93458 0.000 0.000 0.956 0.000 0.044
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0162 0.68496 0.004 0.996 0.000 0.000 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.4249 0.32923 0.000 0.568 0.000 0.000 0.432
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.96146 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 6 0.2562 0.57841 0.172 0.000 0.000 0.000 0.000 0.828
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.4136 0.06604 0.560 0.000 0.000 0.428 0.000 0.012
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.3374 0.67558 0.020 0.208 0.000 0.000 0.772 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.2697 0.60945 0.000 0.000 0.000 0.000 0.188 0.812
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 6 0.0547 0.68593 0.020 0.000 0.000 0.000 0.000 0.980
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.3756 0.31318 0.600 0.000 0.000 0.400 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.4659 0.66289 0.020 0.208 0.000 0.000 0.704 0.068
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3920 0.69345 0.740 0.020 0.000 0.000 0.016 0.224
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.5161 0.66862 0.108 0.120 0.000 0.000 0.704 0.068
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.3747 0.28269 0.000 0.000 0.000 0.000 0.396 0.604
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3374 0.70217 0.772 0.000 0.000 0.000 0.020 0.208
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 5 0.5868 0.19956 0.304 0.000 0.000 0.000 0.472 0.224
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 6 0.3804 0.38677 0.424 0.000 0.000 0.000 0.000 0.576
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.3602 0.69166 0.760 0.000 0.000 0.000 0.032 0.208
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.5796 0.04849 0.180 0.000 0.000 0.432 0.000 0.388
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.0000 0.89308 0.000 0.000 0.000 1.000 0.000 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.2948 0.73617 0.092 0.000 0.000 0.000 0.848 0.060
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.0632 0.66561 0.976 0.000 0.000 0.024 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 5 0.6027 0.00111 0.252 0.000 0.000 0.000 0.408 0.340
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.2854 0.67347 0.000 0.792 0.000 0.000 0.208 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.0458 0.76025 0.000 0.000 0.000 0.000 0.984 0.016
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.0790 0.68210 0.032 0.000 0.000 0.000 0.000 0.968
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.4382 0.62736 0.228 0.000 0.000 0.000 0.696 0.076
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.3514 0.67563 0.020 0.208 0.000 0.000 0.768 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 5 0.1682 0.75793 0.020 0.000 0.000 0.000 0.928 0.052
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.2969 0.49607 0.224 0.000 0.000 0.000 0.000 0.776
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.3221 0.64205 0.000 0.264 0.000 0.000 0.736 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.0547 0.68502 0.020 0.000 0.000 0.000 0.000 0.980
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 5 0.0547 0.75978 0.020 0.000 0.000 0.000 0.980 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.2968 0.71188 0.816 0.000 0.000 0.000 0.016 0.168
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.3482 0.33709 0.316 0.000 0.000 0.000 0.000 0.684
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.3866 0.25179 0.000 0.484 0.516 0.000 0.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.4599 0.60247 0.212 0.000 0.000 0.000 0.684 0.104
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 5 0.1408 0.76165 0.020 0.000 0.000 0.000 0.944 0.036
#> 434163EA-432B-41F3-8321-7180A8635124 5 0.4049 0.52061 0.020 0.332 0.000 0.000 0.648 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0000 0.89308 0.000 0.000 0.000 1.000 0.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3374 0.70217 0.772 0.000 0.000 0.000 0.020 0.208
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.0000 0.89308 0.000 0.000 0.000 1.000 0.000 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.1501 0.67227 0.076 0.000 0.000 0.000 0.000 0.924
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.2969 0.70024 0.776 0.000 0.000 0.000 0.000 0.224
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 5 0.2941 0.69353 0.000 0.000 0.000 0.000 0.780 0.220
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 2 0.0000 0.72163 0.000 1.000 0.000 0.000 0.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 6 0.3674 0.43847 0.268 0.000 0.000 0.000 0.016 0.716
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.1501 0.66418 0.076 0.000 0.000 0.000 0.000 0.924
#> 36B2E208-FF01-4249-92C3-BE77D426691B 6 0.2003 0.65064 0.000 0.000 0.000 0.000 0.116 0.884
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 5 0.1501 0.75019 0.000 0.076 0.000 0.000 0.924 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 2 0.4314 0.04659 0.020 0.536 0.000 0.000 0.444 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 2 0.0000 0.72163 0.000 1.000 0.000 0.000 0.000 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.3966 0.68426 0.044 0.184 0.000 0.000 0.760 0.012
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.2003 0.60440 0.884 0.000 0.000 0.116 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 6 0.5703 0.18040 0.168 0.000 0.000 0.000 0.360 0.472
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 5 0.0865 0.76029 0.000 0.000 0.000 0.000 0.964 0.036
#> B730E9AD-DA24-46A3-BE56-A89447421C09 5 0.3727 0.11499 0.000 0.388 0.000 0.000 0.612 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.3756 0.31318 0.600 0.000 0.000 0.400 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.4059 0.63784 0.000 0.720 0.000 0.000 0.228 0.052
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3261 0.70828 0.780 0.000 0.000 0.000 0.016 0.204
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.4899 0.67329 0.108 0.116 0.000 0.000 0.724 0.052
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 2 0.0000 0.72163 0.000 1.000 0.000 0.000 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 5 0.3446 0.53207 0.000 0.000 0.000 0.000 0.692 0.308
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.1501 0.66418 0.076 0.000 0.000 0.000 0.000 0.924
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.3868 0.03612 0.508 0.000 0.000 0.000 0.000 0.492
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.2912 0.48437 0.784 0.000 0.000 0.216 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.3422 0.70048 0.792 0.000 0.000 0.000 0.040 0.168
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.3330 0.37894 0.716 0.000 0.000 0.284 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.3404 0.69863 0.760 0.000 0.000 0.000 0.016 0.224
#> 26635F72-F34D-4543-908F-484441832E9E 2 0.2854 0.51655 0.000 0.792 0.208 0.000 0.000 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.3866 -0.14384 0.516 0.000 0.000 0.484 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 2 0.2854 0.67347 0.000 0.792 0.000 0.000 0.208 0.000
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 0.5392 0.37171 0.584 0.000 0.000 0.224 0.000 0.192
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 1 0.3490 0.43519 0.724 0.000 0.000 0.268 0.000 0.008
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 5 0.0547 0.75986 0.000 0.000 0.000 0.000 0.980 0.020
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 5 0.0547 0.75978 0.020 0.000 0.000 0.000 0.980 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 5 0.4659 0.66289 0.020 0.208 0.000 0.000 0.704 0.068
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#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.1501 0.66418 0.076 0.000 0.000 0.000 0.000 0.924
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.0000 0.89308 0.000 0.000 0.000 1.000 0.000 0.000
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#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 5 0.1003 0.76083 0.020 0.000 0.000 0.000 0.964 0.016
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 5 0.0458 0.76025 0.000 0.000 0.000 0.000 0.984 0.016
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.2597 0.77328 0.000 0.176 0.824 0.000 0.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.4389 0.44330 0.660 0.000 0.000 0.288 0.000 0.052
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 5 0.4029 0.33428 0.000 0.292 0.000 0.000 0.680 0.028
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.3765 0.30405 0.596 0.000 0.000 0.404 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.3288 0.65919 0.000 0.724 0.000 0.000 0.276 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.2941 0.67541 0.000 0.220 0.000 0.000 0.780 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 5 0.0000 0.76103 0.000 0.000 0.000 0.000 1.000 0.000
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#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 6 0.1444 0.66633 0.072 0.000 0.000 0.000 0.000 0.928
#> 21385544-2FC4-4EB8-AF55-1C046216E189 5 0.1148 0.76270 0.020 0.004 0.000 0.000 0.960 0.016
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#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.0458 0.68577 0.016 0.000 0.000 0.000 0.000 0.984
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 6 0.5696 0.02226 0.160 0.000 0.000 0.396 0.000 0.444
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.2883 0.70537 0.788 0.000 0.000 0.000 0.000 0.212
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.0547 0.68502 0.020 0.000 0.000 0.000 0.000 0.980
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.3738 0.69735 0.752 0.000 0.000 0.000 0.040 0.208
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.2912 0.67257 0.000 0.784 0.000 0.000 0.216 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.2969 0.67359 0.000 0.224 0.000 0.000 0.776 0.000
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.4672 0.66448 0.188 0.000 0.000 0.684 0.000 0.128
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.1910 0.65185 0.000 0.000 0.000 0.000 0.108 0.892
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.1610 0.70969 0.000 0.916 0.000 0.000 0.084 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.0000 0.89308 0.000 0.000 0.000 1.000 0.000 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 5 0.2255 0.73937 0.080 0.000 0.000 0.000 0.892 0.028
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.3017 0.57118 0.164 0.000 0.000 0.000 0.020 0.816
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.5353 0.34272 0.368 0.000 0.000 0.000 0.516 0.116
#> C2750CB6-DD39-41E2-B615-271D72A8876C 6 0.4690 -0.00370 0.400 0.000 0.000 0.000 0.048 0.552
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3374 0.67558 0.020 0.208 0.000 0.000 0.772 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 5 0.1682 0.75793 0.020 0.000 0.000 0.000 0.928 0.052
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.2996 0.70323 0.000 0.228 0.772 0.000 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.93146 0.000 0.000 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 5 0.1444 0.75723 0.000 0.000 0.000 0.000 0.928 0.072
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.0790 0.75505 0.000 0.032 0.000 0.000 0.968 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.93146 0.000 0.000 1.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.798 0.939 0.971 0.238 0.765 0.765
#> 3 3 0.362 0.707 0.794 1.112 0.646 0.547
#> 4 4 0.300 0.498 0.724 0.168 0.861 0.717
#> 5 5 0.378 0.529 0.740 0.165 0.808 0.571
#> 6 6 0.484 0.423 0.681 0.094 0.880 0.644
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9786 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9006 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9786 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.0000 0.9786 0.000 1.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9786 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9786 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.9786 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.0000 0.9786 0.000 1.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.0000 0.9786 0.000 1.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.0000 0.9786 0.000 1.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9786 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.9786 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.0000 0.9786 0.000 1.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9786 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.9786 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.0000 0.9006 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9786 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.0376 0.9010 0.996 0.004
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9786 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.9786 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9786 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9786 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 2 0.0000 0.9786 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9006 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.0000 0.9786 0.000 1.000
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#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0000 0.9786 0.000 1.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.0000 0.9786 0.000 1.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 2 0.0000 0.9786 0.000 1.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9786 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.0000 0.9786 0.000 1.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5059 0.8586 0.112 0.888
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.0000 0.9786 0.000 1.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 2 0.0000 0.9786 0.000 1.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9786 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9006 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.5294 0.8940 0.880 0.120
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.0000 0.9786 0.000 1.000
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#> 434163EA-432B-41F3-8321-7180A8635124 2 0.0000 0.9786 0.000 1.000
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#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.0000 0.9786 0.000 1.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9786 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9786 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.0000 0.9786 0.000 1.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9786 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 2 0.9954 0.0240 0.460 0.540
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9786 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9786 0.000 1.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.0000 0.9786 0.000 1.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 1 0.0672 0.9012 0.992 0.008
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 2 0.0000 0.9786 0.000 1.000
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#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 2 0.0000 0.9786 0.000 1.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 2 0.0000 0.9786 0.000 1.000
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#> 97A49141-0141-4583-B366-A4720270D6F2 1 0.0000 0.9006 1.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 2 0.0000 0.9786 0.000 1.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.6343 0.7951 0.160 0.840
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 2 0.0000 0.9786 0.000 1.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.9833 0.1690 0.424 0.576
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#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.0000 0.9786 0.000 1.000
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#> 939AB9FA-9956-4A78-B676-444DA091D1AC 2 0.0000 0.9786 0.000 1.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 2 0.0000 0.9786 0.000 1.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 2 0.0000 0.9786 0.000 1.000
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#> CF00D656-8854-47A0-9991-9F39CB7FEC86 1 0.0000 0.9006 1.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 1 0.4939 0.8994 0.892 0.108
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#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 1 0.0000 0.9006 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 2 0.0000 0.9786 0.000 1.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.8955 0.5086 0.312 0.688
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#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.6343 0.7951 0.160 0.840
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#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.4939 0.8635 0.108 0.892
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#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 2 0.0000 0.9786 0.000 1.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 2 0.0000 0.9786 0.000 1.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 2 0.0000 0.9786 0.000 1.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 2 0.0000 0.9786 0.000 1.000
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#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.0000 0.9786 0.000 1.000
