Date: 2019-12-26 01:25:10 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 17581 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] 17581 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 | ||
|---|---|---|---|---|---|---|
| CV:pam | 2 | 1.000 | 0.966 | 0.977 | ** | |
| ATC:kmeans | 2 | 0.990 | 0.959 | 0.982 | ** | |
| SD:mclust | 3 | 0.972 | 0.936 | 0.970 | ** | |
| ATC:NMF | 2 | 0.967 | 0.950 | 0.979 | ** | |
| SD:kmeans | 3 | 0.965 | 0.933 | 0.967 | ** | |
| MAD:mclust | 3 | 0.943 | 0.933 | 0.972 | * | |
| ATC:skmeans | 4 | 0.938 | 0.908 | 0.962 | * | 2 |
| CV:NMF | 3 | 0.932 | 0.925 | 0.971 | * | 2 |
| SD:skmeans | 2 | 0.906 | 0.952 | 0.977 | * | |
| CV:skmeans | 3 | 0.887 | 0.919 | 0.967 | ||
| SD:NMF | 3 | 0.854 | 0.877 | 0.953 | ||
| MAD:skmeans | 3 | 0.824 | 0.874 | 0.945 | ||
| CV:mclust | 2 | 0.805 | 0.912 | 0.960 | ||
| SD:pam | 3 | 0.778 | 0.887 | 0.925 | ||
| MAD:NMF | 3 | 0.774 | 0.849 | 0.937 | ||
| CV:kmeans | 3 | 0.747 | 0.882 | 0.924 | ||
| MAD:pam | 4 | 0.743 | 0.760 | 0.901 | ||
| MAD:kmeans | 4 | 0.682 | 0.801 | 0.866 | ||
| ATC:pam | 2 | 0.661 | 0.875 | 0.937 | ||
| ATC:mclust | 2 | 0.424 | 0.789 | 0.892 | ||
| ATC:hclust | 2 | 0.274 | 0.622 | 0.824 | ||
| CV:hclust | 3 | 0.258 | 0.666 | 0.801 | ||
| SD:hclust | 3 | 0.181 | 0.695 | 0.763 | ||
| MAD:hclust | 3 | 0.138 | 0.655 | 0.734 |
**: 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 0.7287 0.862 0.937 0.442 0.547 0.547
#> CV:NMF 2 0.9625 0.945 0.978 0.466 0.535 0.535
#> MAD:NMF 2 0.5530 0.721 0.874 0.446 0.529 0.529
#> ATC:NMF 2 0.9666 0.950 0.979 0.461 0.541 0.541
#> SD:skmeans 2 0.9061 0.952 0.977 0.470 0.531 0.531
#> CV:skmeans 2 0.8745 0.916 0.966 0.481 0.523 0.523
#> MAD:skmeans 2 0.4772 0.853 0.907 0.477 0.530 0.530
#> ATC:skmeans 2 1.0000 0.983 0.994 0.501 0.499 0.499
#> SD:mclust 2 0.8550 0.912 0.949 0.412 0.587 0.587
#> CV:mclust 2 0.8050 0.912 0.960 0.461 0.528 0.528
#> MAD:mclust 2 0.6084 0.877 0.936 0.403 0.603 0.603
#> ATC:mclust 2 0.4238 0.789 0.892 0.418 0.591 0.591
#> SD:kmeans 2 0.3973 0.773 0.860 0.373 0.582 0.582
#> CV:kmeans 2 0.5103 0.861 0.905 0.341 0.591 0.591
#> MAD:kmeans 2 0.3127 0.735 0.842 0.410 0.573 0.573
#> ATC:kmeans 2 0.9903 0.959 0.982 0.500 0.500 0.500
#> SD:pam 2 0.5097 0.700 0.865 0.320 0.717 0.717
#> CV:pam 2 1.0000 0.966 0.977 0.212 0.801 0.801
#> MAD:pam 2 0.2466 0.529 0.700 0.381 0.503 0.503
#> ATC:pam 2 0.6606 0.875 0.937 0.482 0.517 0.517
#> SD:hclust 2 0.1300 0.743 0.777 0.322 0.829 0.829
#> CV:hclust 2 0.2373 0.591 0.780 0.364 0.704 0.704
#> MAD:hclust 2 0.0991 0.577 0.750 0.367 0.770 0.770
#> ATC:hclust 2 0.2737 0.622 0.824 0.429 0.507 0.507
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.854 0.877 0.953 0.3089 0.815 0.677
#> CV:NMF 3 0.932 0.925 0.971 0.2481 0.833 0.701
#> MAD:NMF 3 0.774 0.849 0.937 0.3552 0.803 0.648
#> ATC:NMF 3 0.828 0.869 0.928 0.3819 0.739 0.553
#> SD:skmeans 3 0.894 0.912 0.963 0.3698 0.695 0.486
#> CV:skmeans 3 0.887 0.919 0.967 0.2935 0.773 0.598
#> MAD:skmeans 3 0.824 0.874 0.945 0.3713 0.689 0.476
#> ATC:skmeans 3 0.898 0.917 0.963 0.3035 0.788 0.599
#> SD:mclust 3 0.972 0.936 0.970 0.1345 0.935 0.892
#> CV:mclust 3 0.774 0.865 0.943 0.0996 0.846 0.742
#> MAD:mclust 3 0.943 0.933 0.972 0.1795 0.916 0.863
#> ATC:mclust 3 0.812 0.898 0.953 0.2084 0.582 0.449
#> SD:kmeans 3 0.965 0.933 0.967 0.3159 0.921 0.866
#> CV:kmeans 3 0.747 0.882 0.924 0.4548 0.906 0.843
#> MAD:kmeans 3 0.857 0.888 0.952 0.2511 0.892 0.818
#> ATC:kmeans 3 0.669 0.782 0.895 0.2350 0.632 0.413
#> SD:pam 3 0.778 0.887 0.925 0.5738 0.784 0.703
#> CV:pam 3 0.549 0.773 0.877 1.2705 0.755 0.695
#> MAD:pam 3 0.367 0.644 0.763 0.4583 0.546 0.379
#> ATC:pam 3 0.611 0.680 0.811 0.2466 0.728 0.534
#> SD:hclust 3 0.181 0.695 0.763 0.5760 0.723 0.666
#> CV:hclust 3 0.258 0.666 0.801 0.5064 0.708 0.592
#> MAD:hclust 3 0.138 0.655 0.734 0.4434 0.755 0.685
#> ATC:hclust 3 0.314 0.548 0.776 0.3891 0.609 0.394
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.679 0.710 0.829 0.2484 0.791 0.527
#> CV:NMF 4 0.633 0.731 0.831 0.1659 0.925 0.826
#> MAD:NMF 4 0.693 0.754 0.839 0.2059 0.789 0.512
#> ATC:NMF 4 0.821 0.844 0.925 0.1431 0.837 0.592
#> SD:skmeans 4 0.739 0.650 0.842 0.1517 0.796 0.501
#> CV:skmeans 4 0.786 0.797 0.907 0.1816 0.816 0.554
#> MAD:skmeans 4 0.753 0.706 0.871 0.1322 0.817 0.539
#> ATC:skmeans 4 0.938 0.908 0.962 0.1357 0.865 0.633
#> SD:mclust 4 0.807 0.844 0.934 0.4874 0.754 0.550
#> CV:mclust 4 0.694 0.819 0.891 0.3941 0.764 0.548
#> MAD:mclust 4 0.731 0.831 0.924 0.4731 0.757 0.546
#> ATC:mclust 4 0.672 0.721 0.865 0.2624 0.798 0.615
#> SD:kmeans 4 0.704 0.833 0.884 0.4206 0.750 0.530
#> CV:kmeans 4 0.753 0.849 0.919 0.3688 0.759 0.551
#> MAD:kmeans 4 0.682 0.801 0.866 0.3540 0.752 0.527
#> ATC:kmeans 4 0.625 0.663 0.823 0.1468 0.732 0.427
#> SD:pam 4 0.739 0.753 0.895 0.3874 0.724 0.497
#> CV:pam 4 0.475 0.688 0.825 0.3947 0.725 0.520
#> MAD:pam 4 0.743 0.760 0.901 0.2649 0.729 0.494
#> ATC:pam 4 0.555 0.604 0.806 0.1403 0.672 0.363
#> SD:hclust 4 0.229 0.629 0.710 0.1847 0.962 0.931
#> CV:hclust 4 0.294 0.649 0.805 0.0445 0.980 0.955
#> MAD:hclust 4 0.253 0.479 0.717 0.1859 0.896 0.809
#> ATC:hclust 4 0.373 0.626 0.680 0.1278 0.758 0.471
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.624 0.631 0.786 0.0755 0.838 0.484
#> CV:NMF 5 0.631 0.697 0.798 0.1274 0.816 0.533
#> MAD:NMF 5 0.636 0.613 0.802 0.0602 0.881 0.603
#> ATC:NMF 5 0.609 0.618 0.784 0.0696 0.841 0.502
#> SD:skmeans 5 0.780 0.705 0.838 0.0655 0.869 0.562
#> CV:skmeans 5 0.769 0.758 0.877 0.0741 0.881 0.598
#> MAD:skmeans 5 0.806 0.771 0.887 0.0705 0.872 0.571
#> ATC:skmeans 5 0.849 0.845 0.923 0.0651 0.860 0.535
#> SD:mclust 5 0.652 0.716 0.856 0.0565 0.945 0.827
#> CV:mclust 5 0.683 0.704 0.840 0.0633 0.918 0.742
#> MAD:mclust 5 0.678 0.695 0.818 0.0650 0.962 0.875
#> ATC:mclust 5 0.561 0.592 0.807 0.1254 0.813 0.535
#> SD:kmeans 5 0.715 0.625 0.814 0.0962 0.925 0.760
#> CV:kmeans 5 0.643 0.546 0.726 0.1077 0.830 0.517
#> MAD:kmeans 5 0.728 0.605 0.783 0.1070 0.886 0.641
#> ATC:kmeans 5 0.845 0.841 0.908 0.0796 0.855 0.561
#> SD:pam 5 0.622 0.559 0.771 0.0938 0.895 0.676
#> CV:pam 5 0.486 0.534 0.738 0.1009 0.844 0.561
#> MAD:pam 5 0.704 0.719 0.844 0.0944 0.857 0.562
#> ATC:pam 5 0.618 0.573 0.797 0.0878 0.793 0.472
#> SD:hclust 5 0.350 0.474 0.721 0.0977 0.901 0.816
#> CV:hclust 5 0.381 0.589 0.758 0.1059 0.949 0.882
#> MAD:hclust 5 0.346 0.483 0.711 0.0861 0.962 0.915
#> ATC:hclust 5 0.435 0.595 0.741 0.0702 0.939 0.803
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.649 0.557 0.755 0.0462 0.909 0.636
#> CV:NMF 6 0.725 0.536 0.762 0.0569 0.914 0.670
#> MAD:NMF 6 0.641 0.569 0.743 0.0467 0.916 0.667
#> ATC:NMF 6 0.630 0.516 0.707 0.0508 0.928 0.694
#> SD:skmeans 6 0.778 0.729 0.859 0.0472 0.902 0.588
#> CV:skmeans 6 0.753 0.719 0.826 0.0462 0.930 0.691
#> MAD:skmeans 6 0.769 0.665 0.814 0.0445 0.914 0.630
#> ATC:skmeans 6 0.840 0.773 0.894 0.0394 0.920 0.653
#> SD:mclust 6 0.632 0.587 0.749 0.0585 0.911 0.689
#> CV:mclust 6 0.633 0.603 0.758 0.0496 0.926 0.728
#> MAD:mclust 6 0.648 0.549 0.753 0.0486 0.905 0.676
#> ATC:mclust 6 0.608 0.595 0.755 0.0569 0.921 0.742
#> SD:kmeans 6 0.700 0.656 0.797 0.0515 0.898 0.627
#> CV:kmeans 6 0.657 0.613 0.732 0.0626 0.872 0.526
#> MAD:kmeans 6 0.721 0.674 0.803 0.0446 0.874 0.531
#> ATC:kmeans 6 0.759 0.629 0.796 0.0484 0.974 0.893
#> SD:pam 6 0.622 0.397 0.712 0.0338 0.876 0.584
#> CV:pam 6 0.509 0.497 0.720 0.0386 0.951 0.812
#> MAD:pam 6 0.690 0.614 0.811 0.0399 0.940 0.746
#> ATC:pam 6 0.629 0.503 0.702 0.0629 0.922 0.729
#> SD:hclust 6 0.413 0.455 0.651 0.0815 0.854 0.685
#> CV:hclust 6 0.420 0.569 0.737 0.0532 0.971 0.926
#> MAD:hclust 6 0.408 0.408 0.655 0.0627 0.902 0.768
#> ATC:hclust 6 0.507 0.579 0.730 0.0583 0.928 0.757
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 17581 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 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 0.130 0.743 0.777 0.3224 0.829 0.829
#> 3 3 0.181 0.695 0.763 0.5760 0.723 0.666
#> 4 4 0.229 0.629 0.710 0.1847 0.962 0.931
#> 5 5 0.350 0.474 0.721 0.0977 0.901 0.816
#> 6 6 0.413 0.455 0.651 0.0815 0.854 0.685
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.311 0.80397 0.056 0.944
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.833 0.61476 0.264 0.736
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.260 0.80252 0.044 0.956
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.529 0.79021 0.120 0.880
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.895 0.65667 0.312 0.688
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.753 0.72531 0.216 0.784
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.753 0.72531 0.216 0.784
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.795 0.95612 0.760 0.240
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.311 0.80071 0.056 0.944
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.881 0.88721 0.700 0.300
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.753 0.72531 0.216 0.784
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.518 0.78531 0.116 0.884
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.295 0.80155 0.052 0.948
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.781 0.74985 0.232 0.768
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.730 0.71297 0.204 0.796
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.295 0.81294 0.052 0.948
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.827 0.68454 0.260 0.740
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.662 0.74593 0.172 0.828
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.625 0.80086 0.156 0.844
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#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.260 0.80773 0.044 0.956
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.814 0.95386 0.748 0.252
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.482 0.81247 0.104 0.896
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.260 0.80653 0.044 0.956
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.343 0.80781 0.064 0.936
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.430 0.81005 0.088 0.912
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.278 0.80865 0.048 0.952
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.373 0.80836 0.072 0.928
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.969 0.26185 0.396 0.604
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.482 0.81289 0.104 0.896
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 2 0.886 0.64969 0.304 0.696
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.753 0.72531 0.216 0.784
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.260 0.80631 0.044 0.956
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.388 0.79390 0.076 0.924
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 2 0.802 0.69610 0.244 0.756
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.584 0.78888 0.140 0.860
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.260 0.81314 0.044 0.956
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 2 0.932 0.57599 0.348 0.652
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.753 0.94258 0.784 0.216
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.402 0.81116 0.080 0.920
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.482 0.79651 0.104 0.896
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.494 0.79315 0.108 0.892
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.574 0.77656 0.136 0.864
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.808 0.69075 0.248 0.752
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.311 0.80071 0.056 0.944
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.311 0.80071 0.056 0.944
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.295 0.80754 0.052 0.948
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.881 0.67931 0.300 0.700
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.358 0.80151 0.068 0.932
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.946 0.37628 0.364 0.636
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.430 0.80904 0.088 0.912
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.871 0.66644 0.292 0.708
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.730 0.71307 0.204 0.796
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.358 0.80151 0.068 0.932
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.881 0.66166 0.300 0.700
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.662 0.79335 0.172 0.828
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.295 0.80155 0.052 0.948
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.595 0.76207 0.144 0.856
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.753 0.94258 0.784 0.216
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.671 0.76486 0.176 0.824
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.494 0.80635 0.108 0.892
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.788 0.95516 0.764 0.236
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.295 0.80273 0.052 0.948
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.760 0.73375 0.220 0.780
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.552 0.78186 0.128 0.872
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.295 0.80649 0.052 0.948
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.260 0.80451 0.044 0.956
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.753 0.94258 0.784 0.216
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.814 0.95386 0.748 0.252
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.997 -0.10167 0.468 0.532
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.644 0.79534 0.164 0.836
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.625 0.77505 0.156 0.844
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.946 0.65150 0.636 0.364
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.563 0.78140 0.132 0.868
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.738 0.76435 0.208 0.792
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.745 0.73583 0.212 0.788
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.706 0.71205 0.192 0.808
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.416 0.81401 0.084 0.916
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.343 0.80414 0.064 0.936
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 2 0.871 0.59771 0.292 0.708
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.961 0.23060 0.384 0.616
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.416 0.80672 0.084 0.916
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.311 0.80004 0.056 0.944
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.552 0.80822 0.128 0.872
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.358 0.80296 0.068 0.932
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.552 0.77052 0.128 0.872
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.563 0.80521 0.132 0.868
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.921 0.63337 0.336 0.664
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.327 0.80746 0.060 0.940
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.913 0.66289 0.328 0.672
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.358 0.80816 0.068 0.932
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.833 0.94105 0.736 0.264
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.895 0.65667 0.312 0.688
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.833 0.94105 0.736 0.264
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.574 0.77445 0.136 0.864
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.714 0.74456 0.196 0.804
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.373 0.81091 0.072 0.928
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.311 0.80355 0.056 0.944
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.615 0.76904 0.152 0.848
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.402 0.80349 0.080 0.920
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.821 0.95079 0.744 0.256
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.722 0.77146 0.200 0.800
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.625 0.78553 0.156 0.844
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.802 0.70571 0.244 0.756
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.416 0.80739 0.084 0.916
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.278 0.80431 0.048 0.952
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.402 0.81330 0.080 0.920
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.706 0.72124 0.192 0.808
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.680 0.72960 0.180 0.820
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.278 0.80485 0.048 0.952
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.456 0.79659 0.096 0.904
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.808 0.74659 0.248 0.752
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.943 0.61912 0.360 0.640
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.722 0.72407 0.200 0.800
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.574 0.76546 0.136 0.864
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.788 0.72849 0.236 0.764
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.552 0.78824 0.128 0.872
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.808 0.69075 0.248 0.752
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.753 0.72915 0.216 0.784
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.943 0.61912 0.360 0.640
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.921 0.63337 0.336 0.664
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.295 0.80137 0.052 0.948
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.722 0.71400 0.200 0.800
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.909 0.66748 0.324 0.676
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.921 0.63337 0.336 0.664
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.520 0.73565 0.136 0.820 0.044
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.927 0.17985 0.316 0.504 0.180
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.199 0.74072 0.048 0.948 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.534 0.74539 0.084 0.824 0.092
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.555 0.82387 0.768 0.212 0.020
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.573 0.64548 0.272 0.720 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.585 0.61917 0.268 0.720 0.012
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.220 0.95738 0.056 0.004 0.940
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.217 0.73624 0.048 0.944 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.380 0.88465 0.052 0.056 0.892
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.552 0.64691 0.268 0.728 0.004
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.653 0.72550 0.128 0.760 0.112
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.206 0.73791 0.044 0.948 0.008
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.753 0.58693 0.348 0.600 0.052
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.797 0.61830 0.156 0.660 0.184
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.344 0.76793 0.088 0.896 0.016
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.602 0.80104 0.700 0.288 0.012
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.756 0.65947 0.148 0.692 0.160
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.700 0.71344 0.248 0.692 0.060
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.790 0.59694 0.300 0.616 0.084
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.641 0.75575 0.160 0.760 0.080
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.885 0.47594 0.320 0.540 0.140
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.536 0.75027 0.168 0.800 0.032
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.728 0.67253 0.148 0.712 0.140
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.873 0.45786 0.352 0.528 0.120
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.618 0.72887 0.112 0.780 0.108
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.206 0.74082 0.044 0.948 0.008
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.672 0.71709 0.220 0.720 0.060
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.659 0.81742 0.728 0.216 0.056
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.684 0.67688 0.272 0.684 0.044
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.555 0.82387 0.768 0.212 0.020
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.603 0.70815 0.244 0.732 0.024
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.206 0.75124 0.044 0.948 0.008
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.554 0.70487 0.236 0.752 0.012
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.751 0.65569 0.152 0.696 0.152
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.520 0.73565 0.136 0.820 0.044
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.673 0.70923 0.128 0.748 0.124
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.188 0.74300 0.044 0.952 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.540 0.69074 0.256 0.740 0.004
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.813 0.75505 0.632 0.244 0.124
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.331 0.76061 0.064 0.908 0.028
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.503 0.73914 0.132 0.828 0.040
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.811 0.39588 0.504 0.428 0.068
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.234 0.95377 0.048 0.012 0.940
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.469 0.75775 0.096 0.852 0.052
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.217 0.73624 0.048 0.944 0.008
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.855 0.53937 0.312 0.568 0.120
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.560 0.82335 0.764 0.216 0.020
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.484 0.77442 0.776 0.224 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.956 0.18460 0.228 0.476 0.296
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.843 0.38162 0.120 0.588 0.292
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.731 0.59831 0.324 0.628 0.048
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.525 0.75819 0.096 0.828 0.076
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.650 0.73862 0.140 0.760 0.100
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.560 0.75558 0.136 0.804 0.060
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.217 0.95697 0.048 0.008 0.944
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.550 0.82227 0.772 0.208 0.020
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.991 0.26077 0.388 0.276 0.336
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.568 0.82358 0.764 0.212 0.024
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.679 0.50380 0.324 0.648 0.028
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.234 0.75890 0.048 0.940 0.012
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.838 0.54973 0.168 0.624 0.208
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.484 0.77442 0.776 0.224 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.686 0.69951 0.252 0.696 0.052
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.762 0.30231 0.348 0.596 0.056
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.562 0.72422 0.156 0.796 0.048
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.346 0.76992 0.096 0.892 0.012
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.741 0.67650 0.256 0.668 0.076
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.872 0.47978 0.336 0.540 0.124
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.507 0.69079 0.224 0.772 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.555 0.82387 0.768 0.212 0.020
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.781 0.62756 0.268 0.640 0.092
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.555 0.82387 0.768 0.212 0.020
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.585 0.61917 0.268 0.720 0.012
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.588 0.61913 0.272 0.716 0.012
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#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.249 0.73818 0.060 0.932 0.008
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.577 0.82464 0.756 0.220 0.024
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.616 0.64625 0.288 0.696 0.016
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.199 0.73811 0.048 0.948 0.004
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.692 0.69713 0.128 0.736 0.136
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.141 0.94409 0.036 0.000 0.964
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.541 0.71017 0.224 0.764 0.012
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.460 0.76565 0.152 0.832 0.016
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.207 0.95590 0.060 0.000 0.940
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.206 0.74179 0.044 0.948 0.008
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.669 0.57290 0.580 0.408 0.012
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.721 0.39523 0.324 0.632 0.044
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.417 0.76685 0.092 0.872 0.036
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.176 0.75654 0.040 0.956 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.141 0.94409 0.036 0.000 0.964
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.217 0.95697 0.048 0.008 0.944
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.912 0.26856 0.512 0.160 0.328
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.631 0.55556 0.328 0.660 0.012
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.459 0.71343 0.172 0.820 0.008
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.710 0.64115 0.216 0.080 0.704
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.463 0.73259 0.164 0.824 0.012
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.701 0.64459 0.308 0.652 0.040
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.620 0.66587 0.276 0.704 0.020
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.774 0.64433 0.136 0.676 0.188
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.496 0.76432 0.116 0.836 0.048
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.353 0.75170 0.068 0.900 0.032
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.777 0.76913 0.660 0.232 0.108
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.911 0.21536 0.168 0.524 0.308
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.367 0.76823 0.064 0.896 0.040
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.434 0.75948 0.084 0.868 0.048
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.577 0.69387 0.232 0.748 0.020
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.499 0.75702 0.112 0.836 0.052
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.646 0.71571 0.116 0.764 0.120
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.555 0.71780 0.212 0.768 0.020
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.910 0.37066 0.360 0.492 0.148
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.268 0.76532 0.028 0.932 0.040
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.507 0.77362 0.772 0.224 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.270 0.75542 0.056 0.928 0.016
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.264 0.94429 0.048 0.020 0.932
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.555 0.82387 0.768 0.212 0.020
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.264 0.94429 0.048 0.020 0.932
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.764 0.28542 0.352 0.592 0.056
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.548 0.67162 0.264 0.732 0.004
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.489 0.76022 0.096 0.844 0.060
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.293 0.75239 0.040 0.924 0.036
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.698 0.70083 0.140 0.732 0.128
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.280 0.75756 0.092 0.908 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.249 0.95039 0.048 0.016 0.936
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.706 0.66199 0.288 0.664 0.048
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.551 0.72286 0.220 0.764 0.016
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.596 0.76686 0.672 0.324 0.004
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.507 0.76042 0.116 0.832 0.052
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.255 0.76031 0.040 0.936 0.024
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.335 0.75273 0.108 0.888 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.772 0.63933 0.148 0.680 0.172
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.645 0.68427 0.104 0.764 0.132
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.227 0.75714 0.040 0.944 0.016
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.635 0.66686 0.204 0.744 0.052
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.840 0.52079 0.328 0.568 0.104
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.551 0.77763 0.800 0.156 0.044
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.803 0.61472 0.172 0.656 0.172
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.686 0.69817 0.128 0.740 0.132
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.670 0.63764 0.280 0.684 0.036
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.441 0.72481 0.160 0.832 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.617 0.78637 0.680 0.308 0.012
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.559 0.63640 0.276 0.720 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.551 0.77763 0.800 0.156 0.044
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.910 0.37066 0.360 0.492 0.148
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.206 0.73812 0.044 0.948 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.808 0.61042 0.168 0.652 0.180
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.484 0.77442 0.776 0.224 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.910 0.37066 0.360 0.492 0.148
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.5432 0.67471 0.156 0.764 0.040 0.040
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.9011 0.08881 0.340 0.408 0.152 0.100
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.2714 0.66567 0.004 0.884 0.000 0.112
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.5287 0.69505 0.028 0.780 0.064 0.128
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.7033 0.51701 0.136 0.528 0.000 0.336
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.6693 0.39087 0.088 0.488 0.000 0.424
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0672 0.90724 0.008 0.008 0.984 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3196 0.65213 0.008 0.856 0.000 0.136
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3705 0.80515 0.016 0.040 0.868 0.076
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.7067 0.51481 0.124 0.540 0.004 0.332
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.6813 0.67053 0.124 0.696 0.088 0.092
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2999 0.65274 0.004 0.864 0.000 0.132
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.8233 0.47999 0.292 0.480 0.032 0.196
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.8302 0.56434 0.124 0.572 0.148 0.156
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.3793 0.71761 0.076 0.864 0.016 0.044
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3760 0.74569 0.828 0.156 0.004 0.012
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.7919 0.60077 0.120 0.608 0.120 0.152
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.7599 0.64023 0.172 0.604 0.044 0.180
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.8476 0.49377 0.268 0.500 0.064 0.168
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.6839 0.68596 0.128 0.688 0.060 0.124
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.9207 0.37582 0.244 0.412 0.092 0.252
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.6242 0.67793 0.204 0.692 0.020 0.084
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.7708 0.61042 0.128 0.628 0.120 0.124
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.9154 0.34978 0.268 0.388 0.076 0.268
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.6306 0.68204 0.076 0.732 0.096 0.096
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3105 0.65396 0.004 0.856 0.000 0.140
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.7628 0.62291 0.212 0.596 0.044 0.148
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3855 0.73877 0.856 0.092 0.040 0.012
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.7801 0.54109 0.164 0.508 0.020 0.308
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.7089 0.63954 0.180 0.620 0.016 0.184
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3491 0.68197 0.028 0.864 0.004 0.104
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.6852 0.61979 0.148 0.608 0.004 0.240
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.7970 0.59091 0.128 0.604 0.120 0.148
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.5432 0.67471 0.156 0.764 0.040 0.040
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.7207 0.64171 0.104 0.668 0.104 0.124
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3105 0.67000 0.012 0.868 0.000 0.120
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6886 0.62648 0.136 0.612 0.008 0.244
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6598 0.59957 0.712 0.112 0.092 0.084
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4190 0.71371 0.040 0.844 0.024 0.092
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.5463 0.67424 0.148 0.764 0.028 0.060
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6996 0.47555 0.596 0.304 0.048 0.052
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.2099 0.89615 0.008 0.012 0.936 0.044
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.5437 0.69392 0.120 0.776 0.036 0.068
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.3052 0.64993 0.004 0.860 0.000 0.136
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.9038 0.43308 0.240 0.432 0.080 0.248
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.2528 0.75262 0.908 0.080 0.008 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.4483 0.69236 0.808 0.104 0.000 0.088
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.9621 0.22039 0.204 0.388 0.240 0.168
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.8405 0.22145 0.044 0.488 0.212 0.256
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.8185 0.44577 0.188 0.428 0.024 0.360
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5795 0.69972 0.112 0.760 0.052 0.076
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.7048 0.67101 0.136 0.676 0.076 0.112
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.6084 0.69293 0.124 0.740 0.052 0.084
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1917 0.90131 0.008 0.012 0.944 0.036
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2602 0.75024 0.908 0.076 0.008 0.008
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.9428 0.75774 0.188 0.164 0.220 0.428
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.2658 0.75482 0.904 0.080 0.012 0.004
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6634 0.31297 0.412 0.524 0.020 0.044
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2408 0.70176 0.016 0.920 0.004 0.060
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.8353 0.52696 0.104 0.560 0.152 0.184
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.4483 0.69236 0.808 0.104 0.000 0.088
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.7586 0.60849 0.236 0.592 0.044 0.128
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7442 0.02449 0.440 0.452 0.040 0.068
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.5882 0.66745 0.168 0.736 0.040 0.056
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4958 0.70724 0.080 0.788 0.008 0.124
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.7977 0.57327 0.248 0.552 0.048 0.152
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.9106 0.37905 0.284 0.420 0.088 0.208
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.6298 0.60647 0.100 0.632 0.000 0.268
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.8493 0.52632 0.236 0.516 0.072 0.176
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.6693 0.39087 0.088 0.488 0.000 0.424
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.6822 0.39881 0.100 0.488 0.000 0.412
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5325 0.72436 0.104 0.780 0.024 0.092
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.6823 0.60868 0.196 0.604 0.000 0.200
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6049 0.67393 0.132 0.684 0.000 0.184
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.3346 0.70910 0.028 0.888 0.024 0.060
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.3346 0.70910 0.028 0.888 0.024 0.060
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.7890 0.48974 0.180 0.476 0.016 0.328
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.2099 0.89615 0.008 0.012 0.936 0.044
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.6852 0.66947 0.108 0.692 0.076 0.124
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.8825 0.50218 0.172 0.516 0.164 0.148
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.5603 0.70981 0.104 0.772 0.048 0.076
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.6232 0.64682 0.224 0.688 0.032 0.056
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.3050 0.71275 0.044 0.900 0.012 0.044
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4188 0.67855 0.040 0.812 0.000 0.148
#> F1099B84-FE2A-419C-9948-D0754C1AF902 4 0.8958 0.88361 0.316 0.068 0.212 0.404
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.6600 0.43013 0.084 0.520 0.000 0.396
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.7268 0.54408 0.152 0.532 0.004 0.312
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.4063 0.73672 0.808 0.172 0.004 0.016
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.2999 0.65274 0.004 0.864 0.000 0.132
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#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2821 0.70763 0.028 0.912 0.020 0.040
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.9161 0.38134 0.256 0.408 0.084 0.252
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.3450 0.64894 0.008 0.836 0.000 0.156
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.9768 0.04087 0.296 0.292 0.264 0.148
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.5890 0.69442 0.120 0.752 0.048 0.080
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2610 0.75784 0.900 0.088 0.012 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.8284 -0.05063 0.392 0.432 0.060 0.116
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.3450 0.64894 0.008 0.836 0.000 0.156
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.2473 0.75434 0.908 0.080 0.012 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.6862 0.53102 0.312 0.560 0.000 0.128
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.2831 0.66395 0.004 0.876 0.000 0.120
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.7264 0.64299 0.116 0.664 0.116 0.104
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2053 0.86580 0.004 0.000 0.924 0.072
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.6924 0.61675 0.180 0.608 0.004 0.208
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.6117 0.69658 0.136 0.708 0.012 0.144
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0712 0.90516 0.008 0.004 0.984 0.004
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.3161 0.66795 0.012 0.864 0.000 0.124
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.5851 0.57181 0.660 0.272 0.000 0.068
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.7149 0.27774 0.376 0.528 0.032 0.064
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4543 0.71519 0.084 0.828 0.024 0.064
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.2485 0.70142 0.016 0.916 0.004 0.064
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2053 0.86580 0.004 0.000 0.924 0.072
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1917 0.90131 0.008 0.012 0.944 0.036
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 4 0.8969 0.88340 0.312 0.068 0.216 0.404
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.6247 0.34642 0.428 0.516 0.000 0.056
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5677 0.62603 0.064 0.680 0.000 0.256
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.6707 0.49930 0.144 0.036 0.684 0.136
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.5392 0.66217 0.072 0.724 0.000 0.204
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.7937 0.54412 0.256 0.520 0.024 0.200
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.7312 0.54541 0.152 0.520 0.004 0.324
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.7842 0.59917 0.096 0.612 0.140 0.152
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.5336 0.70552 0.096 0.784 0.032 0.088
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3672 0.68688 0.012 0.848 0.012 0.128
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.5951 0.64963 0.752 0.104 0.088 0.056
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.8878 -0.10936 0.064 0.416 0.208 0.312
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.3877 0.71456 0.048 0.864 0.024 0.064
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4650 0.70494 0.072 0.828 0.044 0.056
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.6317 0.59013 0.280 0.624 0.000 0.096
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5304 0.69962 0.108 0.788 0.048 0.056
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.7089 0.64914 0.104 0.676 0.092 0.128
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6394 0.62132 0.244 0.636 0.000 0.120
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.9365 0.27857 0.300 0.368 0.100 0.232
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3391 0.71177 0.028 0.884 0.020 0.068
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.4547 0.68957 0.804 0.104 0.000 0.092
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2742 0.69498 0.008 0.900 0.008 0.084
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2421 0.88209 0.008 0.020 0.924 0.048
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2457 0.75303 0.912 0.076 0.008 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.2421 0.88209 0.008 0.020 0.924 0.048
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.7443 0.00263 0.444 0.448 0.040 0.068
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.6835 0.55050 0.124 0.560 0.000 0.316
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.5484 0.70261 0.112 0.776 0.040 0.072
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3617 0.68098 0.012 0.860 0.020 0.108
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.7546 0.63151 0.124 0.640 0.100 0.136
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3404 0.69935 0.032 0.864 0.000 0.104
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.2153 0.89250 0.008 0.020 0.936 0.036
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.8033 0.56786 0.220 0.536 0.036 0.208
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6555 0.63979 0.212 0.632 0.000 0.156
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.4540 0.71055 0.772 0.196 0.000 0.032
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5545 0.70727 0.100 0.776 0.048 0.076
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.2536 0.70758 0.028 0.924 0.020 0.028
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4786 0.68019 0.104 0.788 0.000 0.108
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.8107 0.57918 0.128 0.592 0.136 0.144
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.6233 0.62128 0.024 0.700 0.084 0.192
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3575 0.70198 0.028 0.868 0.012 0.092
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6680 0.59754 0.212 0.668 0.036 0.084
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.8781 0.43124 0.288 0.460 0.076 0.176
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3699 0.68061 0.864 0.048 0.008 0.080
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.8396 0.55355 0.148 0.564 0.144 0.144
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.7163 0.64055 0.112 0.672 0.108 0.108
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.7749 0.47525 0.156 0.484 0.016 0.344
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5361 0.64845 0.068 0.724 0.000 0.208
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.3946 0.73669 0.812 0.172 0.004 0.012
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.6909 0.45658 0.116 0.520 0.000 0.364
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3699 0.68061 0.864 0.048 0.008 0.080
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9365 0.27857 0.300 0.368 0.100 0.232
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3052 0.65098 0.004 0.860 0.000 0.136
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.8315 0.56649 0.148 0.572 0.144 0.136
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.4483 0.69236 0.808 0.104 0.000 0.088
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.9365 0.27857 0.300 0.368 0.100 0.232
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4580 0.52755 0.104 0.800 0.016 0.036 0.044
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.8269 0.07992 0.296 0.444 0.088 0.040 0.132
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4648 0.35604 0.012 0.716 0.004 0.244 0.024
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4912 0.50352 0.012 0.768 0.020 0.120 0.080
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1393 0.78942 0.956 0.012 0.000 0.008 0.024
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.5494 0.63967 0.048 0.348 0.004 0.592 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.4168 0.62566 0.008 0.168 0.004 0.784 0.036
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0727 0.91608 0.000 0.012 0.980 0.004 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4887 0.28827 0.012 0.664 0.004 0.300 0.020
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3174 0.83688 0.000 0.036 0.868 0.080 0.016
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.5364 0.65253 0.040 0.348 0.004 0.600 0.008
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4803 0.53102 0.056 0.800 0.036 0.064 0.044
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4910 0.30060 0.012 0.672 0.004 0.288 0.024
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.6951 0.10609 0.164 0.532 0.016 0.272 0.016
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.6492 0.44164 0.052 0.684 0.084 0.120 0.060
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2900 0.52116 0.028 0.864 0.000 0.108 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3175 0.78154 0.872 0.064 0.000 0.020 0.044
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.6009 0.47376 0.052 0.720 0.068 0.108 0.052
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.6157 0.35281 0.084 0.640 0.036 0.232 0.008
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.7110 0.22841 0.152 0.564 0.036 0.228 0.020
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5333 0.50677 0.064 0.748 0.036 0.132 0.020
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.7850 -0.05332 0.128 0.440 0.068 0.340 0.024
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.5961 0.41298 0.148 0.664 0.004 0.160 0.024
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.5755 0.48893 0.056 0.740 0.060 0.092 0.052
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.7754 -0.15679 0.136 0.408 0.052 0.380 0.024
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4583 0.53468 0.020 0.808 0.052 0.076 0.044
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4858 0.27865 0.012 0.656 0.000 0.308 0.024
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.5857 0.40525 0.108 0.680 0.012 0.180 0.020
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2394 0.77715 0.916 0.036 0.012 0.004 0.032
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.6243 0.36375 0.076 0.436 0.008 0.468 0.012
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0693 0.79098 0.980 0.012 0.000 0.008 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.5975 0.14162 0.100 0.592 0.004 0.296 0.008
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4611 0.40226 0.020 0.732 0.004 0.224 0.020
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.6127 -0.36198 0.080 0.456 0.000 0.448 0.016
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.6046 0.47052 0.056 0.716 0.060 0.116 0.052
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4580 0.52755 0.104 0.800 0.016 0.036 0.044
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.5214 0.50917 0.040 0.772 0.044 0.092 0.052
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4665 0.35163 0.012 0.704 0.004 0.260 0.020
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.5671 -0.19825 0.052 0.544 0.008 0.392 0.004
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.4913 0.67721 0.764 0.064 0.036 0.004 0.132
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3125 0.53418 0.016 0.864 0.004 0.104 0.012
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.5604 0.49208 0.128 0.732 0.016 0.068 0.056
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6546 0.32450 0.572 0.312 0.036 0.056 0.024
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.1701 0.90676 0.000 0.016 0.936 0.048 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.5230 0.51278 0.100 0.760 0.016 0.084 0.040
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4931 0.29300 0.012 0.668 0.004 0.292 0.024
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.7547 0.02170 0.136 0.480 0.056 0.312 0.016
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0960 0.79112 0.972 0.016 0.000 0.008 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.4715 0.71498 0.780 0.052 0.000 0.104 0.064
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.8525 0.20100 0.112 0.492 0.176 0.148 0.072
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.7215 -0.12852 0.000 0.440 0.080 0.100 0.380
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.6375 0.57623 0.076 0.356 0.008 0.536 0.024
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.4792 0.54795 0.072 0.784 0.016 0.104 0.024
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5115 0.51263 0.084 0.776 0.028 0.072 0.040
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3869 0.53598 0.056 0.848 0.020 0.052 0.024
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1549 0.91117 0.000 0.016 0.944 0.040 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0740 0.78878 0.980 0.008 0.000 0.008 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.4992 0.77315 0.008 0.092 0.084 0.044 0.772
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1087 0.79269 0.968 0.016 0.000 0.008 0.008
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6358 0.19899 0.388 0.516 0.012 0.056 0.028
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3544 0.46615 0.008 0.812 0.000 0.164 0.016
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.7105 0.36961 0.040 0.628 0.084 0.104 0.144
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.4587 0.71836 0.788 0.052 0.000 0.104 0.056
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.6075 0.36517 0.132 0.668 0.020 0.164 0.016
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.6899 0.12211 0.408 0.456 0.008 0.048 0.080
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4914 0.51708 0.120 0.776 0.016 0.052 0.036