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 2 0.0000 0.9786 0.000 1.000
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#> AC2D5D97-6FBD-4E61-A023-644F26549D04 2 0.0000 0.9786 0.000 1.000
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#> E7545EEB-D0D4-410F-B2AC-C93CCA3C33DA 2 0.0000 0.9786 0.000 1.000
#> EF3D2659-7C4A-4003-A1B1-9A47A5388034 2 0.0000 0.9786 0.000 1.000
#> 09A7BAD6-4AB2-428A-B96C-BC3C298C4496 2 0.0000 0.9786 0.000 1.000
#> 02D46E43-75BB-4A0A-8A02-403C7FBFB112 2 0.0000 0.9786 0.000 1.000
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#> 853C84D3-A446-4D7D-B3FA-D9010BDA365A 2 0.0000 0.9786 0.000 1.000
#> 14A8964B-E0FB-4546-A5C5-CE6D7CC0B498 2 0.0000 0.9786 0.000 1.000
#> 4C838D35-B667-46DA-836F-068453D254DA 2 0.0000 0.9786 0.000 1.000
#> 3A1F4A59-8776-48A3-8DB6-4D7F5F30F17A 2 0.0000 0.9786 0.000 1.000
#> 04C256C6-2F29-4DD5-8676-1ED619352F63 2 0.0000 0.9786 0.000 1.000
#> 1B031718-A23A-403A-8C5E-A7CFF396F783 2 0.6148 0.8064 0.152 0.848
#> AE4887D1-578B-4258-9B1B-715FD9C2B43A 1 0.0000 0.9006 1.000 0.000
#> FBD8AD03-C7D8-4225-9B7C-2F24E83A1BB3 2 0.0000 0.9786 0.000 1.000
#> 976924B0-5799-4AC9-804F-78C8568037CA 2 0.8081 0.6499 0.248 0.752
#> DC37D1AD-3F31-430F-90E4-97FF8919EE34 1 0.5059 0.8983 0.888 0.112
#> 2343975A-0AB3-448E-A633-4B433B1DF960 2 0.0000 0.9786 0.000 1.000
#> C55652F1-9D90-4229-ACC6-AA3D6AA07546 2 0.0000 0.9786 0.000 1.000
#> 2D74E62B-B972-42C4-ABD2-A0DBDAAEC043 1 0.5178 0.8965 0.884 0.116
#> 7441B31D-C6DA-4F1B-8013-DB0BF98F673C 2 0.0000 0.9786 0.000 1.000
#> F3285881-878E-4190-BB96-9A2303C76346 2 0.0000 0.9786 0.000 1.000
#> 2821CF4C-03C0-4DB2-BFC1-EB19B6254223 2 0.0000 0.9786 0.000 1.000
#> 5EBB0D5E-C257-4682-943B-DD6E10B9C73C 2 0.0000 0.9786 0.000 1.000
#> 735C0AD9-1788-4FA8-9373-BAF2DDFFA15E 2 0.0000 0.9786 0.000 1.000
#> 09795FC0-F3A4-4C44-B659-52160C59ECA9 1 0.4939 0.8994 0.892 0.108
#> 234C42B7-E6A1-4CB3-9B30-D066541E918B 2 0.0000 0.9786 0.000 1.000
#> E4E148E4-12B3-4384-9D16-4EFA666F59D8 2 0.0000 0.9786 0.000 1.000
#> B977CA7B-1173-4FC8-A078-4E41327E5DF8 2 0.5178 0.8536 0.116 0.884
#> 93429F04-8404-4E8C-B654-9D2216BA432C 2 0.0000 0.9786 0.000 1.000
#> 00C397B0-B7CD-4783-A770-2D0264DE4A73 2 0.0000 0.9786 0.000 1.000
#> BE4E89F3-9A3A-4D12-8F02-C78CFE5BA101 2 0.0000 0.9786 0.000 1.000
#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 2 0.0000 0.9786 0.000 1.000
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 2 0.6343 0.7951 0.160 0.840
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 2 0.0000 0.9786 0.000 1.000
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 1 0.6343 0.8651 0.840 0.160
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 2 0.0000 0.9786 0.000 1.000
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 2 0.9881 0.1247 0.436 0.564
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 1 0.4939 0.8994 0.892 0.108
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 2 0.0000 0.9786 0.000 1.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.0000 0.9786 0.000 1.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 2 0.0000 0.9786 0.000 1.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.6343 0.7951 0.160 0.840
#> 1501020D-0CDC-48B4-8756-33099804FEC6 2 0.0000 0.9786 0.000 1.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.0000 0.9786 0.000 1.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 2 0.0000 0.9786 0.000 1.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 2 0.0000 0.9786 0.000 1.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 2 0.0000 0.9786 0.000 1.000
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.0000 0.9786 0.000 1.000
#> F79C78B6-421E-4634-A403-4EC822299308 2 0.0000 0.9786 0.000 1.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 2 0.0000 0.9786 0.000 1.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 2 0.9933 0.0577 0.452 0.548
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 2 0.0000 0.9786 0.000 1.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 2 0.0000 0.9786 0.000 1.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 2 0.0000 0.9786 0.000 1.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 2 0.0000 0.9786 0.000 1.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 1 0.0000 0.9006 1.000 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 2 0.0000 0.9786 0.000 1.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.6343 0.7951 0.160 0.840
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 2 0.0000 0.9786 0.000 1.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 2 0.0000 0.9786 0.000 1.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 2 0.0000 0.9786 0.000 1.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 2 0.0000 0.9786 0.000 1.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 2 0.6343 0.7951 0.160 0.840
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 2 0.0000 0.9786 0.000 1.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 2 0.0000 0.9786 0.000 1.000
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.0000 0.9786 0.000 1.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 2 0.0000 0.9786 0.000 1.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.6623 0.7775 0.172 0.828
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 2 0.0000 0.9786 0.000 1.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 2 0.0000 0.9786 0.000 1.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.0000 0.9786 0.000 1.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 1 0.4298 0.9005 0.912 0.088
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 2 0.0000 0.9786 0.000 1.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 2 0.0000 0.9786 0.000 1.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 1 0.6343 0.8651 0.840 0.160
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 2 0.0000 0.9786 0.000 1.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 2 0.0000 0.9786 0.000 1.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 2 0.0000 0.9786 0.000 1.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 2 0.0000 0.9786 0.000 1.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.0000 0.9786 0.000 1.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 2 0.0000 0.9786 0.000 1.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 2 0.0000 0.9786 0.000 1.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 1 0.0000 0.9006 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 2 0.6343 0.7951 0.160 0.840
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 2 0.0000 0.9786 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.9786 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.3431 0.9141 0.064 0.936
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.9006 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.9786 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.0000 0.9006 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.0000 0.9786 0.000 1.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9786 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 2 0.0000 0.9786 0.000 1.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9786 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.9786 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 2 0.0000 0.9786 0.000 1.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.0000 0.9786 0.000 1.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.9786 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.9786 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.9786 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 2 0.8443 0.5998 0.272 0.728
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.9786 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9786 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 2 0.0376 0.9749 0.004 0.996
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6343 0.8651 0.840 0.160
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.0000 0.9786 0.000 1.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.9786 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.9786 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.9786 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9786 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.6343 0.7951 0.160 0.840
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.9786 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.5519 0.8385 0.128 0.872
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9006 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 1 0.0672 0.9012 0.992 0.008
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0000 0.9786 0.000 1.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.0000 0.9786 0.000 1.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.5059 0.8983 0.888 0.112
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0000 0.9786 0.000 1.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.6343 0.7951 0.160 0.840
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0000 0.9786 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.0000 0.9786 0.000 1.000
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.0000 0.9786 0.000 1.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.0000 0.9786 0.000 1.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.0000 0.9786 0.000 1.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 1 0.9988 0.2088 0.520 0.480
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.0000 0.9786 0.000 1.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.0000 0.9786 0.000 1.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9786 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9786 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.0000 0.9786 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9786 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.0000 0.9786 0.000 1.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.9006 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.0000 0.9786 0.000 1.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.2778 0.9314 0.048 0.952
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9786 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9786 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 2 0.0000 0.9786 0.000 1.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9786 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.0000 0.9786 0.000 1.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9006 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9786 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.0000 0.9786 0.000 1.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9786 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.0000 0.9786 0.000 1.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.0000 0.9786 0.000 1.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.5059 0.8983 0.888 0.112
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9006 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9786 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.0000 0.9786 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9006 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5431 0.8527 0.284 0.716 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.8150 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.5650 0.4093 0.688 0.312 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0592 0.8386 0.988 0.012 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.5254 0.8555 0.264 0.736 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.5621 0.8362 0.308 0.692 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0892 0.8331 0.980 0.020 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.8400 1.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.8400 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0747 0.8369 0.984 0.016 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5216 0.8543 0.260 0.740 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.1031 0.8388 0.976 0.024 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0747 0.8396 0.984 0.016 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5591 0.8371 0.304 0.696 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4887 0.6622 0.772 0.228 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.8150 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.5216 0.8517 0.260 0.740 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.8150 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.5254 0.8525 0.264 0.736 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0892 0.8386 0.980 0.020 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.1411 0.8370 0.964 0.036 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.3116 0.7807 0.892 0.108 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.8725 0.0852 0.416 0.108 0.476
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.8150 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.2066 0.8303 0.940 0.060 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.5178 0.8558 0.256 0.744 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0747 0.8397 0.984 0.016 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0424 0.8395 0.992 0.008 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1529 0.8260 0.960 0.040 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.5497 0.8440 0.292 0.708 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1905 0.8178 0.956 0.028 0.016
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5365 0.8519 0.252 0.744 0.004
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.1031 0.8403 0.976 0.024 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.1031 0.8350 0.976 0.024 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5397 0.8515 0.280 0.720 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.8150 0.000 0.000 1.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.7156 0.6633 0.028 0.400 0.572
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#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.6597 0.7687 0.120 0.124 0.756
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.0237 0.8400 0.996 0.004 0.000
#> 6D711561-D549-44C7-885F-F3B846DB130C 2 0.5254 0.8555 0.264 0.736 0.000
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.0892 0.8331 0.980 0.020 0.000
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.7535 0.6303 0.176 0.692 0.132
#> 1501020D-0CDC-48B4-8756-33099804FEC6 1 0.6225 -0.1375 0.568 0.432 0.000
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.5363 0.8554 0.276 0.724 0.000
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.1163 0.8391 0.972 0.028 0.000
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.1031 0.8398 0.976 0.024 0.000
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.2434 0.8236 0.940 0.036 0.024
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 2 0.5291 0.8568 0.268 0.732 0.000
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.0892 0.8331 0.980 0.020 0.000
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.1031 0.8401 0.976 0.024 0.000
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.7785 0.5114 0.672 0.136 0.192
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 1 0.4121 0.7213 0.832 0.168 0.000
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.1860 0.8188 0.948 0.052 0.000
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.0000 0.8400 1.000 0.000 0.000
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.0892 0.8361 0.980 0.020 0.000
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0000 0.8150 0.000 0.000 1.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.5948 0.2347 0.640 0.360 0.000
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 2 0.8138 0.7105 0.232 0.636 0.132
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.0592 0.8385 0.988 0.012 0.000
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.0747 0.8369 0.984 0.016 0.000
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.1860 0.8291 0.948 0.052 0.000
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 1 0.5905 0.2677 0.648 0.352 0.000
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.8681 0.4557 0.216 0.188 0.596
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.5138 0.6046 0.748 0.252 0.000
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.7037 0.3273 0.636 0.328 0.036
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.5497 0.8384 0.292 0.708 0.000
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.4452 0.6824 0.808 0.192 0.000
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.7485 0.6197 0.172 0.696 0.132
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.3340 0.7691 0.880 0.120 0.000
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.1289 0.8369 0.968 0.032 0.000
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 2 0.6305 0.3555 0.484 0.516 0.000
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.6309 0.7807 0.100 0.128 0.772
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 1 0.1031 0.8375 0.976 0.024 0.000
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.1411 0.8370 0.964 0.036 0.000
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.4931 0.2886 0.032 0.828 0.140
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.0592 0.8377 0.988 0.012 0.000
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 1 0.4750 0.6579 0.784 0.216 0.000
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.0424 0.8390 0.992 0.008 0.000