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.5024 0.37078 0.052 0.676 0.000 0.264 0.008
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.6633 0.33042 0.156 0.616 0.020 0.184 0.024
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.7807 0.07063 0.152 0.476 0.060 0.288 0.024
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.5391 0.43626 0.036 0.448 0.004 0.508 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0693 0.79098 0.980 0.012 0.000 0.008 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.6774 0.30059 0.124 0.596 0.036 0.228 0.016
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0693 0.79098 0.980 0.012 0.000 0.008 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.4168 0.62566 0.008 0.168 0.004 0.784 0.036
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.4508 0.63845 0.020 0.172 0.004 0.768 0.036
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4389 0.52262 0.056 0.784 0.004 0.144 0.012
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#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.7297 0.05579 0.152 0.496 0.028 0.304 0.020
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.7419 0.30329 0.532 0.056 0.268 0.024 0.120
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.5698 0.39829 0.116 0.676 0.004 0.188 0.016
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.7303 0.22354 0.152 0.552 0.048 0.228 0.020
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.3342 0.54487 0.020 0.876 0.020 0.048 0.036
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0693 0.79098 0.980 0.012 0.000 0.008 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.1533 0.79259 0.952 0.024 0.004 0.004 0.016
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.4599 0.54991 0.068 0.792 0.016 0.108 0.016
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4538 0.53061 0.072 0.804 0.008 0.072 0.044
#> F694D119-BF58-4449-A811-CB7A2165D8C0 4 0.5773 0.63630 0.052 0.356 0.004 0.572 0.016
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.4996 0.49694 0.144 0.756 0.004 0.048 0.048
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4931 0.29300 0.012 0.668 0.004 0.292 0.024
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4388 0.44707 0.012 0.768 0.004 0.180 0.036
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.1549 0.91117 0.000 0.016 0.944 0.040 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.4187 0.51868 0.060 0.804 0.004 0.120 0.012
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4538 0.53061 0.072 0.804 0.008 0.072 0.044
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4354 0.43104 0.008 0.772 0.004 0.172 0.044
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.3838 0.53850 0.052 0.844 0.012 0.072 0.020
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4256 0.46261 0.016 0.772 0.008 0.188 0.016
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4079 0.46133 0.012 0.792 0.004 0.164 0.028
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.9657 -0.11257 0.240 0.300 0.204 0.128 0.128
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.5054 0.48736 0.164 0.744 0.004 0.044 0.044
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2312 0.77671 0.920 0.032 0.012 0.004 0.032
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.4168 0.62566 0.008 0.168 0.004 0.784 0.036
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4127 0.47853 0.020 0.792 0.008 0.164 0.016
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.3596 0.54671 0.024 0.864 0.024 0.052 0.036
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.3692 0.76646 0.840 0.084 0.000 0.020 0.056
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.6314 -0.20483 0.088 0.504 0.000 0.384 0.024
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.2968 0.53469 0.028 0.872 0.000 0.092 0.008
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.3753 0.74231 0.856 0.032 0.052 0.020 0.040
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.2478 0.87889 0.000 0.008 0.904 0.028 0.060
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.3921 0.54174 0.036 0.832 0.008 0.100 0.024
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.5023 0.53408 0.064 0.784 0.028 0.076 0.048
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.6545 0.39455 0.192 0.636 0.008 0.084 0.080
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.7250 0.18477 0.336 0.496 0.016 0.056 0.096
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.3310 0.77453 0.860 0.084 0.000 0.016 0.040
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.5028 0.26415 0.012 0.648 0.004 0.312 0.024
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4867 0.29536 0.012 0.668 0.004 0.296 0.020
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2761 0.50169 0.000 0.872 0.000 0.104 0.024
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.7911 -0.02918 0.136 0.452 0.072 0.316 0.024
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4879 0.24644 0.012 0.636 0.000 0.332 0.020
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.9356 -0.01975 0.248 0.348 0.184 0.088 0.132
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.3716 0.53739 0.056 0.852 0.012 0.060 0.020
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.1538 0.79385 0.952 0.020 0.004 0.004 0.020
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.7734 0.07010 0.356 0.424 0.024 0.044 0.152
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4879 0.24644 0.012 0.636 0.000 0.332 0.020
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.1340 0.79136 0.960 0.016 0.004 0.004 0.016
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.6849 0.08941 0.272 0.492 0.000 0.220 0.016
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4726 0.34367 0.012 0.704 0.004 0.256 0.024
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.5231 0.51394 0.052 0.776 0.060 0.060 0.052
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2478 0.87889 0.000 0.008 0.904 0.028 0.060
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.6346 -0.22641 0.112 0.496 0.004 0.380 0.008
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.5895 0.26966 0.092 0.604 0.000 0.288 0.016
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0693 0.91487 0.000 0.012 0.980 0.000 0.008
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4689 0.34723 0.012 0.700 0.004 0.264 0.020
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.6314 0.56030 0.636 0.184 0.000 0.052 0.128
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.6700 0.22193 0.336 0.536 0.012 0.040 0.076
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4260 0.53931 0.056 0.824 0.012 0.068 0.040
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.3849 0.46154 0.012 0.800 0.004 0.168 0.016
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2478 0.87889 0.000 0.008 0.904 0.028 0.060
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1549 0.91117 0.000 0.016 0.944 0.040 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.3579 0.83508 0.068 0.008 0.084 0.000 0.840
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.5824 0.18352 0.392 0.520 0.000 0.084 0.004
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5146 -0.29807 0.016 0.492 0.004 0.480 0.008
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.6528 0.54113 0.096 0.052 0.668 0.148 0.036
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.5419 0.03552 0.024 0.556 0.000 0.396 0.024
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.6727 0.13504 0.152 0.540 0.012 0.284 0.012
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.5748 0.44450 0.056 0.444 0.000 0.488 0.012
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.5844 0.46434 0.024 0.724 0.084 0.108 0.060
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.3452 0.54090 0.036 0.848 0.004 0.104 0.008
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4411 0.41436 0.012 0.732 0.000 0.232 0.024
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4432 0.71185 0.808 0.060 0.036 0.008 0.088
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.7120 -0.00212 0.000 0.324 0.084 0.096 0.496
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.3508 0.53218 0.020 0.848 0.012 0.108 0.012
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3269 0.54835 0.020 0.880 0.024 0.048 0.028
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.6291 0.29315 0.236 0.580 0.000 0.172 0.012
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.3782 0.54904 0.052 0.852 0.012 0.036 0.048
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.5020 0.51710 0.040 0.784 0.040 0.088 0.048
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6373 0.25960 0.204 0.572 0.000 0.212 0.012
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.8372 -0.07612 0.168 0.404 0.084 0.312 0.032
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4047 0.50045 0.012 0.788 0.008 0.176 0.016
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.4776 0.71073 0.776 0.052 0.000 0.104 0.068
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4158 0.44805 0.008 0.792 0.004 0.152 0.044
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1965 0.89504 0.000 0.024 0.924 0.052 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0693 0.79098 0.980 0.012 0.000 0.008 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1965 0.89504 0.000 0.024 0.924 0.052 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.6901 0.11600 0.412 0.452 0.008 0.048 0.080
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.5734 0.60772 0.048 0.404 0.004 0.532 0.012
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4583 0.54791 0.072 0.792 0.008 0.104 0.024
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4628 0.38728 0.012 0.716 0.000 0.240 0.032
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.5459 0.50235 0.052 0.756 0.044 0.100 0.048
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4684 0.39958 0.020 0.712 0.000 0.244 0.024
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1661 0.90687 0.000 0.024 0.940 0.036 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.6367 0.14411 0.124 0.552 0.012 0.308 0.004
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6463 0.15458 0.144 0.556 0.000 0.280 0.020
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.4429 0.73744 0.792 0.112 0.000 0.028 0.068
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3825 0.54360 0.052 0.848 0.012 0.060 0.028
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.2533 0.51629 0.008 0.888 0.000 0.096 0.008
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.5805 0.37053 0.104 0.664 0.004 0.208 0.020
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.6223 0.46324 0.056 0.704 0.072 0.116 0.052
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.6019 0.36251 0.012 0.668 0.024 0.112 0.184
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3807 0.44737 0.012 0.776 0.000 0.204 0.008
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6335 0.42688 0.172 0.660 0.008 0.084 0.076
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.7606 0.15890 0.164 0.512 0.044 0.252 0.028
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3301 0.72736 0.848 0.000 0.000 0.072 0.080
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.6636 0.43861 0.068 0.676 0.088 0.112 0.056
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5216 0.51145 0.048 0.776 0.052 0.072 0.052
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.6001 0.63290 0.072 0.340 0.004 0.568 0.016
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5322 0.05318 0.044 0.544 0.000 0.408 0.004
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.3310 0.77453 0.860 0.084 0.000 0.016 0.040
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.5234 0.68003 0.028 0.268 0.004 0.672 0.028
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3301 0.72736 0.848 0.000 0.000 0.072 0.080
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.8372 -0.07612 0.168 0.404 0.084 0.312 0.032
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4951 0.29196 0.012 0.664 0.004 0.296 0.024
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6518 0.45069 0.068 0.688 0.084 0.096 0.064
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.4715 0.71498 0.780 0.052 0.000 0.104 0.064
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.8372 -0.07612 0.168 0.404 0.084 0.312 0.032
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.4964 0.39623 0.072 0.188 0.004 0.708 0.016 0.012
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.7697 0.17086 0.244 0.108 0.052 0.480 0.104 0.012
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3945 0.77386 0.000 0.612 0.000 0.380 0.000 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.5213 -0.01302 0.004 0.316 0.008 0.608 0.052 0.012
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1621 0.79690 0.944 0.016 0.000 0.020 0.012 0.008
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.6042 0.63812 0.028 0.180 0.000 0.244 0.000 0.548
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.4575 0.48797 0.000 0.224 0.000 0.060 0.016 0.700
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0260 0.92363 0.000 0.000 0.992 0.000 0.000 0.008
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3690 0.82312 0.000 0.684 0.000 0.308 0.000 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.2501 0.86132 0.000 0.004 0.872 0.016 0.000 0.108
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.5843 0.63989 0.024 0.148 0.000 0.264 0.000 0.564
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.3021 0.51357 0.016 0.076 0.020 0.868 0.000 0.020
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3584 0.82460 0.000 0.688 0.000 0.308 0.000 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6106 0.15419 0.104 0.040 0.008 0.596 0.008 0.244
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3812 0.49278 0.004 0.036 0.056 0.816 0.000 0.088
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4226 0.23959 0.004 0.264 0.000 0.692 0.000 0.040
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.4334 0.77018 0.772 0.140 0.000 0.040 0.036 0.012
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3230 0.51558 0.004 0.032 0.044 0.856 0.000 0.064
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.6083 0.37067 0.040 0.116 0.028 0.624 0.000 0.192
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.6039 0.27500 0.088 0.052 0.016 0.636 0.008 0.200
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.5214 0.47024 0.024 0.132 0.028 0.712 0.000 0.104
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.6950 -0.03783 0.084 0.052 0.056 0.468 0.000 0.340
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.6263 0.29292 0.096 0.268 0.000 0.556 0.004 0.076
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2755 0.51706 0.008 0.032 0.036 0.888 0.000 0.036
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.6965 -0.13435 0.084 0.048 0.040 0.452 0.008 0.368
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3679 0.47998 0.000 0.128 0.032 0.812 0.008 0.020
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4186 0.82667 0.000 0.656 0.000 0.312 0.000 0.032
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4797 0.45851 0.056 0.056 0.000 0.740 0.008 0.140
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2649 0.77892 0.880 0.028 0.000 0.076 0.016 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.5858 0.37950 0.052 0.052 0.004 0.436 0.000 0.456
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0837 0.80003 0.972 0.004 0.000 0.020 0.000 0.004
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#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0837 0.80003 0.972 0.004 0.000 0.020 0.000 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1668 0.90906 0.000 0.004 0.928 0.008 0.000 0.060
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.6731 0.18300 0.344 0.112 0.004 0.476 0.040 0.024
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.6214 0.60135 0.024 0.164 0.000 0.300 0.004 0.508
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.4441 0.41091 0.040 0.204 0.004 0.728 0.000 0.024
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4380 0.68753 0.000 0.544 0.000 0.436 0.012 0.008
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.2422 0.52409 0.004 0.016 0.024 0.900 0.000 0.056
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.5535 -0.44611 0.012 0.436 0.000 0.460 0.000 0.092
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1536 0.91502 0.000 0.004 0.940 0.016 0.000 0.040
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.6138 0.20179 0.084 0.080 0.008 0.592 0.000 0.236
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.6946 0.14971 0.100 0.212 0.000 0.472 0.000 0.216
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.6011 0.69093 0.636 0.196 0.000 0.048 0.088 0.032
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.3871 0.44645 0.020 0.152 0.004 0.792 0.004 0.028
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.3789 0.01553 0.000 0.332 0.000 0.660 0.000 0.008
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.6453 -0.19227 0.092 0.352 0.000 0.468 0.000 0.088
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3406 0.51099 0.008 0.032 0.048 0.848 0.000 0.064
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.5904 -0.16923 0.004 0.320 0.000 0.512 0.156 0.008
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.4264 -0.54517 0.000 0.488 0.000 0.496 0.000 0.016
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.6080 0.34160 0.124 0.200 0.000 0.616 0.028 0.032
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.6595 0.20936 0.096 0.060 0.028 0.584 0.008 0.224
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4417 0.68974 0.776 0.064 0.000 0.004 0.068 0.088
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3731 0.49821 0.016 0.036 0.052 0.832 0.000 0.064
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2252 0.51490 0.000 0.044 0.028 0.908 0.000 0.020
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.6172 0.62446 0.060 0.108 0.000 0.264 0.004 0.564
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5860 0.60721 0.024 0.548 0.000 0.292 0.000 0.136
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.4233 0.76578 0.764 0.160 0.000 0.044 0.028 0.004
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.5830 0.61166 0.012 0.204 0.000 0.164 0.016 0.604
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.4417 0.68974 0.776 0.064 0.000 0.004 0.068 0.088
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.7452 -0.07454 0.108 0.052 0.076 0.448 0.004 0.312
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3905 0.82792 0.000 0.668 0.000 0.316 0.000 0.016
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.3748 0.50944 0.008 0.052 0.056 0.828 0.000 0.056
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.6055 0.67034 0.652 0.136 0.000 0.028 0.072 0.112
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.7452 -0.07454 0.108 0.052 0.076 0.448 0.004 0.312
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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.397 0.773 0.860 0.3733 0.582 0.582
#> 3 3 0.965 0.933 0.967 0.3159 0.921 0.866
#> 4 4 0.704 0.833 0.884 0.4206 0.750 0.530
#> 5 5 0.715 0.625 0.814 0.0962 0.925 0.760
#> 6 6 0.700 0.656 0.797 0.0515 0.898 0.627
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0938 0.8881 0.012 0.988
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.4690 0.7796 0.100 0.900
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0938 0.8881 0.012 0.988
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.1414 0.8891 0.020 0.980
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.9209 0.7348 0.664 0.336
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0938 0.8881 0.012 0.988
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0938 0.8881 0.012 0.988
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.8499 0.6010 0.724 0.276
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0938 0.8881 0.012 0.988
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.8499 0.6010 0.724 0.276
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0938 0.8900 0.012 0.988
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4022 0.8603 0.080 0.920
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0672 0.8893 0.008 0.992
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.4690 0.8439 0.100 0.900
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.7950 0.6640 0.240 0.760
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.1843 0.8869 0.028 0.972
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.9209 0.7348 0.664 0.336
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.6438 0.7748 0.164 0.836
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3879 0.8629 0.076 0.924
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.6343 0.7793 0.160 0.840
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.4022 0.8603 0.080 0.920
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.7674 0.6884 0.224 0.776
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0938 0.8881 0.012 0.988
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.7950 0.6635 0.240 0.760
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.5294 0.8251 0.120 0.880
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4022 0.8603 0.080 0.920
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0938 0.8881 0.012 0.988
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.4022 0.8603 0.080 0.920
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.9209 0.7348 0.664 0.336
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.2043 0.8855 0.032 0.968
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.9209 0.7348 0.664 0.336
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3114 0.8744 0.056 0.944
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0672 0.8893 0.008 0.992
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0672 0.8894 0.008 0.992
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.9977 0.1540 0.528 0.472
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0938 0.8881 0.012 0.988
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.8016 0.6567 0.244 0.756
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0938 0.8881 0.012 0.988
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0376 0.8903 0.004 0.996
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.8327 0.7254 0.736 0.264
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.5178 0.8281 0.116 0.884
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0938 0.8881 0.012 0.988
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.9944 -0.3362 0.456 0.544
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.8499 0.6010 0.724 0.276
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0938 0.8881 0.012 0.988
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0938 0.8881 0.012 0.988
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.5178 0.8286 0.116 0.884
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.9209 0.7348 0.664 0.336
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.9209 0.7348 0.664 0.336
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.8499 0.6010 0.724 0.276
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.7815 0.6776 0.232 0.768
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.4022 0.8616 0.080 0.920
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.3733 0.8655 0.072 0.928
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.4022 0.8603 0.080 0.920
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4022 0.8603 0.080 0.920
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.8499 0.6010 0.724 0.276
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.9209 0.7348 0.664 0.336
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.7883 0.6707 0.236 0.764
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.9209 0.7348 0.664 0.336
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0938 0.8881 0.012 0.988
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0938 0.8881 0.012 0.988
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.8909 0.5371 0.308 0.692
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.9209 0.7348 0.664 0.336
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.4022 0.8603 0.080 0.920
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7602 0.5114 0.220 0.780
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0672 0.8893 0.008 0.992
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0672 0.8893 0.008 0.992
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.4022 0.8603 0.080 0.920
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.5178 0.8286 0.116 0.884
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0672 0.8893 0.008 0.992
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.9209 0.7348 0.664 0.336
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.6247 0.7851 0.156 0.844
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.9209 0.7348 0.664 0.336
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0938 0.8881 0.012 0.988
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0938 0.8881 0.012 0.988
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.8903 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0938 0.8881 0.012 0.988
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.2043 0.8855 0.032 0.968
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1414 0.8891 0.020 0.980
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.3733 0.8654 0.072 0.928
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.9209 0.7348 0.664 0.336
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.1633 0.8881 0.024 0.976
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.8499 0.6010 0.724 0.276
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4022 0.8603 0.080 0.920
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.9000 0.5275 0.316 0.684
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.1633 0.8881 0.024 0.976
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0938 0.8881 0.012 0.988
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.1633 0.8881 0.024 0.976
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0938 0.8881 0.012 0.988
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.6801 0.7041 0.820 0.180
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0938 0.8881 0.012 0.988
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0938 0.8881 0.012 0.988
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.9209 0.7348 0.664 0.336
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#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.9209 0.7348 0.664 0.336
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1414 0.8891 0.020 0.980
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.8499 0.6010 0.724 0.276
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.9209 0.7348 0.664 0.336
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.8499 0.6010 0.724 0.276
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 1.0000 0.4299 0.500 0.500
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.8903 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.1414 0.8891 0.020 0.980
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1414 0.8891 0.020 0.980
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6343 0.7793 0.160 0.840
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0938 0.8881 0.012 0.988
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.8499 0.6010 0.724 0.276
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.4161 0.8574 0.084 0.916
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0938 0.8881 0.012 0.988
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.9209 0.7348 0.664 0.336
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.8903 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4022 0.8603 0.080 0.920
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0938 0.8881 0.012 0.988
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.8499 0.5987 0.276 0.724
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1633 0.8845 0.024 0.976
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.8903 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0938 0.8881 0.012 0.988
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.9815 0.1418 0.420 0.580
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.9209 0.7348 0.664 0.336
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.7453 0.7093 0.212 0.788
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.6531 0.7722 0.168 0.832
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2043 0.8855 0.032 0.968
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0672 0.8893 0.008 0.992
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.9209 0.7348 0.664 0.336
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0938 0.8881 0.012 0.988
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.9209 0.7348 0.664 0.336
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9686 0.2835 0.396 0.604
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0938 0.8881 0.012 0.988
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5519 0.8163 0.128 0.872
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.9209 0.7348 0.664 0.336
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.9944 -0.0367 0.456 0.544
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9705 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.1031 0.9562 0.024 0.976 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1031 0.9706 0.000 0.976 0.024
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9705 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9579 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1163 0.9701 0.000 0.972 0.028
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1163 0.9701 0.000 0.972 0.028
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.1163 0.9330 0.028 0.000 0.972
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1031 0.9706 0.000 0.976 0.024
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.1163 0.9330 0.028 0.000 0.972
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1163 0.9701 0.000 0.972 0.028
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9705 0.000 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1031 0.9706 0.000 0.976 0.024
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0237 0.9703 0.000 0.996 0.004
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0747 0.9627 0.000 0.984 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0237 0.9703 0.000 0.996 0.004
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9579 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0592 0.9651 0.000 0.988 0.012
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0237 0.9703 0.000 0.996 0.004
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0237 0.9703 0.000 0.996 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9705 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6095 0.3233 0.000 0.608 0.392
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1031 0.9706 0.000 0.976 0.024
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0747 0.9627 0.000 0.984 0.016
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0237 0.9703 0.000 0.996 0.004
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9705 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1163 0.9701 0.000 0.972 0.028
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0237 0.9703 0.000 0.996 0.004
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9579 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0237 0.9703 0.000 0.996 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9579 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0237 0.9703 0.000 0.996 0.004
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1163 0.9701 0.000 0.972 0.028
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1163 0.9701 0.000 0.972 0.028
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.5905 0.4761 0.000 0.352 0.648
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1031 0.9706 0.000 0.976 0.024
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0747 0.9627 0.000 0.984 0.016
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1031 0.9706 0.000 0.976 0.024
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1163 0.9701 0.000 0.972 0.028
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9579 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9705 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1031 0.9706 0.000 0.976 0.024
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.4452 0.6505 0.808 0.192 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.1163 0.9330 0.028 0.000 0.972
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1031 0.9706 0.000 0.976 0.024
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1031 0.9706 0.000 0.976 0.024
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0237 0.9703 0.000 0.996 0.004
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9579 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9579 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1267 0.9128 0.004 0.024 0.972
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4399 0.7722 0.000 0.812 0.188
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0237 0.9703 0.000 0.996 0.004
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9705 0.000 1.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9705 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9705 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1163 0.9330 0.028 0.000 0.972
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9579 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.4291 0.7720 0.000 0.820 0.180
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9579 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0592 0.9714 0.000 0.988 0.012
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1031 0.9706 0.000 0.976 0.024
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4346 0.7669 0.000 0.816 0.184
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9579 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0237 0.9703 0.000 0.996 0.004
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.6625 0.4128 0.660 0.316 0.024
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9705 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1031 0.9706 0.000 0.976 0.024
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0237 0.9703 0.000 0.996 0.004
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0237 0.9703 0.000 0.996 0.004
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1163 0.9701 0.000 0.972 0.028
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9579 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0237 0.9703 0.000 0.996 0.004
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9579 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1163 0.9701 0.000 0.972 0.028
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.1163 0.9701 0.000 0.972 0.028
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9705 0.000 1.000 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1163 0.9701 0.000 0.972 0.028
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.1163 0.9701 0.000 0.972 0.028
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0237 0.9712 0.000 0.996 0.004
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9705 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9579 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0237 0.9703 0.000 0.996 0.004
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.1163 0.9330 0.028 0.000 0.972
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9705 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.5465 0.5870 0.000 0.712 0.288
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0747 0.9714 0.000 0.984 0.016
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9705 0.000 1.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9705 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1031 0.9706 0.000 0.976 0.024
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.4291 0.7437 0.820 0.000 0.180
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1163 0.9701 0.000 0.972 0.028
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1163 0.9701 0.000 0.972 0.028
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9579 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1031 0.9706 0.000 0.976 0.024
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9579 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1031 0.9706 0.000 0.976 0.024
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.1163 0.9330 0.028 0.000 0.972
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0237 0.9703 0.000 0.996 0.004
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.1163 0.9330 0.028 0.000 0.972
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9579 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.1163 0.9701 0.000 0.972 0.028
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.7824 0.4325 0.064 0.356 0.580
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.1163 0.9330 0.028 0.000 0.972
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9705 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9579 1.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1031 0.9706 0.000 0.976 0.024
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.0747 0.9649 0.000 0.984 0.016
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9579 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.1031 0.9706 0.000 0.976 0.024
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.0592 0.9651 0.000 0.988 0.012
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0237 0.9703 0.000 0.996 0.004
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.0000 0.9705 0.000 1.000 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.4504 0.7502 0.000 0.804 0.196
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9705 0.000 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.1031 0.9709 0.000 0.976 0.024
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9579 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9579 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0237 0.9703 0.000 0.996 0.004
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1031 0.9706 0.000 0.976 0.024
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.9579 1.000 0.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9579 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.1163 0.9330 0.028 0.000 0.972
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9579 1.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.1163 0.9330 0.028 0.000 0.972
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1163 0.9701 0.000 0.972 0.028
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9705 0.000 1.000 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0237 0.9703 0.000 0.996 0.004
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.1031 0.9706 0.000 0.976 0.024
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.1163 0.9701 0.000 0.972 0.028
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.1163 0.9330 0.028 0.000 0.972
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.1163 0.9091 0.000 0.028 0.972
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0000 0.9705 0.000 1.000 0.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0237 0.9703 0.000 0.996 0.004
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0237 0.9703 0.000 0.996 0.004
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0747 0.9713 0.000 0.984 0.016
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9579 1.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.1163 0.9330 0.028 0.000 0.972
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9579 1.000 0.000 0.000
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#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0237 0.9538 0.996 0.000 0.004
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0747 0.9627 0.000 0.984 0.016
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0592 0.9651 0.000 0.988 0.012
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0237 0.9703 0.000 0.996 0.004
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1163 0.9701 0.000 0.972 0.028
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9579 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1163 0.9701 0.000 0.972 0.028
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9579 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6215 0.2929 0.000 0.428 0.572
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1031 0.9706 0.000 0.976 0.024
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9705 0.000 1.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9579 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.5058 0.6640 0.000 0.756 0.244
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.1902 0.8030 0.000 0.064 0.004 0.932
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.1585 0.8251 0.004 0.040 0.004 0.952
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3873 0.8827 0.000 0.772 0.000 0.228
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.1474 0.8165 0.000 0.052 0.000 0.948
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3873 0.8827 0.000 0.772 0.000 0.228
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0817 0.7790 0.000 0.976 0.000 0.024
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3726 0.8850 0.000 0.788 0.000 0.212
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.3801 0.7853 0.000 0.220 0.000 0.780
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0188 0.8501 0.000 0.000 0.004 0.996
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3726 0.7893 0.000 0.212 0.000 0.788
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3688 0.7903 0.000 0.208 0.000 0.792
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.3266 0.8101 0.000 0.168 0.000 0.832
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.6522 0.6442 0.000 0.224 0.144 0.632
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3831 0.8847 0.000 0.792 0.004 0.204
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4018 0.7814 0.000 0.224 0.004 0.772
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0188 0.8491 0.000 0.004 0.000 0.996
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2921 0.8659 0.000 0.860 0.000 0.140
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3569 0.7968 0.000 0.196 0.000 0.804
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4103 0.7701 0.000 0.256 0.000 0.744
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.3400 0.8126 0.000 0.180 0.000 0.820
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2814 0.8621 0.000 0.868 0.000 0.132
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.3074 0.7655 0.000 0.000 0.152 0.848
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4483 0.8366 0.000 0.712 0.004 0.284
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3610 0.8838 0.000 0.800 0.000 0.200
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0592 0.7831 0.000 0.984 0.000 0.016
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4088 0.8801 0.000 0.764 0.004 0.232
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.2207 0.9017 0.932 0.024 0.004 0.040
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4155 0.8748 0.000 0.756 0.004 0.240
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.3726 0.8850 0.000 0.788 0.000 0.212
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.3688 0.7903 0.000 0.208 0.000 0.792
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0188 0.9570 0.000 0.000 0.996 0.004
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.5161 0.3161 0.000 0.300 0.024 0.676
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.0188 0.8491 0.000 0.004 0.000 0.996
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.1211 0.8480 0.000 0.040 0.000 0.960
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0188 0.8510 0.000 0.004 0.000 0.996
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.3441 0.7243 0.000 0.120 0.024 0.856
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.1930 0.8115 0.004 0.056 0.004 0.936
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3873 0.8827 0.000 0.772 0.000 0.228
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.0376 0.8481 0.000 0.004 0.004 0.992
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.3569 0.7968 0.000 0.196 0.000 0.804
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.7234 0.2908 0.568 0.204 0.004 0.224
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.1661 0.8143 0.000 0.052 0.004 0.944
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3726 0.8850 0.000 0.788 0.000 0.212
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.3569 0.7968 0.000 0.196 0.000 0.804
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3908 0.7860 0.000 0.212 0.004 0.784
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3870 0.7879 0.000 0.208 0.004 0.788
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0592 0.7831 0.000 0.984 0.000 0.016
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.1474 0.8220 0.000 0.052 0.000 0.948
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.3123 0.8723 0.000 0.844 0.000 0.156
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.3975 0.5217 0.000 0.240 0.000 0.760
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.3444 0.6283 0.000 0.184 0.000 0.816
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.1743 0.8107 0.000 0.056 0.004 0.940
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.3726 0.8850 0.000 0.788 0.000 0.212
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.1042 0.9495 0.972 0.008 0.020 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0592 0.7831 0.000 0.984 0.000 0.016
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1305 0.7741 0.000 0.960 0.004 0.036
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3837 0.8839 0.000 0.776 0.000 0.224
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4018 0.8837 0.000 0.772 0.004 0.224
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4072 0.7723 0.000 0.252 0.000 0.748
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0524 0.9580 0.004 0.008 0.988 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0524 0.9633 0.988 0.008 0.004 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.2814 0.8621 0.000 0.868 0.000 0.132
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.8377 0.2605 0.036 0.220 0.472 0.272
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.0592 0.8506 0.000 0.016 0.000 0.984
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.3837 0.8839 0.000 0.776 0.000 0.224
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.4011 0.7851 0.000 0.208 0.008 0.784
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.3942 0.8784 0.000 0.764 0.000 0.236
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.0564 0.8477 0.004 0.004 0.004 0.988
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.1396 0.8490 0.004 0.032 0.004 0.960
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.3893 0.7921 0.000 0.196 0.008 0.796
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.0188 0.8491 0.000 0.004 0.000 0.996
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.4790 0.0618 0.000 0.620 0.000 0.380
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.3837 0.7838 0.000 0.224 0.000 0.776
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 4 0.4916 -0.1397 0.000 0.424 0.000 0.576
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0524 0.9633 0.988 0.008 0.004 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.0817 0.8381 0.000 0.024 0.000 0.976
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.3688 0.7903 0.000 0.208 0.000 0.792
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.3907 0.8807 0.000 0.768 0.000 0.232
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.3266 0.8766 0.000 0.832 0.000 0.168
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0524 0.9580 0.004 0.008 0.988 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 4 0.4761 0.4453 0.000 0.000 0.372 0.628
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.0188 0.8491 0.000 0.004 0.000 0.996
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.4866 -0.0374 0.000 0.596 0.000 0.404
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0524 0.9580 0.004 0.008 0.988 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.4018 0.8819 0.000 0.772 0.004 0.224
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.3688 0.8849 0.000 0.792 0.000 0.208
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 4 0.1211 0.8483 0.000 0.040 0.000 0.960
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 4 0.4008 0.7763 0.000 0.244 0.000 0.756
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.0188 0.9602 0.004 0.000 0.996 0.000
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.2731 0.7654 0.092 0.896 0.004 0.008
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#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0779 0.7828 0.000 0.980 0.004 0.016
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.0592 0.8430 0.000 0.016 0.000 0.984
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0188 0.8491 0.000 0.004 0.000 0.996
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3528 0.8823 0.000 0.808 0.000 0.192
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4283 0.8621 0.000 0.740 0.004 0.256
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3873 0.8827 0.000 0.772 0.000 0.228
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4741 0.7790 0.000 0.668 0.004 0.328
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3933 0.7925 0.004 0.196 0.004 0.796
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.1716 0.8984 0.936 0.064 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1211 0.8480 0.000 0.040 0.000 0.960
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.3975 0.7781 0.000 0.240 0.000 0.760
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0707 0.7810 0.000 0.980 0.000 0.020
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0188 0.9657 0.996 0.004 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0592 0.7831 0.000 0.984 0.000 0.016
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9657 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.7716 0.1178 0.000 0.224 0.380 0.396
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3726 0.8850 0.000 0.788 0.000 0.212
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0000 0.8508 0.000 0.000 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0336 0.9651 0.992 0.008 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4123 0.7800 0.000 0.220 0.008 0.772
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.5350 -0.00519 0.000 0.052 0.000 0.488 0.460
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.4979 0.00156 0.000 0.028 0.000 0.492 0.480
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0955 0.72823 0.000 0.968 0.000 0.004 0.028
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.5264 0.48668 0.000 0.196 0.000 0.676 0.128
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.4874 0.31948 0.000 0.600 0.000 0.032 0.368
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4862 0.32571 0.000 0.604 0.000 0.032 0.364
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0955 0.72823 0.000 0.968 0.000 0.004 0.028
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.5322 0.24458 0.000 0.552 0.000 0.056 0.392
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.2511 0.72446 0.000 0.028 0.000 0.892 0.080
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0162 0.73613 0.000 0.996 0.000 0.004 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4313 0.49742 0.000 0.008 0.000 0.636 0.356
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1493 0.75309 0.000 0.028 0.000 0.948 0.024
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.1725 0.75141 0.000 0.020 0.000 0.936 0.044
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0290 0.94965 0.992 0.000 0.000 0.000 0.008
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0794 0.75348 0.000 0.028 0.000 0.972 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.2439 0.71064 0.000 0.004 0.000 0.876 0.120
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.1197 0.74252 0.000 0.000 0.000 0.952 0.048
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1582 0.75291 0.000 0.028 0.000 0.944 0.028
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.6042 0.37611 0.000 0.008 0.100 0.532 0.360
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4182 0.26821 0.000 0.644 0.000 0.004 0.352
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1195 0.75239 0.000 0.028 0.000 0.960 0.012
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4551 0.47372 0.000 0.016 0.000 0.616 0.368
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.2209 0.73510 0.000 0.032 0.000 0.912 0.056
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0404 0.73381 0.000 0.988 0.000 0.000 0.012
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1608 0.73520 0.000 0.000 0.000 0.928 0.072
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4909 0.43705 0.000 0.032 0.000 0.588 0.380
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.3239 0.71955 0.000 0.068 0.000 0.852 0.080
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0510 0.73343 0.000 0.984 0.000 0.000 0.016
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4940 0.28775 0.000 0.576 0.000 0.032 0.392
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1399 0.74921 0.000 0.000 0.020 0.952 0.028
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.6433 0.29864 0.000 0.340 0.000 0.188 0.472
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1195 0.75239 0.000 0.028 0.000 0.960 0.012
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0290 0.73474 0.000 0.992 0.000 0.000 0.008
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.2685 0.65358 0.000 0.880 0.000 0.028 0.092
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0609 0.94475 0.980 0.000 0.000 0.000 0.020
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.0955 0.75348 0.000 0.028 0.000 0.968 0.004
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4976 -0.05680 0.000 0.504 0.000 0.028 0.468
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.6207 0.14586 0.420 0.004 0.000 0.120 0.456
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 5 0.5693 0.15892 0.000 0.452 0.000 0.080 0.468
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0162 0.73613 0.000 0.996 0.000 0.004 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2488 0.70856 0.000 0.004 0.000 0.872 0.124
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0162 0.95055 0.996 0.000 0.000 0.000 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0404 0.94895 0.988 0.000 0.000 0.000 0.012
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0324 0.95017 0.000 0.000 0.992 0.004 0.004
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.6568 0.05629 0.000 0.500 0.004 0.276 0.220
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4663 0.45846 0.000 0.020 0.000 0.604 0.376
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3242 0.68709 0.000 0.040 0.000 0.844 0.116
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.1579 0.75206 0.000 0.024 0.000 0.944 0.032
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.1082 0.75340 0.000 0.028 0.000 0.964 0.008
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0162 0.95055 0.996 0.000 0.000 0.000 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.6739 -0.06769 0.000 0.356 0.004 0.424 0.216
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.5322 0.01618 0.004 0.040 0.000 0.476 0.480
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1697 0.70845 0.000 0.932 0.000 0.008 0.060
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.4465 0.45683 0.000 0.024 0.000 0.672 0.304
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2179 0.71695 0.000 0.000 0.000 0.888 0.112
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.7104 0.35794 0.308 0.052 0.000 0.144 0.496
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.5819 -0.08408 0.000 0.092 0.000 0.456 0.452
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0162 0.73613 0.000 0.996 0.000 0.004 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2068 0.72448 0.000 0.004 0.000 0.904 0.092
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3521 0.62984 0.000 0.004 0.000 0.764 0.232
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4763 0.36133 0.000 0.632 0.000 0.032 0.336
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3231 0.66038 0.000 0.004 0.000 0.800 0.196
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.4420 0.43905 0.000 0.692 0.000 0.028 0.280
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.5044 -0.10171 0.000 0.464 0.000 0.032 0.504
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.4854 0.40333 0.000 0.044 0.000 0.648 0.308
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0880 0.72966 0.000 0.968 0.000 0.000 0.032
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4714 0.37105 0.000 0.644 0.000 0.032 0.324
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.5019 0.25094 0.000 0.632 0.000 0.316 0.052
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.1195 0.75433 0.000 0.028 0.000 0.960 0.012
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4717 0.43715 0.000 0.020 0.000 0.584 0.396
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.1082 0.75313 0.000 0.028 0.000 0.964 0.008
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.2054 0.73979 0.000 0.028 0.000 0.920 0.052
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.5107 0.29723 0.000 0.356 0.000 0.596 0.048
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.5353 -0.03997 0.000 0.052 0.000 0.476 0.472
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.1281 0.75216 0.000 0.032 0.000 0.956 0.012
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0324 0.73595 0.000 0.992 0.000 0.004 0.004
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.3678 0.80222 0.804 0.012 0.004 0.008 0.172
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.4301 0.46366 0.000 0.712 0.000 0.028 0.260
#> DBFA1780-4558-436A-A434-05DAFD0F675A 5 0.4425 0.32154 0.000 0.244 0.000 0.040 0.716
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0290 0.94965 0.992 0.000 0.000 0.000 0.008
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0324 0.73562 0.000 0.992 0.000 0.004 0.004
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0162 0.95055 0.996 0.000 0.000 0.000 0.004
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.3662 0.49652 0.000 0.744 0.000 0.004 0.252
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4940 0.42255 0.000 0.032 0.000 0.576 0.392
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.1502 0.93577 0.004 0.000 0.940 0.000 0.056
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0404 0.73381 0.000 0.988 0.000 0.000 0.012
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.7040 0.20934 0.008 0.008 0.424 0.204 0.356
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.1106 0.75458 0.000 0.024 0.000 0.964 0.012
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0162 0.73613 0.000 0.996 0.000 0.004 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.3522 0.64536 0.000 0.004 0.004 0.780 0.212
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.95057 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.1331 0.71930 0.000 0.952 0.000 0.008 0.040
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.4902 0.05035 0.000 0.024 0.000 0.508 0.468
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4651 0.46337 0.000 0.020 0.000 0.608 0.372
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.4637 0.10819 0.000 0.012 0.000 0.536 0.452
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.2286 0.71809 0.000 0.000 0.004 0.888 0.108
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.2139 0.73672 0.000 0.032 0.000 0.916 0.052
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.6536 0.08859 0.000 0.196 0.000 0.408 0.396
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0703 0.94566 0.976 0.000 0.000 0.000 0.024
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4298 0.50210 0.000 0.008 0.000 0.640 0.352
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 4 0.6569 -0.10464 0.000 0.336 0.000 0.448 0.216
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.3594 0.80335 0.804 0.012 0.004 0.004 0.176
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0404 0.94895 0.988 0.000 0.000 0.000 0.012
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.4920 0.29910 0.000 0.584 0.000 0.032 0.384
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.2592 0.72688 0.000 0.052 0.000 0.892 0.056
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.3333 0.65067 0.000 0.004 0.000 0.788 0.208
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.1830 0.70170 0.000 0.924 0.000 0.008 0.068
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0404 0.73381 0.000 0.988 0.000 0.000 0.012
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#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0324 0.73562 0.000 0.992 0.000 0.004 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.1357 0.72305 0.000 0.948 0.000 0.004 0.048
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.5171 0.04775 0.000 0.040 0.000 0.504 0.456
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.4266 0.63723 0.000 0.120 0.000 0.776 0.104
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0671 0.73356 0.000 0.980 0.000 0.016 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1502 0.93577 0.004 0.000 0.940 0.000 0.056
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.3594 0.80335 0.804 0.012 0.004 0.004 0.176
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.4428 0.32499 0.004 0.284 0.000 0.020 0.692
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0880 0.73076 0.000 0.968 0.000 0.000 0.032
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.4021 0.71818 0.000 0.000 0.780 0.052 0.168
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1041 0.72675 0.000 0.964 0.000 0.004 0.032
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3662 0.61193 0.000 0.004 0.000 0.744 0.252
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 5 0.6420 0.22278 0.000 0.260 0.000 0.232 0.508
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.1195 0.75239 0.000 0.028 0.000 0.960 0.012
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.2304 0.72598 0.000 0.008 0.000 0.892 0.100
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4179 0.52133 0.000 0.776 0.000 0.152 0.072
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0162 0.95055 0.996 0.000 0.000 0.000 0.004
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.6629 0.05173 0.000 0.324 0.004 0.468 0.204
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.1300 0.75306 0.000 0.016 0.000 0.956 0.028
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.3526 0.68181 0.000 0.096 0.000 0.832 0.072
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.6433 0.34203 0.000 0.188 0.000 0.340 0.472
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.5071 0.12681 0.000 0.036 0.000 0.540 0.424
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1195 0.75239 0.000 0.028 0.000 0.960 0.012
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3424 0.50749 0.000 0.760 0.000 0.000 0.240
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.5867 0.47623 0.000 0.000 0.604 0.180 0.216
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.2344 0.73127 0.000 0.032 0.000 0.904 0.064
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3181 0.63690 0.000 0.856 0.000 0.072 0.072
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0162 0.95237 0.000 0.000 0.996 0.000 0.004
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0290 0.95026 0.992 0.000 0.000 0.000 0.008
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.6528 0.24495 0.372 0.020 0.000 0.120 0.488
#> 3C032234-C350-4170-B8F7-F8DE8269E713 5 0.6608 0.16770 0.000 0.244 0.000 0.300 0.456
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.2927 0.70957 0.000 0.040 0.000 0.868 0.092
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3119 0.64125 0.000 0.860 0.000 0.072 0.068
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1403 0.75290 0.000 0.024 0.000 0.952 0.024
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2825 0.66015 0.000 0.860 0.000 0.016 0.124
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0162 0.95516 0.004 0.000 0.996 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3231 0.66033 0.000 0.004 0.000 0.800 0.196
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 5 0.4757 0.19819 0.000 0.380 0.000 0.024 0.596
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.3477 0.66977 0.000 0.040 0.000 0.824 0.136
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.3033 0.71030 0.000 0.084 0.000 0.864 0.052
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0880 0.73018 0.000 0.968 0.000 0.000 0.032
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.1195 0.75239 0.000 0.028 0.000 0.960 0.012
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4893 0.46892 0.000 0.704 0.000 0.088 0.208
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0693 0.73366 0.000 0.980 0.000 0.008 0.012
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.5650 0.14427 0.000 0.460 0.000 0.076 0.464
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2439 0.71064 0.000 0.004 0.000 0.876 0.120
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3861 0.63156 0.728 0.000 0.000 0.008 0.264
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1403 0.75290 0.000 0.024 0.000 0.952 0.024
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.1399 0.75097 0.000 0.028 0.000 0.952 0.020
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4675 0.45314 0.000 0.020 0.000 0.600 0.380
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4276 0.47316 0.000 0.724 0.000 0.032 0.244
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0290 0.94965 0.992 0.000 0.000 0.000 0.008
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4301 0.46366 0.000 0.712 0.000 0.028 0.260
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0880 0.94606 0.968 0.000 0.000 0.000 0.032
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.6966 0.14060 0.000 0.008 0.252 0.384 0.356
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0290 0.73474 0.000 0.992 0.000 0.000 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1582 0.74858 0.000 0.028 0.000 0.944 0.028
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0794 0.94423 0.972 0.000 0.000 0.000 0.028
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4817 0.46836 0.000 0.008 0.016 0.608 0.368
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.3298 0.62781 0.000 0.000 0.000 0.236 0.756 0.008
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.2994 0.63426 0.000 0.000 0.000 0.208 0.788 0.004
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0993 0.78968 0.000 0.964 0.000 0.000 0.024 0.012
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.6826 0.27246 0.000 0.224 0.000 0.504 0.140 0.132
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1745 0.92329 0.924 0.000 0.000 0.000 0.020 0.056
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.4314 0.29844 0.000 0.444 0.000 0.000 0.020 0.536
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.4463 0.30411 0.000 0.456 0.000 0.000 0.028 0.516
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.94086 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1500 0.78548 0.000 0.936 0.000 0.000 0.012 0.052
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.94086 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.3875 0.50098 0.000 0.260 0.000 0.008 0.016 0.716
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.3787 0.71504 0.000 0.000 0.000 0.780 0.100 0.120
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0405 0.79011 0.000 0.988 0.000 0.000 0.004 0.008
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.3817 0.10571 0.000 0.000 0.000 0.568 0.000 0.432
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1327 0.74703 0.000 0.000 0.000 0.936 0.000 0.064
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.2623 0.76062 0.000 0.000 0.000 0.852 0.016 0.132
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1245 0.93008 0.952 0.000 0.000 0.000 0.016 0.032
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0603 0.76773 0.000 0.000 0.000 0.980 0.016 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.2597 0.67280 0.000 0.000 0.000 0.824 0.000 0.176
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.2178 0.71038 0.000 0.000 0.000 0.868 0.000 0.132
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1863 0.73206 0.000 0.000 0.000 0.896 0.000 0.104
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5188 -0.06981 0.000 0.004 0.076 0.496 0.000 0.424
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 5 0.4808 0.11025 0.000 0.468 0.000 0.000 0.480 0.052
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0891 0.76970 0.000 0.000 0.000 0.968 0.024 0.008
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.4057 0.31300 0.000 0.008 0.000 0.436 0.000 0.556
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3436 0.73957 0.000 0.004 0.000 0.812 0.056 0.128
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0790 0.78754 0.000 0.968 0.000 0.000 0.000 0.032
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2003 0.75622 0.000 0.000 0.000 0.884 0.000 0.116
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.1151 0.92948 0.956 0.000 0.000 0.000 0.032 0.012
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.4313 0.42234 0.000 0.020 0.000 0.372 0.004 0.604
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.2805 0.69181 0.000 0.012 0.000 0.828 0.000 0.160
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0777 0.78144 0.000 0.972 0.000 0.000 0.004 0.024
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.4644 0.30066 0.000 0.456 0.000 0.000 0.040 0.504
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1003 0.76760 0.000 0.000 0.000 0.964 0.020 0.016
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.4307 0.64653 0.000 0.148 0.000 0.100 0.744 0.008
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1138 0.76945 0.000 0.004 0.000 0.960 0.024 0.012
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0458 0.78548 0.000 0.984 0.000 0.000 0.000 0.016
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.2882 0.72218 0.000 0.812 0.000 0.000 0.008 0.180
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1967 0.89942 0.904 0.000 0.000 0.000 0.084 0.012
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2636 0.76095 0.000 0.004 0.000 0.860 0.016 0.120
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 5 0.4767 0.55881 0.000 0.252 0.000 0.020 0.672 0.056
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.4041 0.59742 0.164 0.000 0.000 0.060 0.764 0.012
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.94086 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 5 0.5294 0.59234 0.000 0.212 0.000 0.044 0.660 0.084
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0777 0.78888 0.000 0.972 0.000 0.000 0.004 0.024
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2597 0.67280 0.000 0.000 0.000 0.824 0.000 0.176
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0858 0.93271 0.968 0.000 0.000 0.000 0.028 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1245 0.93008 0.952 0.000 0.000 0.000 0.016 0.032
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2218 0.83056 0.000 0.000 0.884 0.104 0.000 0.012
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.7574 -0.07763 0.000 0.312 0.000 0.184 0.308 0.196
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.4151 0.35844 0.000 0.008 0.000 0.412 0.004 0.576
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3896 0.63564 0.000 0.000 0.000 0.748 0.196 0.056
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.1910 0.76658 0.000 0.000 0.000 0.892 0.000 0.108
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.2383 0.76278 0.000 0.000 0.000 0.880 0.024 0.096
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.94086 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.7671 0.14458 0.000 0.256 0.000 0.244 0.304 0.196
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.3219 0.63562 0.004 0.000 0.000 0.192 0.792 0.012
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1713 0.78319 0.000 0.928 0.000 0.000 0.044 0.028
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.4561 0.25259 0.000 0.000 0.000 0.428 0.536 0.036
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1594 0.92417 0.932 0.000 0.000 0.000 0.016 0.052
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2416 0.68954 0.000 0.000 0.000 0.844 0.000 0.156
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.3488 0.62021 0.108 0.000 0.000 0.060 0.820 0.012
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 5 0.3969 0.60279 0.000 0.012 0.000 0.276 0.700 0.012
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0547 0.78645 0.000 0.980 0.000 0.000 0.000 0.020
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2178 0.70897 0.000 0.000 0.000 0.868 0.000 0.132
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3126 0.57729 0.000 0.000 0.000 0.752 0.000 0.248
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 6 0.4097 0.24117 0.000 0.488 0.000 0.000 0.008 0.504
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.2854 0.63642 0.000 0.000 0.000 0.792 0.000 0.208
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.4095 -0.17444 0.000 0.512 0.000 0.000 0.008 0.480
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.4781 0.47655 0.000 0.320 0.000 0.000 0.072 0.608
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.5573 0.14875 0.000 0.004 0.000 0.416 0.460 0.120
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1333 0.77035 0.000 0.944 0.000 0.000 0.008 0.048
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.3925 0.34231 0.000 0.656 0.000 0.008 0.004 0.332
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.6363 0.18392 0.000 0.460 0.000 0.340 0.036 0.164
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.2257 0.76267 0.000 0.000 0.000 0.876 0.008 0.116
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0790 0.93165 0.968 0.000 0.000 0.000 0.032 0.000
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#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1594 0.77459 0.000 0.932 0.000 0.000 0.016 0.052
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0993 0.76913 0.000 0.000 0.000 0.964 0.024 0.012
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.5292 0.41833 0.000 0.616 0.000 0.052 0.288 0.044
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#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2562 0.67494 0.000 0.000 0.000 0.828 0.000 0.172
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#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0858 0.76030 0.000 0.000 0.000 0.968 0.004 0.028
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2480 0.76130 0.000 0.000 0.000 0.872 0.024 0.104
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.4348 0.39711 0.000 0.008 0.000 0.376 0.016 0.600
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.3023 0.54009 0.000 0.768 0.000 0.000 0.000 0.232
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1092 0.93034 0.960 0.000 0.000 0.000 0.020 0.020
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4086 -0.14718 0.000 0.528 0.000 0.000 0.008 0.464
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2688 0.89177 0.868 0.000 0.000 0.000 0.068 0.064
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.5903 0.27466 0.000 0.000 0.208 0.364 0.000 0.428
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0790 0.78748 0.000 0.968 0.000 0.000 0.000 0.032
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2651 0.75778 0.000 0.000 0.000 0.860 0.028 0.112
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1594 0.92578 0.932 0.000 0.000 0.000 0.016 0.052
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.4601 0.34862 0.000 0.004 0.032 0.408 0.000 0.556
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 17581 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 0.906 0.952 0.977 0.4705 0.531 0.531
#> 3 3 0.894 0.912 0.963 0.3698 0.695 0.486
#> 4 4 0.739 0.650 0.842 0.1517 0.796 0.501
#> 5 5 0.780 0.705 0.838 0.0655 0.869 0.562
#> 6 6 0.778 0.729 0.859 0.0472 0.902 0.588
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9797 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4815 0.8846 0.896 0.104
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9797 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0376 0.9794 0.004 0.996
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0376 0.9722 0.996 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9797 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9797 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9715 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9797 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9715 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9797 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0376 0.9794 0.004 0.996
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9797 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0376 0.9794 0.004 0.996
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0376 0.9794 0.004 0.996
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0376 0.9794 0.004 0.996
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0376 0.9722 0.996 0.004
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0376 0.9794 0.004 0.996
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.9129 0.5065 0.328 0.672
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0376 0.9794 0.004 0.996
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0376 0.9794 0.004 0.996
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.5629 0.8500 0.132 0.868
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9797 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2043 0.9559 0.032 0.968
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0672 0.9771 0.008 0.992
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0376 0.9794 0.004 0.996
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9797 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0376 0.9794 0.004 0.996
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0376 0.9722 0.996 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0376 0.9794 0.004 0.996
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0376 0.9722 0.996 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0376 0.9794 0.004 0.996
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9797 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9797 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.1184 0.9603 0.984 0.016
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9797 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0376 0.9794 0.004 0.996
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9797 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9797 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0376 0.9722 0.996 0.004
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0376 0.9794 0.004 0.996
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9797 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0376 0.9722 0.996 0.004
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.9715 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9797 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9797 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0376 0.9794 0.004 0.996
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0376 0.9722 0.996 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0376 0.9722 0.996 0.004
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.9715 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.9522 0.4060 0.372 0.628
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.5408 0.8598 0.124 0.876
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0376 0.9794 0.004 0.996
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0376 0.9794 0.004 0.996
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0376 0.9794 0.004 0.996
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.9715 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0376 0.9722 0.996 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.9323 0.4668 0.348 0.652
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0376 0.9722 0.996 0.004
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0376 0.9722 0.996 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9797 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.7056 0.7760 0.808 0.192
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0376 0.9722 0.996 0.004
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0376 0.9794 0.004 0.996
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0376 0.9722 0.996 0.004
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9797 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9797 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0376 0.9794 0.004 0.996
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.7815 0.7098 0.232 0.768
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9797 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0376 0.9722 0.996 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.6148 0.8262 0.152 0.848
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0376 0.9722 0.996 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9797 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.9797 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9797 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9797 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0376 0.9794 0.004 0.996
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0376 0.9794 0.004 0.996
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0376 0.9794 0.004 0.996
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0376 0.9722 0.996 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0376 0.9794 0.004 0.996
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.9715 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0376 0.9794 0.004 0.996
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.6247 0.8224 0.844 0.156
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0376 0.9794 0.004 0.996
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9797 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0376 0.9794 0.004 0.996
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9797 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0376 0.9722 0.996 0.004
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9797 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9797 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0376 0.9722 0.996 0.004
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9797 0.000 1.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0376 0.9722 0.996 0.004
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9797 0.000 1.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.0000 0.9715 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.9797 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.9715 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0376 0.9722 0.996 0.004
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9797 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.0000 0.9715 1.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.9715 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0376 0.9794 0.004 0.996
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0376 0.9722 0.996 0.004
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9797 0.000 1.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.4939 0.8783 0.108 0.892
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0376 0.9722 0.996 0.004
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9797 0.000 1.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.6973 0.7814 0.812 0.188
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0376 0.9794 0.004 0.996
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.7602 0.7357 0.780 0.220
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.0000 0.9715 1.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0376 0.9794 0.004 0.996
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#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0376 0.9722 0.996 0.004
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#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0376 0.9794 0.004 0.996
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#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0376 0.9722 0.996 0.004
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0376 0.9722 0.996 0.004
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.0000 0.9715 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0376 0.9722 0.996 0.004
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.0000 0.9715 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.9797 0.000 1.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0376 0.9794 0.004 0.996
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0376 0.9794 0.004 0.996
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#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.0000 0.9715 1.000 0.000
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#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0376 0.9794 0.004 0.996
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#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0376 0.9722 0.996 0.004
#> B422FFF3-623B-419A-964E-046BAE3578B3 1 0.0000 0.9715 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0376 0.9722 0.996 0.004
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.0938 0.9739 0.012 0.988
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.0376 0.9794 0.004 0.996
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0376 0.9722 0.996 0.004
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.0000 0.9715 1.000 0.000
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.7219 0.7564 0.200 0.800
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.0000 0.9797 0.000 1.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0376 0.9794 0.004 0.996
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0376 0.9794 0.004 0.996
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.0376 0.9794 0.004 0.996
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 1 0.0000 0.9715 1.000 0.000
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.6887 0.7772 0.184 0.816
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.0376 0.9722 0.996 0.004
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0376 0.9722 0.996 0.004
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.0376 0.9794 0.004 0.996
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0376 0.9794 0.004 0.996
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.0000 0.9797 0.000 1.000
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.4562 0.8902 0.096 0.904
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.0000 0.9797 0.000 1.000
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.0000 0.9797 0.000 1.000
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.0376 0.9794 0.004 0.996
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.0376 0.9794 0.004 0.996
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 1 0.0376 0.9722 0.996 0.004
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 1 0.5629 0.8462 0.868 0.132
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#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.0376 0.9722 0.996 0.004
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 1 0.0000 0.9715 1.000 0.000
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.0000 0.9715 1.000 0.000
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0376 0.9722 0.996 0.004
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0376 0.9794 0.004 0.996
#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.0000 0.9715 1.000 0.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.0376 0.9794 0.004 0.996
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.0376 0.9794 0.004 0.996
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0376 0.9794 0.004 0.996
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0376 0.9794 0.004 0.996
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0376 0.9794 0.004 0.996
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0376 0.9794 0.004 0.996
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 1 0.7219 0.7649 0.800 0.200
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0376 0.9722 0.996 0.004
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0376 0.9722 0.996 0.004
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9797 0.000 1.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0672 0.9740 0.008 0.992
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 1 0.7528 0.7393 0.784 0.216
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.0000 0.9715 1.000 0.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0376 0.9722 0.996 0.004
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9797 0.000 1.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.0000 0.9715 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0000 0.9797 0.000 1.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.6048 0.8315 0.852 0.148
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0376 0.9794 0.004 0.996
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.0000 0.9715 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.9977 0.0761 0.472 0.528
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0376 0.9794 0.004 0.996
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0376 0.9722 0.996 0.004
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.0000 0.9715 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.9797 0.000 1.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0376 0.9794 0.004 0.996
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.0000 0.9715 1.000 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.6712 0.7878 0.176 0.824
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0376 0.9794 0.004 0.996
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0376 0.9794 0.004 0.996
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0376 0.9722 0.996 0.004
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0376 0.9722 0.996 0.004
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0376 0.9794 0.004 0.996
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9797 0.000 1.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9797 0.000 1.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.9170 0.4957 0.332 0.668
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9797 0.000 1.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9797 0.000 1.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.0000 0.9715 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0376 0.9794 0.004 0.996
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.9797 0.000 1.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9797 0.000 1.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0376 0.9794 0.004 0.996
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0376 0.9794 0.004 0.996
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0376 0.9794 0.004 0.996
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.0000 0.9715 1.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9797 0.000 1.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0376 0.9722 0.996 0.004
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9797 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9797 0.000 1.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0938 0.9740 0.012 0.988
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0376 0.9722 0.996 0.004
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9797 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0376 0.9794 0.004 0.996
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0376 0.9722 0.996 0.004
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.0000 0.9715 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0376 0.9794 0.004 0.996
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0376 0.9794 0.004 0.996
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9797 0.000 1.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0376 0.9722 0.996 0.004
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0376 0.9722 0.996 0.004
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9797 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9797 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9797 0.000 1.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0376 0.9794 0.004 0.996
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9797 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.0000 0.9715 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0376 0.9794 0.004 0.996
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0376 0.9722 0.996 0.004
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0376 0.9722 0.996 0.004
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9797 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0376 0.9722 0.996 0.004
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9797 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9797 0.000 1.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0376 0.9794 0.004 0.996
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0000 0.9715 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9797 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9797 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.9715 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9797 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9797 0.000 1.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.0376 0.9722 0.996 0.004
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0376 0.9794 0.004 0.996
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0376 0.9794 0.004 0.996
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.9715 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.9715 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0376 0.9722 0.996 0.004
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.1184 0.9673 0.016 0.984
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9797 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9715 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9797 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0376 0.9794 0.004 0.996
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9797 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0376 0.9794 0.004 0.996
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0376 0.9794 0.004 0.996
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0376 0.9794 0.004 0.996
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0376 0.9722 0.996 0.004
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.7376 0.7405 0.208 0.792
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0376 0.9794 0.004 0.996
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0376 0.9794 0.004 0.996
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9797 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9797 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0376 0.9794 0.004 0.996
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9797 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9715 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0376 0.9794 0.004 0.996
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0376 0.9722 0.996 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0376 0.9794 0.004 0.996
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9715 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0376 0.9722 0.996 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9715 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0376 0.9722 0.996 0.004
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9797 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0376 0.9794 0.004 0.996
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0376 0.9794 0.004 0.996
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0376 0.9794 0.004 0.996
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9797 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9715 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0376 0.9794 0.004 0.996
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9797 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0376 0.9722 0.996 0.004
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0376 0.9794 0.004 0.996
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0376 0.9794 0.004 0.996
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9797 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.7674 0.7295 0.776 0.224
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.5519 0.8467 0.128 0.872
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9797 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9797 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.0000 0.9715 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0376 0.9722 0.996 0.004
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0376 0.9794 0.004 0.996
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0376 0.9794 0.004 0.996
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.5178 0.8697 0.116 0.884
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9797 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0376 0.9722 0.996 0.004
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9797 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0376 0.9722 0.996 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.6531 0.8000 0.832 0.168
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9797 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.1414 0.9670 0.020 0.980
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0376 0.9722 0.996 0.004
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9715 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2356 0.9063 0.072 0.928 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.9759 1.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9753 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9753 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9759 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9753 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9753 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9212 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9753 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9212 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9753 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.6126 0.4258 0.000 0.400 0.600
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9753 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 3 0.0000 0.9212 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.9212 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9753 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9759 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.0000 0.9212 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 3 0.0000 0.9212 0.000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0000 0.9212 0.000 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5560 0.5525 0.000 0.700 0.300
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.0000 0.9212 0.000 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9753 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0000 0.9212 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.4235 0.7643 0.000 0.176 0.824
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 3 0.6244 0.3228 0.000 0.440 0.560
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9753 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 3 0.0000 0.9212 0.000 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9759 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.4555 0.7284 0.000 0.800 0.200
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9759 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0892 0.9574 0.000 0.980 0.020
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9753 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9753 0.000 1.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.9212 0.000 0.000 1.000
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#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9753 0.000 1.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.4121 0.7884 0.832 0.168 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9753 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9753 0.000 1.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9212 0.000 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0592 0.9647 0.000 0.988 0.012
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0592 0.9651 0.012 0.988 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9753 0.000 1.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9753 0.000 1.000 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9753 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9753 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0000 0.9212 0.000 0.000 1.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.1860 0.9276 0.052 0.948 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9759 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9753 0.000 1.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9753 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 3 0.3192 0.8350 0.000 0.112 0.888
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9759 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9753 0.000 1.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9753 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9759 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9212 0.000 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 3 0.6192 0.3756 0.000 0.420 0.580
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 3 0.6204 0.3665 0.000 0.424 0.576
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9753 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9759 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9759 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9753 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9753 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9753 0.000 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 3 0.0000 0.9212 0.000 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9753 0.000 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.9212 0.000 0.000 1.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.3879 0.7938 0.000 0.848 0.152
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9759 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9759 1.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9753 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9759 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.1163 0.9508 0.028 0.972 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9753 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 3 0.5254 0.6769 0.000 0.264 0.736