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.1289 0.8390 0.968 0.032 0.000
#> A2007795-C728-4688-B199-AE89500011D2 2 0.5254 0.8555 0.264 0.736 0.000
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 1 0.6079 0.1850 0.612 0.388 0.000
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.3816 0.7443 0.852 0.148 0.000
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.8150 0.000 0.000 1.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.8460 0.0138 0.472 0.088 0.440
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.2066 0.8304 0.940 0.060 0.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.5254 0.8525 0.264 0.736 0.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.5578 0.8463 0.240 0.748 0.012
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.8150 0.000 0.000 1.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 1 0.6225 -0.1360 0.568 0.432 0.000
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0424 0.8144 0.000 0.008 0.992
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.0237 0.8400 0.996 0.004 0.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.5560 0.8411 0.300 0.700 0.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.1031 0.8404 0.976 0.024 0.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.5650 0.8318 0.312 0.688 0.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.5760 0.3403 0.672 0.328 0.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0000 0.8400 1.000 0.000 0.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.2846 0.8163 0.924 0.056 0.020
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.6045 0.7124 0.380 0.620 0.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.6307 -0.2824 0.512 0.488 0.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.5254 0.8566 0.264 0.736 0.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.7505 0.5748 0.696 0.144 0.160
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.5497 0.8503 0.292 0.708 0.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.5216 0.8517 0.260 0.740 0.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.9323 0.0788 0.312 0.188 0.500
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.8354 0.6291 0.104 0.320 0.576
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.2176 0.8135 0.948 0.032 0.020
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.5216 0.5799 0.740 0.260 0.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.5968 0.7490 0.364 0.636 0.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.4399 0.6915 0.812 0.188 0.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.6026 0.2078 0.624 0.376 0.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.8930 0.1920 0.536 0.316 0.148
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.5254 0.8555 0.264 0.736 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.7266 0.7912 0.232 0.688 0.080
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.8150 0.000 0.000 1.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.1163 0.8077 0.000 0.028 0.972
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.5216 0.5797 0.740 0.260 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.5706 0.4191 0.680 0.320 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.6322 0.7793 0.108 0.120 0.772
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.3551 0.7662 0.868 0.132 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.7860 0.6741 0.204 0.664 0.132
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0892 0.8331 0.980 0.020 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.4565 0.7707 0.860 0.076 0.064
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3141 0.8006 0.912 0.068 0.020
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.3412 0.7908 0.876 0.124 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0237 0.8402 0.996 0.004 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.5136 0.3363 0.044 0.824 0.132
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.1753 0.8225 0.952 0.048 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.8400 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.5254 0.8555 0.264 0.736 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.5216 0.8548 0.260 0.740 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0592 0.8366 0.988 0.012 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.5363 0.8562 0.276 0.724 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.8400 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.8150 0.000 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.5882 0.3810 0.652 0.348 0.000
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.6372 0.6493 0.764 0.084 0.152
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.5327 0.8513 0.272 0.728 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.5327 0.8548 0.272 0.728 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.2165 0.8268 0.936 0.064 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.5327 0.8513 0.272 0.728 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.1031 0.8350 0.976 0.024 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.8150 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.5706 0.8229 0.320 0.680 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.8400 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.6308 -0.3098 0.508 0.492 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0892 0.8368 0.980 0.020 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.1289 0.8314 0.968 0.032 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.6935 0.6996 0.024 0.372 0.604
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.8150 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.4654 0.6668 0.792 0.208 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.1289 0.8383 0.968 0.032 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.8150 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.6669 0.4884 0.332 0.564 0.000 0.104
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.4655 0.3099 0.684 0.312 0.000 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0895 0.7210 0.976 0.004 0.000 0.020
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.6773 0.6630 0.136 0.276 0.000 0.588
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 1 0.7902 -0.5058 0.352 0.296 0.000 0.352
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.2662 0.6782 0.900 0.084 0.000 0.016
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1305 0.7197 0.960 0.004 0.000 0.036
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1576 0.7180 0.948 0.004 0.000 0.048
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0672 0.7217 0.984 0.008 0.000 0.008
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.6756 0.6939 0.148 0.252 0.000 0.600
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.3384 0.6653 0.860 0.024 0.000 0.116
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0336 0.7198 0.992 0.000 0.000 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 1 0.7844 -0.4457 0.368 0.368 0.000 0.264
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.4978 0.1815 0.612 0.004 0.000 0.384
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.4621 0.6081 0.284 0.708 0.000 0.008
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.4594 0.6076 0.280 0.712 0.000 0.008
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0817 0.7170 0.976 0.000 0.000 0.024
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.2266 0.6795 0.912 0.084 0.000 0.004
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.4225 0.5871 0.792 0.024 0.000 0.184
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.7432 -0.0295 0.480 0.032 0.408 0.080
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1706 0.7113 0.948 0.016 0.000 0.036
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.5944 0.3675 0.140 0.696 0.000 0.164
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0592 0.7199 0.984 0.016 0.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1305 0.7198 0.960 0.004 0.000 0.036
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4804 0.2400 0.616 0.000 0.000 0.384
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.6946 0.7510 0.200 0.212 0.000 0.588
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1109 0.7187 0.968 0.004 0.000 0.028
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.5631 0.5534 0.224 0.700 0.000 0.076
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.4713 0.2482 0.640 0.000 0.000 0.360
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4964 0.2452 0.616 0.004 0.000 0.380
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.7020 0.5651 0.136 0.332 0.000 0.532
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.7879 0.5073 0.012 0.332 0.464 0.192
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.1182 0.7191 0.968 0.016 0.000 0.016
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4950 0.2467 0.620 0.004 0.000 0.376
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4950 0.2564 0.620 0.004 0.000 0.376
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.4567 0.6081 0.276 0.716 0.000 0.008
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0336 0.7213 0.992 0.008 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.4746 0.6012 0.304 0.688 0.000 0.008
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.6391 0.4840 0.304 0.604 0.000 0.092
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0336 0.7211 0.992 0.008 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.6856 -0.0373 0.576 0.140 0.000 0.284
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.6781 0.2486 0.440 0.036 0.492 0.032
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.5158 0.4645 0.472 0.524 0.000 0.004
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.7449 0.6750 0.292 0.208 0.000 0.500
#> 36B2E208-FF01-4249-92C3-BE77D426691B 4 0.6944 0.7585 0.216 0.196 0.000 0.588
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0376 0.7220 0.000 0.004 0.992 0.004
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0817 0.7170 0.976 0.000 0.000 0.024
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#> 24294D96-D0E1-4C7E-80B6-9DCAFE07D841 1 0.1743 0.7113 0.940 0.004 0.000 0.056
#> F79761A5-F77A-4B51-A3B7-86B75AE039D5 3 0.9192 0.2573 0.220 0.180 0.460 0.140
#> 47591CEC-4DEE-4C6D-8A86-269868F34412 4 0.7362 0.6723 0.220 0.256 0.000 0.524
#> 9CB66448-1A6C-4ED5-A58C-AAC10E67AD85 2 0.4920 0.1493 0.004 0.628 0.000 0.368
#> 865E87D1-9582-4E3D-BBB7-AFC0B146BBA9 4 0.7093 0.7461 0.212 0.220 0.000 0.568
#> 6D8F34CA-09F7-4650-AE2B-1A9B46049926 3 0.6697 0.3886 0.360 0.036 0.568 0.036
#> D90EBFB9-7412-4233-A893-41926CAF2A8A 3 0.6191 0.5430 0.272 0.032 0.660 0.036
#> E2C271FC-EEBA-47A8-9E51-C0A221175D7D 1 0.1297 0.7180 0.964 0.016 0.000 0.020
#> 6D711561-D549-44C7-885F-F3B846DB130C 4 0.7176 0.7199 0.196 0.252 0.000 0.552
#> 4BF521F6-7804-49BA-8C56-28E253531628 1 0.3048 0.6629 0.876 0.108 0.000 0.016
#> AD2D1626-9F5C-4EF2-AC1B-89C085F575EB 2 0.6054 0.5368 0.256 0.656 0.000 0.088
#> 1501020D-0CDC-48B4-8756-33099804FEC6 1 0.4964 0.0904 0.616 0.380 0.000 0.004
#> CDF1C573-AEBF-4655-9EE2-9E5723A1A0CE 2 0.5038 0.5768 0.336 0.652 0.000 0.012
#> 82964248-7145-4D55-9634-DC0173F2FA5A 1 0.4508 0.5731 0.780 0.036 0.000 0.184
#> 82666B79-9FDE-4AEB-BEEE-B0EB5928DE67 1 0.4905 0.2436 0.632 0.004 0.000 0.364
#> E871822F-87BC-482E-9E8C-2C40B00CBC4F 1 0.2392 0.7080 0.924 0.016 0.008 0.052
#> 8AC7406E-558E-437D-A335-5BDA778EAAF3 4 0.6794 0.6589 0.136 0.280 0.000 0.584
#> F79C78B6-421E-4634-A403-4EC822299308 1 0.2593 0.6816 0.904 0.080 0.000 0.016
#> 55C670A7-67DD-491D-9D0E-B0D9EFFCA5B0 1 0.1940 0.6956 0.924 0.000 0.000 0.076
#> C52126E0-3DF8-4134-B9E8-5A57168D114F 1 0.3716 0.6819 0.872 0.036 0.064 0.028
#> B0C7C628-003D-4529-A9F2-435F7A2DA053 1 0.2675 0.6955 0.908 0.048 0.000 0.044
#> 003FAA08-D5CA-4F6F-AC93-1B8EC205701D 1 0.4964 0.2452 0.616 0.004 0.000 0.380
#> 2843FA7E-CDC1-4D4E-96F2-B87BFB91FA20 1 0.1576 0.7167 0.948 0.004 0.000 0.048
#> 17950863-DF00-40E0-86DA-1FEC9B6C72A4 1 0.4950 0.2467 0.620 0.004 0.000 0.376
#> C653CC8E-7598-4332-A053-D72CFBC380DF 3 0.0188 0.7225 0.004 0.000 0.996 0.000
#> B58BFFE5-4390-4791-8385-A04A35CA1149 1 0.5132 -0.1850 0.548 0.448 0.000 0.004
#> 59D61CB1-50C2-48C8-8DC9-1A9DEEF75D06 1 0.7113 -0.3074 0.456 0.416 0.000 0.128
#> 438E34A4-1A92-4C59-A580-38CAA4A1DD1E 1 0.4088 0.5476 0.764 0.004 0.000 0.232
#> 26299BB0-A792-439E-B5BF-D0A17629C3B9 1 0.1174 0.7191 0.968 0.012 0.000 0.020
#> BDDB8226-723E-426F-973F-59D14E9EEB06 1 0.4072 0.4881 0.748 0.000 0.000 0.252
#> 5E7AB2A6-8186-4756-AD46-31A134D1019B 1 0.5497 -0.2314 0.524 0.460 0.000 0.016
#> 7A3997B2-1D86-4666-BFBC-24404002AE06 3 0.6807 0.2827 0.404 0.040 0.524 0.032
#> 8CD2EAF7-DA52-4E01-9E01-CC457076E0D6 1 0.5105 0.0252 0.564 0.004 0.000 0.432
#> 3308C8BE-C64C-43AA-AF02-DA1C984725D6 1 0.5207 0.3558 0.680 0.028 0.000 0.292
#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 2 0.5465 0.5441 0.392 0.588 0.000 0.020
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 1 0.5848 0.0585 0.584 0.040 0.000 0.376
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.6423 0.4554 0.336 0.580 0.000 0.084
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 1 0.3764 0.5634 0.784 0.000 0.000 0.216
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 1 0.2255 0.6904 0.920 0.068 0.000 0.012
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 4 0.7201 0.7235 0.268 0.188 0.000 0.544
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.5800 0.5646 0.256 0.036 0.688 0.020
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 1 0.0376 0.7202 0.992 0.004 0.000 0.004
#> E9061D61-4774-464E-ABE4-EB15CD889141 1 0.3390 0.6365 0.852 0.132 0.000 0.016
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.4920 0.1493 0.004 0.628 0.000 0.368
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 1 0.2300 0.6952 0.920 0.064 0.000 0.016
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.5329 0.5008 0.420 0.012 0.000 0.568
#> 93E69515-4C47-4E68-8842-818DE0E369E2 1 0.1297 0.7180 0.964 0.016 0.000 0.020
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 1 0.0921 0.7166 0.972 0.000 0.000 0.028
#> A2007795-C728-4688-B199-AE89500011D2 4 0.7098 0.5124 0.132 0.376 0.000 0.492
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.7001 0.7549 0.244 0.180 0.000 0.576
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 1 0.3280 0.6549 0.860 0.016 0.000 0.124
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.6296 0.2931 0.616 0.036 0.324 0.024
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 1 0.2593 0.6860 0.904 0.016 0.000 0.080
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.4769 0.6008 0.308 0.684 0.000 0.008
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.6499 0.1668 0.112 0.612 0.000 0.276
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.5607 0.3405 0.488 0.492 0.000 0.020
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.3306 0.6483 0.840 0.004 0.000 0.156
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.7218 0.4128 0.316 0.520 0.000 0.164
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.0921 0.7166 0.972 0.000 0.000 0.028
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 1 0.7849 -0.3976 0.400 0.284 0.000 0.316
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 1 0.4964 0.0292 0.616 0.380 0.000 0.004
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0895 0.7202 0.976 0.004 0.000 0.020
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.1284 0.7158 0.964 0.012 0.000 0.024
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 4 0.6994 0.7362 0.288 0.152 0.000 0.560
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 4 0.6936 0.7592 0.224 0.188 0.000 0.588
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.5800 0.3751 0.128 0.708 0.000 0.164
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.2489 0.7068 0.912 0.068 0.000 0.020
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.7910 0.2541 0.332 0.308 0.000 0.360
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.4594 0.6076 0.280 0.712 0.000 0.008
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 3 0.8122 0.0884 0.412 0.044 0.420 0.124
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.8633 0.3606 0.328 0.120 0.460 0.092
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.0895 0.7211 0.976 0.004 0.000 0.020
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 4 0.5060 0.5194 0.412 0.004 0.000 0.584
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.5217 0.5546 0.380 0.608 0.000 0.012
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 1 0.4610 0.4505 0.744 0.236 0.000 0.020
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 1 0.5213 0.4601 0.724 0.052 0.000 0.224
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.3051 0.6897 0.884 0.088 0.000 0.028
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 4 0.6912 0.7590 0.216 0.192 0.000 0.592
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.3108 0.5092 0.112 0.872 0.000 0.016
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0376 0.7224 0.004 0.000 0.992 0.004
#> 4F501635-545A-479A-A95E-12C4AC30BA50 4 0.5060 0.5194 0.412 0.004 0.000 0.584
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.5165 0.3631 0.484 0.004 0.000 0.512
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.6389 0.5483 0.264 0.040 0.656 0.040
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.2593 0.6658 0.892 0.104 0.000 0.004