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9212 0.000 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9753 0.000 1.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9753 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9212 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9753 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9753 0.000 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.0000 0.9759 1.000 0.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9753 0.000 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9753 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9212 0.000 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9212 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9759 1.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0000 0.9759 1.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9753 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.9212 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9753 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 3 0.4605 0.7553 0.000 0.204 0.796
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9753 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.9212 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.1031 0.9530 0.000 0.976 0.024
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9753 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9759 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.6168 0.3973 0.000 0.412 0.588
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9753 0.000 1.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9753 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.3551 0.8329 0.868 0.132 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9753 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 3 0.0000 0.9212 0.000 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9753 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0000 0.9212 0.000 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9753 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9759 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9753 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9212 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9759 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9212 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9759 1.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9753 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9753 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9753 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.0000 0.9212 0.000 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9753 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9212 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 3 0.5138 0.6607 0.000 0.252 0.748
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9753 0.000 1.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9759 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9753 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9753 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9753 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.9212 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9753 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9753 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9753 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.9212 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9759 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.0000 0.9212 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.4555 0.7583 0.000 0.200 0.800
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.6180 0.2659 0.000 0.584 0.416
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9753 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9759 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9753 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9759 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9212 0.000 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9753 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0592 0.9130 0.000 0.012 0.988
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9759 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.0000 0.9212 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.1940 0.33006 0.000 0.076 0.000 0.924
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.2216 0.29572 0.000 0.092 0.000 0.908
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1389 0.40355 0.000 0.952 0.000 0.048
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4817 0.41424 0.000 0.000 0.388 0.612
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.2530 0.74797 0.000 0.000 0.888 0.112
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5827 0.63101 0.000 0.396 0.036 0.568
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.6356 0.48613 0.000 0.088 0.308 0.604
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3074 0.57431 0.000 0.152 0.000 0.848
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.5016 0.37341 0.000 0.396 0.600 0.004
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.4855 0.40133 0.000 0.000 0.400 0.600
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.7758 -0.38707 0.000 0.396 0.368 0.236
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.4331 0.48405 0.000 0.000 0.288 0.712
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4877 0.65136 0.000 0.408 0.000 0.592
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.2944 0.23726 0.000 0.868 0.004 0.128
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0336 0.84992 0.000 0.000 0.992 0.008
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4898 0.76305 0.000 0.584 0.000 0.416
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4697 0.29441 0.000 0.000 0.644 0.356
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0188 0.47838 0.000 0.996 0.000 0.004
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4356 0.48357 0.000 0.000 0.292 0.708
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.5476 0.76477 0.020 0.584 0.000 0.396
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4855 0.77593 0.000 0.600 0.000 0.400
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.7835 -0.41816 0.000 0.396 0.336 0.268
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.7055 -0.00727 0.000 0.396 0.480 0.124
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.7793 -0.39795 0.000 0.396 0.356 0.248
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3402 0.53216 0.000 0.004 0.164 0.832
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.6555 -0.00748 0.000 0.076 0.480 0.444
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4843 0.77884 0.000 0.604 0.000 0.396
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#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.2149 0.55969 0.000 0.912 0.000 0.088
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.4992 0.02343 0.524 0.000 0.000 0.476
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.5016 0.77630 0.004 0.600 0.000 0.396
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.7273 0.37748 0.148 0.400 0.000 0.452
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.4855 0.40133 0.000 0.000 0.400 0.600
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.3444 0.54154 0.000 0.816 0.000 0.184
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.2048 0.50395 0.000 0.008 0.064 0.928
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.6381 0.60056 0.000 0.196 0.152 0.652
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4989 0.70813 0.000 0.528 0.000 0.472
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.5376 0.64677 0.000 0.396 0.016 0.588
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.5898 0.74819 0.048 0.604 0.000 0.348
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.1867 0.89089 0.928 0.000 0.072 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.3400 0.06146 0.000 0.180 0.000 0.820
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4981 0.71705 0.000 0.536 0.000 0.464
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.2469 0.85291 0.892 0.108 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.4331 0.53422 0.000 0.288 0.712 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0188 0.46952 0.000 0.996 0.000 0.004
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.4967 -0.02474 0.000 0.000 0.548 0.452
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4877 0.76927 0.000 0.592 0.000 0.408
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.6393 -0.02349 0.000 0.064 0.480 0.456
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.0469 0.44494 0.000 0.012 0.000 0.988
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.3726 0.71712 0.788 0.212 0.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.4790 0.65705 0.000 0.380 0.000 0.620
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4277 0.54491 0.000 0.280 0.720 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0000 0.46248 0.000 0.000 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4500 -0.26582 0.000 0.684 0.000 0.316
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.1118 0.40913 0.000 0.036 0.000 0.964
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.85588 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2149 0.55969 0.000 0.912 0.000 0.088
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.0336 0.45103 0.000 0.008 0.000 0.992
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0000 0.46248 0.000 0.000 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.3528 0.62915 0.000 0.000 0.808 0.192
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5000 0.67992 0.000 0.504 0.000 0.496
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.6660 0.37614 0.000 0.288 0.592 0.120
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0188 0.96705 0.996 0.004 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4843 0.40729 0.000 0.000 0.396 0.604
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4843 0.65803 0.000 0.396 0.000 0.604
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.47417 0.000 1.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2149 0.55969 0.000 0.912 0.000 0.088
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5016 0.37341 0.000 0.396 0.600 0.004
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4843 0.77884 0.000 0.604 0.000 0.396
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4855 0.40133 0.000 0.000 0.400 0.600
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.97092 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5016 0.37341 0.000 0.396 0.600 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.0404 0.46797 0.000 0.012 0.000 0.000 0.988
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4126 0.66086 0.620 0.000 0.000 0.000 0.380
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.5831 0.54544 0.000 0.220 0.000 0.172 0.608
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4291 0.15978 0.000 0.464 0.000 0.536 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.4297 0.13839 0.000 0.472 0.000 0.528 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.3983 0.41200 0.000 0.340 0.000 0.660 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.4088 0.74706 0.000 0.000 0.000 0.368 0.632
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.65780 0.000 0.000 0.000 1.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.6178 0.18014 0.000 0.000 0.536 0.296 0.168
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3876 0.01490 0.000 0.000 0.000 0.684 0.316
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0609 0.64757 0.000 0.000 0.000 0.980 0.020
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.3074 0.34975 0.000 0.000 0.000 0.804 0.196
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4219 -0.39506 0.000 0.000 0.000 0.584 0.416
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.4201 0.22536 0.000 0.000 0.408 0.592 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3039 0.74403 0.000 0.808 0.000 0.000 0.192
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.2773 0.59883 0.000 0.000 0.164 0.836 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 5 0.4101 0.74710 0.000 0.000 0.000 0.372 0.628
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2929 0.39589 0.000 0.000 0.000 0.820 0.180
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0000 0.65780 0.000 0.000 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.3857 0.45852 0.000 0.312 0.000 0.688 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4283 0.07837 0.000 0.544 0.000 0.456 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.3669 0.76477 0.000 0.000 0.816 0.056 0.128
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.4307 -0.42260 0.000 0.496 0.000 0.000 0.504
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 5 0.4299 0.74028 0.000 0.000 0.004 0.388 0.608
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3949 0.40681 0.000 0.668 0.000 0.332 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.3661 0.67696 0.000 0.724 0.000 0.000 0.276
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.4088 0.67256 0.632 0.000 0.000 0.000 0.368
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4210 0.54888 0.000 0.588 0.000 0.000 0.412
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1943 0.64430 0.000 0.000 0.056 0.924 0.020
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
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#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 4 0.0898 0.64975 0.000 0.008 0.000 0.972 0.020
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 5 0.4225 0.74612 0.000 0.004 0.000 0.364 0.632
#> DCD932D2-B708-487A-93C1-8485FBE9048A 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 5 0.0000 0.47400 0.000 0.000 0.000 0.000 1.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.4686 0.55630 0.020 0.596 0.000 0.000 0.384
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.3710 0.57980 0.000 0.000 0.192 0.784 0.024
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 3 0.0404 0.93962 0.012 0.000 0.988 0.000 0.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4150 0.57176 0.000 0.612 0.000 0.000 0.388
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 4 0.6539 0.20857 0.200 0.000 0.000 0.432 0.368
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 3 0.3011 0.80167 0.000 0.000 0.844 0.016 0.140
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 5 0.5648 0.56273 0.000 0.000 0.076 0.448 0.476
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 5 0.4088 0.74706 0.000 0.000 0.000 0.368 0.632
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.4088 0.67256 0.632 0.000 0.000 0.000 0.368
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 5 0.4294 -0.29546 0.000 0.000 0.000 0.468 0.532
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.0162 0.65817 0.000 0.000 0.004 0.996 0.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.4088 0.45119 0.368 0.000 0.632 0.000 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0290 0.86580 0.000 0.992 0.000 0.000 0.008
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.0794 0.64216 0.000 0.000 0.000 0.972 0.028
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 5 0.4225 0.74612 0.000 0.004 0.000 0.364 0.632
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 5 0.4182 0.73071 0.000 0.000 0.000 0.400 0.600
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.3684 0.67266 0.000 0.720 0.000 0.000 0.280
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.2516 0.74705 0.000 0.860 0.000 0.140 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 5 0.3508 0.15409 0.252 0.000 0.000 0.000 0.748
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.0000 0.65780 0.000 0.000 0.000 1.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4138 0.57489 0.000 0.616 0.000 0.000 0.384
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4268 -0.42359 0.000 0.000 0.000 0.556 0.444
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4182 0.28879 0.000 0.600 0.000 0.000 0.400
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.2020 0.85834 0.000 0.000 0.900 0.000 0.100
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 5 0.5627 0.08169 0.240 0.044 0.000 0.052 0.664
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.4294 0.14931 0.000 0.468 0.000 0.532 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.5304 0.52468 0.000 0.560 0.000 0.056 0.384
#> 2356B998-0930-403F-9B04-57A18A150955 5 0.4126 0.74553 0.000 0.000 0.000 0.380 0.620
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 5 0.4671 0.72737 0.000 0.028 0.000 0.332 0.640
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 5 0.4138 0.74411 0.000 0.000 0.000 0.384 0.616
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4150 0.57176 0.000 0.612 0.000 0.000 0.388
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.4088 0.67256 0.632 0.000 0.000 0.000 0.368
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4323 0.43906 0.000 0.656 0.000 0.012 0.332
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.0794 0.64216 0.000 0.000 0.000 0.972 0.028
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0162 0.94657 0.000 0.000 0.996 0.000 0.004
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 5 0.4088 0.74706 0.000 0.000 0.000 0.368 0.632
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.4074 0.67569 0.636 0.000 0.000 0.000 0.364
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4551 0.57593 0.000 0.616 0.000 0.016 0.368
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 5 0.4060 0.74462 0.000 0.000 0.000 0.360 0.640
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.5939 0.27371 0.000 0.344 0.000 0.536 0.120
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0162 0.86718 0.000 0.996 0.000 0.000 0.004
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.0404 0.46638 0.012 0.000 0.000 0.000 0.988
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.6796 -0.30579 0.000 0.352 0.000 0.360 0.288
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1836 0.82420 0.000 0.932 0.000 0.036 0.032
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.4354 0.66533 0.624 0.000 0.000 0.008 0.368
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0162 0.86688 0.000 0.996 0.000 0.000 0.004
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.1671 0.87691 0.000 0.000 0.924 0.076 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.65780 0.000 0.000 0.000 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.4138 0.32780 0.000 0.384 0.000 0.616 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 5 0.4288 0.74234 0.000 0.000 0.004 0.384 0.612
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.2966 0.38625 0.000 0.000 0.000 0.816 0.184
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 5 0.4227 0.24443 0.000 0.420 0.000 0.000 0.580
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.5784 0.51145 0.000 0.252 0.000 0.144 0.604
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4182 -0.32424 0.000 0.000 0.000 0.600 0.400
#> F5F7B591-062D-4FF0-AB68-73D678574318 5 0.5446 0.66657 0.000 0.100 0.000 0.272 0.628
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.4457 0.66190 0.620 0.012 0.000 0.000 0.368
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.1410 0.42495 0.000 0.000 0.000 0.060 0.940
#> DB7FD043-2A8F-480A-A208-912D99CE8848 5 0.4150 0.74208 0.000 0.000 0.000 0.388 0.612
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0703 0.85828 0.000 0.976 0.000 0.000 0.024
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0404 0.93989 0.000 0.000 0.988 0.012 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 5 0.4101 0.74723 0.000 0.000 0.000 0.372 0.628
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2891 0.71978 0.000 0.824 0.000 0.000 0.176
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4088 0.67256 0.632 0.000 0.000 0.000 0.368
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.3048 0.57357 0.000 0.176 0.000 0.820 0.004
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.5791 0.62290 0.000 0.140 0.000 0.260 0.600
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1908 0.80157 0.000 0.908 0.000 0.000 0.092
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.4291 0.64045 0.000 0.000 0.000 0.464 0.536
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0162 0.86652 0.000 0.996 0.000 0.004 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.94960 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0703 0.64498 0.000 0.000 0.000 0.976 0.024
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4263 0.71997 0.000 0.760 0.000 0.060 0.180
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 5 0.4088 0.74706 0.000 0.000 0.000 0.368 0.632
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 5 0.4088 0.74706 0.000 0.000 0.000 0.368 0.632
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 5 0.5439 0.68575 0.000 0.000 0.068 0.372 0.560
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1792 0.81033 0.000 0.916 0.000 0.000 0.084
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0290 0.86464 0.000 0.992 0.000 0.000 0.008
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4150 0.57176 0.000 0.612 0.000 0.000 0.388
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.4304 0.02836 0.000 0.000 0.484 0.516 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.1043 0.88148 0.960 0.000 0.000 0.040 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.4201 0.72167 0.000 0.000 0.000 0.408 0.592
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.4114 0.74661 0.000 0.000 0.000 0.376 0.624
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0404 0.65691 0.000 0.000 0.000 0.988 0.012
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.3752 0.50134 0.000 0.708 0.000 0.292 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0880 0.84956 0.000 0.968 0.000 0.032 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4278 0.12524 0.000 0.000 0.452 0.548 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.86858 0.000 1.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.4101 0.74710 0.000 0.000 0.000 0.372 0.628
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.91693 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4138 0.26812 0.000 0.000 0.384 0.616 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.2527 0.72568 0.000 0.000 0.000 0.168 0.832 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.3138 0.77627 0.108 0.000 0.000 0.060 0.832 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.81963 0.000 1.000 0.000 0.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.2790 0.69051 0.000 0.140 0.000 0.840 0.020 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5714 0.27601 0.000 0.464 0.000 0.000 0.168 0.368
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.5683 0.32106 0.000 0.484 0.000 0.000 0.168 0.348
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.92454 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0363 0.81636 0.000 0.988 0.000 0.012 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.92454 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.5525 0.45639 0.000 0.180 0.000 0.024 0.168 0.628
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#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.5062 0.44464 0.000 0.196 0.000 0.000 0.168 0.636
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.2730 0.69579 0.000 0.000 0.000 0.808 0.000 0.192
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3851 0.15439 0.000 0.000 0.000 0.540 0.000 0.460
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 4 0.3126 0.60288 0.000 0.248 0.000 0.752 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.2983 0.68793 0.000 0.136 0.000 0.832 0.032 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.2996 0.62393 0.000 0.000 0.000 0.772 0.000 0.228
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.1387 0.75342 0.000 0.068 0.000 0.932 0.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.2191 0.77568 0.120 0.000 0.000 0.000 0.876 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.3376 0.71488 0.000 0.004 0.000 0.180 0.792 0.024
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.2527 0.71144 0.000 0.000 0.000 0.832 0.000 0.168
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2513 0.73967 0.000 0.852 0.000 0.000 0.140 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.2730 0.73511 0.000 0.000 0.808 0.000 0.000 0.192
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0146 0.78696 0.000 0.004 0.000 0.996 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.3979 0.15746 0.000 0.456 0.000 0.540 0.004 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.92454 0.000 0.000 1.000 0.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.92454 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.2527 0.77035 0.168 0.000 0.000 0.000 0.832 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.5664 0.51703 0.000 0.032 0.000 0.180 0.168 0.620
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.1773 0.77388 0.000 0.036 0.000 0.932 0.016 0.016
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2442 0.72283 0.000 0.852 0.000 0.144 0.004 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 6 0.3843 0.11380 0.000 0.000 0.000 0.452 0.000 0.548
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3316 0.71596 0.000 0.804 0.000 0.004 0.164 0.028
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.92454 0.000 0.000 1.000 0.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 6 0.2135 0.72593 0.000 0.000 0.000 0.128 0.000 0.872
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.5462 0.29329 0.000 0.476 0.000 0.000 0.400 0.124
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.0725 0.78792 0.000 0.000 0.000 0.976 0.012 0.012
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0146 0.78696 0.000 0.004 0.000 0.996 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0603 0.81574 0.000 0.980 0.000 0.000 0.016 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3073 0.68129 0.000 0.000 0.008 0.788 0.000 0.204
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2997 0.72017 0.000 0.844 0.000 0.096 0.060 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3756 0.27462 0.000 0.600 0.000 0.400 0.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.2697 0.73437 0.000 0.188 0.000 0.000 0.812 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 6 0.2941 0.61086 0.000 0.000 0.220 0.000 0.000 0.780
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2302 0.83176 0.872 0.000 0.000 0.000 0.120 0.008
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3717 0.36024 0.000 0.000 0.000 0.616 0.000 0.384
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0713 0.78863 0.000 0.000 0.000 0.972 0.000 0.028
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.2706 0.68656 0.000 0.000 0.000 0.008 0.160 0.832
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.3754 0.69467 0.000 0.776 0.000 0.000 0.152 0.072
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4734 0.61524 0.000 0.680 0.000 0.000 0.168 0.152
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.3867 0.00744 0.000 0.000 0.488 0.000 0.000 0.512
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.81963 0.000 1.000 0.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0363 0.78945 0.000 0.000 0.000 0.988 0.000 0.012
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.98958 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.3230 0.59406 0.000 0.000 0.212 0.000 0.012 0.776
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 17581 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 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 0.510 0.700 0.865 0.3200 0.717 0.717
#> 3 3 0.778 0.887 0.925 0.5738 0.784 0.703
#> 4 4 0.739 0.753 0.895 0.3874 0.724 0.497
#> 5 5 0.622 0.559 0.771 0.0938 0.895 0.676
#> 6 6 0.622 0.397 0.712 0.0338 0.876 0.584
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.3584 0.82079 0.068 0.932
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3879 0.81687 0.076 0.924
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.84367 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3274 0.82528 0.060 0.940
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.9881 0.20746 0.436 0.564
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.84367 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4161 0.76914 0.084 0.916
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.7299 0.79624 0.796 0.204
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3114 0.82690 0.056 0.944
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.9358 0.69287 0.648 0.352
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.84367 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.3584 0.82079 0.068 0.932
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.84367 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0376 0.84319 0.004 0.996
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3879 0.81397 0.076 0.924
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0376 0.84319 0.004 0.996
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.9881 0.20746 0.436 0.564
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3584 0.82079 0.068 0.932
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3584 0.82079 0.068 0.932
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.3584 0.82079 0.068 0.932
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3274 0.82528 0.060 0.940
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.7139 0.53413 0.196 0.804
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.84367 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.4431 0.79697 0.092 0.908
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.84367 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3274 0.82528 0.060 0.940
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.84367 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.2948 0.82895 0.052 0.948
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.9977 0.01190 0.528 0.472
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.84367 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.9881 0.20746 0.436 0.564
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.84367 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.84367 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.84367 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.9881 0.55302 0.564 0.436
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0376 0.84319 0.004 0.996
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3584 0.82079 0.068 0.932
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.84367 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.84367 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.9944 0.01417 0.544 0.456
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3274 0.82528 0.060 0.940
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.84367 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.8661 0.50838 0.288 0.712
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.8713 0.74877 0.708 0.292
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.84367 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.84367 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.3274 0.82528 0.060 0.940
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.9881 0.20746 0.436 0.564
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.9881 0.20746 0.436 0.564
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.9393 0.68765 0.644 0.356
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4939 0.77665 0.108 0.892
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0376 0.84205 0.004 0.996
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.3584 0.82079 0.068 0.932
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.3274 0.82528 0.060 0.940
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3274 0.82528 0.060 0.940
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.9393 0.68767 0.644 0.356
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.9881 0.20746 0.436 0.564
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.3584 0.82079 0.068 0.932
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.9909 0.19370 0.444 0.556
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0938 0.83785 0.012 0.988
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2948 0.82870 0.052 0.948
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.3733 0.81899 0.072 0.928
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.9881 0.20746 0.436 0.564
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.3584 0.82079 0.068 0.932
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.5629 0.76845 0.132 0.868
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.3584 0.82079 0.068 0.932
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.84367 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.3584 0.82079 0.068 0.932
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0376 0.84319 0.004 0.996
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.84367 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.9881 0.20746 0.436 0.564
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0376 0.84319 0.004 0.996
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#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.8327 0.76745 0.736 0.264
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.84367 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.2778 0.83052 0.048 0.952
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.84367 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.3584 0.82079 0.068 0.932
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.1843 0.83736 0.028 0.972
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3274 0.82528 0.060 0.940
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.64582 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.3584 0.82079 0.068 0.932
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0376 0.84319 0.004 0.996
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0376 0.84319 0.004 0.996
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.84367 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0376 0.84319 0.004 0.996
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3584 0.82079 0.068 0.932
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.84367 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.9358 0.69270 0.648 0.352
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3274 0.82528 0.060 0.940
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.9866 0.21515 0.432 0.568
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3584 0.82079 0.068 0.932
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.9850 0.56847 0.572 0.428
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.9881 0.20746 0.436 0.564
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.9209 0.71046 0.664 0.336
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.7453 0.66819 0.212 0.788
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.84367 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3584 0.82079 0.068 0.932
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3431 0.82313 0.064 0.936
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.3584 0.82079 0.068 0.932
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.84367 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.9732 0.61191 0.596 0.404
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.3274 0.82528 0.060 0.940
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.84367 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.9896 0.20072 0.440 0.560
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2778 0.83050 0.048 0.952
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3584 0.82079 0.068 0.932
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.84367 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.3584 0.82079 0.068 0.932
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3584 0.82079 0.068 0.932
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.84367 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.84367 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.9248 0.70622 0.660 0.340
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.9881 0.20746 0.436 0.564
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.3584 0.82079 0.068 0.932
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3584 0.82079 0.068 0.932
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0376 0.84205 0.004 0.996
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.84367 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.9881 0.20746 0.436 0.564
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.84367 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.8813 0.42442 0.300 0.700
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9754 -0.24843 0.408 0.592
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.84367 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.3584 0.82079 0.068 0.932
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.9881 0.20746 0.436 0.564
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.9909 -0.31229 0.444 0.556
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.3482 0.9115 0.000 0.872 0.128
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3686 0.9097 0.000 0.860 0.140
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0237 0.9158 0.004 0.996 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2261 0.9112 0.000 0.932 0.068
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9602 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0237 0.9158 0.004 0.996 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0237 0.9158 0.004 0.996 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.2356 0.8855 0.072 0.000 0.928
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2496 0.9109 0.004 0.928 0.068
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.8688 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0829 0.9181 0.004 0.984 0.012
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.3686 0.9097 0.000 0.860 0.140
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0237 0.9158 0.004 0.996 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.2356 0.9218 0.000 0.928 0.072
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3752 0.9076 0.000 0.856 0.144
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2356 0.9218 0.000 0.928 0.072
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9602 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3686 0.9097 0.000 0.860 0.140
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3619 0.9107 0.000 0.864 0.136
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.3686 0.9097 0.000 0.860 0.140
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3412 0.9129 0.000 0.876 0.124
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6126 0.4210 0.000 0.600 0.400
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0237 0.9158 0.004 0.996 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.3752 0.9076 0.000 0.856 0.144
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.3482 0.8967 0.000 0.872 0.128
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3686 0.9097 0.000 0.860 0.140
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0237 0.9158 0.004 0.996 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.3686 0.9097 0.000 0.860 0.140
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9602 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.2590 0.9221 0.004 0.924 0.072
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9602 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.2066 0.9232 0.000 0.940 0.060
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0237 0.9158 0.004 0.996 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0829 0.9181 0.004 0.984 0.012
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.1860 0.8255 0.000 0.052 0.948
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2066 0.9227 0.000 0.940 0.060
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3752 0.9076 0.000 0.856 0.144
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0237 0.9158 0.004 0.996 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1129 0.9199 0.004 0.976 0.020
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0237 0.9565 0.996 0.004 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3686 0.9097 0.000 0.860 0.140
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0829 0.9181 0.004 0.984 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5216 0.5036 0.740 0.260 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.8688 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0237 0.9158 0.004 0.996 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0237 0.9158 0.004 0.996 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.3686 0.9097 0.000 0.860 0.140
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9602 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9602 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.8688 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.5216 0.7714 0.000 0.740 0.260
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.2356 0.9218 0.000 0.928 0.072
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.2711 0.9138 0.000 0.912 0.088
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.3686 0.9097 0.000 0.860 0.140
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3686 0.9097 0.000 0.860 0.140
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.8688 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9602 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.3686 0.9097 0.000 0.860 0.140
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9602 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.1182 0.9168 0.012 0.976 0.012
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2400 0.9121 0.004 0.932 0.064
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.3686 0.9097 0.000 0.860 0.140
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9602 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.3686 0.9097 0.000 0.860 0.140
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.5276 0.8796 0.052 0.820 0.128
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.3686 0.9097 0.000 0.860 0.140
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0475 0.9170 0.004 0.992 0.004
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.3686 0.9097 0.000 0.860 0.140
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.2448 0.9217 0.000 0.924 0.076
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0237 0.9158 0.004 0.996 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9602 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.2625 0.9216 0.000 0.916 0.084
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9602 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0237 0.9158 0.004 0.996 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5621 0.5008 0.308 0.692 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0829 0.9181 0.004 0.984 0.012
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0237 0.9158 0.004 0.996 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.1129 0.9202 0.004 0.976 0.020
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0424 0.9188 0.000 0.992 0.008
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.3038 0.9192 0.000 0.896 0.104
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9602 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.2356 0.9218 0.000 0.928 0.072
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.2356 0.8855 0.072 0.000 0.928
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.3686 0.9097 0.000 0.860 0.140
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.3551 0.7250 0.000 0.132 0.868
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0237 0.9158 0.004 0.996 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.2261 0.9223 0.000 0.932 0.068
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.2356 0.9218 0.000 0.928 0.072
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0237 0.9158 0.004 0.996 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.8058 0.3809 0.376 0.072 0.552
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0237 0.9158 0.004 0.996 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0475 0.9170 0.004 0.992 0.004
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9602 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0237 0.9158 0.004 0.996 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9602 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0237 0.9158 0.004 0.996 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.2356 0.8855 0.072 0.000 0.928
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.2301 0.9231 0.004 0.936 0.060
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.2356 0.8855 0.072 0.000 0.928
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9602 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0237 0.9158 0.004 0.996 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.8017 0.6091 0.140 0.208 0.652
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.1860 0.8824 0.052 0.000 0.948
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.2356 0.9218 0.000 0.928 0.072
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0237 0.9566 0.996 0.000 0.004
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0237 0.9158 0.004 0.996 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.3879 0.9031 0.000 0.848 0.152
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9602 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.2261 0.9112 0.000 0.932 0.068
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.3686 0.9097 0.000 0.860 0.140
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.2590 0.9221 0.004 0.924 0.072
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.3686 0.9097 0.000 0.860 0.140
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.3412 0.7349 0.000 0.124 0.876
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.3686 0.9097 0.000 0.860 0.140
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0983 0.9191 0.004 0.980 0.016
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9602 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9602 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.2356 0.9218 0.000 0.928 0.072
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.2301 0.9226 0.004 0.936 0.060
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.6576 0.7471 0.192 0.740 0.068
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9602 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.2356 0.8855 0.072 0.000 0.928
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#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3619 0.9107 0.000 0.864 0.136
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3340 0.9130 0.000 0.880 0.120
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.3686 0.9097 0.000 0.860 0.140
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0237 0.9158 0.004 0.996 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.8688 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.3686 0.9097 0.000 0.860 0.140
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0237 0.9158 0.004 0.996 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9602 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3116 0.9192 0.000 0.892 0.108
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3686 0.9097 0.000 0.860 0.140
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0237 0.9158 0.004 0.996 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.3752 0.9076 0.000 0.856 0.144
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2537 0.9128 0.000 0.920 0.080
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2200 0.9228 0.004 0.940 0.056
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.2590 0.9221 0.004 0.924 0.072
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.1753 0.8299 0.000 0.048 0.952
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9602 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.3686 0.9097 0.000 0.860 0.140
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3686 0.9097 0.000 0.860 0.140
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2356 0.9218 0.000 0.928 0.072
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0237 0.9158 0.004 0.996 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9602 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0237 0.9158 0.004 0.996 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0661 0.9525 0.988 0.008 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6192 0.2245 0.000 0.420 0.580
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0237 0.9158 0.004 0.996 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.3686 0.9097 0.000 0.860 0.140
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9602 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.8419 0.1756 0.088 0.408 0.504
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.2149 0.77594 0.000 0.088 0.000 0.912
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.1022 0.80855 0.000 0.032 0.000 0.968
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.4933 0.26145 0.000 0.432 0.000 0.568
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4134 0.56053 0.000 0.740 0.000 0.260
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1474 0.84163 0.000 0.948 0.000 0.052
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0188 0.81371 0.000 0.004 0.000 0.996
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4543 0.54380 0.000 0.324 0.000 0.676
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4948 0.32805 0.000 0.440 0.000 0.560
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0469 0.81304 0.000 0.012 0.000 0.988
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.2011 0.80557 0.000 0.080 0.000 0.920
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.7666 -0.05096 0.000 0.212 0.396 0.392
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0817 0.85808 0.000 0.976 0.000 0.024
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4955 0.32025 0.000 0.444 0.000 0.556
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0592 0.81493 0.000 0.016 0.000 0.984
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1474 0.81411 0.000 0.052 0.000 0.948
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.5000 -0.15893 0.000 0.500 0.000 0.500
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4967 -0.00494 0.000 0.548 0.000 0.452
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1716 0.83489 0.000 0.936 0.000 0.064
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1302 0.79870 0.000 0.000 0.044 0.956
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.5000 0.09920 0.000 0.500 0.000 0.500
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.2281 0.80873 0.000 0.904 0.000 0.096
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0817 0.93766 0.976 0.000 0.000 0.024
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.1474 0.81405 0.000 0.052 0.000 0.948
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.2011 0.83905 0.000 0.920 0.000 0.080
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.5606 0.09717 0.480 0.020 0.000 0.500
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1302 0.84778 0.000 0.956 0.000 0.044
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2216 0.85607 0.000 0.000 0.908 0.092
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1940 0.78608 0.000 0.076 0.000 0.924
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4948 0.32805 0.000 0.440 0.000 0.560
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.2921 0.71976 0.000 0.140 0.000 0.860
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.2589 0.79168 0.000 0.884 0.000 0.116
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4916 0.26591 0.000 0.576 0.000 0.424
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.1557 0.81312 0.000 0.056 0.000 0.944
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.2222 0.79041 0.016 0.060 0.000 0.924
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.1637 0.81097 0.000 0.060 0.000 0.940
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0707 0.86023 0.000 0.980 0.000 0.020
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.4431 0.57359 0.000 0.304 0.000 0.696
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3649 0.69830 0.000 0.204 0.000 0.796