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.6998 0.2451 0.416 0.468 0.000 0.116
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.2924 0.6683 0.884 0.100 0.000 0.016
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.2450 0.6932 0.912 0.016 0.000 0.072
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0707 0.7214 0.980 0.000 0.000 0.020
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.5040 0.2362 0.628 0.008 0.000 0.364
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.1297 0.7180 0.964 0.016 0.000 0.020
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.4920 0.1493 0.004 0.628 0.000 0.368
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.4804 0.2400 0.616 0.000 0.000 0.384
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0779 0.7207 0.980 0.004 0.000 0.016
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 4 0.6860 0.7151 0.164 0.244 0.000 0.592
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.4485 0.5951 0.248 0.740 0.000 0.012
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.4697 0.2971 0.644 0.000 0.000 0.356
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 4 0.7830 0.4014 0.272 0.324 0.000 0.404
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.1297 0.7180 0.964 0.016 0.000 0.020
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.6074 0.1757 0.600 0.060 0.000 0.340
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.1833 0.7109 0.944 0.032 0.000 0.024
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.4746 0.6022 0.304 0.688 0.000 0.008
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.6912 0.7590 0.216 0.192 0.000 0.592
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.5038 0.3639 0.684 0.020 0.000 0.296
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.5055 0.5647 0.368 0.624 0.000 0.008
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4964 0.2452 0.616 0.004 0.000 0.380
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 1 0.7605 -0.3940 0.452 0.212 0.000 0.336
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.1182 0.7186 0.968 0.016 0.000 0.016
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.6875 0.7546 0.220 0.184 0.000 0.596
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.4936 0.2518 0.624 0.004 0.000 0.372
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.4804 0.2400 0.616 0.000 0.000 0.384
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.7577 0.5217 0.004 0.328 0.484 0.184
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.7241 0.000 0.000 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.5220 0.4980 0.424 0.008 0.000 0.568
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.2522 0.6891 0.908 0.016 0.000 0.076
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.7241 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.5802 0.07918 0.096 0.516 0.000 0.388 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.5971 0.41273 0.404 0.496 0.000 0.004 0.096
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.2993 0.72785 0.884 0.044 0.000 0.024 0.048
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 4 0.3039 0.66491 0.012 0.152 0.000 0.836 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.5727 0.36911 0.100 0.340 0.000 0.560 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.4186 0.66567 0.768 0.184 0.000 0.004 0.044
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.3323 0.73028 0.868 0.048 0.000 0.040 0.044
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.3986 0.72336 0.828 0.048 0.000 0.080 0.044
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.1990 0.72951 0.928 0.028 0.000 0.004 0.040
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 4 0.2411 0.68230 0.008 0.108 0.000 0.884 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.4608 0.63394 0.700 0.036 0.000 0.260 0.004
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.2544 0.72948 0.900 0.028 0.000 0.064 0.008
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.6047 0.13789 0.124 0.500 0.000 0.376 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.3242 0.60231 0.172 0.012 0.000 0.816 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.3289 0.51870 0.088 0.860 0.000 0.036 0.016
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.3346 0.52198 0.092 0.856 0.000 0.036 0.016
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.2802 0.72575 0.876 0.016 0.000 0.100 0.008
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.3628 0.58719 0.772 0.216 0.000 0.000 0.012
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.4948 0.28726 0.536 0.028 0.000 0.436 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 4 0.6912 -0.06694 0.300 0.004 0.304 0.392 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.3597 0.68919 0.800 0.012 0.000 0.180 0.008
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.6019 -0.08151 0.036 0.496 0.000 0.424 0.044
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.2170 0.73347 0.924 0.020 0.000 0.020 0.036
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.2701 0.72294 0.896 0.048 0.000 0.012 0.044
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.6575 0.27769 0.488 0.100 0.000 0.380 0.032
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.2017 0.68903 0.008 0.080 0.000 0.912 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.1901 0.73548 0.932 0.004 0.000 0.024 0.040
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.7523 0.26512 0.092 0.500 0.000 0.232 0.176
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.4262 0.01610 0.440 0.000 0.000 0.560 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.6046 0.50931 0.600 0.060 0.000 0.296 0.044
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.3916 0.58298 0.012 0.256 0.000 0.732 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 5 0.6346 0.34395 0.048 0.048 0.380 0.004 0.520
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#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.2746 0.72838 0.872 0.008 0.000 0.112 0.008
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.66606 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 6 0.6370 0.36071 0.036 0.008 0.000 0.300 0.144 0.512
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.3391 0.67320 0.148 0.000 0.000 0.812 0.024 0.016
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1644 0.46683 0.920 0.000 0.000 0.000 0.076 0.004
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.3239 0.69256 0.012 0.004 0.000 0.064 0.072 0.848
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 6 0.4170 0.66844 0.040 0.000 0.000 0.168 0.032 0.760
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.3384 0.41607 0.760 0.000 0.000 0.228 0.004 0.008
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.1333 0.48372 0.944 0.000 0.000 0.000 0.048 0.008
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.1257 0.49409 0.952 0.000 0.000 0.000 0.028 0.020
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.2003 0.46118 0.884 0.000 0.000 0.000 0.116 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.0909 0.70334 0.000 0.000 0.000 0.012 0.020 0.968
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.5263 0.10262 0.552 0.000 0.000 0.020 0.060 0.368
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4080 0.34666 0.724 0.000 0.000 0.020 0.236 0.020
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 6 0.5765 0.20334 0.064 0.000 0.000 0.428 0.044 0.464
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 6 0.3575 0.61706 0.128 0.000 0.000 0.000 0.076 0.796
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0146 0.73033 0.000 0.004 0.996 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.4339 0.55470 0.016 0.012 0.000 0.716 0.236 0.020
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0291 0.73028 0.000 0.004 0.992 0.000 0.004 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.4231 0.55878 0.016 0.012 0.000 0.724 0.232 0.016
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.5350 -0.15854 0.532 0.000 0.000 0.012 0.376 0.080
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 4 0.5118 0.13006 0.452 0.000 0.000 0.484 0.052 0.012
#> FE853F93-5273-434D-8021-E084F9494E05 6 0.5673 0.10291 0.336 0.000 0.000 0.008 0.136 0.520
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 5 0.7011 0.35788 0.060 0.004 0.264 0.000 0.416 0.256
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.5760 0.45332 0.412 0.000 0.000 0.004 0.436 0.148
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.6674 0.34199 0.032 0.012 0.000 0.240 0.232 0.484
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.2964 0.38216 0.792 0.000 0.000 0.004 0.204 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.1588 0.46962 0.924 0.000 0.000 0.000 0.072 0.004
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.5496 0.24199 0.600 0.000 0.000 0.012 0.240 0.148
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 6 0.0779 0.70481 0.008 0.000 0.000 0.008 0.008 0.976
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.3867 0.16012 0.660 0.000 0.000 0.000 0.328 0.012
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.8171 0.17313 0.064 0.172 0.000 0.240 0.140 0.384
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 6 0.6012 -0.13875 0.320 0.000 0.000 0.000 0.256 0.424
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4018 0.39405 0.768 0.000 0.000 0.004 0.112 0.116
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 6 0.3256 0.69608 0.020 0.000 0.000 0.112 0.032 0.836
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 2 0.4841 0.23912 0.000 0.536 0.412 0.000 0.048 0.004
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.1908 0.47590 0.900 0.000 0.000 0.000 0.096 0.004
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5437 0.24223 0.608 0.000 0.000 0.008 0.204 0.180
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.5478 0.18408 0.584 0.000 0.000 0.004 0.240 0.172
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.4206 0.56025 0.016 0.012 0.000 0.728 0.228 0.016
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.3844 0.39518 0.764 0.000 0.000 0.028 0.192 0.016
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.4084 0.56764 0.016 0.008 0.000 0.736 0.224 0.016
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 6 0.5639 0.56542 0.036 0.004 0.000 0.200 0.124 0.636
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.3533 0.38940 0.776 0.000 0.000 0.020 0.196 0.008
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 6 0.5327 0.37708 0.268 0.000 0.000 0.020 0.096 0.616
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.5889 0.43161 0.100 0.004 0.532 0.004 0.340 0.020
#> 69595C5D-6655-4065-8943-90045A2B2478 6 0.6792 0.28438 0.200 0.008 0.000 0.276 0.048 0.468
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 6 0.2716 0.68947 0.096 0.000 0.000 0.028 0.008 0.868
#> 36B2E208-FF01-4249-92C3-BE77D426691B 6 0.0806 0.70760 0.020 0.000 0.000 0.008 0.000 0.972
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0291 0.73028 0.000 0.004 0.992 0.000 0.004 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.4242 -0.05305 0.572 0.000 0.000 0.004 0.412 0.012
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.3470 0.27204 0.740 0.000 0.000 0.000 0.248 0.012
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 5 0.6754 0.41505 0.208 0.004 0.276 0.004 0.468 0.040
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.1387 0.47360 0.932 0.000 0.000 0.000 0.068 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.3243 0.42685 0.780 0.000 0.000 0.208 0.004 0.008
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.6666 -0.03350 0.468 0.000 0.000 0.064 0.172 0.296
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0146 0.73033 0.000 0.004 0.996 0.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 6 0.2795 0.67000 0.044 0.000 0.000 0.000 0.100 0.856
#> B730E9AD-DA24-46A3-BE56-A89447421C09 6 0.6815 0.43624 0.196 0.052 0.004 0.052 0.120 0.576
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.3721 0.40447 0.728 0.000 0.000 0.252 0.004 0.016
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.7288 0.19779 0.040 0.464 0.000 0.096 0.104 0.296
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.3878 0.39763 0.772 0.000 0.000 0.000 0.112 0.116
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 2 0.4053 0.37246 0.300 0.676 0.004 0.000 0.020 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.4598 0.61583 0.016 0.004 0.644 0.004 0.316 0.016
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0291 0.71601 0.000 0.992 0.004 0.004 0.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 6 0.6513 0.38358 0.068 0.004 0.000 0.284 0.128 0.516
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 6 0.3210 0.67199 0.124 0.000 0.000 0.012 0.032 0.832
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.3479 0.42561 0.768 0.000 0.000 0.212 0.008 0.012
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.1262 0.49631 0.956 0.000 0.000 0.008 0.016 0.020
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4908 0.10410 0.472 0.000 0.000 0.480 0.036 0.012
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.2308 0.47457 0.892 0.000 0.000 0.000 0.040 0.068
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.6392 0.49743 0.028 0.164 0.604 0.000 0.148 0.056
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.4688 0.31302 0.400 0.000 0.000 0.560 0.032 0.008
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 6 0.3543 0.65652 0.024 0.008 0.040 0.000 0.096 0.832
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3216 0.61207 0.032 0.000 0.000 0.852 0.052 0.064
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.3273 0.67649 0.136 0.000 0.000 0.824 0.024 0.016
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 6 0.2573 0.66648 0.024 0.000 0.000 0.000 0.112 0.864
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 6 0.6040 -0.02571 0.280 0.000 0.000 0.004 0.252 0.464
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.1141 0.48152 0.948 0.000 0.000 0.000 0.052 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.3405 0.31023 0.724 0.004 0.000 0.000 0.272 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0146 0.73033 0.000 0.004 0.996 0.000 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.4633 0.63482 0.008 0.048 0.684 0.000 0.252 0.008
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 6 0.5884 -0.20594 0.384 0.000 0.000 0.000 0.200 0.416
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.2454 0.43332 0.840 0.000 0.000 0.000 0.160 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0436 0.71516 0.000 0.988 0.000 0.004 0.004 0.004
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 6 0.4032 0.53715 0.068 0.000 0.000 0.000 0.192 0.740
#> 7DA4280C-511E-493E-B187-88ECCA427C33 6 0.7983 0.29865 0.088 0.228 0.000 0.128 0.120 0.436
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.5547 -0.07926 0.516 0.108 0.004 0.000 0.368 0.004
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 2 0.6035 -0.00504 0.068 0.452 0.004 0.436 0.024 0.016
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.3502 0.66897 0.160 0.000 0.000 0.800 0.024 0.016
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 6 0.7505 0.49519 0.132 0.116 0.004 0.128 0.084 0.536
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.4910 0.61675 0.028 0.008 0.648 0.004 0.292 0.020
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.5457 0.29339 0.612 0.000 0.000 0.160 0.216 0.012
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.4118 0.01058 0.592 0.000 0.000 0.004 0.396 0.008
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.4801 0.32464 0.696 0.000 0.000 0.016 0.096 0.192
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.1501 0.48436 0.924 0.000 0.000 0.000 0.076 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 6 0.4636 0.45596 0.148 0.000 0.000 0.000 0.160 0.692
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.5134 0.09437 0.468 0.000 0.000 0.472 0.028 0.032
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.5558 0.41477 0.428 0.000 0.008 0.008 0.476 0.080
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.3035 0.44709 0.828 0.000 0.000 0.016 0.148 0.008
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 6 0.5069 0.63086 0.032 0.004 0.000 0.144 0.116 0.704
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 6 0.6115 0.08043 0.240 0.000 0.004 0.008 0.248 0.500
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 2 0.4910 0.19958 0.000 0.520 0.424 0.000 0.052 0.004
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 6 0.0767 0.70376 0.004 0.000 0.000 0.008 0.012 0.976
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.5519 0.53264 0.008 0.180 0.624 0.000 0.180 0.008
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.5141 0.04829 0.504 0.000 0.000 0.004 0.072 0.420
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.5374 -0.32125 0.476 0.004 0.004 0.004 0.444 0.068
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 6 0.1807 0.69103 0.020 0.000 0.000 0.000 0.060 0.920
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 6 0.0520 0.70391 0.008 0.000 0.000 0.008 0.000 0.984
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.5099 -0.27132 0.496 0.000 0.000 0.000 0.424 0.080
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 4 0.4417 0.55336 0.016 0.012 0.000 0.712 0.236 0.024
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 1 0.4768 0.30100 0.668 0.000 0.000 0.008 0.244 0.080
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0551 0.73044 0.000 0.004 0.984 0.004 0.008 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 6 0.6739 -0.14316 0.292 0.016 0.004 0.012 0.244 0.432
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.4296 0.63014 0.020 0.004 0.668 0.000 0.300 0.008
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.4231 0.55878 0.016 0.012 0.000 0.724 0.232 0.016
#> DFADB933-D083-4175-88A6-72086FD5115E 1 0.6235 -0.38366 0.356 0.000 0.000 0.004 0.344 0.296
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0291 0.73046 0.000 0.004 0.992 0.000 0.004 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.3149 0.39378 0.824 0.000 0.000 0.000 0.132 0.044
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 1 0.5755 0.29623 0.552 0.000 0.000 0.328 0.060 0.060
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 1 0.5229 -0.28619 0.492 0.000 0.000 0.004 0.424 0.080
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.5905 0.16608 0.536 0.000 0.000 0.012 0.244 0.208
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 6 0.4111 0.65045 0.000 0.024 0.000 0.084 0.112 0.780
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.4023 0.33303 0.724 0.000 0.000 0.020 0.240 0.016
#> FE330797-5A40-45A8-98DF-43A33369E90F 1 0.5266 0.04998 0.576 0.000 0.000 0.004 0.312 0.108
#> DAD951A3-C22E-42F0-BB02-854413DDC351 1 0.5955 -0.38589 0.440 0.000 0.000 0.008 0.384 0.168
#> 2C8F0772-0369-4774-8FF5-EA5F729023F2 6 0.6465 0.54679 0.152 0.032 0.000 0.168 0.052 0.596
#> 301164A4-320D-4A28-AF0D-3DB2CCFD4518 3 0.0551 0.73044 0.000 0.004 0.984 0.004 0.008 0.000
#> BBBBFEB6-A5A4-49E1-933E-BC292673402E 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> CEC3699E-8DDB-4197-A4ED-93AF06852CCD 4 0.2912 0.66919 0.116 0.000 0.000 0.844 0.040 0.000
#> A4338E43-C48E-4D1F-9CAB-83DCBC2120E0 6 0.1370 0.70867 0.012 0.000 0.000 0.036 0.004 0.948
#> FF65D6EB-1906-47CC-BE39-B78EACA16821 4 0.6634 0.13706 0.012 0.016 0.000 0.428 0.248 0.296
#> 1A685E67-A37C-446D-BD58-200D2289E7B5 6 0.0405 0.70382 0.004 0.000 0.000 0.008 0.000 0.988
#> 8BD73BB2-5676-42F3-871E-E149EBC1F7A0 6 0.4306 0.67380 0.080 0.004 0.000 0.108 0.032 0.776
#> 8523C305-848B-4825-B3A2-B37D4E6977F6 1 0.1262 0.49631 0.956 0.000 0.000 0.008 0.016 0.020
#> 1739DA32-1AD3-4487-9C6F-3BB1C4C42AEA 6 0.2963 0.68269 0.096 0.000 0.000 0.012 0.036 0.856
#> 1019E38A-603B-4631-99F5-9FEF5CB91855 6 0.2573 0.66051 0.024 0.000 0.000 0.000 0.112 0.864
#> 271AB61C-7B2D-4874-BCD5-803572F485CE 6 0.1180 0.70671 0.012 0.000 0.000 0.012 0.016 0.960
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#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 5 0.6825 0.33683 0.152 0.004 0.304 0.004 0.472 0.064
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.6068 0.53308 0.344 0.000 0.000 0.008 0.448 0.200
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.4561 0.55440 0.016 0.012 0.000 0.704 0.236 0.032
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 6 0.6573 0.33594 0.016 0.020 0.000 0.236 0.240 0.488
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0551 0.73044 0.000 0.004 0.984 0.004 0.008 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.2868 0.67282 0.112 0.000 0.000 0.852 0.032 0.004
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0291 0.73028 0.000 0.004 0.992 0.000 0.004 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 1 0.2812 0.45507 0.856 0.000 0.000 0.000 0.048 0.096
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.6305 0.24023 0.032 0.004 0.000 0.516 0.168 0.280
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 1 0.4408 -0.09425 0.560 0.000 0.000 0.004 0.416 0.020
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 6 0.5026 0.62242 0.088 0.000 0.000 0.204 0.028 0.680
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 4 0.7289 0.30812 0.284 0.092 0.004 0.456 0.148 0.016
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.0665 0.49656 0.980 0.000 0.000 0.004 0.008 0.008
#> DDC71530-38B7-483F-83DC-1BCC550719C3 1 0.4317 -0.05154 0.572 0.000 0.000 0.004 0.408 0.016
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 6 0.2376 0.69091 0.068 0.000 0.000 0.000 0.044 0.888
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 6 0.1296 0.69867 0.012 0.000 0.000 0.004 0.032 0.952
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 4 0.6692 -0.01085 0.016 0.012 0.000 0.368 0.244 0.360
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.5711 -0.10480 0.520 0.108 0.004 0.000 0.356 0.012
#> C5102A81-265F-4CD9-9B6C-390348FB690C 6 0.4377 0.66850 0.040 0.004 0.000 0.160 0.040 0.756
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.4231 0.55878 0.016 0.012 0.000 0.724 0.232 0.016
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 6 0.6492 -0.11049 0.036 0.004 0.164 0.000 0.340 0.456
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 3 0.7135 0.32724 0.108 0.132 0.412 0.000 0.340 0.008
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.1663 0.46462 0.912 0.000 0.000 0.000 0.088 0.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 6 0.3134 0.62654 0.036 0.000 0.000 0.000 0.144 0.820
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2170 0.60722 0.016 0.000 0.000 0.908 0.060 0.016
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.3224 0.67016 0.132 0.000 0.000 0.824 0.040 0.004
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 6 0.6192 -0.08144 0.284 0.000 0.000 0.012 0.240 0.464
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.5808 -0.40586 0.444 0.004 0.008 0.004 0.436 0.104
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 6 0.0767 0.70441 0.012 0.000 0.000 0.008 0.004 0.976
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 4 0.5525 0.50683 0.016 0.072 0.000 0.644 0.236 0.032
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0405 0.72947 0.000 0.004 0.988 0.000 0.008 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 6 0.2826 0.64784 0.028 0.000 0.000 0.000 0.128 0.844
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 6 0.3796 0.60194 0.084 0.000 0.000 0.000 0.140 0.776
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.4034 0.63927 0.008 0.004 0.680 0.000 0.300 0.008
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 4 0.5335 0.36450 0.352 0.000 0.000 0.556 0.076 0.016
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 6 0.6370 0.59750 0.104 0.044 0.004 0.148 0.064 0.636
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.3875 0.39922 0.716 0.000 0.000 0.260 0.008 0.016
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.6197 0.55374 0.300 0.000 0.004 0.008 0.468 0.220
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3979 0.10059 0.628 0.000 0.000 0.000 0.360 0.012
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 6 0.5345 0.25807 0.188 0.000 0.000 0.000 0.220 0.592
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0363 0.49321 0.988 0.000 0.000 0.000 0.012 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0436 0.71516 0.000 0.988 0.000 0.004 0.004 0.004
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.5753 0.17894 0.556 0.000 0.000 0.012 0.264 0.168
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.3225 0.44023 0.820 0.000 0.000 0.016 0.148 0.016
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 6 0.0767 0.70376 0.004 0.000 0.000 0.008 0.012 0.976
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 4 0.5172 0.52104 0.016 0.016 0.000 0.660 0.244 0.064
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.5105 0.15238 0.564 0.000 0.000 0.004 0.080 0.352
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 6 0.5212 0.61780 0.032 0.004 0.000 0.156 0.120 0.688
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0779 0.49748 0.976 0.000 0.000 0.008 0.008 0.008
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0146 0.73033 0.000 0.004 0.996 0.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 6 0.4974 0.41148 0.128 0.004 0.004 0.000 0.192 0.672
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.5055 -0.25662 0.500 0.000 0.004 0.004 0.440 0.052
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.4218 0.56181 0.016 0.008 0.000 0.724 0.232 0.020
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 6 0.0665 0.70391 0.008 0.000 0.000 0.008 0.004 0.980
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.6099 0.32215 0.348 0.000 0.000 0.000 0.368 0.284
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.3438 0.58486 0.016 0.008 0.000 0.816 0.144 0.016
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.5453 0.24553 0.604 0.000 0.000 0.012 0.244 0.140
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 6 0.4418 0.63455 0.140 0.000 0.000 0.100 0.016 0.744
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0520 0.49573 0.984 0.000 0.000 0.000 0.008 0.008
#> C2750CB6-DD39-41E2-B615-271D72A8876C 6 0.1492 0.69583 0.024 0.000 0.000 0.000 0.036 0.940
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.5807 0.05958 0.516 0.000 0.000 0.004 0.284 0.196
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5640 0.20481 0.572 0.000 0.000 0.012 0.264 0.152
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.5076 -0.06744 0.000 0.456 0.476 0.000 0.064 0.004
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0436 0.72942 0.000 0.004 0.988 0.004 0.004 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 6 0.2586 0.67566 0.032 0.000 0.000 0.000 0.100 0.868
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.5958 0.48735 0.388 0.000 0.000 0.008 0.436 0.168
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0146 0.73130 0.000 0.000 0.996 0.000 0.004 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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 17524 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.962 0.985 0.2760 0.725 0.725
#> 3 3 0.748 0.868 0.942 1.0484 0.678 0.564
#> 4 4 0.477 0.550 0.774 0.2305 0.730 0.450
#> 5 5 0.536 0.587 0.769 0.1011 0.852 0.547
#> 6 6 0.604 0.519 0.726 0.0632 0.906 0.629
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.0000 0.9897 0.000 1.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 1 0.0000 0.9542 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 2 0.0000 0.9897 0.000 1.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 2 0.0000 0.9897 0.000 1.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.9897 0.000 1.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.0000 0.9897 0.000 1.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 2 0.0000 0.9897 0.000 1.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 2 0.0000 0.9897 0.000 1.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 2 0.0000 0.9897 0.000 1.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 2 0.0000 0.9897 0.000 1.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.9897 0.000 1.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.0000 0.9897 0.000 1.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 2 0.0000 0.9897 0.000 1.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.0000 0.9897 0.000 1.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 2 0.0000 0.9897 0.000 1.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 1 0.0000 0.9542 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.9897 0.000 1.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 1 0.0000 0.9542 1.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.0000 0.9897 0.000 1.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 2 0.0000 0.9897 0.000 1.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 2 0.0000 0.9897 0.000 1.000
#> FE853F93-5273-434D-8021-E084F9494E05 2 0.0000 0.9897 0.000 1.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 1 0.0000 0.9542 1.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 1 0.0000 0.9542 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 2 0.0000 0.9897 0.000 1.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.9897 0.000 1.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 2 0.0000 0.9897 0.000 1.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 2 0.0000 0.9897 0.000 1.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 2 0.0000 0.9897 0.000 1.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.0000 0.9897 0.000 1.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 2 0.0000 0.9897 0.000 1.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.9897 0.000 1.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 2 0.0000 0.9897 0.000 1.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 2 0.0000 0.9897 0.000 1.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.0000 0.9897 0.000 1.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 1 0.0000 0.9542 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 1 0.0000 0.9542 1.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 2 0.0000 0.9897 0.000 1.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 2 0.0000 0.9897 0.000 1.000
#> 434163EA-432B-41F3-8321-7180A8635124 2 0.0672 0.9817 0.008 0.992
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.0000 0.9897 0.000 1.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 2 0.0000 0.9897 0.000 1.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.0000 0.9897 0.000 1.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.9897 0.000 1.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 2 0.0000 0.9897 0.000 1.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 2 0.0000 0.9897 0.000 1.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 1 0.0000 0.9542 1.000 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.0000 0.9897 0.000 1.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.0000 0.9897 0.000 1.000
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#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 1 0.0000 0.9542 1.000 0.000
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 2 0.0000 0.9897 0.000 1.000
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 2 0.0000 0.9897 0.000 1.000
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0000 0.9897 0.000 1.000
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 1 0.0000 0.9542 1.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 2 0.0000 0.9897 0.000 1.000
#> 20287718-EDD7-4046-A498-E65C86803178 1 0.0000 0.9542 1.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 2 0.0000 0.9897 0.000 1.000
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 2 0.0000 0.9897 0.000 1.000
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 2 0.0000 0.9897 0.000 1.000
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 2 0.0000 0.9897 0.000 1.000
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 2 0.0000 0.9897 0.000 1.000
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 2 0.0000 0.9897 0.000 1.000
#> DDC71530-38B7-483F-83DC-1BCC550719C3 2 0.0000 0.9897 0.000 1.000
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.0000 0.9897 0.000 1.000
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 2 0.0000 0.9897 0.000 1.000
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.0000 0.9897 0.000 1.000
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 2 0.0000 0.9897 0.000 1.000
#> C5102A81-265F-4CD9-9B6C-390348FB690C 2 0.0000 0.9897 0.000 1.000
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 2 0.0000 0.9897 0.000 1.000
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.0000 0.9542 1.000 0.000
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 1 0.6801 0.7879 0.820 0.180
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 2 0.0000 0.9897 0.000 1.000
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 2 0.0000 0.9897 0.000 1.000
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 2 0.0000 0.9897 0.000 1.000
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 2 0.0000 0.9897 0.000 1.000
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.0000 0.9897 0.000 1.000
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 2 0.0000 0.9897 0.000 1.000
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0000 0.9897 0.000 1.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.0000 0.9897 0.000 1.000
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 1 0.0000 0.9542 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 1 0.0000 0.9542 1.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 2 0.0000 0.9897 0.000 1.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 2 0.0000 0.9897 0.000 1.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 1 0.0000 0.9542 1.000 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 2 0.0000 0.9897 0.000 1.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.9897 0.000 1.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 2 0.0000 0.9897 0.000 1.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 2 0.8327 0.6207 0.264 0.736
#> C20F209A-2102-4502-80FA-17AF04601987 2 0.0000 0.9897 0.000 1.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 2 0.0000 0.9897 0.000 1.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 2 0.0000 0.9897 0.000 1.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.9897 0.000 1.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 2 0.0000 0.9897 0.000 1.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 2 0.0000 0.9897 0.000 1.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.0000 0.9897 0.000 1.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.9897 0.000 1.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 2 0.0000 0.9897 0.000 1.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.9897 0.000 1.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 2 0.0000 0.9897 0.000 1.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 1 0.0000 0.9542 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 2 0.9977 0.0397 0.472 0.528