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.1302 0.84413 0.044 0.956 0.000 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.2408 0.81852 0.000 0.896 0.000 0.104
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.2530 0.79351 0.000 0.888 0.000 0.112
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4713 0.28310 0.000 0.640 0.000 0.360
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4431 0.58269 0.000 0.304 0.000 0.696
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4955 0.31870 0.000 0.444 0.000 0.556
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.3649 0.66408 0.000 0.796 0.000 0.204
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.4972 0.22871 0.000 0.456 0.000 0.544
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.4967 0.29911 0.000 0.452 0.000 0.548
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 4 0.6426 0.06839 0.392 0.000 0.072 0.536
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0336 0.86430 0.000 0.992 0.000 0.008
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.3172 0.74012 0.000 0.840 0.000 0.160
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.3793 0.81660 0.112 0.044 0.844 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4817 0.43488 0.000 0.388 0.000 0.612
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.4972 0.19649 0.000 0.544 0.000 0.456
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.0707 0.81163 0.000 0.020 0.000 0.980
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4967 0.29969 0.000 0.452 0.000 0.548
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.1398 0.80126 0.000 0.004 0.040 0.956
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.1940 0.82478 0.000 0.924 0.000 0.076
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4941 0.33721 0.000 0.436 0.000 0.564
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.4431 0.45866 0.000 0.696 0.000 0.304
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 4 0.7662 -0.06755 0.180 0.400 0.004 0.416
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.0188 0.81371 0.000 0.004 0.000 0.996
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.4817 0.43488 0.000 0.388 0.000 0.612
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.1302 0.84778 0.000 0.956 0.000 0.044
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 4 0.4477 0.44241 0.000 0.000 0.312 0.688
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.0592 0.81236 0.000 0.016 0.000 0.984
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.4981 0.27165 0.000 0.464 0.000 0.536
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.4981 0.27593 0.000 0.464 0.000 0.536
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.3726 0.66819 0.000 0.788 0.000 0.212
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#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.0921 0.81018 0.000 0.028 0.000 0.972
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.4459 0.62384 0.188 0.032 0.000 0.780
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.1557 0.79879 0.000 0.056 0.000 0.944
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.2530 0.75761 0.000 0.112 0.000 0.888
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.94991 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1302 0.81506 0.000 0.044 0.000 0.956
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.2647 0.76648 0.000 0.120 0.000 0.880
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0188 0.86526 0.000 0.996 0.000 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.5000 -0.10828 0.000 0.500 0.000 0.500
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3311 0.72146 0.000 0.828 0.000 0.172
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4040 0.59942 0.000 0.752 0.000 0.248
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4955 0.31870 0.000 0.444 0.000 0.556
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2329 0.87829 0.916 0.012 0.000 0.072
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4163 0.79039 0.000 0.076 0.828 0.096
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.86610 0.000 1.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0000 0.81347 0.000 0.000 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.96363 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.8247 0.22415 0.360 0.044 0.452 0.144
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.5255 0.60999 0.000 0.072 0.000 0.304 0.624
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.4402 0.62897 0.000 0.012 0.000 0.352 0.636
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3861 0.56394 0.000 0.712 0.000 0.004 0.284
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.5874 0.49322 0.000 0.208 0.000 0.188 0.604
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5083 0.61149 0.000 0.700 0.000 0.140 0.160
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2424 0.70662 0.000 0.868 0.000 0.000 0.132
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4249 0.35758 0.000 0.568 0.000 0.000 0.432
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.6166 0.45906 0.000 0.556 0.000 0.244 0.200
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.4171 0.59480 0.000 0.000 0.000 0.396 0.604
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3586 0.57423 0.000 0.736 0.000 0.000 0.264
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.3534 0.45070 0.000 0.000 0.000 0.744 0.256
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3684 0.37361 0.000 0.000 0.000 0.720 0.280
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.5663 0.18454 0.000 0.384 0.000 0.532 0.084
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3796 0.36657 0.000 0.000 0.000 0.700 0.300
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3835 0.43516 0.000 0.012 0.000 0.744 0.244
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.2852 0.45455 0.000 0.000 0.000 0.828 0.172
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3115 0.46570 0.000 0.036 0.000 0.852 0.112
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5628 0.22946 0.000 0.000 0.244 0.624 0.132
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0162 0.73596 0.000 0.996 0.000 0.000 0.004
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3895 0.35022 0.000 0.000 0.000 0.680 0.320
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.6148 0.23008 0.000 0.268 0.000 0.552 0.180
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 5 0.4150 0.03056 0.000 0.000 0.000 0.388 0.612
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.73594 0.000 1.000 0.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0000 0.49826 0.000 0.000 0.000 1.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.6261 0.21957 0.000 0.264 0.000 0.536 0.200
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4958 0.15925 0.000 0.400 0.000 0.568 0.032
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2879 0.71332 0.000 0.868 0.000 0.032 0.100
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1894 0.72018 0.000 0.920 0.000 0.072 0.008
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.4108 0.35739 0.000 0.000 0.008 0.684 0.308
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.6452 -0.05480 0.000 0.328 0.000 0.476 0.196
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.3816 0.36101 0.000 0.000 0.000 0.696 0.304
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.73594 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6349 0.40145 0.000 0.520 0.000 0.268 0.212
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4402 0.36879 0.000 0.012 0.000 0.636 0.352
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1725 0.72604 0.000 0.936 0.000 0.044 0.020
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5396 0.01752 0.492 0.012 0.000 0.464 0.032
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3932 0.55642 0.000 0.672 0.000 0.000 0.328
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.3586 0.57423 0.000 0.736 0.000 0.000 0.264
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.4009 0.43481 0.000 0.004 0.000 0.684 0.312
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.5252 0.50076 0.000 0.000 0.632 0.292 0.076
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.5068 0.62000 0.000 0.060 0.000 0.300 0.640
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.2516 0.44384 0.000 0.000 0.000 0.860 0.140
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.5678 0.56390 0.000 0.128 0.000 0.260 0.612
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4902 0.32090 0.000 0.048 0.000 0.648 0.304
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3452 0.39655 0.000 0.000 0.000 0.756 0.244
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.4182 0.61023 0.000 0.000 0.000 0.400 0.600
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5002 0.52747 0.000 0.636 0.000 0.312 0.052
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4321 0.37943 0.000 0.600 0.000 0.004 0.396
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.4101 0.61988 0.000 0.000 0.000 0.372 0.628
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.1106 0.49931 0.000 0.012 0.000 0.964 0.024
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7027 -0.33911 0.008 0.380 0.000 0.312 0.300
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.4821 -0.40414 0.000 0.020 0.000 0.516 0.464
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.5378 0.53064 0.000 0.548 0.000 0.060 0.392
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2690 0.46148 0.000 0.000 0.000 0.844 0.156
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.0290 0.49863 0.000 0.000 0.000 0.992 0.008
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0609 0.73724 0.000 0.980 0.000 0.020 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.0000 0.49826 0.000 0.000 0.000 1.000 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0162 0.73647 0.000 0.996 0.000 0.000 0.004
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.2471 0.70478 0.000 0.864 0.000 0.000 0.136
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5441 0.54310 0.000 0.624 0.000 0.096 0.280
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.73594 0.000 1.000 0.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6519 0.18894 0.000 0.408 0.000 0.400 0.192
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 5 0.6287 -0.13057 0.000 0.296 0.000 0.184 0.520
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.5724 0.33366 0.000 0.112 0.000 0.584 0.304
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.6102 0.24562 0.000 0.264 0.000 0.560 0.176
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.2690 0.43817 0.000 0.000 0.000 0.844 0.156
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.4941 0.29386 0.000 0.000 0.044 0.628 0.328
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.6717 0.29260 0.000 0.408 0.000 0.336 0.256
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.5840 0.12064 0.000 0.416 0.000 0.488 0.096
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.4940 0.17688 0.000 0.392 0.000 0.576 0.032
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0162 0.73596 0.000 0.996 0.000 0.000 0.004
#> F1099B84-FE2A-419C-9948-D0754C1AF902 5 0.5730 0.28041 0.348 0.000 0.040 0.032 0.580
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0162 0.73640 0.000 0.996 0.000 0.000 0.004
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.5198 0.60700 0.000 0.688 0.000 0.164 0.148
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3661 0.56732 0.000 0.724 0.000 0.000 0.276
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0880 0.73564 0.000 0.968 0.000 0.000 0.032
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.1965 0.84195 0.000 0.000 0.904 0.096 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.6001 0.40882 0.000 0.580 0.000 0.244 0.176
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.2966 0.83992 0.000 0.000 0.816 0.000 0.184
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.3203 0.69007 0.000 0.820 0.000 0.012 0.168
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.4262 0.38428 0.000 0.000 0.560 0.440 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.2777 0.43331 0.000 0.120 0.000 0.864 0.016
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.3561 0.59703 0.000 0.740 0.000 0.000 0.260
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.0510 0.49847 0.000 0.000 0.000 0.984 0.016
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.5557 0.17178 0.000 0.472 0.000 0.068 0.460
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.4101 0.61779 0.000 0.000 0.000 0.372 0.628
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4849 0.38042 0.000 0.140 0.000 0.724 0.136
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.3857 0.35316 0.000 0.000 0.000 0.688 0.312
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.3246 0.44412 0.000 0.000 0.008 0.808 0.184
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 5 0.4242 0.59035 0.000 0.000 0.000 0.428 0.572
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.4058 0.61541 0.000 0.740 0.000 0.236 0.024
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4325 0.40511 0.000 0.064 0.000 0.756 0.180
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#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1408 0.73466 0.000 0.948 0.000 0.008 0.044
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.1851 0.73104 0.000 0.912 0.000 0.000 0.088
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0880 0.73749 0.000 0.968 0.000 0.000 0.032
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.3949 0.33615 0.000 0.000 0.000 0.668 0.332
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2966 0.83992 0.000 0.000 0.816 0.000 0.184
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.2777 0.71569 0.000 0.864 0.000 0.016 0.120
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3550 0.68722 0.000 0.796 0.000 0.020 0.184
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.3586 0.57423 0.000 0.736 0.000 0.000 0.264
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.3661 0.57078 0.000 0.724 0.000 0.000 0.276
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.4210 -0.03677 0.000 0.000 0.000 0.588 0.412
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.6736 -0.03467 0.000 0.412 0.000 0.312 0.276
#> 29635F4D-3149-49BC-B960-FF863D10F747 5 0.6456 0.08028 0.000 0.184 0.000 0.368 0.448
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2966 0.83992 0.000 0.000 0.816 0.000 0.184
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.5731 -0.17034 0.084 0.436 0.000 0.000 0.480
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.1597 0.72453 0.000 0.940 0.000 0.048 0.012
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4964 0.62558 0.000 0.700 0.000 0.096 0.204
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3684 0.65122 0.000 0.000 0.720 0.280 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.73594 0.000 1.000 0.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4161 0.38039 0.000 0.000 0.000 0.608 0.392
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0324 0.73722 0.000 0.992 0.000 0.004 0.004
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.3684 0.37361 0.000 0.000 0.000 0.720 0.280
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0771 0.49796 0.000 0.004 0.000 0.976 0.020
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 5 0.5064 0.58395 0.000 0.088 0.000 0.232 0.680
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.4392 0.62195 0.000 0.008 0.000 0.380 0.612
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.2964 0.43597 0.000 0.120 0.000 0.856 0.024
#> F5F7B591-062D-4FF0-AB68-73D678574318 5 0.4756 0.09630 0.000 0.288 0.000 0.044 0.668
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.1444 0.73428 0.000 0.948 0.000 0.012 0.040
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.5576 0.16373 0.000 0.388 0.000 0.536 0.076
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.4273 -0.41204 0.000 0.000 0.000 0.552 0.448
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0404 0.73616 0.000 0.988 0.000 0.000 0.012
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4219 0.42614 0.000 0.000 0.584 0.416 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.4306 -0.46362 0.000 0.000 0.000 0.508 0.492
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 5 0.5329 0.58559 0.000 0.052 0.000 0.432 0.516
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.6398 0.46769 0.188 0.032 0.000 0.172 0.608
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.2971 0.69840 0.000 0.836 0.000 0.008 0.156
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.5099 0.62783 0.000 0.052 0.000 0.336 0.612
#> 981123DE-D55E-41D1-8850-1A41376F1DED 5 0.4960 0.54902 0.000 0.080 0.000 0.232 0.688
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.3837 0.36219 0.000 0.000 0.000 0.692 0.308
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0510 0.73724 0.000 0.984 0.000 0.000 0.016
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.89665 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4114 0.39699 0.000 0.000 0.000 0.624 0.376
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0162 0.73596 0.000 0.996 0.000 0.000 0.004
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.5759 -0.25590 0.000 0.092 0.000 0.520 0.388
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 5 0.4201 0.58216 0.000 0.000 0.000 0.408 0.592
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0671 0.73742 0.000 0.980 0.000 0.004 0.016
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3876 0.35510 0.000 0.000 0.000 0.684 0.316
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.5389 0.19841 0.000 0.508 0.000 0.056 0.436
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.6353 0.23752 0.000 0.480 0.000 0.348 0.172
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6482 0.16001 0.000 0.440 0.000 0.372 0.188
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2891 0.44969 0.000 0.000 0.000 0.824 0.176
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3913 0.34471 0.000 0.000 0.000 0.676 0.324
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.3895 0.35022 0.000 0.000 0.000 0.680 0.320
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4569 0.40025 0.000 0.104 0.000 0.748 0.148
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0404 0.73737 0.000 0.988 0.000 0.000 0.012
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.73594 0.000 1.000 0.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.6651 0.02270 0.336 0.000 0.000 0.428 0.236
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4808 0.08103 0.000 0.000 0.348 0.620 0.032
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0162 0.73647 0.000 0.996 0.000 0.000 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4030 0.31954 0.000 0.000 0.000 0.648 0.352
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.94464 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.5375 0.30158 0.000 0.000 0.200 0.664 0.136
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.4617 -5.81e-03 0.000 0.048 0.000 0.624 0.324 0.004
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.4092 3.95e-02 0.000 0.020 0.000 0.636 0.344 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.5583 4.42e-02 0.000 0.548 0.000 0.208 0.244 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.5604 -2.14e-01 0.000 0.172 0.000 0.556 0.268 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.4855 3.33e-01 0.000 0.640 0.000 0.000 0.256 0.104
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2597 4.75e-01 0.000 0.824 0.000 0.000 0.176 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 8.99e-01 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.5731 -1.05e-02 0.000 0.512 0.000 0.212 0.276 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 8.99e-01 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.5855 2.02e-01 0.000 0.520 0.000 0.012 0.308 0.160
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1204 4.91e-01 0.000 0.000 0.000 0.944 0.056 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.5279 1.18e-01 0.000 0.604 0.000 0.200 0.196 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.5706 2.43e-01 0.000 0.000 0.000 0.336 0.176 0.488
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3175 4.74e-01 0.000 0.000 0.000 0.744 0.000 0.256
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.7062 -4.59e-02 0.000 0.384 0.000 0.352 0.108 0.156
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3163 4.87e-01 0.000 0.000 0.000 0.764 0.004 0.232
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5301 5.35e-02 0.000 0.004 0.000 0.492 0.088 0.416
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.3828 1.75e-01 0.000 0.000 0.000 0.560 0.000 0.440
#> A4967738-7FC2-4270-A149-56E459EDB875 6 0.6069 1.47e-01 0.000 0.028 0.000 0.344 0.136 0.492
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.4584 -6.36e-02 0.000 0.000 0.452 0.000 0.036 0.512
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0937 5.38e-01 0.000 0.960 0.000 0.000 0.040 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3103 4.97e-01 0.000 0.000 0.000 0.784 0.008 0.208
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.7491 9.68e-02 0.000 0.212 0.000 0.180 0.228 0.380
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.5292 1.59e-01 0.000 0.000 0.000 0.520 0.372 0.108
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0547 5.37e-01 0.000 0.980 0.000 0.000 0.020 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 6 0.4361 9.87e-02 0.000 0.000 0.000 0.424 0.024 0.552
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.7472 6.06e-02 0.000 0.212 0.000 0.160 0.256 0.372
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.7154 -1.80e-01 0.000 0.336 0.000 0.284 0.076 0.304
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3348 4.70e-01 0.000 0.768 0.000 0.000 0.216 0.016
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.2020 5.35e-01 0.000 0.920 0.000 0.020 0.040 0.020
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.3052 4.94e-01 0.000 0.000 0.000 0.780 0.004 0.216
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.7515 -3.04e-01 0.000 0.228 0.000 0.316 0.308 0.148
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.3217 4.92e-01 0.000 0.000 0.000 0.768 0.008 0.224
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0458 5.37e-01 0.000 0.984 0.000 0.000 0.016 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6280 1.63e-01 0.000 0.492 0.000 0.036 0.312 0.160
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0146 9.25e-01 0.996 0.000 0.000 0.004 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.6506 -5.01e-02 0.000 0.020 0.000 0.380 0.272 0.328
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1341 5.38e-01 0.000 0.948 0.000 0.024 0.028 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.7391 -1.46e-01 0.396 0.020 0.000 0.284 0.068 0.232
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 8.99e-01 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.5969 -9.53e-02 0.000 0.440 0.000 0.244 0.316 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.5279 1.18e-01 0.000 0.604 0.000 0.200 0.196 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 6 0.6081 1.74e-01 0.000 0.012 0.000 0.384 0.176 0.428
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 6 0.6129 1.13e-01 0.000 0.000 0.328 0.324 0.000 0.348
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.4236 8.49e-02 0.000 0.036 0.000 0.656 0.308 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.5663 3.11e-01 0.000 0.012 0.000 0.228 0.180 0.580
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4915 2.03e-02 0.000 0.140 0.000 0.652 0.208 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.3861 4.75e-01 0.000 0.052 0.000 0.772 0.008 0.168
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3936 4.23e-01 0.000 0.000 0.000 0.688 0.024 0.288
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 8.99e-01 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.3593 3.23e-01 0.000 0.000 0.000 0.748 0.228 0.024
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6380 1.88e-01 0.000 0.528 0.000 0.052 0.184 0.236
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.5442 8.67e-02 0.000 0.576 0.000 0.204 0.220 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.3774 1.28e-01 0.000 0.000 0.000 0.664 0.328 0.008
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 6 0.4723 1.47e-01 0.000 0.020 0.000 0.396 0.020 0.564
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.5793 -2.68e-02 0.008 0.308 0.000 0.520 0.164 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.6124 -2.51e-01 0.000 0.020 0.000 0.436 0.388 0.156
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.6426 -8.32e-02 0.000 0.396 0.000 0.192 0.384 0.028
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.3851 1.20e-01 0.000 0.000 0.000 0.540 0.000 0.460
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 6 0.3930 1.22e-01 0.000 0.000 0.000 0.420 0.004 0.576
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1461 5.38e-01 0.000 0.940 0.000 0.000 0.044 0.016
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 6 0.3797 1.19e-01 0.000 0.000 0.000 0.420 0.000 0.580
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#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0458 5.40e-01 0.000 0.984 0.000 0.000 0.016 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.3390 2.14e-01 0.016 0.000 0.000 0.028 0.140 0.816
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.3782 3.25e-01 0.000 0.000 0.588 0.000 0.000 0.412
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0547 5.37e-01 0.000 0.980 0.000 0.000 0.020 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.3529 4.99e-01 0.000 0.000 0.000 0.764 0.028 0.208
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 9.29e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.6589 3.39e-01 0.012 0.000 0.152 0.100 0.160 0.576
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 17581 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 0.855 0.912 0.949 0.4125 0.587 0.587
#> 3 3 0.972 0.936 0.970 0.1345 0.935 0.892
#> 4 4 0.807 0.844 0.934 0.4874 0.754 0.550
#> 5 5 0.652 0.716 0.856 0.0565 0.945 0.827
#> 6 6 0.632 0.587 0.749 0.0585 0.911 0.689
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4431 0.9224 0.092 0.908
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.4939 0.9109 0.108 0.892
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4431 0.9224 0.092 0.908
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.1184 0.9556 0.016 0.984
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9226 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1184 0.9556 0.016 0.984
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2778 0.9454 0.048 0.952
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.6048 0.8833 0.852 0.148
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4431 0.9224 0.092 0.908
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.6048 0.8833 0.852 0.148
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9561 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9561 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2603 0.9471 0.044 0.956
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9561 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0000 0.9561 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9561 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9226 1.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9561 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9561 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.9561 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9561 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0000 0.9561 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4431 0.9224 0.092 0.908
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0000 0.9561 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.9561 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9561 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1184 0.9556 0.016 0.984
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9561 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9226 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9561 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9226 1.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9561 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1184 0.9556 0.016 0.984
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4022 0.9292 0.080 0.920
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.5059 0.8470 0.112 0.888
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4431 0.9224 0.092 0.908
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9561 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.2603 0.9471 0.044 0.956
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1184 0.9556 0.016 0.984
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9226 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9561 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4431 0.9224 0.092 0.908
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.9993 0.0276 0.516 0.484
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.6048 0.8833 0.852 0.148
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4431 0.9224 0.092 0.908
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2778 0.9454 0.048 0.952
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9561 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9226 1.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9226 1.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.6048 0.8833 0.852 0.148
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.1184 0.9556 0.016 0.984
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.9561 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9561 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9561 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9561 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.6048 0.8833 0.852 0.148
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9226 1.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.0000 0.9561 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9226 1.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4431 0.9224 0.092 0.908
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4431 0.9224 0.092 0.908
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.0000 0.9561 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9226 1.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9561 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.5294 0.9004 0.120 0.880
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2948 0.9439 0.052 0.948
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1414 0.9548 0.020 0.980
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.9561 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0000 0.9561 0.000 1.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1184 0.9556 0.016 0.984
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9226 1.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0000 0.9561 0.000 1.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9226 1.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1184 0.9556 0.016 0.984
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.3879 0.9317 0.076 0.924
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.2236 0.9504 0.036 0.964
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.4431 0.9224 0.092 0.908
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9561 0.000 1.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0376 0.9561 0.004 0.996
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9561 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9226 1.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.9561 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.6048 0.8833 0.852 0.148
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9561 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.0000 0.9561 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9561 0.000 1.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4431 0.9224 0.092 0.908
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9561 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4431 0.9224 0.092 0.908
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.9226 1.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1184 0.9556 0.016 0.984
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1184 0.9556 0.016 0.984
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9226 1.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3114 0.9418 0.056 0.944
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9226 1.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4431 0.9224 0.092 0.908
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.6048 0.8833 0.852 0.148
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.9561 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.6048 0.8833 0.852 0.148
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9226 1.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.1184 0.9556 0.016 0.984
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.9754 0.1675 0.408 0.592
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.6048 0.8833 0.852 0.148
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9561 0.000 1.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9226 1.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1184 0.9556 0.016 0.984
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.0000 0.9561 0.000 1.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9226 1.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.2603 0.9471 0.044 0.956
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.6048 0.8658 0.148 0.852
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9561 0.000 1.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.3431 0.9375 0.064 0.936
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.0000 0.9561 0.000 1.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9561 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.9561 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9226 1.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9226 1.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9561 0.000 1.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1843 0.9529 0.028 0.972
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.9226 1.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9226 1.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.6048 0.8833 0.852 0.148
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9226 1.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.6048 0.8833 0.852 0.148
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1184 0.9556 0.016 0.984
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9561 0.000 1.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0000 0.9561 0.000 1.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.4431 0.9224 0.092 0.908
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.1184 0.9556 0.016 0.984
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.6048 0.8833 0.852 0.148
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#> 8FB28200-513F-4697-8B49-65CC424FDF5E 2 0.4431 0.9224 0.092 0.908
#> DA35F73E-1856-41B6-994E-76919556C971 2 0.2043 0.9516 0.032 0.968
#> EA2E8ECB-841C-4224-9468-ED2D649C31A3 1 0.0000 0.9226 1.000 0.000
#> F0912DE2-2B34-4E4B-89C8-BDC2D051F144 1 0.6048 0.8833 0.852 0.148
#> D671E954-4CAC-4449-8EB1-163E478FE052 2 0.4431 0.9224 0.092 0.908
#> 33F20F2D-51A4-4038-B1C2-D5BE14BAB1CB 1 0.9954 0.1711 0.540 0.460
#> 9AF9E9CF-2D77-455E-8D47-10537BADD98F 2 0.0000 0.9561 0.000 1.000
#> 9E781A09-CBB2-496A-B3F6-B1B8B514836F 2 0.2236 0.9504 0.036 0.964
#> 4D112BD8-1A35-43CB-896A-16F48147811B 1 0.0000 0.9226 1.000 0.000
#> 0034ECFD-CA94-4615-94D2-E950A2B240ED 2 0.0000 0.9561 0.000 1.000
#> FBD43A48-C880-45FF-BB6A-08F922DE93B5 2 0.0000 0.9561 0.000 1.000
#> E5C1A89F-C3D9-4DC8-A35F-D2834B155843 2 0.0000 0.9561 0.000 1.000
#> 6A73B561-CF9C-49DD-8B8B-09036538CAA4 1 0.6048 0.8833 0.852 0.148
#> 795D478D-E1FE-49EB-92AD-8B1B145F944B 2 0.0938 0.9559 0.012 0.988
#> 6203B63E-6D3F-4399-B524-9573A9BD1E11 2 0.4431 0.9224 0.092 0.908
#> BDD03456-777B-4E94-8240-CD6B1D4EAC51 2 0.3879 0.9312 0.076 0.924
#> DE32121C-B7F5-4A94-9977-8F4B2D3BE976 2 0.0000 0.9561 0.000 1.000
#> 27C0EEBE-589F-41D9-8BF7-C7DA0ED87A3B 2 0.4431 0.9224 0.092 0.908
#> EE24DCB8-2927-42D4-AD8C-588EA01A64C7 2 0.0000 0.9561 0.000 1.000
#> A86D241D-FE25-40B7-A61C-B919D30FA545 2 0.0000 0.9561 0.000 1.000
#> 50A7A07E-B452-466D-97BF-978C4F9C47DA 2 0.0000 0.9561 0.000 1.000
#> 0E6AE036-64ED-4489-AE40-55F77089A890 2 0.0000 0.9561 0.000 1.000
#> BC9A5294-255F-47A4-8879-11C441093A3D 2 0.0000 0.9561 0.000 1.000
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.0000 0.9561 0.000 1.000
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 2 0.4431 0.9224 0.092 0.908
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 2 0.4431 0.9224 0.092 0.908
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 2 0.1843 0.9531 0.028 0.972
#> 3508F4B0-1ADA-4937-B924-424AC2596341 2 0.0000 0.9561 0.000 1.000
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 2 0.0000 0.9561 0.000 1.000
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 2 0.9661 0.4119 0.392 0.608
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.0000 0.9226 1.000 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.4022 0.9295 0.080 0.920
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.0000 0.9226 1.000 0.000
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 1 0.6048 0.8833 0.852 0.148
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.6048 0.8833 0.852 0.148
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.9226 1.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0000 0.9561 0.000 1.000
#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.6048 0.8833 0.852 0.148
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.0000 0.9561 0.000 1.000
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.0000 0.9561 0.000 1.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0000 0.9561 0.000 1.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.9561 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9561 0.000 1.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0000 0.9561 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0000 0.9561 0.000 1.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9226 1.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9226 1.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.4431 0.9224 0.092 0.908
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.4431 0.9224 0.092 0.908
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.0000 0.9561 0.000 1.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.9988 0.2645 0.520 0.480
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9226 1.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.1843 0.9529 0.028 0.972
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.6048 0.8833 0.852 0.148
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4431 0.9224 0.092 0.908
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.4431 0.9224 0.092 0.908
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0000 0.9561 0.000 1.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.6048 0.8833 0.852 0.148
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.0000 0.9561 0.000 1.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9561 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.9933 0.1470 0.548 0.452
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.6048 0.8833 0.852 0.148
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.1184 0.9556 0.016 0.984
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.9561 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.5842 0.8841 0.860 0.140
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.4431 0.9224 0.092 0.908
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.9561 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9561 0.000 1.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9226 1.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9226 1.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.1633 0.9540 0.024 0.976
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4431 0.9224 0.092 0.908
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.4431 0.9224 0.092 0.908
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.4431 0.9224 0.092 0.908
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.2603 0.9471 0.044 0.956
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4431 0.9224 0.092 0.908
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.6048 0.8833 0.852 0.148
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9561 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4431 0.9224 0.092 0.908
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4431 0.9224 0.092 0.908
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9561 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9561 0.000 1.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.1184 0.9556 0.016 0.984
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.9970 -0.0842 0.468 0.532
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.4431 0.9224 0.092 0.908
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9226 1.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.1184 0.9556 0.016 0.984
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.1184 0.9556 0.016 0.984
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.9561 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9226 1.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4431 0.9224 0.092 0.908
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9561 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9226 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.6048 0.8833 0.852 0.148
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9561 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9561 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4431 0.9224 0.092 0.908
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.9922 0.1700 0.552 0.448
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9226 1.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.1843 0.9529 0.028 0.972
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.2603 0.9471 0.044 0.956
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1843 0.9529 0.028 0.972
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9561 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.1184 0.9556 0.016 0.984
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.9850 0.0830 0.428 0.572
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9561 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9226 1.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.5178 0.8405 0.884 0.116
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1184 0.9556 0.016 0.984
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9226 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4431 0.9224 0.092 0.908
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4431 0.9224 0.092 0.908
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9561 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.6048 0.8833 0.852 0.148
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4431 0.9224 0.092 0.908
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4431 0.9224 0.092 0.908
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.6048 0.8833 0.852 0.148
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4431 0.9224 0.092 0.908
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4431 0.9224 0.092 0.908
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.4022 0.9291 0.080 0.920
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9561 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1414 0.9548 0.020 0.980
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.6048 0.8833 0.852 0.148
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.6048 0.8833 0.852 0.148
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9226 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.4431 0.9224 0.092 0.908
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9561 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.9635 0.2377 0.388 0.612
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1633 0.9539 0.024 0.976
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9561 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.1184 0.9556 0.016 0.984
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0000 0.9561 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9561 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1184 0.9556 0.016 0.984
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9226 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.9561 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9561 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9561 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4431 0.9224 0.092 0.908
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1184 0.9556 0.016 0.984
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9561 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4431 0.9224 0.092 0.908
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.9580 0.2642 0.380 0.620
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9561 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0376 0.9208 0.996 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1843 0.9529 0.028 0.972
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.7883 0.7858 0.764 0.236
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9226 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.6048 0.8833 0.852 0.148
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.9850 0.2157 0.572 0.428
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9561 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9561 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1184 0.9556 0.016 0.984
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.9561 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4431 0.9224 0.092 0.908
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.6623 0.8614 0.828 0.172
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9561 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4431 0.9224 0.092 0.908
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9226 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.1414 0.9548 0.020 0.980
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9561 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4431 0.9224 0.092 0.908
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.0000 0.9561 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4431 0.9224 0.092 0.908
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1184 0.9556 0.016 0.984
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4431 0.9224 0.092 0.908
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.0000 0.9561 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9226 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.9561 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9561 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9561 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1184 0.9556 0.016 0.984
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9226 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1184 0.9556 0.016 0.984
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9226 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.4939 0.8512 0.108 0.892
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2236 0.9502 0.036 0.964
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9561 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9226 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0938 0.9500 0.012 0.988
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0237 0.9727 0.000 0.996 0.004
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3644 0.8482 0.124 0.872 0.004
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0237 0.9727 0.000 0.996 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0592 0.9711 0.000 0.988 0.012
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#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.9534 1.000 0.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0747 0.9701 0.000 0.984 0.016
#> A5572139-03CA-4299-98B6-13A2945649D0 3 0.0747 0.9474 0.016 0.000 0.984
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.1753 0.9516 0.000 0.952 0.048
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.1529 0.9570 0.000 0.960 0.040
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0747 0.9702 0.000 0.984 0.016
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0592 0.9711 0.000 0.988 0.012
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0592 0.9711 0.000 0.988 0.012
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.1753 0.9516 0.000 0.952 0.048
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0592 0.9711 0.000 0.988 0.012
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9534 1.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9534 1.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0237 0.9727 0.000 0.996 0.004
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0237 0.9727 0.000 0.996 0.004
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.1753 0.9516 0.000 0.952 0.048
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.4737 0.8402 0.084 0.852 0.064
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9534 1.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0237 0.9727 0.000 0.996 0.004
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0747 0.9474 0.016 0.000 0.984
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0237 0.9727 0.000 0.996 0.004
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.2400 0.9178 0.064 0.932 0.004
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.1643 0.9546 0.000 0.956 0.044
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0747 0.9474 0.016 0.000 0.984
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.1289 0.9624 0.000 0.968 0.032
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0592 0.9711 0.000 0.988 0.012
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.5873 0.4417 0.684 0.312 0.004
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0747 0.9474 0.016 0.000 0.984
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.9726 0.000 1.000 0.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.1643 0.9542 0.000 0.956 0.044
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.4002 0.7734 0.840 0.000 0.160
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0237 0.9727 0.000 0.996 0.004
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.1643 0.9542 0.000 0.956 0.044
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0592 0.9711 0.000 0.988 0.012
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9534 1.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9534 1.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0237 0.9723 0.000 0.996 0.004
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0237 0.9727 0.000 0.996 0.004
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0237 0.9727 0.000 0.996 0.004
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0237 0.9727 0.000 0.996 0.004
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0237 0.9727 0.000 0.996 0.004
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0237 0.9727 0.000 0.996 0.004
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0747 0.9474 0.016 0.000 0.984
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0592 0.9711 0.000 0.988 0.012
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0237 0.9727 0.000 0.996 0.004
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0237 0.9727 0.000 0.996 0.004
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0592 0.9711 0.000 0.988 0.012