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 2 0.0000 0.9897 0.000 1.000
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.0000 0.9897 0.000 1.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.0000 0.9897 0.000 1.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.8207 0.6838 0.744 0.256
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 2 0.0000 0.9897 0.000 1.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 2 0.0000 0.9897 0.000 1.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 1 0.0000 0.9542 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.0000 0.9897 0.000 1.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 2 0.0000 0.9897 0.000 1.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 2 0.0000 0.9897 0.000 1.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 2 0.0000 0.9897 0.000 1.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 2 0.0000 0.9897 0.000 1.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 1 0.0000 0.9542 1.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 1 0.0000 0.9542 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 2 0.0000 0.9897 0.000 1.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 2 0.0000 0.9897 0.000 1.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 1 0.0000 0.9542 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.2448 0.8551 0.076 0.924 0.000
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.9343 0.000 0.000 1.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 1 0.2878 0.8755 0.904 0.096 0.000
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.0000 0.9428 1.000 0.000 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0000 0.8818 0.000 1.000 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.4346 0.7788 0.184 0.816 0.000
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 1 0.0000 0.9428 1.000 0.000 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.0000 0.9428 1.000 0.000 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.0000 0.9428 1.000 0.000 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.0000 0.9428 1.000 0.000 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.0000 0.8818 0.000 1.000 0.000
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.0424 0.9397 0.992 0.008 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.0000 0.9428 1.000 0.000 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 2 0.5098 0.7158 0.248 0.752 0.000
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 1 0.0424 0.9397 0.992 0.008 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.9343 0.000 0.000 1.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 2 0.0000 0.8818 0.000 1.000 0.000
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.9343 0.000 0.000 1.000
#> 479B4832-82DB-4176-9D24-D588F2903617 2 0.3619 0.8177 0.136 0.864 0.000
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.0237 0.9414 0.996 0.004 0.000
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.0000 0.9428 1.000 0.000 0.000
#> FE853F93-5273-434D-8021-E084F9494E05 1 0.1753 0.9147 0.952 0.048 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.0000 0.9343 0.000 0.000 1.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.9343 0.000 0.000 1.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.0592 0.9377 0.988 0.012 0.000
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.0000 0.8818 0.000 1.000 0.000
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.0000 0.9428 1.000 0.000 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.0000 0.9428 1.000 0.000 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.0000 0.9428 1.000 0.000 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 2 0.4654 0.7570 0.208 0.792 0.000
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.0000 0.9428 1.000 0.000 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.0000 0.8818 0.000 1.000 0.000
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.0000 0.9428 1.000 0.000 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.0000 0.9428 1.000 0.000 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.5733 0.5853 0.324 0.676 0.000
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.9343 0.000 0.000 1.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1163 0.9143 0.000 0.028 0.972
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.0000 0.9428 1.000 0.000 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.0000 0.9428 1.000 0.000 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.0000 0.9428 1.000 0.000 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 2 0.3816 0.8088 0.148 0.852 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.0000 0.9428 1.000 0.000 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 2 0.5465 0.6568 0.288 0.712 0.000
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 2 0.0000 0.8818 0.000 1.000 0.000
#> E6AF8360-3A04-41E9-97D3-871067377F76 1 0.0000 0.9428 1.000 0.000 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.6235 0.2160 0.564 0.436 0.000
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.0000 0.9343 0.000 0.000 1.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.5327 0.6850 0.272 0.728 0.000
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 2 0.6295 0.1519 0.472 0.528 0.000
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.3038 0.8389 0.104 0.896 0.000
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0000 0.9343 0.000 0.000 1.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.0000 0.9428 1.000 0.000 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.0000 0.9428 1.000 0.000 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 3 0.3551 0.7910 0.132 0.000 0.868
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.0000 0.9428 1.000 0.000 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.0000 0.9428 1.000 0.000 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 1 0.4654 0.7450 0.792 0.208 0.000
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.9343 0.000 0.000 1.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 1 0.4555 0.7570 0.800 0.200 0.000
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.0000 0.8818 0.000 1.000 0.000
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.0000 0.9428 1.000 0.000 0.000
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0000 0.8818 0.000 1.000 0.000
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.0000 0.9428 1.000 0.000 0.000
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.0000 0.9428 1.000 0.000 0.000
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.0000 0.9343 0.000 0.000 1.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.0000 0.8818 0.000 1.000 0.000
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 2 0.1964 0.8652 0.056 0.944 0.000
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 1 0.2878 0.8753 0.904 0.096 0.000
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 1 0.0000 0.9428 1.000 0.000 0.000
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.0000 0.9428 1.000 0.000 0.000
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 1 0.0000 0.9428 1.000 0.000 0.000
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.0000 0.9428 1.000 0.000 0.000
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.0592 0.9248 0.000 0.012 0.988
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.0000 0.9428 1.000 0.000 0.000
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.0237 0.9313 0.000 0.004 0.996
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 1 0.5905 0.4668 0.648 0.352 0.000
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 1 0.4842 0.7215 0.776 0.224 0.000
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.5497 0.6023 0.708 0.292 0.000
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.0000 0.9428 1.000 0.000 0.000
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.0000 0.9428 1.000 0.000 0.000
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.0000 0.9428 1.000 0.000 0.000
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.9343 0.000 0.000 1.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.9343 0.000 0.000 1.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 1 0.0000 0.9428 1.000 0.000 0.000
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.9343 0.000 0.000 1.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.0000 0.9428 1.000 0.000 0.000
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.0000 0.8818 0.000 1.000 0.000
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.2356 0.8937 0.928 0.000 0.072
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.0000 0.8818 0.000 1.000 0.000
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.0000 0.9428 1.000 0.000 0.000
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 1 0.2066 0.9057 0.940 0.060 0.000
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 1 0.2165 0.9025 0.936 0.064 0.000
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0000 0.8818 0.000 1.000 0.000
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.0000 0.9343 0.000 0.000 1.000
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.0892 0.9333 0.980 0.020 0.000
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 1 0.0000 0.9428 1.000 0.000 0.000
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 1 0.0000 0.9428 1.000 0.000 0.000
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.0000 0.9428 1.000 0.000 0.000
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 1 0.0000 0.9428 1.000 0.000 0.000
#> 60A51C36-7423-4C84-8034-325DE57046BE 1 0.0000 0.9428 1.000 0.000 0.000
#> E3A5FB64-EB24-4A24-9B79-539012C57711 3 0.5968 0.4445 0.364 0.000 0.636
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.0000 0.9428 1.000 0.000 0.000
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 2 0.0000 0.8818 0.000 1.000 0.000
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.9343 0.000 0.000 1.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 2 0.4931 0.7341 0.232 0.768 0.000
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0000 0.9343 0.000 0.000 1.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.0000 0.8818 0.000 1.000 0.000
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0000 0.9343 0.000 0.000 1.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 1 0.0000 0.9428 1.000 0.000 0.000
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.0000 0.9428 1.000 0.000 0.000
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 2 0.0661 0.8802 0.008 0.988 0.004
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#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.3686 0.8310 0.860 0.140 0.000
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.5760 0.5251 0.672 0.328 0.000
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0000 0.9343 0.000 0.000 1.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.1163 0.9283 0.972 0.028 0.000
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0000 0.8818 0.000 1.000 0.000
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 1 0.0000 0.9428 1.000 0.000 0.000
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 3 0.5431 0.5850 0.284 0.000 0.716
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.0000 0.9428 1.000 0.000 0.000
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.0000 0.9428 1.000 0.000 0.000
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.0000 0.9428 1.000 0.000 0.000
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.0000 0.8818 0.000 1.000 0.000
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.0000 0.9428 1.000 0.000 0.000
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.0000 0.9428 1.000 0.000 0.000
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.1529 0.8717 0.040 0.960 0.000
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.0000 0.8818 0.000 1.000 0.000
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.0000 0.9428 1.000 0.000 0.000
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.0000 0.8818 0.000 1.000 0.000
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.0000 0.9428 1.000 0.000 0.000
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.9343 0.000 0.000 1.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 3 0.4605 0.6974 0.204 0.000 0.796
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.0424 0.9392 0.992 0.000 0.008
#> F17B682D-A902-4730-A300-5C163209F7CD 2 0.3551 0.8206 0.132 0.868 0.000
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.2537 0.8529 0.080 0.920 0.000
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 3 0.5835 0.5028 0.340 0.000 0.660
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 1 0.6308 -0.0123 0.508 0.492 0.000
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.0000 0.9428 1.000 0.000 0.000
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.9343 0.000 0.000 1.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.4931 0.7331 0.232 0.768 0.000
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.0000 0.9428 1.000 0.000 0.000
#> C2750CB6-DD39-41E2-B615-271D72A8876C 1 0.5560 0.5860 0.700 0.300 0.000
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.0000 0.9428 1.000 0.000 0.000
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.0000 0.9428 1.000 0.000 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0000 0.9343 0.000 0.000 1.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.9343 0.000 0.000 1.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 1 0.3686 0.8314 0.860 0.140 0.000
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.0237 0.9414 0.996 0.004 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.9343 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.4459 0.62195 0.032 0.780 0.000 0.188
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2281 0.63586 0.096 0.000 0.000 0.904
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 1 0.1867 0.65257 0.928 0.000 0.000 0.072
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.0592 0.79250 0.000 0.984 0.000 0.016
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 2 0.6201 0.19460 0.060 0.564 0.000 0.376
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.4564 0.19678 0.328 0.000 0.000 0.672
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 1 0.4898 0.57820 0.584 0.000 0.000 0.416
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4564 0.55202 0.672 0.000 0.000 0.328
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 1 0.4543 0.65771 0.676 0.000 0.000 0.324
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.4585 0.53180 0.000 0.668 0.000 0.332
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 1 0.4888 0.42767 0.588 0.000 0.000 0.412
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 1 0.4661 0.64710 0.652 0.000 0.000 0.348
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.6229 0.17678 0.056 0.416 0.000 0.528
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.1022 0.64331 0.032 0.000 0.000 0.968
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.4564 0.30872 0.000 0.328 0.000 0.672
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0188 0.90259 0.000 0.004 0.996 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.3024 0.61001 0.000 0.148 0.000 0.852
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 1 0.4898 0.56656 0.584 0.000 0.000 0.416
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 1 0.4477 0.66022 0.688 0.000 0.000 0.312
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.2345 0.63484 0.100 0.000 0.000 0.900
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.5092 0.72835 0.140 0.000 0.764 0.096
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 1 0.1867 0.65241 0.928 0.000 0.000 0.072
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.4477 0.56624 0.000 0.688 0.000 0.312
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 1 0.4713 0.62722 0.640 0.000 0.000 0.360
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 1 0.3873 0.69122 0.772 0.000 0.000 0.228
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4916 0.39011 0.576 0.000 0.000 0.424
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.4584 0.32784 0.004 0.300 0.000 0.696
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 1 0.4250 0.67700 0.724 0.000 0.000 0.276
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.2081 0.78489 0.000 0.916 0.000 0.084
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.2704 0.58625 0.124 0.000 0.000 0.876
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4103 0.53125 0.744 0.000 0.000 0.256
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.7216 0.44735 0.208 0.548 0.000 0.244
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.0707 0.89684 0.000 0.020 0.980 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 1 0.4406 0.66963 0.700 0.000 0.000 0.300
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.4941 0.54284 0.564 0.000 0.000 0.436
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.4790 0.53913 0.620 0.000 0.000 0.380
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.2859 0.64008 0.008 0.112 0.000 0.880
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 1 0.4382 0.67303 0.704 0.000 0.000 0.296
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.3667 0.64133 0.056 0.088 0.000 0.856
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4998 -0.16138 0.000 0.488 0.000 0.512
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.4998 -0.39260 0.488 0.000 0.000 0.512
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 1 0.6649 0.55707 0.560 0.100 0.000 0.340
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.2814 0.79355 0.132 0.000 0.868 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 2 0.7198 0.15467 0.160 0.520 0.000 0.320
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3052 0.62221 0.004 0.136 0.000 0.860
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.4898 0.28586 0.000 0.584 0.000 0.416
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0188 0.90259 0.000 0.004 0.996 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.1022 0.62007 0.968 0.000 0.000 0.032
#> EC051A62-B493-477D-AC36-BB25B09B421B 1 0.1978 0.64986 0.928 0.000 0.004 0.068
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.5837 0.27288 0.668 0.000 0.260 0.072
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 1 0.2814 0.67652 0.868 0.000 0.000 0.132
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 1 0.4996 0.44807 0.516 0.000 0.000 0.484
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.5599 0.30971 0.288 0.048 0.000 0.664
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0188 0.90259 0.000 0.004 0.996 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.2565 0.65174 0.032 0.056 0.000 0.912
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.5018 0.52548 0.012 0.656 0.000 0.332
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 1 0.4996 0.44519 0.516 0.000 0.000 0.484
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0376 0.78822 0.004 0.992 0.000 0.004
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 4 0.4103 0.45970 0.256 0.000 0.000 0.744
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 1 0.4277 0.67447 0.720 0.000 0.000 0.280
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.0592 0.89758 0.016 0.000 0.984 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.1557 0.79190 0.000 0.944 0.000 0.056
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.4103 0.46903 0.000 0.256 0.000 0.744
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.0707 0.64297 0.020 0.000 0.000 0.980
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.4817 -0.08729 0.388 0.000 0.000 0.612
#> 40424A8F-CE23-436B-8F65-4919F90F6691 4 0.4977 -0.18717 0.460 0.000 0.000 0.540
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.4992 -0.35240 0.476 0.000 0.000 0.524
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4746 0.49937 0.632 0.000 0.000 0.368
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4857 0.50886 0.008 0.324 0.668 0.000
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 1 0.4994 0.46268 0.520 0.000 0.000 0.480
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.1798 0.87545 0.000 0.016 0.944 0.040
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.3873 0.62829 0.096 0.060 0.000 0.844
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.2281 0.63586 0.096 0.000 0.000 0.904
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 4 0.5282 0.41371 0.276 0.036 0.000 0.688
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.4761 0.40386 0.664 0.000 0.004 0.332
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 1 0.4977 0.50990 0.540 0.000 0.000 0.460
#> F4F647DC-C630-429C-AD49-ADA43B652781 1 0.4304 0.67375 0.716 0.000 0.000 0.284
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.0592 0.64122 0.016 0.000 0.000 0.984
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 4 0.4855 -0.06202 0.400 0.000 0.000 0.600
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.1557 0.79190 0.000 0.944 0.000 0.056
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.7640 -0.15134 0.432 0.000 0.356 0.212
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1042 0.78690 0.020 0.972 0.000 0.008
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 1 0.4454 0.66180 0.692 0.000 0.000 0.308
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.2281 0.63586 0.096 0.000 0.000 0.904
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.4661 0.10638 0.348 0.000 0.000 0.652
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0524 0.78810 0.008 0.988 0.000 0.004
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 3 0.5446 0.70989 0.184 0.004 0.736 0.076
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 1 0.2704 0.66976 0.876 0.000 0.000 0.124
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 4 0.4222 0.21768 0.272 0.000 0.000 0.728
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.2469 0.59349 0.108 0.000 0.000 0.892
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 1 0.4679 0.63480 0.648 0.000 0.000 0.352
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.2149 0.63913 0.088 0.000 0.000 0.912
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.2530 0.64071 0.112 0.000 0.000 0.888
#> E3A5FB64-EB24-4A24-9B79-539012C57711 1 0.2773 0.54915 0.880 0.004 0.116 0.000
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 1 0.4522 0.66718 0.680 0.000 0.000 0.320
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 4 0.4996 -0.17127 0.000 0.484 0.000 0.516
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 1 0.4579 0.28076 0.720 0.272 0.004 0.004
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0188 0.90259 0.000 0.004 0.996 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 4 0.4877 0.04375 0.000 0.408 0.000 0.592
#> 5D663B98-8416-4305-A891-111B7A4DC40B 3 0.0657 0.89950 0.004 0.012 0.984 0.000
#> D2F7F14F-1588-4BBF-90D6-279D7BB7F661 4 0.4830 0.33243 0.392 0.000 0.000 0.608
#> 8BAC314B-C994-40F7-83CA-8B8F6748967A 1 0.4452 0.68444 0.732 0.000 0.008 0.260
#> 41F68F11-1545-4453-929B-F12FEBFA68AC 4 0.9212 0.01929 0.280 0.140 0.148 0.432
#> C9A2A53A-5140-4A59-9266-C585B7D30C1B 4 0.4994 -0.10926 0.000 0.480 0.000 0.520
#> 81F13318-E3B9-4EAE-99CE-0BDE653B62D1 1 0.3149 0.56094 0.880 0.000 0.032 0.088
#> E19921D5-F1F8-47CA-8DED-05CDAE943115 2 0.3494 0.71223 0.004 0.824 0.000 0.172
#> 60E02B4E-7046-4F35-B36A-03ED8CADBD5A 4 0.0707 0.64021 0.020 0.000 0.000 0.980
#> 416D3E7A-FA56-4958-8855-45FDA9C498EE 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 810FC459-F77D-462D-90B7-E77C1FD43981 1 0.5872 0.16205 0.576 0.384 0.000 0.040
#> 3EBAE078-E104-40F3-8877-05DB38BDE79E 3 0.1059 0.89234 0.016 0.000 0.972 0.012
#> 55450362-68C6-41FA-8C51-44C5DE425B6D 4 0.5296 -0.17265 0.008 0.496 0.000 0.496
#> DFADB933-D083-4175-88A6-72086FD5115E 4 0.4877 -0.07841 0.408 0.000 0.000 0.592
#> 5FA2525E-4CC3-458F-9D84-EC64052623F9 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 55788408-50CF-4518-8A82-1D94AEA7444E 1 0.4855 0.59548 0.600 0.000 0.000 0.400
#> 9BF8D68C-0B11-4592-AB5D-7FAF3E75DB17 4 0.2469 0.63295 0.108 0.000 0.000 0.892
#> 5364EF43-AEF5-49FE-A4BC-EC2659017EA0 4 0.1792 0.64317 0.068 0.000 0.000 0.932
#> 60FBFC07-C569-4069-8B71-8030DF0CAE53 1 0.4008 0.49159 0.756 0.000 0.000 0.244
#> D3C27C72-A62F-4140-8A98-9DEFA384D688 2 0.0000 0.78737 0.000 1.000 0.000 0.000
#> CDC642C3-EA74-4FC1-87CA-2748A039BF97 1 0.4679 0.63752 0.648 0.000 0.000 0.352
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#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 1 0.3400 0.63162 0.820 0.000 0.000 0.180
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 3 0.7786 -0.06491 0.204 0.004 0.412 0.380
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.2466 0.63716 0.096 0.004 0.000 0.900
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.2408 0.63215 0.104 0.000 0.000 0.896
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 2 0.7768 -0.05954 0.260 0.428 0.000 0.312
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 1 0.2888 0.66984 0.872 0.004 0.000 0.124
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.0921 0.78205 0.028 0.972 0.000 0.000
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.3400 0.72830 0.000 0.820 0.000 0.180
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0188 0.90259 0.000 0.004 0.996 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.7386 0.30150 0.488 0.008 0.132 0.372
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 4 0.7226 0.22769 0.220 0.232 0.000 0.548
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0188 0.90211 0.004 0.000 0.996 0.000
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 1 0.4277 0.67360 0.720 0.000 0.000 0.280
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.0657 0.79196 0.004 0.984 0.000 0.012
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.4948 -0.25829 0.440 0.000 0.000 0.560
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 1 0.3448 0.51946 0.828 0.004 0.168 0.000
#> C20F209A-2102-4502-80FA-17AF04601987 1 0.3764 0.68492 0.784 0.000 0.000 0.216
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 4 0.4830 0.33353 0.392 0.000 0.000 0.608
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 1 0.3569 0.68910 0.804 0.000 0.000 0.196
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.3764 0.69681 0.000 0.784 0.000 0.216
#> 21385544-2FC4-4EB8-AF55-1C046216E189 4 0.4994 0.00253 0.480 0.000 0.000 0.520
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 1 0.4522 0.65780 0.680 0.000 0.000 0.320
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.5512 0.19175 0.016 0.496 0.000 0.488
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.3074 0.74887 0.000 0.848 0.000 0.152
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 1 0.1389 0.60389 0.952 0.000 0.000 0.048
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3764 0.70367 0.000 0.784 0.000 0.216
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 1 0.4356 0.67603 0.708 0.000 0.000 0.292
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 4 0.6508 0.32645 0.296 0.000 0.104 0.600
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 1 0.4283 0.67916 0.740 0.004 0.000 0.256
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.5744 0.07403 0.028 0.436 0.000 0.536
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 4 0.5681 -0.02509 0.028 0.404 0.000 0.568
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 1 0.2814 0.51310 0.868 0.000 0.132 0.000
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.5763 0.53147 0.096 0.204 0.000 0.700
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.4382 0.50535 0.704 0.000 0.000 0.296
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.3764 0.66053 0.000 0.784 0.000 0.216
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 1 0.4431 0.67105 0.696 0.000 0.000 0.304
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.2565 0.63647 0.032 0.056 0.000 0.912
#> E258343D-271F-419D-A083-9AB6DF9A377B 1 0.1211 0.58963 0.960 0.000 0.000 0.040
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5000 0.29338 0.504 0.000 0.000 0.496
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0188 0.90221 0.000 0.004 0.996 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.90315 0.000 0.000 1.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.5884 -0.04278 0.364 0.044 0.000 0.592
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 1 0.3528 0.68848 0.808 0.000 0.000 0.192
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.90315 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 2 0.3732 0.69586 0.000 0.792 0.000 0.176 0.032
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0162 0.93262 0.004 0.000 0.996 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.1403 0.72660 0.024 0.000 0.000 0.952 0.024
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.2964 0.61607 0.120 0.000 0.000 0.024 0.856
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 2 0.2036 0.74820 0.024 0.920 0.000 0.056 0.000
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 4 0.5435 0.37550 0.000 0.352 0.000 0.576 0.072
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.3749 0.66695 0.080 0.000 0.000 0.816 0.104
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.6497 0.42224 0.212 0.000 0.000 0.312 0.476
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4072 0.68571 0.792 0.000 0.000 0.100 0.108
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.4836 0.57346 0.044 0.000 0.000 0.304 0.652
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 2 0.5000 0.64543 0.068 0.688 0.000 0.240 0.004
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 5 0.5325 0.18575 0.052 0.000 0.000 0.428 0.520
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 5 0.5594 0.60530 0.136 0.000 0.000 0.232 0.632
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.4747 0.65019 0.012 0.148 0.000 0.752 0.088
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.2983 0.70619 0.096 0.000 0.000 0.864 0.040
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.3317 0.57215 0.004 0.188 0.000 0.804 0.004
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.1492 0.71051 0.004 0.040 0.000 0.948 0.008
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.4976 0.28091 0.028 0.000 0.000 0.468 0.504
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 5 0.4169 0.62526 0.004 0.016 0.000 0.256 0.724
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.1484 0.72606 0.008 0.000 0.000 0.944 0.048
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3534 0.63481 0.256 0.000 0.744 0.000 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.3585 0.53141 0.220 0.004 0.000 0.004 0.772
#> C6AD4922-9981-4493-9F33-87A449B6EE55 2 0.4033 0.69201 0.016 0.744 0.000 0.236 0.004
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.4734 0.47917 0.024 0.000 0.000 0.372 0.604
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.3229 0.67735 0.032 0.000 0.000 0.128 0.840
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.4171 0.69597 0.784 0.000 0.000 0.112 0.104
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.5506 0.34902 0.120 0.220 0.000 0.656 0.004
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.2286 0.67762 0.004 0.000 0.000 0.108 0.888
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 2 0.3835 0.66102 0.000 0.744 0.000 0.244 0.012
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 4 0.5246 0.20286 0.384 0.000 0.000 0.564 0.052
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.4049 0.65979 0.780 0.000 0.000 0.056 0.164
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 4 0.7567 -0.14563 0.044 0.248 0.000 0.368 0.340
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1281 0.91180 0.012 0.032 0.956 0.000 0.000
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.3690 0.66584 0.020 0.000 0.000 0.200 0.780
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 5 0.6647 0.32580 0.232 0.000 0.000 0.344 0.424
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.5013 0.61446 0.700 0.000 0.000 0.108 0.192
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.0960 0.71808 0.016 0.008 0.000 0.972 0.004
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 5 0.3929 0.67458 0.028 0.000 0.000 0.208 0.764
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.1648 0.72003 0.000 0.040 0.000 0.940 0.020
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.4822 -0.07965 0.016 0.416 0.000 0.564 0.004
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.6103 0.18575 0.160 0.000 0.000 0.548 0.292
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 5 0.6065 0.38816 0.012 0.092 0.000 0.364 0.532
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.2818 0.79705 0.012 0.000 0.856 0.000 0.132
#> 69595C5D-6655-4065-8943-90045A2B2478 5 0.6347 0.15904 0.000 0.160 0.000 0.408 0.432
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3190 0.62777 0.012 0.140 0.000 0.840 0.008
#> 36B2E208-FF01-4249-92C3-BE77D426691B 2 0.4498 0.45193 0.004 0.632 0.004 0.356 0.004
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0162 0.93243 0.004 0.000 0.996 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 5 0.4450 -0.00445 0.488 0.000 0.000 0.004 0.508
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.2674 0.58563 0.140 0.000 0.000 0.004 0.856
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.4183 0.65218 0.780 0.000 0.136 0.000 0.084
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.1195 0.63704 0.028 0.000 0.000 0.012 0.960
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.5843 0.21106 0.124 0.000 0.000 0.572 0.304
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.4232 0.64389 0.020 0.040 0.000 0.788 0.152
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.4323 0.65192 0.152 0.024 0.004 0.788 0.032
#> B730E9AD-DA24-46A3-BE56-A89447421C09 2 0.5603 0.58588 0.076 0.624 0.000 0.288 0.012
#> D81BBAD4-FE03-4BC9-9633-E3E2A67E2960 4 0.5820 0.21541 0.120 0.000 0.000 0.572 0.308
#> F7521DF9-6103-449E-9C4A-A6BF64A12135 2 0.0579 0.75458 0.008 0.984 0.000 0.000 0.008
#> 470C134A-3828-4519-9BBC-16DBFA40F5A6 1 0.4221 0.63983 0.732 0.000 0.000 0.236 0.032
#> ACFF3E0E-61B6-4374-8482-6C0E8BE77BD0 5 0.1892 0.67099 0.004 0.000 0.000 0.080 0.916
#> 6D025B7D-BA51-43F7-A0D6-E9A32F4222E2 3 0.0404 0.92975 0.012 0.000 0.988 0.000 0.000
#> A3637BB5-A497-442A-BCA8-625A6A5E78F7 2 0.3355 0.71628 0.000 0.804 0.000 0.184 0.012
#> F1EA5736-FBCC-423A-BADE-9FAF4E52AB4C 4 0.3010 0.63586 0.000 0.172 0.000 0.824 0.004
#> EEBD1572-2A01-4C56-AF36-9525E2F435E6 4 0.1952 0.71393 0.084 0.000 0.000 0.912 0.004
#> 939AB9FA-9956-4A78-B676-444DA091D1AC 4 0.5504 0.48943 0.224 0.000 0.000 0.644 0.132