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9726 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0237 0.9727 0.000 0.996 0.004
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.6008 0.3788 0.000 0.372 0.628
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0237 0.9727 0.000 0.996 0.004
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9534 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0237 0.9727 0.000 0.996 0.004
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9726 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.1031 0.9668 0.000 0.976 0.024
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9534 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0237 0.9727 0.000 0.996 0.004
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0592 0.9711 0.000 0.988 0.012
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9534 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1163 0.9394 0.028 0.000 0.972
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0424 0.9718 0.000 0.992 0.008
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0592 0.9711 0.000 0.988 0.012
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0237 0.9727 0.000 0.996 0.004
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.5956 0.4237 0.672 0.324 0.004
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9534 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0237 0.9727 0.000 0.996 0.004
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0237 0.9727 0.000 0.996 0.004
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0237 0.9727 0.000 0.996 0.004
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.1753 0.9516 0.000 0.952 0.048
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0237 0.9727 0.000 0.996 0.004
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.4235 0.7884 0.000 0.824 0.176
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0592 0.9711 0.000 0.988 0.012
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9534 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.3784 0.7472 0.864 0.132 0.004
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0237 0.9727 0.000 0.996 0.004
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9534 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0237 0.9727 0.000 0.996 0.004
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0237 0.9727 0.000 0.996 0.004
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0592 0.9711 0.000 0.988 0.012
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1163 0.9394 0.028 0.000 0.972
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0237 0.9727 0.000 0.996 0.004
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0237 0.9727 0.000 0.996 0.004
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0747 0.9474 0.016 0.000 0.984
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0237 0.9727 0.000 0.996 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0237 0.9727 0.000 0.996 0.004
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0237 0.9727 0.000 0.996 0.004
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0592 0.9711 0.000 0.988 0.012
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0237 0.9727 0.000 0.996 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1163 0.9394 0.028 0.000 0.972
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0747 0.9474 0.016 0.000 0.984
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9534 1.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0475 0.9709 0.004 0.992 0.004
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0592 0.9711 0.000 0.988 0.012
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.5269 0.6459 0.016 0.200 0.784
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0237 0.9727 0.000 0.996 0.004
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0592 0.9711 0.000 0.988 0.012
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9726 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.1753 0.9526 0.000 0.952 0.048
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.1031 0.9666 0.000 0.976 0.024
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0237 0.9727 0.000 0.996 0.004
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9534 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0237 0.9723 0.000 0.996 0.004
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0747 0.9702 0.000 0.984 0.016
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0592 0.9711 0.000 0.988 0.012
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0237 0.9727 0.000 0.996 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0237 0.9727 0.000 0.996 0.004
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0747 0.9702 0.000 0.984 0.016
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0237 0.9727 0.000 0.996 0.004
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.6912 0.1781 0.016 0.540 0.444
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0592 0.9711 0.000 0.988 0.012
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9534 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0237 0.9727 0.000 0.996 0.004
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0661 0.9399 0.008 0.004 0.988
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9534 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0747 0.9474 0.016 0.000 0.984
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.6008 0.4090 0.664 0.332 0.004
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0592 0.9711 0.000 0.988 0.012
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0424 0.9719 0.000 0.992 0.008
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0237 0.9727 0.000 0.996 0.004
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.1753 0.9516 0.000 0.952 0.048
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0237 0.9727 0.000 0.996 0.004
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0747 0.9474 0.016 0.000 0.984
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.1529 0.9570 0.000 0.960 0.040
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0237 0.9727 0.000 0.996 0.004
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9534 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9726 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0592 0.9711 0.000 0.988 0.012
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0237 0.9727 0.000 0.996 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.2165 0.9391 0.000 0.936 0.064
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0237 0.9727 0.000 0.996 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0237 0.9727 0.000 0.996 0.004
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0237 0.9727 0.000 0.996 0.004
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.3551 0.8662 0.000 0.868 0.132
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9534 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.1753 0.9516 0.000 0.952 0.048
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.1031 0.9668 0.000 0.976 0.024
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0592 0.9711 0.000 0.988 0.012
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0237 0.9727 0.000 0.996 0.004
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9534 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0237 0.9727 0.000 0.996 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9534 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.5465 0.6267 0.000 0.712 0.288
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0237 0.9727 0.000 0.996 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0747 0.9702 0.000 0.984 0.016
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9534 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.2537 0.9232 0.000 0.920 0.080
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.1211 0.8499 0.040 0.960 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4776 0.5115 0.000 0.624 0.000 0.376
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0336 0.8774 0.000 0.992 0.000 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4817 0.4887 0.000 0.612 0.000 0.388
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4855 0.4652 0.000 0.600 0.000 0.400
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0000 0.9460 0.000 0.000 0.000 1.000
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#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.4855 0.4652 0.000 0.600 0.000 0.400
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.4855 0.4652 0.000 0.600 0.000 0.400
#> DCD932D2-B708-487A-93C1-8485FBE9048A 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 4 0.0188 0.9426 0.000 0.004 0.000 0.996
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.0336 0.9388 0.008 0.000 0.000 0.992
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.1211 0.8505 0.040 0.960 0.000 0.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.4855 0.4317 0.600 0.400 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.2814 0.8078 0.000 0.868 0.000 0.132
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.4981 0.0437 0.536 0.000 0.464 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 4 0.4222 0.5620 0.000 0.272 0.000 0.728
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 4 0.4994 -0.1030 0.000 0.480 0.000 0.520
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.2408 0.8356 0.000 0.104 0.000 0.896
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4730 0.5310 0.000 0.636 0.000 0.364
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.2921 0.8021 0.000 0.860 0.000 0.140
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.4941 0.1716 0.000 0.000 0.564 0.436
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0188 0.8787 0.000 0.996 0.000 0.004
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4406 0.6293 0.000 0.700 0.000 0.300
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.4855 0.4652 0.000 0.600 0.000 0.400
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.0817 0.9240 0.000 0.024 0.000 0.976
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.4804 0.4606 0.616 0.384 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0592 0.8742 0.000 0.984 0.000 0.016
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.1118 0.9112 0.000 0.036 0.000 0.964
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.4164 0.6127 0.736 0.264 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.1211 0.8556 0.000 0.960 0.000 0.040
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4941 0.3774 0.000 0.564 0.000 0.436
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4103 0.6859 0.000 0.744 0.000 0.256
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4804 0.4964 0.000 0.616 0.000 0.384
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2149 0.8352 0.000 0.912 0.000 0.088
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3024 0.7953 0.000 0.852 0.000 0.148
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.4713 0.3942 0.000 0.360 0.000 0.640
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4843 0.4732 0.000 0.604 0.000 0.396
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0336 0.8772 0.000 0.992 0.000 0.008
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.3726 0.6785 0.000 0.000 0.212 0.788
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4843 0.4732 0.000 0.604 0.000 0.396
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3837 0.7224 0.000 0.776 0.000 0.224
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4855 0.4317 0.600 0.400 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4431 0.6232 0.000 0.696 0.000 0.304
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4830 0.4810 0.000 0.608 0.000 0.392
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3024 0.7950 0.000 0.852 0.000 0.148
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9485 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3123 0.7907 0.000 0.844 0.000 0.156
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.3907 0.6464 0.000 0.232 0.000 0.768
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0469 0.8756 0.000 0.988 0.000 0.012
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.1022 0.9184 0.000 0.000 0.032 0.968
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8800 0.000 1.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0000 0.9460 0.000 0.000 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9479 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0000 0.9460 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2377 0.7504 0.000 0.872 0.000 0.000 0.128
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.4430 0.2815 0.004 0.456 0.000 0.000 0.540
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3741 0.6868 0.000 0.732 0.000 0.004 0.264
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2389 0.7578 0.000 0.880 0.000 0.116 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0290 0.9178 0.992 0.000 0.000 0.000 0.008
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1740 0.7825 0.000 0.932 0.000 0.056 0.012
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3074 0.7559 0.000 0.804 0.000 0.000 0.196
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9365 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3967 0.6832 0.000 0.724 0.000 0.012 0.264
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0290 0.9305 0.000 0.000 0.992 0.000 0.008
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.3790 0.6016 0.000 0.724 0.000 0.272 0.004
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1331 0.8444 0.000 0.040 0.000 0.952 0.008
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3807 0.7037 0.000 0.748 0.000 0.012 0.240
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.2179 0.7960 0.000 0.100 0.000 0.896 0.004
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0162 0.8633 0.000 0.000 0.000 0.996 0.004
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4074 0.4765 0.000 0.636 0.000 0.364 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9226 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.8636 0.000 0.000 0.000 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.2677 0.7813 0.000 0.112 0.000 0.872 0.016
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0162 0.8633 0.000 0.000 0.000 0.996 0.004
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#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0566 0.7904 0.000 0.984 0.000 0.012 0.004
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0703 0.7872 0.000 0.976 0.000 0.000 0.024
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.4045 0.4365 0.000 0.000 0.000 0.644 0.356
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2813 0.7495 0.832 0.000 0.000 0.000 0.168
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0162 0.8633 0.000 0.000 0.000 0.996 0.004
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0290 0.8632 0.000 0.000 0.000 0.992 0.008
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4206 0.5561 0.000 0.272 0.000 0.708 0.020
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2970 0.7490 0.000 0.828 0.000 0.004 0.168
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9226 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0324 0.7893 0.000 0.992 0.000 0.004 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.4305 -0.0110 0.488 0.000 0.000 0.000 0.512
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.2171 0.7949 0.000 0.000 0.064 0.912 0.024
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3143 0.7310 0.000 0.796 0.000 0.000 0.204
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0290 0.8632 0.000 0.000 0.000 0.992 0.008
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9226 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4489 0.2863 0.000 0.008 0.000 0.572 0.420
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 6 0.3867 0.42481 0.000 0.488 0.000 0.000 0.000 0.512
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 6 0.5077 0.17275 0.000 0.088 0.000 0.000 0.360 0.552
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.2451 0.47625 0.000 0.884 0.000 0.000 0.056 0.060
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4772 0.51476 0.000 0.700 0.000 0.188 0.016 0.096
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0260 0.94869 0.992 0.000 0.000 0.000 0.000 0.008
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5552 -0.08930 0.000 0.452 0.000 0.104 0.008 0.436
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4405 -0.48415 0.000 0.504 0.000 0.000 0.024 0.472
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2512 0.47309 0.000 0.880 0.000 0.000 0.060 0.060
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0632 0.92526 0.000 0.000 0.976 0.000 0.024 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.6212 0.30859 0.000 0.456 0.000 0.292 0.012 0.240
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.3894 0.74020 0.000 0.120 0.000 0.784 0.008 0.088
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2209 0.49112 0.000 0.904 0.000 0.004 0.040 0.052
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1643 0.75645 0.000 0.000 0.000 0.924 0.008 0.068
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3506 0.75982 0.000 0.000 0.000 0.792 0.052 0.156
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4345 0.45887 0.000 0.624 0.000 0.348 0.020 0.008
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2988 0.76888 0.000 0.000 0.000 0.824 0.024 0.152
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3472 0.71030 0.000 0.008 0.000 0.820 0.096 0.076
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.1461 0.75454 0.000 0.000 0.000 0.940 0.044 0.016
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3952 0.75944 0.000 0.048 0.000 0.772 0.016 0.164
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2633 0.71796 0.000 0.000 0.000 0.864 0.104 0.032
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 6 0.3515 0.74369 0.000 0.324 0.000 0.000 0.000 0.676
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3278 0.76341 0.000 0.000 0.000 0.808 0.040 0.152
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.3739 0.65934 0.000 0.000 0.000 0.768 0.056 0.176
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3764 0.76047 0.000 0.044 0.000 0.784 0.012 0.160
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3102 0.46700 0.000 0.816 0.000 0.000 0.028 0.156
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0291 0.77130 0.000 0.004 0.000 0.992 0.004 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.5707 0.16353 0.000 0.316 0.000 0.528 0.008 0.148
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.5278 0.59933 0.000 0.256 0.000 0.636 0.036 0.072
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3293 0.51879 0.000 0.824 0.000 0.040 0.008 0.128
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.5401 -0.34723 0.000 0.504 0.000 0.040 0.040 0.416
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.5501 0.42107 0.000 0.000 0.200 0.564 0.236 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4088 0.11128 0.000 0.616 0.000 0.016 0.000 0.368
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.2945 0.76801 0.000 0.000 0.000 0.824 0.020 0.156
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1984 0.50123 0.000 0.912 0.000 0.000 0.032 0.056
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4548 0.52742 0.000 0.720 0.000 0.156 0.008 0.116
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.2573 0.79204 0.864 0.000 0.000 0.000 0.112 0.024
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4073 0.75713 0.000 0.056 0.000 0.764 0.016 0.164
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 6 0.3482 0.74612 0.000 0.316 0.000 0.000 0.000 0.684
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.5097 0.27498 0.004 0.068 0.000 0.000 0.508 0.420
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0146 0.93757 0.000 0.000 0.996 0.000 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3860 -0.30918 0.000 0.528 0.000 0.000 0.000 0.472
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2451 0.47625 0.000 0.884 0.000 0.000 0.056 0.060
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1367 0.75924 0.000 0.000 0.000 0.944 0.044 0.012
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.4175 0.65369 0.000 0.000 0.752 0.136 0.108 0.004
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.5752 0.15817 0.000 0.436 0.000 0.024 0.448 0.092
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4765 0.60183 0.000 0.012 0.000 0.700 0.112 0.176
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4732 0.49701 0.000 0.276 0.000 0.660 0.040 0.024
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.3801 0.76245 0.000 0.064 0.000 0.792 0.012 0.132
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.2946 0.76906 0.000 0.012 0.000 0.824 0.004 0.160
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0146 0.93757 0.000 0.000 0.996 0.000 0.004 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.5700 0.19917 0.000 0.424 0.000 0.028 0.468 0.080
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 6 0.3390 0.74845 0.000 0.296 0.000 0.000 0.000 0.704
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3013 0.49029 0.000 0.832 0.000 0.004 0.024 0.140
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.4551 0.49736 0.000 0.060 0.000 0.208 0.712 0.020
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.1528 0.77663 0.000 0.016 0.000 0.944 0.012 0.028
#> 12FD30FF-4D3A-4920-BF80-F44132824017 6 0.4926 0.19270 0.000 0.080 0.000 0.000 0.336 0.584
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4289 0.37434 0.000 0.680 0.000 0.040 0.004 0.276
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2444 0.52559 0.000 0.896 0.000 0.016 0.036 0.052
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.3321 0.70663 0.000 0.000 0.000 0.820 0.080 0.100
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2404 0.74127 0.000 0.000 0.000 0.884 0.080 0.036
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.5538 0.27504 0.000 0.512 0.000 0.148 0.000 0.340
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.1780 0.75003 0.000 0.000 0.000 0.924 0.048 0.028
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.5057 -0.36324 0.000 0.528 0.000 0.016 0.044 0.412
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.4076 0.72031 0.000 0.348 0.000 0.004 0.012 0.636
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5455 0.16424 0.000 0.560 0.000 0.084 0.020 0.336
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 6 0.4242 0.58543 0.000 0.448 0.000 0.000 0.016 0.536
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.5132 0.31035 0.000 0.560 0.000 0.372 0.044 0.024
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4935 0.49053 0.000 0.640 0.000 0.280 0.016 0.064
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4889 0.41898 0.000 0.312 0.000 0.624 0.040 0.024
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.6128 -0.12586 0.000 0.296 0.000 0.432 0.004 0.268
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.3909 0.75613 0.000 0.060 0.000 0.772 0.008 0.160
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.3318 0.68270 0.000 0.024 0.000 0.824 0.132 0.020
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.5232 0.42186 0.000 0.568 0.000 0.356 0.040 0.036
#> 21821B38-6786-4078-9918-EC0E877C1533 6 0.3499 0.74322 0.000 0.320 0.000 0.000 0.000 0.680
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4092 0.46403 0.000 0.636 0.000 0.344 0.020 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4332 0.10548 0.000 0.672 0.000 0.000 0.052 0.276
#> F1099B84-FE2A-419C-9948-D0754C1AF902 5 0.4591 0.37422 0.408 0.000 0.000 0.000 0.552 0.040
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.4343 0.14968 0.000 0.648 0.000 0.016 0.016 0.320
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.4913 0.48422 0.000 0.392 0.000 0.056 0.004 0.548
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1845 0.48977 0.000 0.920 0.000 0.000 0.052 0.028
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.3975 -0.32571 0.000 0.544 0.000 0.000 0.004 0.452
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.2527 0.75227 0.000 0.000 0.832 0.000 0.168 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.6703 -0.25321 0.000 0.320 0.000 0.360 0.032 0.288
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0603 0.94033 0.980 0.000 0.000 0.000 0.004 0.016
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.2230 0.50511 0.000 0.892 0.000 0.000 0.024 0.084
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 5 0.5479 0.43953 0.008 0.000 0.080 0.256 0.628 0.028
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4183 0.54703 0.000 0.268 0.000 0.696 0.020 0.016
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.2213 0.53471 0.000 0.908 0.000 0.032 0.012 0.048
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.1845 0.75052 0.000 0.000 0.000 0.920 0.052 0.028
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.3043 0.44199 0.000 0.792 0.000 0.000 0.008 0.200
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.5253 0.58279 0.000 0.052 0.000 0.124 0.688 0.136
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4033 0.65282 0.000 0.072 0.000 0.756 0.004 0.168
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.6562 0.33107 0.000 0.108 0.000 0.124 0.532 0.236
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.3139 0.68576 0.000 0.000 0.000 0.812 0.160 0.028
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.4436 0.52904 0.000 0.272 0.000 0.680 0.028 0.020
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.6492 0.29405 0.000 0.432 0.000 0.312 0.028 0.228
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0146 0.95092 0.996 0.000 0.000 0.000 0.004 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.2383 0.76487 0.000 0.052 0.000 0.900 0.028 0.020
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.4880 0.38962 0.000 0.656 0.000 0.076 0.012 0.256
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 5 0.4603 0.35644 0.416 0.000 0.000 0.000 0.544 0.040
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0146 0.93757 0.000 0.000 0.996 0.000 0.004 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 6 0.5044 0.57994 0.000 0.392 0.000 0.040 0.020 0.548
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.4453 0.47239 0.000 0.636 0.000 0.328 0.016 0.020
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.1633 0.75195 0.000 0.000 0.000 0.932 0.044 0.024
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.3825 0.43116 0.000 0.744 0.000 0.032 0.004 0.220
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#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1845 0.49056 0.000 0.920 0.000 0.000 0.052 0.028
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.3956 0.46232 0.000 0.748 0.000 0.040 0.008 0.204
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.0858 0.76444 0.000 0.000 0.000 0.968 0.004 0.028
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.2308 0.49240 0.000 0.892 0.000 0.000 0.040 0.068
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.4517 0.57058 0.000 0.128 0.000 0.112 0.740 0.020
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.3850 0.76334 0.000 0.064 0.000 0.792 0.016 0.128
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.3283 0.70246 0.804 0.000 0.000 0.000 0.160 0.036
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 5 0.5738 0.53358 0.140 0.012 0.000 0.000 0.532 0.316
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1938 0.49689 0.000 0.920 0.000 0.004 0.040 0.036
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 6 0.3428 0.74878 0.000 0.304 0.000 0.000 0.000 0.696
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.2573 0.49213 0.000 0.864 0.000 0.000 0.024 0.112
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4180 0.60617 0.000 0.216 0.000 0.732 0.024 0.028
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.3847 0.71226 0.000 0.348 0.000 0.000 0.008 0.644
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4056 -0.15334 0.000 0.576 0.000 0.004 0.004 0.416
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.2119 0.49866 0.000 0.904 0.000 0.000 0.036 0.060
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 6 0.4594 0.50550 0.000 0.476 0.000 0.000 0.036 0.488
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 6 0.6450 0.53252 0.000 0.328 0.000 0.036 0.184 0.452
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.5182 0.44071 0.000 0.584 0.000 0.340 0.044 0.032
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.2755 0.51589 0.000 0.856 0.000 0.012 0.012 0.120
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.93908 0.000 0.000 1.000 0.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.4603 0.35644 0.416 0.000 0.000 0.000 0.544 0.040
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 6 0.3528 0.74814 0.000 0.296 0.000 0.000 0.004 0.700
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5709 0.43519 0.000 0.576 0.000 0.264 0.020 0.140
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.6176 0.11784 0.000 0.000 0.464 0.160 0.352 0.024
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4206 0.11587 0.000 0.624 0.000 0.012 0.008 0.356
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4185 0.65060 0.000 0.068 0.000 0.752 0.012 0.168
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.6069 0.32226 0.000 0.360 0.000 0.116 0.036 0.488
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.3247 0.76673 0.000 0.000 0.000 0.808 0.036 0.156
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3758 0.76621 0.000 0.080 0.000 0.812 0.028 0.080
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3605 0.51983 0.000 0.804 0.000 0.060 0.008 0.128
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 5 0.4500 0.40329 0.392 0.000 0.000 0.000 0.572 0.036
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.5665 -0.11894 0.000 0.460 0.000 0.028 0.436 0.076
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.3583 0.71820 0.000 0.144 0.000 0.800 0.008 0.048
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4696 0.49661 0.000 0.660 0.000 0.276 0.016 0.048
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 6 0.3390 0.74845 0.000 0.296 0.000 0.000 0.000 0.704
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5010 0.37808 0.000 0.632 0.000 0.104 0.004 0.260
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.3687 0.76370 0.000 0.032 0.000 0.788 0.016 0.164
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 6 0.4383 0.70836 0.000 0.356 0.000 0.016 0.012 0.616
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 5 0.5517 0.34184 0.000 0.000 0.080 0.348 0.548 0.024
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4304 0.46915 0.000 0.636 0.000 0.336 0.020 0.008
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.3722 0.63735 0.764 0.004 0.000 0.000 0.196 0.036
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2933 0.52463 0.000 0.844 0.000 0.012 0.016 0.128
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1745 0.88840 0.000 0.000 0.924 0.020 0.056 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0146 0.93757 0.000 0.000 0.996 0.000 0.004 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.5260 0.29936 0.012 0.068 0.000 0.000 0.520 0.400
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.6358 0.22231 0.000 0.400 0.000 0.288 0.012 0.300
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4794 0.45812 0.000 0.608 0.000 0.340 0.024 0.028
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1757 0.52162 0.000 0.928 0.000 0.012 0.008 0.052
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.3408 0.76175 0.000 0.000 0.000 0.800 0.048 0.152
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 6 0.3695 0.69458 0.000 0.376 0.000 0.000 0.000 0.624
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1245 0.90790 0.000 0.000 0.952 0.016 0.032 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1841 0.77917 0.000 0.008 0.000 0.920 0.008 0.064
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 6 0.3482 0.74290 0.000 0.316 0.000 0.000 0.000 0.684
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0632 0.93600 0.976 0.000 0.000 0.000 0.000 0.024
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5245 0.44621 0.000 0.652 0.000 0.108 0.024 0.216
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4960 0.45052 0.000 0.600 0.000 0.336 0.020 0.044
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3899 -0.14988 0.000 0.592 0.000 0.000 0.004 0.404
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3588 0.76039 0.000 0.000 0.000 0.788 0.060 0.152
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.5112 0.16429 0.000 0.592 0.000 0.000 0.296 0.112
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2994 0.48250 0.000 0.820 0.000 0.008 0.008 0.164
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4326 -0.02183 0.000 0.572 0.000 0.024 0.000 0.404
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.4467 0.06379 0.000 0.000 0.000 0.508 0.464 0.028
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3612 0.62990 0.764 0.000 0.000 0.000 0.200 0.036
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1780 0.76052 0.000 0.000 0.000 0.924 0.048 0.028
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2810 0.77087 0.000 0.004 0.000 0.832 0.008 0.156
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.5004 0.58269 0.000 0.060 0.000 0.696 0.056 0.188
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2665 0.49670 0.000 0.868 0.000 0.016 0.012 0.104
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4772 -0.20023 0.000 0.516 0.000 0.028 0.012 0.444
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.4516 0.39326 0.400 0.000 0.000 0.000 0.564 0.036
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.3657 0.65992 0.000 0.000 0.036 0.808 0.128 0.028
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2197 0.48958 0.000 0.900 0.000 0.000 0.056 0.044
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2669 0.76933 0.000 0.000 0.000 0.836 0.008 0.156
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.95423 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.4434 0.16007 0.000 0.000 0.000 0.428 0.544 0.028
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 17581 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 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 0.729 0.862 0.937 0.4424 0.547 0.547
#> 3 3 0.854 0.877 0.953 0.3089 0.815 0.677
#> 4 4 0.679 0.710 0.829 0.2484 0.791 0.527
#> 5 5 0.624 0.631 0.786 0.0755 0.838 0.484
#> 6 6 0.649 0.557 0.755 0.0462 0.909 0.636
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0672 0.9537 0.008 0.992
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.9427 0.3325 0.360 0.640
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9557 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9557 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.8207 0.7106 0.744 0.256
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0938 0.9524 0.012 0.988
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0938 0.9524 0.012 0.988
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0938 0.8789 0.988 0.012
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9557 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0938 0.8789 0.988 0.012
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0672 0.9537 0.008 0.992
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9557 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9557 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9557 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.8955 0.5076 0.312 0.688
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9557 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.9358 0.5725 0.648 0.352
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9557 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0376 0.9537 0.004 0.996
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.9557 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9557 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6438 0.7563 0.164 0.836
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0938 0.9524 0.012 0.988
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.9552 0.3596 0.376 0.624
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.5059 0.8333 0.112 0.888
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9557 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0672 0.9537 0.008 0.992
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9557 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.8774 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9557 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.6148 0.8019 0.848 0.152
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9557 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9557 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0938 0.9524 0.012 0.988
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#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9557 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.8774 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.0938 0.8789 0.988 0.012
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9557 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9557 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0938 0.9524 0.012 0.988
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.9358 0.5727 0.648 0.352
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.2603 0.8645 0.956 0.044
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9557 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9557 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9557 0.000 1.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9557 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9557 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.5178 0.8171 0.884 0.116
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9557 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.8774 1.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.9393 0.5652 0.644 0.356
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9557 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.8774 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0938 0.9524 0.012 0.988
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0672 0.9537 0.008 0.992
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9557 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0938 0.8789 0.988 0.012
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0938 0.9524 0.012 0.988
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0938 0.9524 0.012 0.988
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0938 0.8789 0.988 0.012
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9557 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0938 0.9524 0.012 0.988
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.5629 0.8147 0.132 0.868
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9557 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9557 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0938 0.8789 0.988 0.012
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0938 0.8789 0.988 0.012
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0376 0.8780 0.996 0.004
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0938 0.9524 0.012 0.988
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0672 0.9537 0.008 0.992
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0938 0.8789 0.988 0.012
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0938 0.9524 0.012 0.988
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9557 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0938 0.9524 0.012 0.988
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.9323 0.4281 0.348 0.652
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9557 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9557 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.8774 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.8909 0.5159 0.308 0.692
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9557 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9557 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0938 0.9524 0.012 0.988
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0938 0.9524 0.012 0.988
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9557 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0938 0.9524 0.012 0.988
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0938 0.8789 0.988 0.012
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9557 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.9635 0.4997 0.612 0.388
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9557 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0938 0.8789 0.988 0.012
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2948 0.8610 0.948 0.052
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0938 0.8789 0.988 0.012
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.9580 0.5172 0.620 0.380
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0938 0.9524 0.012 0.988
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9557 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9557 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.9557 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0938 0.9524 0.012 0.988
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0938 0.8789 0.988 0.012
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9557 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0938 0.9524 0.012 0.988
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.8774 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9557 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9557 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0938 0.9524 0.012 0.988
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.9044 0.5502 0.680 0.320
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9557 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9557 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0938 0.9524 0.012 0.988
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.0672 0.8785 0.992 0.008
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.8861 0.6507 0.696 0.304
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.8713 0.5487 0.292 0.708
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4815 0.8451 0.104 0.896
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0376 0.9548 0.004 0.996
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9557 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.6973 0.7753 0.812 0.188
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0938 0.9524 0.012 0.988
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.8774 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.7745 0.7504 0.772 0.228
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9557 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9557 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.9000 0.6324 0.684 0.316
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.7299 0.7611 0.796 0.204
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9633 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.9424 1.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9633 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9633 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9424 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9633 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9633 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.8728 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9633 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.8728 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9633 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9633 0.000 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9633 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9633 0.000 1.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1163 0.8554 0.000 0.028 0.972
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9633 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9424 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0237 0.9600 0.000 0.996 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9633 0.000 1.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0237 0.9600 0.000 0.996 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9633 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.6180 0.3466 0.000 0.416 0.584
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0237 0.9599 0.004 0.996 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.6154 0.3759 0.000 0.408 0.592
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.4796 0.6797 0.000 0.780 0.220
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9633 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9633 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9633 0.000 1.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9424 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9633 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9424 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9633 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9633 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9633 0.000 1.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.8728 0.000 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9633 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4002 0.7495 0.000 0.160 0.840
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9633 0.000 1.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9633 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9424 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9633 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.6302 0.0737 0.520 0.480 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9424 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.8728 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9633 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9633 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9633 0.000 1.000 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9424 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9424 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.8728 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.6126 0.2694 0.000 0.600 0.400
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.3482 0.8204 0.000 0.872 0.128
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9633 0.000 1.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9633 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9633 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.8728 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9424 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.6180 0.2189 0.000 0.584 0.416
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9424 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.9424 1.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9633 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.4654 0.6997 0.000 0.208 0.792
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9424 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9633 0.000 1.000 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0000 0.9424 1.000 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9633 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9633 0.000 1.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.9633 0.000 1.000 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.4796 0.6798 0.000 0.780 0.220
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9633 0.000 1.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9424 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.6299 0.1697 0.000 0.476 0.524
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9424 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9633 0.000 1.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5988 0.4169 0.368 0.632 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9633 0.000 1.000 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9633 0.000 1.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9633 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9633 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9633 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9424 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0237 0.9599 0.004 0.996 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.8728 0.000 0.000 1.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9633 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.8728 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9633 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.6299 0.0883 0.524 0.476 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9633 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9633 0.000 1.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.6095 0.3137 0.392 0.000 0.608
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9633 0.000 1.000 0.000
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#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.8728 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9633 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9633 0.000 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9633 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0237 0.8705 0.000 0.004 0.996
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9633 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9633 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9424 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.6111 0.2812 0.000 0.604 0.396
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9633 0.000 1.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9633 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.3551 0.7750 0.868 0.132 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9633 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0237 0.9600 0.000 0.996 0.004
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9633 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0000 0.8728 0.000 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9633 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9424 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9633 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.8728 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9424 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.8728 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9424 1.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9633 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9633 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9633 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0237 0.9600 0.000 0.996 0.004
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9633 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.8728 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9633 0.000 1.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.1289 0.9331 0.032 0.968 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9424 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9633 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9633 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9633 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.8728 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9633 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9633 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9633 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0424 0.8670 0.008 0.000 0.992
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9424 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.6305 0.1442 0.000 0.484 0.516
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5058 0.6417 0.000 0.756 0.244
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9633 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9633 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9424 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9633 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9424 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4291 0.7219 0.000 0.180 0.820
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9633 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.2878 0.8627 0.000 0.904 0.096
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9424 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5948 0.3544 0.360 0.000 0.640
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2060 0.61460 0.052 0.932 0.000 0.016
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4605 0.64360 0.664 0.336 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4776 0.71677 0.000 0.624 0.000 0.376
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4250 0.72501 0.000 0.724 0.000 0.276
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0707 0.91433 0.980 0.020 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.0188 0.80054 0.000 0.004 0.000 0.996
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.0000 0.80087 0.000 0.000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0469 0.89760 0.000 0.012 0.988 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4804 0.70971 0.000 0.616 0.000 0.384
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.1557 0.88752 0.000 0.056 0.944 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.0336 0.80150 0.000 0.008 0.000 0.992
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.1940 0.65844 0.000 0.924 0.000 0.076
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4898 0.66920 0.000 0.584 0.000 0.416
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0469 0.80091 0.000 0.012 0.000 0.988
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1474 0.87157 0.000 0.000 0.948 0.052
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.2081 0.76916 0.000 0.084 0.000 0.916
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1302 0.90798 0.956 0.044 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.5088 0.72005 0.000 0.688 0.024 0.288
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0672 0.79923 0.000 0.008 0.008 0.984
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.4453 0.60020 0.000 0.012 0.744 0.244
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4643 0.07737 0.000 0.344 0.000 0.656
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5320 0.17218 0.000 0.012 0.416 0.572
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.5626 0.31914 0.384 0.028 0.000 0.588
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.6253 -0.06320 0.000 0.544 0.396 0.060
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4483 0.47951 0.000 0.004 0.284 0.712
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3873 0.71411 0.000 0.772 0.000 0.228
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.2281 0.72693 0.000 0.096 0.000 0.904
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4543 0.51766 0.000 0.324 0.000 0.676
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0188 0.91539 0.996 0.004 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0336 0.80150 0.000 0.008 0.000 0.992
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.91562 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.1022 0.79002 0.000 0.032 0.000 0.968
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.0921 0.79261 0.000 0.028 0.000 0.972
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.0188 0.80054 0.000 0.004 0.000 0.996
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.1042 0.89670 0.000 0.020 0.972 0.008
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1867 0.66181 0.000 0.928 0.000 0.072
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.5030 0.65636 0.000 0.188 0.752 0.060
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.3123 0.63619 0.000 0.156 0.000 0.844
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.0817 0.79460 0.000 0.024 0.000 0.976
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0336 0.91478 0.992 0.008 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4981 -0.38167 0.000 0.464 0.000 0.536
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.7456 0.06396 0.508 0.256 0.000 0.236
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.1118 0.90498 0.964 0.036 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.1557 0.88752 0.000 0.056 0.944 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2814 0.68752 0.000 0.868 0.000 0.132
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4843 0.69689 0.000 0.604 0.000 0.396
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1151 0.79701 0.000 0.008 0.024 0.968
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1302 0.90820 0.956 0.044 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1118 0.91047 0.964 0.036 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0336 0.89822 0.000 0.008 0.992 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.2999 0.68769 0.000 0.864 0.004 0.132
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4392 0.59884 0.004 0.012 0.216 0.768
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4661 0.10918 0.000 0.348 0.000 0.652
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4804 0.46584 0.000 0.384 0.000 0.616
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1474 0.88906 0.000 0.052 0.948 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.91562 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.2125 0.66402 0.000 0.920 0.004 0.076
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0188 0.91539 0.996 0.004 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.2081 0.87368 0.916 0.084 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4776 0.71677 0.000 0.624 0.000 0.376
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.1940 0.60343 0.000 0.924 0.076 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1389 0.90649 0.952 0.048 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.0707 0.80042 0.000 0.020 0.000 0.980
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0592 0.91336 0.984 0.016 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2011 0.66529 0.000 0.920 0.000 0.080
#> C6FB2026-B740-459E-9831-93279BBF354E 4 0.4250 0.35615 0.000 0.276 0.000 0.724
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.4500 0.51760 0.000 0.316 0.000 0.684
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.4647 0.46764 0.000 0.008 0.288 0.704
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.0336 0.80027 0.000 0.008 0.000 0.992
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0188 0.91539 0.996 0.004 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.5360 0.23355 0.000 0.012 0.552 0.436
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0188 0.91539 0.996 0.004 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.0188 0.80054 0.000 0.004 0.000 0.996
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.0524 0.79949 0.008 0.004 0.000 0.988
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4992 -0.19386 0.000 0.524 0.000 0.476
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 4 0.0469 0.79955 0.000 0.012 0.000 0.988
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.0469 0.79960 0.000 0.012 0.000 0.988
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4761 0.71635 0.000 0.628 0.000 0.372
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4164 0.41520 0.000 0.264 0.000 0.736
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0188 0.91539 0.996 0.004 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.3024 0.70313 0.000 0.148 0.000 0.852
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.1474 0.88906 0.000 0.052 0.948 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4605 0.72478 0.000 0.664 0.000 0.336
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0336 0.89822 0.000 0.008 0.992 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4866 0.68706 0.000 0.596 0.000 0.404
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.5268 0.43856 0.540 0.452 0.000 0.008
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.3942 0.70269 0.000 0.764 0.000 0.236
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4855 0.69222 0.000 0.600 0.000 0.400
#> F1099B84-FE2A-419C-9948-D0754C1AF902 2 0.7896 -0.17548 0.348 0.360 0.292 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.0188 0.80054 0.000 0.004 0.000 0.996
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.1118 0.79072 0.000 0.036 0.000 0.964
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.1557 0.90291 0.944 0.056 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.4817 0.70627 0.000 0.612 0.000 0.388
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0469 0.91534 0.988 0.012 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0336 0.89822 0.000 0.008 0.992 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.0817 0.79706 0.000 0.024 0.000 0.976
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0336 0.89822 0.000 0.008 0.992 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0188 0.91564 0.996 0.004 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 4 0.0921 0.79240 0.000 0.028 0.000 0.972
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.2695 0.87626 0.008 0.056 0.912 0.024
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.1118 0.89364 0.000 0.036 0.964 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4830 0.45759 0.000 0.392 0.000 0.608
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0336 0.91478 0.992 0.008 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.4981 0.58122 0.000 0.536 0.000 0.464
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.5149 0.47985 0.000 0.016 0.648 0.336
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.1302 0.90798 0.956 0.044 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.2958 0.60138 0.072 0.896 0.004 0.028
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.0469 0.80091 0.000 0.012 0.000 0.988
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#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4936 0.71652 0.004 0.624 0.000 0.372
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.2611 0.57801 0.096 0.896 0.000 0.008
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4746 0.72103 0.000 0.632 0.000 0.368
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4866 0.68403 0.000 0.596 0.000 0.404
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0336 0.89822 0.000 0.008 0.992 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1743 0.88575 0.004 0.056 0.940 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.5070 0.45087 0.580 0.416 0.004 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0336 0.91478 0.992 0.008 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.2216 0.73183 0.000 0.092 0.000 0.908
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.1743 0.88575 0.004 0.056 0.940 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 4 0.0707 0.79648 0.000 0.020 0.000 0.980
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0336 0.80150 0.000 0.008 0.000 0.992
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.0188 0.80147 0.000 0.004 0.000 0.996
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.4431 0.61965 0.000 0.304 0.696 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3801 0.65501 0.000 0.220 0.000 0.780
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.1474 0.90481 0.948 0.052 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.2081 0.66662 0.000 0.916 0.000 0.084
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4103 0.62808 0.000 0.256 0.000 0.744
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4730 0.72124 0.000 0.636 0.000 0.364
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.1356 0.89741 0.960 0.008 0.000 0.032
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.2081 0.65767 0.000 0.916 0.000 0.084
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.4454 0.72474 0.000 0.692 0.000 0.308
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.0592 0.79831 0.000 0.016 0.000 0.984
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.1890 0.88377 0.008 0.056 0.936 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4713 0.72348 0.000 0.640 0.000 0.360
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1743 0.90102 0.940 0.056 0.004 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1022 0.89454 0.000 0.032 0.968 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0188 0.91564 0.996 0.004 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1022 0.89454 0.000 0.032 0.968 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1940 0.88199 0.924 0.076 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.0188 0.80147 0.000 0.004 0.000 0.996
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4761 0.71956 0.000 0.628 0.000 0.372
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4776 0.71677 0.000 0.624 0.000 0.376
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.6121 0.63514 0.000 0.164 0.680 0.156
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.0592 0.79869 0.000 0.016 0.000 0.984
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0188 0.89841 0.000 0.004 0.996 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0817 0.79461 0.000 0.024 0.000 0.976
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.1452 0.77346 0.036 0.008 0.000 0.956
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.1743 0.90102 0.940 0.056 0.004 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2814 0.68771 0.000 0.868 0.000 0.132
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4661 0.72585 0.000 0.652 0.000 0.348
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.2081 0.74239 0.000 0.084 0.000 0.916
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.1733 0.88197 0.000 0.024 0.948 0.028
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4500 0.72805 0.000 0.684 0.000 0.316
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4790 0.71126 0.000 0.620 0.000 0.380
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3074 0.68475 0.000 0.848 0.000 0.152
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0524 0.89778 0.000 0.008 0.988 0.004
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3945 0.71042 0.780 0.004 0.000 0.216
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.5557 0.63404 0.000 0.308 0.652 0.040
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.2845 0.64465 0.000 0.896 0.028 0.076
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.3444 0.66701 0.000 0.184 0.000 0.816
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.0336 0.80027 0.000 0.008 0.000 0.992
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0469 0.91524 0.988 0.012 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.0188 0.80054 0.000 0.004 0.000 0.996
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.7809 0.12257 0.452 0.172 0.364 0.012
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5392 0.69230 0.008 0.056 0.736 0.200
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.5000 0.50599 0.000 0.504 0.000 0.496
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5288 0.46711 0.000 0.732 0.200 0.068
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1302 0.90798 0.956 0.044 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.6579 0.20728 0.012 0.064 0.344 0.580
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.3906 0.71192 0.000 0.292 0.000 0.004 0.704
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.5574 0.66759 0.144 0.196 0.000 0.004 0.656
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0162 0.69611 0.000 0.996 0.000 0.000 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3305 0.44147 0.000 0.776 0.000 0.000 0.224
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0912 0.90277 0.972 0.000 0.000 0.012 0.016
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.2813 0.73768 0.000 0.168 0.000 0.832 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.3480 0.69839 0.000 0.248 0.000 0.752 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0794 0.86169 0.000 0.000 0.972 0.028 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1571 0.67932 0.000 0.936 0.000 0.060 0.004
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3272 0.83730 0.008 0.000 0.860 0.072 0.060
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.2561 0.74119 0.000 0.144 0.000 0.856 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.3861 0.71490 0.000 0.284 0.000 0.004 0.712
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1043 0.70334 0.000 0.960 0.000 0.040 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4156 0.74075 0.000 0.168 0.028 0.784 0.020
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.2617 0.83447 0.000 0.036 0.904 0.032 0.028
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4325 0.66899 0.000 0.064 0.000 0.756 0.180
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0579 0.90338 0.984 0.000 0.000 0.008 0.008
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.6231 0.56417 0.000 0.376 0.008 0.116 0.500
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3515 0.73737 0.004 0.092 0.048 0.848 0.008
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.5536 0.59989 0.000 0.048 0.688 0.208 0.056
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3942 0.57785 0.000 0.728 0.012 0.260 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.5080 0.36243 0.000 0.044 0.588 0.368 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.6324 0.12163 0.168 0.532 0.000 0.296 0.004
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.6082 0.67611 0.000 0.292 0.024 0.092 0.592
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.3355 0.69623 0.000 0.036 0.132 0.832 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 5 0.5289 0.49598 0.000 0.452 0.000 0.048 0.500
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3612 0.44478 0.000 0.732 0.000 0.268 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4302 0.18168 0.000 0.000 0.000 0.520 0.480
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.1168 0.89661 0.960 0.000 0.000 0.008 0.032
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.2674 0.74233 0.000 0.140 0.000 0.856 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0162 0.90325 0.996 0.000 0.000 0.004 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4045 0.25459 0.000 0.644 0.000 0.356 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3983 0.29124 0.000 0.660 0.000 0.340 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.3857 0.63779 0.000 0.312 0.000 0.688 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4953 0.60579 0.000 0.000 0.696 0.088 0.216
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.4196 0.66654 0.000 0.356 0.000 0.004 0.640
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.5101 0.36348 0.000 0.356 0.604 0.032 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3274 0.53162 0.000 0.780 0.000 0.220 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4273 0.15660 0.000 0.552 0.000 0.448 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0671 0.90221 0.980 0.000 0.000 0.004 0.016
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4622 0.55650 0.000 0.700 0.024 0.264 0.012
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.4358 0.57660 0.696 0.284 0.000 0.008 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5391 0.59646 0.616 0.000 0.000 0.084 0.300
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.3145 0.83961 0.008 0.000 0.868 0.064 0.060
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 5 0.4443 0.48091 0.000 0.472 0.000 0.004 0.524
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0703 0.70257 0.000 0.976 0.000 0.024 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.5902 0.62906 0.000 0.208 0.192 0.600 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0771 0.90392 0.976 0.000 0.000 0.020 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0807 0.90355 0.976 0.000 0.000 0.012 0.012
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0992 0.86000 0.000 0.000 0.968 0.024 0.008
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4294 -0.36032 0.000 0.532 0.000 0.000 0.468
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.3467 0.73511 0.004 0.032 0.048 0.864 0.052
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.1851 0.64255 0.000 0.912 0.000 0.000 0.088
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5322 0.51953 0.000 0.672 0.000 0.188 0.140
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 5 0.5142 0.52585 0.000 0.088 0.000 0.244 0.668
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.2955 0.84175 0.004 0.000 0.876 0.060 0.060
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0162 0.90325 0.996 0.000 0.000 0.004 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.5868 0.58471 0.000 0.380 0.000 0.104 0.516
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0566 0.90174 0.984 0.000 0.000 0.004 0.012
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.4973 0.59514 0.632 0.000 0.000 0.048 0.320
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0162 0.69683 0.004 0.996 0.000 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.4464 0.66945 0.000 0.356 0.008 0.004 0.632
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1741 0.89442 0.936 0.000 0.000 0.024 0.040
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.4197 0.74704 0.000 0.148 0.000 0.776 0.076
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.1492 0.89285 0.948 0.004 0.000 0.008 0.040
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 5 0.4582 0.59076 0.000 0.416 0.000 0.012 0.572
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2891 0.59817 0.000 0.824 0.000 0.176 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.4906 0.16296 0.008 0.000 0.028 0.324 0.640
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3331 0.73273 0.000 0.024 0.068 0.864 0.044
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.4297 0.31584 0.000 0.472 0.000 0.528 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0566 0.90174 0.984 0.000 0.000 0.004 0.012
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.5061 0.20364 0.000 0.020 0.388 0.580 0.012
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0566 0.90174 0.984 0.000 0.000 0.004 0.012
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.3816 0.64782 0.000 0.304 0.000 0.696 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.3759 0.71008 0.016 0.220 0.000 0.764 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.4377 0.52062 0.008 0.048 0.000 0.184 0.760
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.4801 0.34445 0.048 0.668 0.000 0.284 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4150 0.15791 0.000 0.612 0.000 0.388 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4968 0.46861 0.000 0.712 0.000 0.152 0.136
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.5439 0.32831 0.000 0.560 0.000 0.372 0.068
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0566 0.90174 0.984 0.000 0.000 0.004 0.012
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4479 0.69672 0.008 0.052 0.000 0.752 0.188
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.2797 0.84344 0.000 0.000 0.880 0.060 0.060
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.6050 -0.07824 0.000 0.544 0.000 0.144 0.312
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.2341 0.84762 0.000 0.012 0.912 0.056 0.020
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.1582 0.69815 0.000 0.944 0.028 0.028 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 5 0.4989 0.69172 0.120 0.156 0.000 0.004 0.720
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.6252 -0.16234 0.000 0.508 0.000 0.164 0.328
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1121 0.70371 0.000 0.956 0.000 0.044 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.8692 -0.08089 0.352 0.100 0.192 0.036 0.320
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.4297 0.30742 0.000 0.472 0.000 0.528 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.4294 0.74581 0.004 0.148 0.000 0.776 0.072
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#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 5 0.4541 0.41763 0.000 0.032 0.000 0.288 0.680
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.1908 0.68040 0.000 0.908 0.000 0.092 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.2707 0.63871 0.000 0.876 0.000 0.100 0.024
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 5 0.5600 0.45527 0.000 0.096 0.316 0.000 0.588
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 5 0.4561 0.52735 0.064 0.012 0.000 0.164 0.760
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0693 0.90094 0.980 0.000 0.000 0.008 0.012
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.3480 0.69967 0.000 0.248 0.000 0.752 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.69747 0.000 1.000 0.000 0.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.6087 -0.10362 0.000 0.540 0.004 0.124 0.332
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.2193 0.88409 0.912 0.000 0.000 0.028 0.060
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 4 0.3326 0.70295 0.000 0.024 0.000 0.824 0.152
#> 2356B998-0930-403F-9B04-57A18A150955 5 0.6698 0.49243 0.000 0.316 0.000 0.260 0.424
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.3870 0.79279 0.792 0.000 0.016 0.016 0.176
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1740 0.85236 0.000 0.000 0.932 0.056 0.012
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.2806 0.56146 0.000 0.844 0.004 0.000 0.152
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 5 0.3928 0.71086 0.000 0.296 0.000 0.004 0.700
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4637 -0.33641 0.000 0.536 0.000 0.012 0.452
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.2997 0.79931 0.840 0.000 0.000 0.012 0.148
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0898 0.90224 0.972 0.000 0.000 0.008 0.020
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.3816 0.52580 0.000 0.696 0.000 0.304 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.2230 0.68547 0.000 0.884 0.000 0.116 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1851 0.64044 0.000 0.912 0.000 0.000 0.088
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.5155 0.63808 0.000 0.132 0.160 0.704 0.004
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.3857 0.36196 0.000 0.688 0.000 0.312 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.7533 -0.19750 0.000 0.400 0.352 0.056 0.192
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 5 0.4021 0.54522 0.000 0.036 0.000 0.200 0.764
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.1485 0.90133 0.948 0.000 0.000 0.020 0.032
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.1026 0.89928 0.968 0.004 0.000 0.004 0.024
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.3895 0.33824 0.000 0.680 0.000 0.320 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0290 0.90348 0.992 0.000 0.000 0.008 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.8270 0.35392 0.280 0.156 0.000 0.372 0.192
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0963 0.70326 0.000 0.964 0.000 0.036 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 5 0.3579 0.72124 0.000 0.240 0.000 0.004 0.756
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1845 0.85122 0.000 0.000 0.928 0.056 0.016
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.4578 0.69616 0.048 0.224 0.000 0.724 0.004
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.1469 0.68840 0.000 0.948 0.000 0.016 0.036
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0404 0.86275 0.000 0.000 0.988 0.012 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0290 0.69942 0.000 0.992 0.000 0.008 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.3430 0.53413 0.220 0.776 0.000 0.004 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.4645 0.71907 0.008 0.272 0.000 0.028 0.692
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1608 0.65755 0.000 0.928 0.000 0.000 0.072
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.3013 0.64705 0.000 0.832 0.000 0.160 0.008
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1740 0.85236 0.000 0.000 0.932 0.056 0.012
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.3080 0.83993 0.008 0.000 0.872 0.060 0.060
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.5685 0.32082 0.556 0.048 0.012 0.004 0.380
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.2189 0.86969 0.904 0.000 0.000 0.012 0.084
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.3876 0.35872 0.000 0.684 0.000 0.316 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.1717 0.85997 0.004 0.000 0.936 0.052 0.008
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3966 0.30362 0.000 0.664 0.000 0.336 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3844 0.74333 0.000 0.132 0.000 0.804 0.064
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.3452 0.70206 0.000 0.244 0.000 0.756 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.7378 0.07040 0.000 0.084 0.468 0.124 0.324
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3910 0.64204 0.000 0.032 0.000 0.772 0.196
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1597 0.67279 0.000 0.940 0.000 0.012 0.048
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2659 0.87176 0.888 0.000 0.000 0.052 0.060
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.5925 0.50564 0.000 0.424 0.000 0.104 0.472
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.5066 0.35943 0.000 0.048 0.000 0.608 0.344
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3662 0.39291 0.000 0.744 0.000 0.004 0.252
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.5198 0.69956 0.712 0.112 0.000 0.012 0.164
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.4297 0.71252 0.000 0.288 0.000 0.020 0.692
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.6461 0.01439 0.000 0.568 0.028 0.128 0.276
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4572 0.37184 0.036 0.684 0.000 0.280 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.3829 0.82709 0.016 0.000 0.828 0.096 0.060
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4926 0.40634 0.000 0.712 0.000 0.112 0.176
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.2863 0.86427 0.876 0.000 0.000 0.064 0.060
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2570 0.64751 0.000 0.888 0.000 0.084 0.028
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2446 0.85276 0.000 0.000 0.900 0.056 0.044
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0324 0.90328 0.992 0.000 0.000 0.004 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.2228 0.85320 0.000 0.000 0.912 0.048 0.040
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.2102 0.87208 0.916 0.012 0.000 0.004 0.068
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.3508 0.69632 0.000 0.252 0.000 0.748 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.2707 0.59597 0.000 0.860 0.000 0.008 0.132
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0566 0.69211 0.000 0.984 0.000 0.004 0.012
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.6771 0.44515 0.000 0.060 0.104 0.284 0.552
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4182 0.17965 0.000 0.600 0.000 0.400 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0162 0.86246 0.000 0.000 0.996 0.004 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4305 0.07666 0.000 0.488 0.000 0.512 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.5551 0.60865 0.104 0.284 0.000 0.612 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2863 0.86427 0.876 0.000 0.000 0.064 0.060
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 5 0.4430 0.53544 0.000 0.456 0.000 0.004 0.540
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4541 0.47581 0.000 0.752 0.000 0.112 0.136
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3949 0.39749 0.000 0.696 0.000 0.300 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.5211 0.53920 0.000 0.004 0.664 0.076 0.256
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2536 0.59384 0.000 0.868 0.000 0.004 0.128
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3655 0.60047 0.000 0.804 0.000 0.160 0.036
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.5639 0.57220 0.000 0.396 0.000 0.080 0.524
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.5289 0.47870 0.000 0.000 0.596 0.340 0.064
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.6460 0.01074 0.416 0.000 0.000 0.404 0.180
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.2727 0.63042 0.000 0.020 0.080 0.012 0.888
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.4330 0.72446 0.000 0.232 0.016 0.016 0.736
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.2824 0.71481 0.000 0.020 0.000 0.864 0.116
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4235 0.08603 0.000 0.576 0.000 0.424 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0693 0.90320 0.980 0.000 0.000 0.008 0.012
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.4045 0.57589 0.000 0.356 0.000 0.644 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.7414 0.07017 0.132 0.000 0.092 0.284 0.492
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4326 0.78202 0.016 0.000 0.764 0.188 0.032
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1792 0.68704 0.000 0.916 0.000 0.084 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.4679 0.71896 0.000 0.220 0.056 0.004 0.720
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2291 0.88556 0.908 0.000 0.000 0.036 0.056
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.2116 0.69814 0.008 0.000 0.076 0.912 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.2457 0.63870 0.000 0.084 0.000 0.880 0.036 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.6715 0.08311 0.288 0.044 0.000 0.472 0.188 0.008
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0713 0.75952 0.000 0.972 0.000 0.028 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3955 0.11149 0.000 0.560 0.000 0.436 0.004 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1806 0.77599 0.908 0.004 0.000 0.000 0.088 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.1151 0.67723 0.000 0.032 0.000 0.000 0.012 0.956
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.2981 0.60263 0.000 0.160 0.000 0.000 0.020 0.820
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.1957 0.72245 0.000 0.000 0.888 0.000 0.112 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4099 0.62392 0.000 0.748 0.000 0.036 0.196 0.020
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.4289 0.48002 0.028 0.000 0.612 0.000 0.360 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.1401 0.67775 0.000 0.028 0.000 0.004 0.020 0.948
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1442 0.64899 0.000 0.040 0.000 0.944 0.012 0.004
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0909 0.76349 0.000 0.968 0.000 0.012 0.000 0.020
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.1364 0.67195 0.000 0.020 0.016 0.000 0.012 0.952
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.4232 0.60399 0.000 0.016 0.796 0.036 0.068 0.084
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 6 0.5655 0.39111 0.000 0.012 0.000 0.208 0.196 0.584
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1663 0.77519 0.912 0.000 0.000 0.000 0.088 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.6162 0.58618 0.000 0.072 0.004 0.588 0.224 0.112
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.5773 0.52124 0.008 0.020 0.068 0.032 0.232 0.640
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.6975 -0.03644 0.000 0.052 0.444 0.088 0.052 0.364
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.7519 0.24026 0.000 0.444 0.036 0.080 0.236 0.204
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.6407 0.16746 0.000 0.012 0.284 0.012 0.216 0.476
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4890 0.55822 0.188 0.700 0.000 0.000 0.032 0.080
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3474 0.66507 0.000 0.056 0.000 0.824 0.104 0.016
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.1198 0.67315 0.000 0.012 0.020 0.004 0.004 0.960
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.6081 0.61119 0.000 0.108 0.000 0.612 0.156 0.124
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1610 0.74265 0.000 0.916 0.000 0.000 0.000 0.084
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3974 0.42368 0.000 0.000 0.000 0.680 0.024 0.296
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3488 0.63177 0.764 0.000 0.000 0.016 0.216 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.2101 0.67133 0.000 0.016 0.016 0.008 0.040 0.920
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0881 0.77997 0.972 0.008 0.000 0.000 0.012 0.008
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.2730 0.66822 0.000 0.808 0.000 0.000 0.000 0.192
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2454 0.69456 0.000 0.840 0.000 0.000 0.000 0.160
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.3189 0.57010 0.000 0.236 0.004 0.000 0.000 0.760
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.6712 0.38225 0.000 0.016 0.228 0.508 0.208 0.040
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4605 0.56028 0.008 0.252 0.000 0.688 0.012 0.040
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.7938 -0.15509 0.000 0.224 0.304 0.200 0.260 0.012
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1265 0.75610 0.008 0.948 0.000 0.000 0.000 0.044
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6224 0.01694 0.000 0.412 0.000 0.012 0.212 0.364
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1461 0.78166 0.940 0.000 0.000 0.016 0.044 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.7905 -0.20157 0.000 0.276 0.008 0.212 0.236 0.268
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.3871 0.45357 0.696 0.288 0.000 0.008 0.004 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6890 -0.03762 0.400 0.000 0.000 0.072 0.344 0.184
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.4367 0.46554 0.032 0.000 0.604 0.000 0.364 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 4 0.3309 0.57351 0.000 0.280 0.000 0.720 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0717 0.76245 0.000 0.976 0.000 0.016 0.000 0.008
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.5677 0.07552 0.000 0.040 0.504 0.000 0.064 0.392
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#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.6823 0.48804 0.000 0.248 0.000 0.464 0.216 0.072
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.2996 0.67041 0.000 0.772 0.000 0.000 0.000 0.228
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.5862 0.53567 0.000 0.020 0.160 0.616 0.188 0.016
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2838 0.63379 0.000 0.808 0.000 0.188 0.000 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.7630 -0.27319 0.000 0.304 0.000 0.288 0.224 0.184
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.5384 0.55934 0.000 0.184 0.000 0.604 0.004 0.208
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.3347 0.63203 0.000 0.000 0.824 0.004 0.068 0.104
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.5927 0.12530 0.300 0.000 0.000 0.044 0.104 0.552
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.2222 0.65617 0.000 0.012 0.000 0.896 0.008 0.084
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2542 0.66347 0.000 0.020 0.000 0.884 0.016 0.080
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.1151 0.66858 0.000 0.000 0.000 0.032 0.012 0.956
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.6047 0.08822 0.000 0.448 0.000 0.012 0.172 0.368
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0777 0.78411 0.972 0.004 0.000 0.000 0.024 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.3807 0.35454 0.000 0.368 0.000 0.000 0.004 0.628
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.8429 0.25032 0.080 0.000 0.232 0.148 0.344 0.196
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 5 0.6466 0.06265 0.016 0.000 0.316 0.004 0.424 0.240
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1010 0.76241 0.000 0.960 0.000 0.004 0.000 0.036
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2359 0.66596 0.000 0.024 0.004 0.904 0.016 0.052
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2912 0.70245 0.784 0.000 0.000 0.000 0.216 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.3251 0.62183 0.008 0.000 0.076 0.004 0.068 0.844
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 17581 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 0.237 0.591 0.780 0.3643 0.704 0.704
#> 3 3 0.258 0.666 0.801 0.5064 0.708 0.592
#> 4 4 0.294 0.649 0.805 0.0445 0.980 0.955
#> 5 5 0.381 0.589 0.758 0.1059 0.949 0.882
#> 6 6 0.420 0.569 0.737 0.0532 0.971 0.926
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4690 0.7518 0.100 0.900
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6887 0.7140 0.184 0.816
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1414 0.7370 0.020 0.980
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4022 0.7513 0.080 0.920
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.9970 0.2971 0.468 0.532
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.3584 0.7539 0.068 0.932
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0938 0.7329 0.012 0.988
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.1633 0.7503 0.976 0.024
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1633 0.7193 0.024 0.976
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.1633 0.7503 0.976 0.024
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.3114 0.7510 0.056 0.944
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.5946 0.7333 0.144 0.856
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1633 0.7193 0.024 0.976
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.9710 0.4259 0.400 0.600
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.9983 0.0512 0.524 0.476
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2603 0.7433 0.044 0.956
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.9963 0.3008 0.464 0.536
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.9580 0.4659 0.380 0.620
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.2043 0.7256 0.032 0.968
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.9909 0.2957 0.444 0.556
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3733 0.7424 0.072 0.928
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.9933 0.1566 0.548 0.452
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.2778 0.7498 0.048 0.952
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.9087 0.5613 0.324 0.676
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.9850 0.2273 0.572 0.428
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4298 0.7427 0.088 0.912
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1633 0.7193 0.024 0.976
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.5629 0.7393 0.132 0.868
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.9977 0.2867 0.472 0.528
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3584 0.7539 0.068 0.932
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.9988 0.2650 0.480 0.520
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.9000 0.5602 0.316 0.684
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1414 0.7329 0.020 0.980
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.2603 0.7514 0.044 0.956
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.9993 -0.0989 0.516 0.484
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.5059 0.7477 0.112 0.888
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.7376 0.6935 0.208 0.792
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1184 0.7351 0.016 0.984
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4431 0.7496 0.092 0.908
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.9993 0.2519 0.484 0.516
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4939 0.7467 0.108 0.892
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4298 0.7512 0.088 0.912
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.9775 0.4197 0.412 0.588
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.1633 0.7503 0.976 0.024
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4161 0.7516 0.084 0.916
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1633 0.7193 0.024 0.976
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.9933 0.1363 0.548 0.452
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.9983 0.2755 0.476 0.524
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.9954 0.3084 0.460 0.540
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.8813 0.5352 0.700 0.300
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 1 0.9795 0.2946 0.584 0.416
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.9732 0.4176 0.404 0.596
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.6887 0.7155 0.184 0.816
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.6531 0.7240 0.168 0.832
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3431 0.7454 0.064 0.936
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.1633 0.7503 0.976 0.024
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.9977 0.2816 0.472 0.528
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.9795 0.2946 0.584 0.416
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.9988 0.2650 0.480 0.520
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6801 0.7165 0.180 0.820
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1414 0.7326 0.020 0.980
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.9323 0.5134 0.348 0.652
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.9963 0.3008 0.464 0.536
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.8763 0.6007 0.296 0.704
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.9754 0.4284 0.408 0.592
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.6048 0.7331 0.148 0.852
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3274 0.7511 0.060 0.940
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.8386 0.6493 0.268 0.732
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.9970 0.2332 0.468 0.532
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.3274 0.7529 0.060 0.940
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.9977 0.2867 0.472 0.528
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.9977 0.0645 0.528 0.472
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.9988 0.2650 0.480 0.520
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1414 0.7370 0.020 0.980
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.8081 0.6514 0.248 0.752
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4161 0.7549 0.084 0.916
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2236 0.7474 0.036 0.964
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.8081 0.6532 0.248 0.752
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.2423 0.7454 0.040 0.960
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.2423 0.7454 0.040 0.960
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.9988 0.2650 0.480 0.520
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.6247 0.7314 0.156 0.844
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.1633 0.7503 0.976 0.024
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.6438 0.7290 0.164 0.836
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.9286 0.4656 0.656 0.344
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.8144 0.6607 0.252 0.748
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4562 0.7517 0.096 0.904
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4298 0.7537 0.088 0.912
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1843 0.7402 0.028 0.972
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.7056 0.6468 0.808 0.192
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1414 0.7321 0.020 0.980
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2603 0.7459 0.044 0.956
#> 1463039D-7953-4216-9E8B-97F681332EFF 2 0.9970 0.2921 0.468 0.532
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1633 0.7193 0.024 0.976
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 2 0.9983 0.2759 0.476 0.524
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.2236 0.7455 0.036 0.964
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.1843 0.7489 0.972 0.028
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.2423 0.7509 0.040 0.960
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.1633 0.7503 0.976 0.024
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 2 0.9954 0.3084 0.460 0.540
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0938 0.7274 0.012 0.988
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.7674 0.6275 0.776 0.224
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.1633 0.7503 0.976 0.024
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3584 0.7468 0.068 0.932
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 2 0.9963 0.3073 0.464 0.536
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1633 0.7193 0.024 0.976
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 1 0.9608 0.3669 0.616 0.384
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 2 0.9970 0.2921 0.468 0.532
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.1184 0.7398 0.016 0.984
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.5408 0.7491 0.124 0.876
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.5408 0.7430 0.124 0.876
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.8327 0.6530 0.264 0.736
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#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2603 0.7502 0.044 0.956
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1843 0.7412 0.028 0.972
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5178 0.7462 0.116 0.884
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.9954 0.2489 0.460 0.540
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.9866 0.3782 0.432 0.568
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.8081 0.6661 0.248 0.752
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5178 0.7409 0.116 0.884
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2948 0.7522 0.052 0.948
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2043 0.7256 0.032 0.968
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.9970 0.2921 0.468 0.532
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1414 0.7370 0.020 0.980
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.9850 0.3868 0.428 0.572
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.7883 0.6194 0.764 0.236
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1184 0.7245 0.016 0.984
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.9393 0.4612 0.356 0.644
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.9933 0.3292 0.452 0.548
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.7950 0.6156 0.760 0.240
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.5115 0.75564 0.228 0.768 0.004
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.6683 -0.16462 0.500 0.492 0.008
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1643 0.79398 0.044 0.956 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4861 0.78387 0.180 0.808 0.012
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2356 0.80532 0.928 0.072 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.3644 0.80309 0.124 0.872 0.004
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1031 0.78500 0.024 0.976 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0237 0.76676 0.004 0.000 0.996
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0592 0.77008 0.012 0.988 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0237 0.76676 0.004 0.000 0.996
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2796 0.80438 0.092 0.908 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.6481 0.72457 0.224 0.728 0.048
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0592 0.77008 0.012 0.988 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.9576 0.01586 0.408 0.396 0.196