#> 40424A8F-CE23-436B-8F65-4919F90F6691 1 0.5391 0.50154 0.616 0.000 0.000 0.300 0.084
#> 0ABF8DA0-9E14-4092-9497-03C355B53246 4 0.5233 0.34634 0.076 0.000 0.000 0.636 0.288
#> 95AFBE7A-9495-433D-8CF0-41D126110428 1 0.4057 0.68973 0.792 0.000 0.000 0.088 0.120
#> 26635F72-F34D-4543-908F-484441832E9E 3 0.4265 0.63540 0.008 0.268 0.712 0.000 0.012
#> 90F51FCE-4CC2-434E-9915-E64B243982C5 4 0.3304 0.64237 0.016 0.000 0.000 0.816 0.168
#> 500CEBA4-F728-42C8-A206-9C44CBCA9EE0 3 0.2206 0.87495 0.068 0.016 0.912 0.000 0.004
#> 7C722601-FE14-4461-96BF-C087EA8CBAA9 4 0.1661 0.72292 0.000 0.036 0.000 0.940 0.024
#> 3BFE71C0-312E-4E2A-BAC8-EAC5C3C9D6A7 4 0.2140 0.72483 0.024 0.012 0.000 0.924 0.040
#> D3138878-37FB-40AE-AA52-D057A25FEDD1 1 0.3774 0.66846 0.816 0.016 0.000 0.140 0.028
#> 6DD54BD4-16D1-478A-8AFC-CC2A27CB6454 1 0.3265 0.70596 0.860 0.000 0.040 0.012 0.088
#> 16B4AC73-E759-45D0-B56E-CB20EF627F6B 5 0.6037 0.35807 0.120 0.000 0.000 0.392 0.488
#> F4F647DC-C630-429C-AD49-ADA43B652781 5 0.2179 0.67621 0.004 0.000 0.000 0.100 0.896
#> CF00D656-8854-47A0-9991-9F39CB7FEC86 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 9EF135A6-03A5-4DAE-8BA2-B74482321BA0 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 05CC46BF-2647-4AB2-A761-F0C068FFEB02 4 0.3710 0.63982 0.192 0.000 0.000 0.784 0.024
#> 719A1E5C-F438-4A11-8EF9-F4385A99004F 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> E435C03F-0277-49C1-83EF-19452082723E 1 0.5664 0.36437 0.560 0.000 0.000 0.348 0.092
#> AC64AA3B-8659-4E96-8E47-B02ABBA77DC6 2 0.3427 0.71132 0.000 0.796 0.000 0.192 0.012
#> 84BFDEC2-0146-4546-AA60-2BA1A4CC062E 1 0.3291 0.69264 0.840 0.000 0.120 0.000 0.040
#> 7DA4280C-511E-493E-B187-88ECCA427C33 2 0.1697 0.74311 0.000 0.932 0.000 0.008 0.060
#> 4440F3AA-48B5-450A-9FC8-5CEB470DD323 5 0.3443 0.67798 0.008 0.012 0.000 0.164 0.816
#> 6DB4D5E8-DA4C-4BD8-8824-6D1A529C9976 4 0.1331 0.71979 0.040 0.000 0.000 0.952 0.008
#> 344E4BB2-5417-486D-A3C5-47EAAE071F50 4 0.4704 0.54180 0.040 0.016 0.000 0.728 0.216
#> 66DCACC7-C31B-4B1F-904B-1C28C6A8FF7A 2 0.0613 0.75703 0.004 0.984 0.000 0.008 0.004
#> 29F3C113-9B39-41DC-8E22-604C92F107DD 1 0.4620 0.29320 0.612 0.012 0.372 0.000 0.004
#> D3D18F42-FDBF-4F9E-9B77-CF6ED79544C5 5 0.2747 0.59927 0.088 0.012 0.000 0.016 0.884
#> BCF9508C-9600-4CA8-924F-A7BDCF8D3636 4 0.5417 0.51572 0.236 0.000 0.000 0.648 0.116
#> 9F6302FA-8F40-49AB-9388-2DC5B3DB58E6 4 0.4924 0.50373 0.272 0.000 0.000 0.668 0.060
#> 2B04A6A1-6F20-4612-8E45-29D38247EAF8 5 0.4380 0.57972 0.020 0.000 0.000 0.304 0.676
#> EEA4E1B4-3C67-40D0-9CC8-15BE56E6BB9D 4 0.1911 0.72787 0.028 0.000 0.004 0.932 0.036
#> 60A51C36-7423-4C84-8034-325DE57046BE 4 0.3123 0.63840 0.184 0.000 0.000 0.812 0.004
#> E3A5FB64-EB24-4A24-9B79-539012C57711 5 0.2511 0.58667 0.088 0.004 0.016 0.000 0.892
#> 1D30F2FD-8743-4E9D-8E85-ED0A3AA217CC 5 0.6279 0.51107 0.200 0.000 0.000 0.268 0.532
#> D287EA4C-D05F-49B8-904A-F26ABAE11A73 4 0.4802 -0.18338 0.012 0.480 0.000 0.504 0.004
#> BF5E7EF3-0DF8-48AF-AEF7-9CB1FD8C502C 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> DEA7A651-250A-49B3-B666-8AF52A8E69D8 5 0.4901 0.43940 0.080 0.188 0.008 0.000 0.724
#> 2F2D0BC0-A680-4AF6-B957-BE9AD2953454 3 0.0162 0.93262 0.004 0.000 0.996 0.000 0.000
#> 356F02A7-7619-4A94-9A54-1ECB15B2F52F 2 0.6685 0.36462 0.264 0.476 0.000 0.256 0.004
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#> A06DA4D5-20AE-4F75-AEEE-10BA07B1E363 4 0.5088 0.56297 0.000 0.228 0.000 0.680 0.092
#> 7E9AF69D-85F2-473E-9BB6-AE28170966A8 4 0.2864 0.71847 0.064 0.008 0.000 0.884 0.044
#> 3739AE63-C535-4FCB-8338-DA654E35B6AB 2 0.0798 0.75319 0.008 0.976 0.000 0.000 0.016
#> AEECBFF3-1D5D-4DB7-930A-126A7BE423E0 4 0.7068 0.36811 0.192 0.000 0.184 0.556 0.068
#> 7EF7768A-75F8-4DFA-A61A-09F106495E82 5 0.3521 0.65205 0.004 0.000 0.000 0.232 0.764
#> DCA244C2-21B8-444F-B15C-DCE2B74CED54 1 0.7395 0.32103 0.452 0.028 0.292 0.220 0.008
#> 3390CB51-B66B-461D-AAE0-90D74FBAF85F 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> E6D816F2-6D98-4E4C-993C-8B8EF017BEA3 5 0.5608 0.36177 0.032 0.024 0.000 0.420 0.524
#> E9061D61-4774-464E-ABE4-EB15CD889141 4 0.4735 0.09596 0.460 0.000 0.000 0.524 0.016
#> 217E0CA2-841E-4560-A9BB-E9B8C2DF361A 2 0.4538 0.46957 0.000 0.620 0.000 0.364 0.016
#> 6923E0E8-FCD7-4D3A-BC56-8C8B0E8DB58B 5 0.4339 0.55424 0.012 0.000 0.000 0.336 0.652
#> F8CEE033-E0B3-408E-BC36-C0FEE5D2E05F 4 0.5313 0.02848 0.444 0.028 0.000 0.516 0.012
#> 93E69515-4C47-4E68-8842-818DE0E369E2 5 0.5264 0.62186 0.092 0.000 0.000 0.256 0.652
#> 3676F62D-740B-4D7F-9C33-A9A7D680582E 5 0.4759 0.53460 0.024 0.004 0.000 0.336 0.636
#> A2007795-C728-4688-B199-AE89500011D2 2 0.2358 0.75699 0.000 0.888 0.000 0.104 0.008
#> E19AD91B-EFA8-4B3D-A627-2118BD95556C 4 0.3034 0.72329 0.060 0.020 0.000 0.880 0.040
#> 25593027-4AA5-4D41-8D93-A6D76237CA86 5 0.4107 0.59374 0.040 0.040 0.044 0.036 0.840
#> 5A88DA5B-1181-4232-BE95-8EF86487FBD7 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 654DB268-A54B-405D-B3BA-4CDC7DC89C4E 3 0.6091 0.31655 0.140 0.000 0.524 0.000 0.336
#> A638AB0E-17DC-4DB7-8986-E7B87C798E0B 5 0.2674 0.64635 0.012 0.000 0.060 0.032 0.896
#> 2ED9F780-A4D9-442E-8742-725183DEAC99 4 0.4186 0.50097 0.044 0.184 0.000 0.768 0.004
#> F583A5CF-B4C4-4E1F-952F-366E46034BE7 2 0.0981 0.75468 0.012 0.972 0.000 0.008 0.008
#> 180867F0-954B-47C7-8B86-CBA55FA1F137 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 4E5BEEDF-3052-4A74-9427-9029CC2FF36E 4 0.1547 0.72651 0.016 0.004 0.000 0.948 0.032
#> 20287718-EDD7-4046-A498-E65C86803178 3 0.0162 0.93243 0.004 0.000 0.996 0.000 0.000
#> 08FE2D32-D899-49B0-BFE8-A0E08B043DB4 4 0.5725 0.47725 0.204 0.000 0.000 0.624 0.172
#> 05F6F2CF-1EC6-4D4B-B245-C76E118AEE6E 4 0.5788 0.31608 0.000 0.300 0.000 0.580 0.120
#> 12F4DEF6-A534-4A65-A108-35F6EC64BFAC 5 0.5114 0.22283 0.036 0.000 0.000 0.472 0.492
#> E8992C89-C499-47F5-9BCA-70A67CB3B96E 4 0.4599 0.63286 0.028 0.172 0.000 0.760 0.040
#> C0FE41D3-6CF5-4C06-A2E6-7C0F2933AE6D 5 0.3093 0.60636 0.080 0.016 0.000 0.032 0.872
#> 19F5FE2C-CA30-471F-B487-8BD62C0FDFD4 1 0.4300 0.67732 0.772 0.000 0.000 0.096 0.132
#> DDC71530-38B7-483F-83DC-1BCC550719C3 5 0.1732 0.60751 0.080 0.000 0.000 0.000 0.920
#> 778C473D-27FC-4323-AC58-21637D3E3F5C 2 0.3170 0.73595 0.036 0.876 0.000 0.048 0.040
#> 12BA7BEF-7095-4F6F-A53B-E486A2C12717 1 0.5838 0.20786 0.512 0.052 0.000 0.416 0.020
#> 5B94B090-3DEB-410A-B2BA-C963831DD865 2 0.4200 0.60130 0.004 0.672 0.000 0.320 0.004
#> 42EF1CDA-78DC-4C59-9581-3A8A904F4943 1 0.4213 0.49048 0.680 0.000 0.000 0.012 0.308
#> C5102A81-265F-4CD9-9B6C-390348FB690C 4 0.3838 0.37310 0.000 0.280 0.000 0.716 0.004
#> 1D02C874-0D6C-4BB2-A5FD-2F112D13930A 4 0.2286 0.66385 0.000 0.108 0.000 0.888 0.004
#> 38FE40F8-9931-43B5-B844-1AAA289F442D 1 0.4613 0.25606 0.580 0.000 0.408 0.008 0.004
#> 61F8D081-47D1-4FB9-9DEA-D7AEB00DBD8A 5 0.4509 0.42902 0.024 0.016 0.232 0.000 0.728
#> FEA99D3F-1C7D-4E44-AC09-6E273E7AC714 5 0.5406 0.03302 0.464 0.000 0.000 0.056 0.480
#> 12717794-B627-4EDF-B486-D3ABC5121EFD 1 0.6808 0.27369 0.472 0.024 0.408 0.032 0.064
#> 9E3CD8DD-DBB6-4983-8700-CB9074F19148 4 0.1364 0.72176 0.036 0.000 0.000 0.952 0.012
#> 3C50609D-819F-4EC0-991E-9549D1BEA12B 4 0.2278 0.72142 0.060 0.000 0.000 0.908 0.032
#> D834C549-080B-41E1-9ED0-5476EFE5C5C1 5 0.6149 0.49735 0.008 0.144 0.000 0.272 0.576
#> 99E25D92-6C07-4691-A604-A3A6899B73CF 5 0.1522 0.61960 0.012 0.044 0.000 0.000 0.944
#> 4BE5A149-C72A-4A37-BAA3-A94F57774B0F 2 0.1780 0.74370 0.024 0.940 0.000 0.008 0.028
#> 5F6A776B-49DE-481F-8B4D-18630411AE98 2 0.4787 0.39382 0.008 0.540 0.000 0.444 0.008
#> E4D97CB5-60BE-468A-BA6C-38A5C3F8155E 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> FF871F11-C2CC-4CCA-A8AF-5B0FF31DEC5A 3 0.0162 0.93243 0.004 0.000 0.996 0.000 0.000
#> 4F501635-545A-479A-A95E-12C4AC30BA50 1 0.5821 0.68949 0.720 0.052 0.120 0.020 0.088
#> 7A85E8B4-EEA5-4165-8396-27B895E552CB 1 0.7287 0.34912 0.516 0.208 0.000 0.212 0.064
#> 0C52C8C5-9F34-42AB-AA93-8122998E116C 3 0.0865 0.92176 0.004 0.000 0.972 0.000 0.024
#> 88DBEE9B-9FF4-40D4-ADD1-471F0173045B 5 0.4114 0.65190 0.040 0.004 0.000 0.184 0.772
#> 48E311AF-131C-4A0B-9DA8-8CD52BB799BF 2 0.1281 0.75429 0.000 0.956 0.000 0.012 0.032
#> F7B93CBE-48E0-43CA-8AD9-718E18CA9DE1 4 0.5759 0.40789 0.276 0.000 0.000 0.596 0.128
#> 4748FBD4-77F9-44DE-82DD-67A847C3FBAA 5 0.3481 0.55405 0.056 0.004 0.100 0.000 0.840
#> C20F209A-2102-4502-80FA-17AF04601987 5 0.0566 0.64494 0.004 0.000 0.000 0.012 0.984
#> 9F70C72E-8D04-4494-8070-CA3782BE1EC5 1 0.2362 0.69946 0.900 0.000 0.000 0.076 0.024
#> 9A1C931E-95E4-4F83-AC77-3373B308E677 5 0.3051 0.66414 0.060 0.000 0.000 0.076 0.864
#> D8D8AA29-4A1B-4C17-80AA-4EDB99DCE0D0 2 0.4425 0.46588 0.000 0.600 0.000 0.392 0.008
#> 21385544-2FC4-4EB8-AF55-1C046216E189 1 0.2628 0.71755 0.884 0.000 0.000 0.088 0.028
#> 65597F25-041D-492C-B9B3-0D10E8694DC7 5 0.6356 0.30955 0.364 0.000 0.000 0.168 0.468
#> 98BC84CC-A8E3-4AEF-92E6-F7798E48DA9A 2 0.6415 0.30073 0.148 0.428 0.000 0.420 0.004
#> 910C53C8-A26D-4EB1-9C0B-A682C6992CCD 2 0.4211 0.54224 0.000 0.636 0.000 0.360 0.004
#> 3ADAC1F9-B593-4DEE-B527-1E1D752DE778 5 0.4934 0.28385 0.364 0.000 0.000 0.036 0.600
#> AED2AEB1-13C7-4ABC-B1AF-38189F097059 2 0.3928 0.59731 0.000 0.700 0.000 0.296 0.004
#> DC13F3D6-8107-435C-B6A0-A84B58CE3E71 5 0.3326 0.67866 0.024 0.000 0.000 0.152 0.824
#> 677534C0-E350-4FD6-B66E-FD1962DAEFA2 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> F1DB8EA2-8AC2-4654-B543-18808D184FFD 1 0.4839 0.60673 0.740 0.004 0.072 0.176 0.008
#> 711ECA33-5EC2-45C3-9250-652581FA75FF 5 0.1153 0.65126 0.004 0.008 0.000 0.024 0.964
#> F17B682D-A902-4730-A300-5C163209F7CD 4 0.3495 0.66182 0.000 0.152 0.000 0.816 0.032
#> 214EB2CE-75EF-4E56-9E7E-F9B7BAB3B5D2 2 0.6786 0.28086 0.224 0.388 0.000 0.384 0.004
#> 55E9F06C-6C7D-4160-8791-65AFF6EE7968 5 0.5210 0.38440 0.184 0.000 0.132 0.000 0.684
#> A0EE8CCC-FFAE-41DD-B6A1-F066B18B024E 4 0.3079 0.69067 0.012 0.092 0.000 0.868 0.028
#> 068EA867-E76C-43B9-BFA4-CAED834583F7 1 0.3389 0.69859 0.836 0.000 0.000 0.048 0.116
#> 86867779-C230-4EC7-BC6E-ED111DEAD561 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 8B60296E-8657-41E9-88C4-47A70E12B28F 2 0.2536 0.74744 0.000 0.868 0.000 0.128 0.004
#> ED698786-FA22-478A-8D7C-97DB75D3AD5A 5 0.4548 0.64067 0.052 0.000 0.000 0.232 0.716
#> C2750CB6-DD39-41E2-B615-271D72A8876C 4 0.5304 0.55070 0.160 0.108 0.000 0.712 0.020
#> E258343D-271F-419D-A083-9AB6DF9A377B 5 0.3039 0.54102 0.192 0.000 0.000 0.000 0.808
#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.5074 0.64303 0.700 0.000 0.000 0.132 0.168
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0404 0.93101 0.012 0.000 0.988 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.6352 0.54453 0.108 0.172 0.000 0.644 0.076
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.3003 0.64521 0.092 0.000 0.000 0.044 0.864
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.93342 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F0569EB4-93AD-4EBC-B588-58F4295FAC75 6 0.4976 0.37254 0.000 0.056 0.000 0.340 0.012 0.592
#> 4F70FC82-A7FC-4589-89A4-9F30D3DBEF7D 3 0.0000 0.92288 0.000 0.000 1.000 0.000 0.000 0.000
#> 8950A092-01BD-45F5-8D56-E014E1DC89FB 4 0.2797 0.64841 0.004 0.140 0.000 0.844 0.008 0.004
#> DDC1DBB4-E52D-497F-BB00-8DC928B5339E 5 0.4494 0.46796 0.072 0.232 0.000 0.004 0.692 0.000
#> CD86EAF7-D370-49DB-A4AF-16C81A2E9585 6 0.3520 0.65963 0.000 0.188 0.000 0.036 0.000 0.776
#> 23AFDA0D-F8F5-42AA-8F64-E6BCACD6ACC6 6 0.5914 0.13902 0.000 0.028 0.000 0.360 0.112 0.500
#> 47B989D5-6F1D-40A2-85D4-1EACD5E0BC87 4 0.3497 0.64654 0.080 0.056 0.000 0.832 0.032 0.000
#> 16715AB8-E908-4CAD-969F-46FBEFD99890 5 0.5018 0.15727 0.396 0.004 0.000 0.064 0.536 0.000
#> 8FDC015D-FFC8-45DE-8199-35928A26F447 1 0.4433 0.55459 0.744 0.168 0.000 0.048 0.040 0.000
#> 16A570C6-306F-4B40-ACDD-C121C977C84C 5 0.4614 0.58216 0.108 0.016 0.000 0.152 0.724 0.000
#> 2CE962FF-8D10-48C9-A632-A4C91D35A2FE 6 0.5282 0.46534 0.004 0.296 0.000 0.116 0.000 0.584
#> 163FF088-61F0-4241-AF7D-D4A20601C23F 2 0.5482 -0.07420 0.008 0.468 0.000 0.428 0.096 0.000
#> 972F503F-19C4-49A0-A97B-3247A8582C5A 5 0.6538 0.42904 0.220 0.140 0.000 0.100 0.540 0.000
#> B91FC9F2-9657-44F8-B93B-327C9CAC2721 4 0.6252 0.43408 0.004 0.048 0.000 0.568 0.188 0.192
#> 6897281D-8CC6-44ED-929A-0C8C1FC80100 4 0.5794 0.43416 0.064 0.272 0.000 0.588 0.076 0.000
#> 7B40F5F4-DB5A-4C19-8438-77272D082927 3 0.0000 0.92288 0.000 0.000 1.000 0.000 0.000 0.000
#> 50600D68-66A1-48AA-95F7-1AA2274A8077 4 0.2913 0.65231 0.004 0.032 0.000 0.848 0.000 0.116
#> 31FADD69-DB0A-4A4C-BB4B-A375E2A55EDE 3 0.0146 0.92213 0.000 0.004 0.996 0.000 0.000 0.000
#> 479B4832-82DB-4176-9D24-D588F2903617 4 0.2094 0.67233 0.000 0.080 0.000 0.900 0.000 0.020
#> 205CFEE1-422E-4FC4-9EBC-87504BB8C820 5 0.5631 0.49954 0.056 0.040 0.000 0.272 0.616 0.016
#> E2FA8975-F717-43B2-9BDB-A2AEB7794365 5 0.5984 0.38951 0.000 0.120 0.000 0.292 0.548 0.040
#> FE853F93-5273-434D-8021-E084F9494E05 4 0.3189 0.65790 0.008 0.056 0.000 0.840 0.096 0.000
#> 2E6FDD29-C90E-441A-9D8A-7FF30553862A 3 0.3594 0.70945 0.204 0.020 0.768 0.000 0.008 0.000
#> D3D7325A-DEB7-4377-98B7-FD7802653E27 3 0.0000 0.92288 0.000 0.000 1.000 0.000 0.000 0.000
#> 1AA76659-62F8-4554-9263-C68BC486BD4B 5 0.5503 0.35701 0.176 0.220 0.000 0.000 0.596 0.008
#> C6AD4922-9981-4493-9F33-87A449B6EE55 6 0.4490 0.63080 0.004 0.148 0.000 0.128 0.000 0.720
#> B41BAD82-D7C5-4CFF-9ECE-9CB5DD35DE7F 5 0.3863 0.56145 0.016 0.016 0.000 0.228 0.740 0.000
#> 381B0249-B1F5-487B-9EBC-BC5955D0D14B 5 0.2022 0.62231 0.052 0.008 0.000 0.024 0.916 0.000
#> 7418A9D3-1352-4101-A68B-CF9F9204D54F 1 0.1738 0.62079 0.928 0.016 0.000 0.004 0.052 0.000
#> E53511A8-FBD0-4B7E-BA0C-8DD149045E0E 4 0.5501 0.44930 0.040 0.280 0.000 0.604 0.000 0.076
#> 0ED640CC-9763-4B00-AFDD-566E7A2B04EC 5 0.1649 0.62538 0.000 0.032 0.000 0.036 0.932 0.000
#> C4F9F719-F797-4BE3-995E-CF9647E142C6 6 0.3091 0.69610 0.000 0.024 0.000 0.148 0.004 0.824
#> 721E9BA5-6CD7-4389-B6BB-D223FC7C6C5E 1 0.5215 0.38401 0.632 0.028 0.016 0.288 0.036 0.000
#> 72BCF7F5-3826-4289-B0C7-505678481099 1 0.3903 0.55264 0.764 0.172 0.000 0.004 0.060 0.000
#> DC0B1502-FEB7-41FE-8EA8-50B2E96EAD2C 2 0.6125 0.21979 0.000 0.516 0.000 0.324 0.112 0.048
#> 6BB98D45-9DDE-46A9-88FF-705B5407D5EF 3 0.0000 0.92288 0.000 0.000 1.000 0.000 0.000 0.000
#> A711D143-F081-45CF-9BC3-0C0974A1961B 3 0.1320 0.89685 0.000 0.036 0.948 0.000 0.000 0.016
#> 3DBCBC2D-4758-4F34-B14A-DECB267EB9E5 5 0.1858 0.63196 0.012 0.012 0.000 0.052 0.924 0.000
#> 9A9AF7C8-64C3-46BB-84C9-52CAE3472067 1 0.5555 0.11931 0.472 0.032 0.000 0.060 0.436 0.000
#> 434163EA-432B-41F3-8321-7180A8635124 1 0.3411 0.59742 0.804 0.024 0.000 0.012 0.160 0.000
#> 535B21A6-C639-4853-9BB2-5B82DCA9CB18 4 0.1501 0.67188 0.000 0.076 0.000 0.924 0.000 0.000
#> 4C407D69-2503-421F-BC8B-F1FEC19FE6AD 5 0.5387 0.31501 0.004 0.112 0.000 0.340 0.544 0.000
#> 88B939BA-BDB0-4799-BC7A-241020CFB12F 4 0.1934 0.67740 0.000 0.044 0.000 0.916 0.000 0.040
#> 99C8C031-AACC-4D06-85B5-9B082226AB3F 4 0.5278 -0.12045 0.004 0.084 0.000 0.472 0.000 0.440
#> E6AF8360-3A04-41E9-97D3-871067377F76 4 0.6810 0.05752 0.292 0.048 0.000 0.404 0.256 0.000
#> B21858C3-BA6C-478D-ACE3-C2325183A7CD 5 0.6114 0.31402 0.004 0.032 0.000 0.120 0.512 0.332
#> 1D3C0C08-AA86-4857-879E-110DA5E35B77 3 0.4151 0.57049 0.044 0.000 0.692 0.000 0.264 0.000
#> 69595C5D-6655-4065-8943-90045A2B2478 5 0.6744 0.02355 0.000 0.036 0.000 0.328 0.360 0.276
#> 93682FC9-FED0-49E5-8887-6CD18394EA1A 4 0.3602 0.60693 0.000 0.072 0.000 0.792 0.000 0.136
#> 36B2E208-FF01-4249-92C3-BE77D426691B 6 0.2792 0.72405 0.004 0.048 0.000 0.052 0.016 0.880
#> FBDC1DC2-D2EB-447C-9B47-83FA9FE40124 3 0.0260 0.92145 0.000 0.008 0.992 0.000 0.000 0.000
#> D720FBA8-827E-48D5-AEC0-735C735CF1D8 1 0.5927 0.06772 0.448 0.324 0.000 0.000 0.228 0.000
#> EC051A62-B493-477D-AC36-BB25B09B421B 5 0.5183 0.39333 0.140 0.256 0.000 0.000 0.604 0.000
#> E26FAF89-FD86-4371-AAF4-C18C1C919BD2 1 0.6141 0.20130 0.520 0.256 0.200 0.000 0.024 0.000
#> DF1E42CF-D0DF-4326-8EFD-9FE823CF344A 5 0.2191 0.58537 0.000 0.120 0.000 0.004 0.876 0.000
#> 3B6765CA-65D6-4CF3-9C47-BBFE663BE404 4 0.6077 0.45087 0.140 0.100 0.000 0.612 0.148 0.000
#> 97BF844E-EB76-4D26-B577-FA14F5B54AF4 4 0.4695 0.52580 0.000 0.032 0.000 0.692 0.232 0.044
#> 97A49141-0141-4583-B366-A4720270D6F2 3 0.0146 0.92213 0.000 0.004 0.996 0.000 0.000 0.000
#> F043185A-D4D2-4503-93FA-A7B7DA684290 4 0.7889 0.09556 0.292 0.064 0.000 0.400 0.136 0.108
#> B730E9AD-DA24-46A3-BE56-A89447421C09 6 0.6419 0.15898 0.016 0.356 0.000 0.212 0.004 0.412
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#> 7B7CD669-4EFD-44A6-B42D-5BD1D9E3C38F 1 0.4089 0.57271 0.744 0.020 0.000 0.032 0.204 0.000
#> B72443A2-7A0E-453C-AAF6-59FC72434E0F 3 0.0547 0.91542 0.000 0.020 0.980 0.000 0.000 0.000
#> AB642383-1611-4355-B03C-08D42FF4676C 3 0.0000 0.92288 0.000 0.000 1.000 0.000 0.000 0.000
#> 98681C7C-BBF1-4B6A-81A3-A3AA32BBE843 4 0.7988 0.21721 0.164 0.048 0.000 0.384 0.132 0.272
#> 1D4337D7-B3AF-4D92-9441-B48D325E9774 5 0.2726 0.59972 0.112 0.032 0.000 0.000 0.856 0.000
#> EE118E80-F125-4655-8845-56A9CBBA0680 3 0.0000 0.92288 0.000 0.000 1.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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.
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