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.9982 -0.09842 0.332 0.308 0.360
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.3129 0.80491 0.088 0.904 0.008
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2711 0.79965 0.912 0.088 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.9550 0.23604 0.340 0.456 0.204
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0892 0.77563 0.020 0.980 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.9904 0.10670 0.380 0.352 0.268
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3587 0.80435 0.088 0.892 0.020
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.9924 0.01449 0.288 0.320 0.392
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3816 0.79543 0.148 0.852 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.9192 0.39032 0.308 0.516 0.176
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.9825 0.03923 0.308 0.268 0.424
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4845 0.79913 0.104 0.844 0.052
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0892 0.76514 0.020 0.980 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.6276 0.74369 0.224 0.736 0.040
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2590 0.80380 0.924 0.072 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3715 0.80240 0.128 0.868 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.2096 0.79570 0.944 0.052 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.9211 0.35066 0.312 0.512 0.176
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1643 0.79446 0.044 0.956 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3715 0.80294 0.128 0.868 0.004
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.8061 0.63066 0.652 0.156 0.192
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.5327 0.71462 0.272 0.728 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.7801 0.61916 0.276 0.636 0.088
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1753 0.79496 0.048 0.952 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4293 0.78932 0.164 0.832 0.004
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.2486 0.79868 0.932 0.060 0.008
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.5207 0.79609 0.124 0.824 0.052
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4399 0.77502 0.188 0.812 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5318 0.72662 0.780 0.204 0.016
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0237 0.76676 0.004 0.000 0.996
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4504 0.77427 0.196 0.804 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0592 0.77008 0.012 0.988 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.9900 -0.00519 0.304 0.292 0.404
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.2496 0.80317 0.928 0.068 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2959 0.80278 0.900 0.100 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.8801 0.32218 0.292 0.148 0.560
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.9224 0.15412 0.160 0.360 0.480
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.9398 0.07510 0.428 0.400 0.172
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.7207 0.48499 0.384 0.584 0.032
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.7065 0.66589 0.276 0.672 0.052
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4609 0.79873 0.128 0.844 0.028
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0237 0.76676 0.004 0.000 0.996
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2772 0.80441 0.916 0.080 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.9224 0.15412 0.160 0.360 0.480
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.2200 0.79611 0.940 0.056 0.004
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6683 0.17361 0.496 0.496 0.008
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1964 0.79650 0.056 0.944 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.9641 0.31512 0.296 0.464 0.240
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.2711 0.80014 0.912 0.088 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.8850 0.34341 0.356 0.516 0.128
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.5115 0.69598 0.768 0.228 0.004
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.5465 0.69083 0.288 0.712 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3910 0.80816 0.104 0.876 0.020
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.8243 0.43617 0.368 0.548 0.084
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.9517 0.28558 0.476 0.312 0.212
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.3551 0.80153 0.132 0.868 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2301 0.80145 0.936 0.060 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.9977 0.12811 0.352 0.300 0.348
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2400 0.80104 0.932 0.064 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1411 0.78983 0.036 0.964 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.6308 0.09380 0.492 0.508 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4521 0.78938 0.180 0.816 0.004
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.3686 0.80199 0.140 0.860 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.7772 0.64527 0.172 0.676 0.152
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.2772 0.80466 0.080 0.916 0.004
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.2772 0.80466 0.080 0.916 0.004
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.2200 0.79611 0.940 0.056 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.5858 0.72256 0.240 0.740 0.020
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0237 0.76676 0.004 0.000 0.996
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.6585 0.70421 0.244 0.712 0.044
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.9083 0.31156 0.280 0.180 0.540
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.8765 0.55088 0.252 0.580 0.168
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.5244 0.74893 0.240 0.756 0.004
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.5012 0.78001 0.204 0.788 0.008
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.2711 0.80158 0.088 0.912 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.6955 0.14030 0.492 0.016 0.492
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1031 0.78410 0.024 0.976 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2537 0.79514 0.080 0.920 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.2448 0.79680 0.924 0.076 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0747 0.76765 0.016 0.984 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1964 0.79552 0.944 0.056 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.2165 0.79873 0.064 0.936 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0424 0.76455 0.008 0.000 0.992
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.2860 0.80444 0.084 0.912 0.004
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0237 0.76676 0.004 0.000 0.996
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.2959 0.80278 0.900 0.100 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0237 0.77854 0.004 0.996 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.7079 0.57201 0.176 0.104 0.720
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0237 0.76676 0.004 0.000 0.996
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.4618 0.79809 0.136 0.840 0.024
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.3295 0.80307 0.896 0.096 0.008
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0747 0.76765 0.016 0.984 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.9574 0.18959 0.292 0.232 0.476
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.2625 0.79968 0.916 0.084 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.2165 0.79779 0.064 0.936 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.5919 0.72570 0.260 0.724 0.016
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.5778 0.76096 0.200 0.768 0.032
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.7652 0.00365 0.512 0.444 0.044
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.9072 0.39049 0.532 0.168 0.300
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.6481 0.72382 0.224 0.728 0.048
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.3851 0.80380 0.136 0.860 0.004
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.2711 0.80383 0.912 0.088 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.3038 0.79995 0.896 0.104 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.4645 0.78163 0.176 0.816 0.008
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.6730 0.68035 0.284 0.680 0.036
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.7392 0.16933 0.468 0.032 0.500
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.2096 0.79570 0.944 0.052 0.004
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0424 0.76455 0.008 0.000 0.992
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.2625 0.79904 0.916 0.084 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0237 0.76676 0.004 0.000 0.996
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1289 0.78889 0.032 0.968 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.4261 0.79613 0.140 0.848 0.012
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.6742 0.71484 0.240 0.708 0.052
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.3573 0.80437 0.120 0.876 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0747 0.78047 0.016 0.984 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0237 0.76676 0.004 0.000 0.996
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.9405 0.17269 0.324 0.192 0.484
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.4861 0.78675 0.180 0.808 0.012
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.3459 0.80498 0.096 0.892 0.012
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.3618 0.80549 0.104 0.884 0.012
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.2796 0.80438 0.092 0.908 0.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.2711 0.80194 0.912 0.088 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0237 0.76676 0.004 0.000 0.996
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.2200 0.79611 0.940 0.056 0.004
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.8591 0.52436 0.300 0.572 0.128
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.7034 0.66516 0.284 0.668 0.048
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.2486 0.79868 0.932 0.060 0.008
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.3337 0.78848 0.908 0.060 0.032
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.6309 0.13417 0.496 0.504 0.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 1 0.5754 0.56839 0.700 0.296 0.004
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.5277 0.78100 0.180 0.796 0.024
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.5633 0.75669 0.208 0.768 0.024
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.6621 0.71782 0.228 0.720 0.052
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.0424 0.76455 0.008 0.000 0.992
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.4399 0.77641 0.188 0.812 0.000
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.4351 0.77944 0.828 0.168 0.004
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.2200 0.79896 0.940 0.056 0.004
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.7677 0.64911 0.252 0.656 0.092
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.6570 0.67747 0.292 0.680 0.028
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 1 0.5656 0.59889 0.712 0.284 0.004
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#> 0034ECFD-CA94-4615-94D2-E950A2B240ED 2 0.7187 0.69956 0.232 0.692 0.076
#> FBD43A48-C880-45FF-BB6A-08F922DE93B5 2 0.3755 0.80414 0.120 0.872 0.008
#> E5C1A89F-C3D9-4DC8-A35F-D2834B155843 2 0.3610 0.80561 0.096 0.888 0.016
#> 6A73B561-CF9C-49DD-8B8B-09036538CAA4 3 0.0237 0.76676 0.004 0.000 0.996
#> 795D478D-E1FE-49EB-92AD-8B1B145F944B 2 0.3966 0.79957 0.100 0.876 0.024
#> 6203B63E-6D3F-4399-B524-9573A9BD1E11 2 0.6267 0.29669 0.452 0.548 0.000
#> BDD03456-777B-4E94-8240-CD6B1D4EAC51 2 0.4749 0.78691 0.172 0.816 0.012
#> DE32121C-B7F5-4A94-9977-8F4B2D3BE976 2 0.4744 0.79547 0.136 0.836 0.028
#> 27C0EEBE-589F-41D9-8BF7-C7DA0ED87A3B 2 0.4842 0.75678 0.224 0.776 0.000
#> EE24DCB8-2927-42D4-AD8C-588EA01A64C7 2 0.8371 0.53581 0.292 0.592 0.116
#> A86D241D-FE25-40B7-A61C-B919D30FA545 2 0.9940 0.04872 0.308 0.388 0.304
#> 50A7A07E-B452-466D-97BF-978C4F9C47DA 2 0.7685 0.54249 0.344 0.596 0.060
#> 0E6AE036-64ED-4489-AE40-55F77089A890 2 0.5158 0.74703 0.232 0.764 0.004
#> BC9A5294-255F-47A4-8879-11C441093A3D 2 0.9928 0.05888 0.276 0.372 0.352
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.9645 0.05342 0.380 0.412 0.208
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 2 0.4974 0.74551 0.236 0.764 0.000
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 2 0.0747 0.76765 0.016 0.984 0.000
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 2 0.5216 0.69224 0.260 0.740 0.000
#> 3508F4B0-1ADA-4937-B924-424AC2596341 2 0.3966 0.80712 0.100 0.876 0.024
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 2 0.5147 0.77930 0.180 0.800 0.020
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 1 0.4521 0.75852 0.816 0.180 0.004
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.2796 0.79933 0.908 0.092 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.6267 0.29669 0.452 0.548 0.000
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.3918 0.78800 0.856 0.140 0.004
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 3 0.0237 0.76676 0.004 0.000 0.996
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.7562 0.68197 0.692 0.160 0.148
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.2711 0.79965 0.912 0.088 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.3340 0.80501 0.120 0.880 0.000
#> A5572139-03CA-4299-98B6-13A2945649D0 3 0.0237 0.76676 0.004 0.000 0.996
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.8543 0.53513 0.292 0.580 0.128
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.8512 0.51563 0.296 0.580 0.124
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.9227 0.38932 0.188 0.520 0.292
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.1989 0.79626 0.048 0.948 0.004
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.2682 0.80366 0.076 0.920 0.004
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.8825 0.50464 0.288 0.560 0.152
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 1 0.6410 0.21056 0.576 0.420 0.004
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.2796 0.79933 0.908 0.092 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.2711 0.79965 0.912 0.088 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0892 0.76514 0.020 0.980 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.5835 0.60057 0.340 0.660 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 3 0.9914 -0.08701 0.348 0.272 0.380
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.8192 0.57742 0.636 0.144 0.220
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.3619 0.79728 0.864 0.136 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0424 0.77659 0.008 0.992 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0237 0.76676 0.004 0.000 0.996
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 1 0.6225 0.18967 0.568 0.432 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.4682 0.75086 0.804 0.192 0.004
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 3 0.9989 -0.11773 0.336 0.312 0.352
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0237 0.76676 0.004 0.000 0.996
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.7357 0.59501 0.332 0.620 0.048
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.5503 0.76511 0.208 0.772 0.020
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.5560 0.56363 0.700 0.300 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0237 0.76676 0.004 0.000 0.996
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.4555 0.77402 0.200 0.800 0.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 1 0.9266 -0.05093 0.424 0.420 0.156
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.4045 0.79860 0.872 0.104 0.024
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.5896 0.68181 0.292 0.700 0.008
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.9274 0.19565 0.384 0.456 0.160
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.4805 0.78827 0.176 0.812 0.012
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.2200 0.79611 0.940 0.056 0.004
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.3340 0.80272 0.880 0.120 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.6881 0.62572 0.320 0.648 0.032
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.6126 0.71738 0.268 0.712 0.020
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.3816 0.79634 0.148 0.852 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.5024 0.76026 0.220 0.776 0.004
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0592 0.77008 0.012 0.988 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.2796 0.80415 0.092 0.908 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0237 0.76676 0.004 0.000 0.996
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.7824 0.52079 0.356 0.580 0.064
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.5529 0.67224 0.296 0.704 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0747 0.77282 0.016 0.984 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.3845 0.80252 0.116 0.872 0.012
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.3375 0.80681 0.100 0.892 0.008
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.1031 0.78527 0.024 0.976 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.8179 0.60665 0.640 0.152 0.208
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.5024 0.76538 0.220 0.776 0.004
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2590 0.80380 0.924 0.072 0.004
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0424 0.77659 0.008 0.992 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.2165 0.79376 0.064 0.936 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.7145 0.70662 0.236 0.692 0.072
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.2711 0.79965 0.912 0.088 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4702 0.77676 0.212 0.788 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.1753 0.79717 0.048 0.952 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.3618 0.80062 0.884 0.104 0.012
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0237 0.76676 0.004 0.000 0.996
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.5852 0.78252 0.152 0.788 0.060
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.7353 0.60945 0.316 0.632 0.052
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 1 0.6286 0.04082 0.536 0.464 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.6309 0.15322 0.496 0.504 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.2448 0.79680 0.924 0.076 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4452 0.75663 0.192 0.808 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0747 0.78047 0.016 0.984 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1163 0.78110 0.028 0.972 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 3 0.9270 0.27576 0.280 0.200 0.520
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0592 0.77008 0.012 0.988 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.7199 0.69578 0.704 0.204 0.092
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.5384 0.77464 0.188 0.788 0.024
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2772 0.80501 0.916 0.080 0.004
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.5178 0.66459 0.744 0.256 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0592 0.77008 0.012 0.988 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.2400 0.80018 0.932 0.064 0.004
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.6008 0.47625 0.664 0.332 0.004
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0592 0.77008 0.012 0.988 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.8087 0.46575 0.364 0.560 0.076
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0237 0.76676 0.004 0.000 0.996
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.5016 0.73165 0.240 0.760 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3038 0.80612 0.104 0.896 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0237 0.76676 0.004 0.000 0.996
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1643 0.79446 0.044 0.956 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4784 0.65949 0.200 0.796 0.004
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.6264 0.34870 0.616 0.380 0.004
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.7334 0.60219 0.328 0.624 0.048
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1289 0.78806 0.032 0.968 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0237 0.76676 0.004 0.000 0.996
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0237 0.76676 0.004 0.000 0.996
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.7392 0.16933 0.468 0.032 0.500
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.5158 0.68673 0.764 0.232 0.004
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0592 0.77901 0.012 0.988 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0424 0.76455 0.008 0.000 0.992
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3500 0.80327 0.116 0.880 0.004
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.5831 0.59075 0.708 0.284 0.008
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.3682 0.80567 0.116 0.876 0.008
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.9833 -0.00480 0.248 0.356 0.396
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.5223 0.78222 0.176 0.800 0.024
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0661 0.77811 0.008 0.988 0.004
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.3009 0.78507 0.920 0.052 0.028
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.9224 0.15412 0.160 0.360 0.480
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.3293 0.80471 0.088 0.900 0.012
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4099 0.80075 0.140 0.852 0.008
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.5754 0.66625 0.296 0.700 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5680 0.75803 0.212 0.764 0.024
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.8109 0.48168 0.352 0.568 0.080
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3619 0.79881 0.136 0.864 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.6622 0.59782 0.164 0.088 0.748
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.2796 0.80700 0.092 0.908 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.3619 0.79728 0.864 0.136 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1031 0.78527 0.024 0.976 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0237 0.76676 0.004 0.000 0.996
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2096 0.79570 0.944 0.052 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0237 0.76676 0.004 0.000 0.996
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4575 0.75368 0.812 0.184 0.004
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.1753 0.79391 0.048 0.952 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.6745 0.36717 0.428 0.560 0.012
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2774 0.80490 0.072 0.920 0.008
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.8836 0.39278 0.352 0.520 0.128
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3192 0.79975 0.112 0.888 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0237 0.76676 0.004 0.000 0.996
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.9641 0.19585 0.324 0.452 0.224
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.3752 0.79783 0.144 0.856 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2796 0.79933 0.908 0.092 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4934 0.79412 0.156 0.820 0.024
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3918 0.80357 0.120 0.868 0.012
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4062 0.78920 0.164 0.836 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.8962 0.47621 0.288 0.548 0.164
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3116 0.80321 0.108 0.892 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1753 0.79729 0.048 0.952 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5497 0.69179 0.292 0.708 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.9743 0.23698 0.440 0.312 0.248
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4172 0.78919 0.840 0.156 0.004
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.8332 0.52653 0.316 0.580 0.104
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.6232 0.74516 0.220 0.740 0.040
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.3340 0.80679 0.120 0.880 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0892 0.77563 0.020 0.980 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.2448 0.79680 0.924 0.076 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1411 0.78983 0.036 0.964 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.4351 0.77944 0.828 0.168 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.7333 0.55783 0.180 0.116 0.704
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0424 0.77972 0.008 0.992 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.9321 0.42629 0.224 0.520 0.256
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.3412 0.80167 0.876 0.124 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.7398 0.55349 0.180 0.120 0.700
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4122 0.76267 0.236 0.760 0.004 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.5147 -0.10759 0.536 0.460 0.004 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1722 0.80336 0.048 0.944 0.000 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4077 0.79576 0.184 0.800 0.012 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1174 0.76064 0.968 0.020 0.000 0.012
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2899 0.81362 0.112 0.880 0.004 0.004
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0927 0.79354 0.016 0.976 0.000 0.008
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0707 0.78079 0.000 0.980 0.000 0.020
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1940 0.81320 0.076 0.924 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.5552 0.73610 0.236 0.708 0.048 0.008
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0707 0.78079 0.000 0.980 0.000 0.020
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.7729 -0.06381 0.408 0.396 0.192 0.004
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.8175 -0.02458 0.336 0.296 0.360 0.008
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2480 0.81456 0.088 0.904 0.008 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2342 0.72971 0.912 0.008 0.000 0.080
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.7756 0.28071 0.340 0.448 0.208 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0779 0.78548 0.004 0.980 0.000 0.016
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.8111 0.05042 0.388 0.340 0.264 0.008
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3301 0.81415 0.088 0.880 0.020 0.012
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.8140 0.08943 0.288 0.316 0.388 0.008
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3401 0.80587 0.152 0.840 0.000 0.008
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.7627 0.42255 0.312 0.500 0.180 0.008
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.7945 0.10410 0.312 0.264 0.420 0.004
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3899 0.80908 0.108 0.840 0.052 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1474 0.77008 0.000 0.948 0.000 0.052
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.5153 0.75449 0.224 0.732 0.040 0.004
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0817 0.76064 0.976 0.024 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3102 0.81272 0.116 0.872 0.004 0.008
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0188 0.75214 0.996 0.000 0.000 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.7477 0.39190 0.324 0.500 0.172 0.004
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1938 0.80443 0.052 0.936 0.000 0.012
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3128 0.81403 0.128 0.864 0.004 0.004
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.6353 0.58462 0.676 0.128 0.188 0.008
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4770 0.71524 0.288 0.700 0.000 0.012
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.6524 0.64254 0.272 0.628 0.092 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.2021 0.80461 0.056 0.932 0.000 0.012
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3257 0.80188 0.152 0.844 0.004 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0967 0.75512 0.976 0.004 0.004 0.016
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4150 0.80528 0.120 0.824 0.056 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.3668 0.78701 0.188 0.808 0.000 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.4088 0.69657 0.808 0.172 0.012 0.008
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3528 0.78708 0.192 0.808 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0707 0.78079 0.000 0.980 0.000 0.020
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.8006 0.07642 0.308 0.288 0.400 0.004
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0469 0.75354 0.988 0.000 0.000 0.012
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2742 0.74207 0.900 0.024 0.000 0.076
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.7220 0.33101 0.288 0.144 0.560 0.008
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.7332 0.15078 0.140 0.372 0.484 0.004
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.7707 0.00436 0.428 0.396 0.168 0.008
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5943 0.50670 0.388 0.576 0.028 0.008
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5624 0.68367 0.280 0.668 0.052 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3707 0.80796 0.132 0.840 0.028 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1389 0.74071 0.952 0.000 0.000 0.048
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.7332 0.15078 0.140 0.372 0.484 0.004
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0188 0.75549 0.996 0.004 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.5151 -0.12593 0.532 0.464 0.004 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2021 0.80628 0.056 0.932 0.000 0.012
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.7837 0.34220 0.300 0.452 0.244 0.004
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.2342 0.73005 0.912 0.008 0.000 0.080
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.7142 0.38943 0.356 0.516 0.124 0.004
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.3810 0.67889 0.804 0.188 0.000 0.008
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4608 0.68608 0.304 0.692 0.000 0.004
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3366 0.81779 0.100 0.872 0.020 0.008
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.6648 0.48121 0.368 0.548 0.080 0.004
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.7800 0.22645 0.476 0.308 0.208 0.008
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.3161 0.81139 0.124 0.864 0.000 0.012
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0524 0.75707 0.988 0.008 0.000 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.8166 0.05017 0.360 0.288 0.344 0.008
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0657 0.75787 0.984 0.012 0.000 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1004 0.79797 0.024 0.972 0.000 0.004
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5294 0.18430 0.484 0.508 0.000 0.008
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.3808 0.80034 0.184 0.808 0.004 0.004
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.3142 0.81300 0.132 0.860 0.000 0.008
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6255 0.66918 0.164 0.680 0.152 0.004
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1978 0.81395 0.068 0.928 0.004 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.1978 0.81395 0.068 0.928 0.004 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.75379 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.4652 0.74383 0.220 0.756 0.020 0.004
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.5168 0.72035 0.248 0.712 0.040 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.7309 0.31692 0.296 0.164 0.536 0.004
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.7361 0.55541 0.272 0.552 0.168 0.008
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4400 0.75898 0.248 0.744 0.004 0.004
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4011 0.78889 0.208 0.784 0.008 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.2741 0.81114 0.096 0.892 0.000 0.012
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.5512 0.12606 0.488 0.016 0.496 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0657 0.79207 0.012 0.984 0.000 0.004
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1978 0.80440 0.068 0.928 0.000 0.004
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.1940 0.72783 0.924 0.000 0.000 0.076
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0817 0.77944 0.000 0.976 0.000 0.024
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1022 0.74491 0.968 0.000 0.000 0.032
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.2222 0.80909 0.060 0.924 0.000 0.016
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0188 0.62818 0.004 0.000 0.996 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.1978 0.81326 0.068 0.928 0.004 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.2742 0.74207 0.900 0.024 0.000 0.076
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0804 0.78812 0.008 0.980 0.000 0.012
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5713 0.49274 0.192 0.088 0.716 0.004
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3945 0.80668 0.144 0.828 0.024 0.004
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.1909 0.75878 0.940 0.048 0.004 0.008
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0921 0.78030 0.000 0.972 0.000 0.028
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.7738 0.21457 0.300 0.224 0.472 0.004
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.2197 0.72897 0.916 0.004 0.000 0.080
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.2222 0.80806 0.060 0.924 0.000 0.016
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.4804 0.72540 0.276 0.708 0.016 0.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.4680 0.77531 0.192 0.772 0.032 0.004
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.5971 -0.00693 0.532 0.428 0.040 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.7369 0.34645 0.540 0.156 0.296 0.008
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.5487 0.73727 0.228 0.716 0.048 0.008
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.2888 0.81406 0.124 0.872 0.004 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.2198 0.73750 0.920 0.008 0.000 0.072
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.2813 0.73531 0.896 0.024 0.000 0.080
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.3961 0.79363 0.172 0.812 0.008 0.008
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.5648 0.68893 0.284 0.672 0.036 0.008
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.5776 0.15851 0.468 0.028 0.504 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0376 0.75421 0.992 0.004 0.000 0.004
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0188 0.62818 0.004 0.000 0.996 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.2197 0.72777 0.916 0.004 0.000 0.080
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1151 0.79748 0.024 0.968 0.000 0.008
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.3854 0.80473 0.152 0.828 0.012 0.008
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.5343 0.72888 0.240 0.708 0.052 0.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.3113 0.81404 0.108 0.876 0.004 0.012
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.78745 0.000 1.000 0.000 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.7724 0.19834 0.316 0.192 0.484 0.008
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.4468 0.79175 0.196 0.780 0.012 0.012
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.2542 0.81438 0.084 0.904 0.012 0.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.2676 0.81512 0.092 0.896 0.012 0.000
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.1940 0.81320 0.076 0.924 0.000 0.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.2125 0.73221 0.920 0.004 0.000 0.076
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.63112 0.000 0.000 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0188 0.75549 0.996 0.004 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.7016 0.54678 0.308 0.560 0.128 0.004
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.5887 0.67681 0.284 0.660 0.048 0.008
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0967 0.75512 0.976 0.004 0.004 0.016
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.1624 0.74121 0.952 0.000 0.028 0.020
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 1 0.5404 -0.14925 0.512 0.476 0.000 0.012
#> AF27FD0A-108C-47D2-9F87-665BED408E99 1 0.4511 0.54388 0.724 0.268 0.000 0.008
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.4448 0.78928 0.188 0.784 0.024 0.004
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.4568 0.77139 0.200 0.772 0.024 0.004
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.5596 0.73158 0.232 0.708 0.052 0.008
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.0188 0.62818 0.004 0.000 0.996 0.000
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.3810 0.78969 0.188 0.804 0.000 0.008
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.2888 0.73860 0.872 0.124 0.000 0.004
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0524 0.75536 0.988 0.004 0.000 0.008
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.6287 0.66763 0.256 0.648 0.092 0.004
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.5544 0.68309 0.296 0.668 0.028 0.008
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 1 0.4313 0.56434 0.736 0.260 0.000 0.004
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.4635 0.77340 0.216 0.756 0.028 0.000
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.2124 0.80929 0.068 0.924 0.000 0.008
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.3617 0.81705 0.124 0.852 0.012 0.012
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.4954 0.76013 0.232 0.736 0.028 0.004
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.6582 0.62455 0.292 0.612 0.088 0.008
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 1 0.3249 0.72424 0.852 0.140 0.000 0.008
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 3 0.7163 0.35972 0.280 0.156 0.560 0.004
#> 38FCA0B0-4399-4061-99AA-B886F54CA0DB 1 0.7643 0.39564 0.520 0.224 0.248 0.008
#> C0DC6757-E0CD-4615-9543-A348500AAE84 2 0.1610 0.79650 0.032 0.952 0.000 0.016
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#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2469 0.81706 0.108 0.892 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0779 0.78548 0.004 0.980 0.000 0.016
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1940 0.72783 0.924 0.000 0.000 0.076
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1004 0.79797 0.024 0.972 0.000 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2888 0.73860 0.872 0.124 0.000 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5925 0.48735 0.196 0.100 0.700 0.004
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0937 0.78963 0.012 0.976 0.000 0.012
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.7551 0.46110 0.220 0.516 0.260 0.004
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2773 0.75220 0.900 0.072 0.000 0.028
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5981 0.48558 0.196 0.104 0.696 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4532 0.70131 0.044 0.752 0.004 0.192 0.008
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.5431 0.16529 0.048 0.448 0.000 0.500 0.004
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1443 0.75532 0.004 0.948 0.000 0.044 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4081 0.73500 0.032 0.784 0.012 0.172 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.4528 0.68534 0.680 0.012 0.000 0.296 0.012
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2741 0.75856 0.004 0.860 0.000 0.132 0.004
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1124 0.74553 0.000 0.960 0.000 0.036 0.004
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.70249 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1502 0.71959 0.000 0.940 0.000 0.056 0.004
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0162 0.70191 0.000 0.000 0.996 0.004 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2068 0.76111 0.000 0.904 0.000 0.092 0.004
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4993 0.65257 0.020 0.708 0.048 0.224 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1502 0.72016 0.000 0.940 0.000 0.056 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6622 0.35862 0.008 0.368 0.148 0.472 0.004
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.7524 -0.44801 0.028 0.272 0.352 0.344 0.004
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2362 0.76434 0.008 0.900 0.008 0.084 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0671 0.73538 0.980 0.004 0.000 0.016 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.7206 -0.12904 0.024 0.436 0.196 0.340 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.1571 0.72800 0.000 0.936 0.000 0.060 0.004
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.7259 0.47243 0.016 0.308 0.264 0.408 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3463 0.75548 0.016 0.836 0.020 0.128 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.7521 -0.39267 0.028 0.280 0.372 0.316 0.004
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3142 0.75400 0.032 0.856 0.000 0.108 0.004
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.6874 0.10860 0.016 0.492 0.176 0.312 0.004
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.6993 0.36443 0.008 0.224 0.336 0.428 0.004
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3590 0.75268 0.008 0.828 0.036 0.128 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2437 0.69660 0.004 0.904 0.000 0.060 0.032
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.4950 0.67333 0.020 0.720 0.032 0.220 0.008
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.4564 0.68579 0.612 0.016 0.000 0.372 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.2911 0.75618 0.008 0.852 0.000 0.136 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.3816 0.75191 0.696 0.000 0.000 0.304 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6660 0.04207 0.012 0.488 0.144 0.352 0.004
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.1788 0.75384 0.008 0.932 0.000 0.056 0.004
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.2953 0.76337 0.028 0.868 0.000 0.100 0.004
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.6145 0.56318 0.072 0.092 0.176 0.660 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4918 0.64609 0.060 0.704 0.000 0.228 0.008
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.5798 0.49212 0.016 0.612 0.084 0.288 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1591 0.75502 0.004 0.940 0.000 0.052 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3048 0.74046 0.000 0.820 0.000 0.176 0.004
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.4102 0.75348 0.692 0.004 0.004 0.300 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3976 0.74763 0.016 0.812 0.048 0.124 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.3838 0.72971 0.044 0.804 0.000 0.148 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.4720 0.59291 0.104 0.136 0.008 0.752 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0162 0.70191 0.000 0.000 0.996 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4002 0.72983 0.044 0.796 0.000 0.152 0.008
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1357 0.72472 0.000 0.948 0.000 0.048 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.6925 0.40053 0.004 0.248 0.308 0.436 0.004
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.3305 0.77098 0.776 0.000 0.000 0.224 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.3044 0.72230 0.840 0.008 0.000 0.148 0.004
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.6729 0.07749 0.040 0.124 0.536 0.300 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.8020 -0.24039 0.032 0.352 0.404 0.160 0.052
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.7216 0.41880 0.036 0.368 0.156 0.436 0.004
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5094 0.32270 0.024 0.556 0.008 0.412 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5358 0.59423 0.024 0.660 0.048 0.268 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3753 0.75475 0.024 0.832 0.024 0.116 0.004
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.70249 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1608 0.75737 0.928 0.000 0.000 0.072 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.8039 -0.23447 0.032 0.348 0.404 0.164 0.052
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.4182 0.72857 0.644 0.004 0.000 0.352 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.5431 0.16486 0.048 0.448 0.000 0.500 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1768 0.75964 0.000 0.924 0.000 0.072 0.004
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.7533 -0.04489 0.052 0.432 0.156 0.352 0.008
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1331 0.73890 0.952 0.008 0.000 0.040 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.6466 0.06492 0.012 0.496 0.116 0.372 0.004
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.5271 0.58230 0.168 0.152 0.000 0.680 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4932 0.59957 0.048 0.668 0.000 0.280 0.004
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2945 0.76637 0.020 0.880 0.012 0.084 0.004
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.5743 0.28334 0.008 0.532 0.068 0.392 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.7248 0.54212 0.036 0.276 0.196 0.488 0.004
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.2629 0.75606 0.000 0.860 0.000 0.136 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.4165 0.74471 0.672 0.008 0.000 0.320 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.7491 0.44486 0.028 0.256 0.340 0.372 0.004
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.4310 0.69003 0.604 0.004 0.000 0.392 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1041 0.74915 0.000 0.964 0.000 0.032 0.004
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5380 -0.08128 0.044 0.488 0.000 0.464 0.004
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.3606 0.74757 0.024 0.816 0.000 0.152 0.008
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2694 0.76192 0.004 0.864 0.000 0.128 0.004
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.5159 0.49643 0.000 0.644 0.072 0.284 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.2213 0.76491 0.008 0.912 0.004 0.072 0.004
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.2213 0.76491 0.008 0.912 0.004 0.072 0.004
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.3857 0.74961 0.688 0.000 0.000 0.312 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.4211 0.64998 0.004 0.728 0.008 0.252 0.008
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0162 0.70191 0.000 0.000 0.996 0.004 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4631 0.63274 0.004 0.704 0.040 0.252 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.6697 0.00776 0.012 0.140 0.440 0.404 0.004
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.6924 0.35027 0.048 0.548 0.164 0.240 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4514 0.70240 0.048 0.748 0.004 0.196 0.004
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4264 0.73191 0.024 0.768 0.008 0.192 0.008
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.2756 0.76074 0.024 0.880 0.000 0.092 0.004
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.7222 -0.04484 0.412 0.008 0.420 0.108 0.052
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0865 0.74454 0.000 0.972 0.000 0.024 0.004
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1983 0.75421 0.008 0.924 0.000 0.060 0.008
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0609 0.73626 0.980 0.000 0.000 0.020 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1697 0.71445 0.000 0.932 0.000 0.060 0.008
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.2813 0.77104 0.832 0.000 0.000 0.168 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1831 0.76075 0.000 0.920 0.000 0.076 0.004
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.1121 0.69057 0.000 0.000 0.956 0.044 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.2112 0.76651 0.004 0.908 0.000 0.084 0.004
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.1851 0.67379 0.000 0.000 0.912 0.088 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.3044 0.72230 0.840 0.008 0.000 0.148 0.004
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0794 0.73769 0.000 0.972 0.000 0.028 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5114 0.48735 0.012 0.088 0.712 0.188 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.70249 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3655 0.74709 0.012 0.828 0.024 0.132 0.004
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 4 0.4740 -0.46924 0.468 0.016 0.000 0.516 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1830 0.72038 0.000 0.924 0.000 0.068 0.008
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.7231 -0.19325 0.036 0.208 0.460 0.296 0.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0794 0.74132 0.972 0.000 0.000 0.028 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.1991 0.76017 0.004 0.916 0.000 0.076 0.004
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.5257 0.65213 0.048 0.692 0.016 0.236 0.008
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.4240 0.69970 0.004 0.756 0.028 0.208 0.004
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.6278 0.24461 0.048 0.416 0.040 0.492 0.004
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.6882 0.46201 0.040 0.128 0.292 0.536 0.004
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.4874 0.64473 0.016 0.704 0.040 0.240 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.2583 0.75990 0.000 0.864 0.000 0.132 0.004
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.2136 0.76579 0.904 0.008 0.000 0.088 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.1106 0.71873 0.964 0.012 0.000 0.024 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.3317 0.72795 0.000 0.804 0.004 0.188 0.004
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.5915 0.57290 0.056 0.624 0.028 0.284 0.008
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.7608 0.01762 0.384 0.024 0.424 0.116 0.052
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.3990 0.74796 0.688 0.004 0.000 0.308 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0290 0.70088 0.000 0.000 0.992 0.008 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0955 0.74198 0.968 0.004 0.000 0.028 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.70249 0.000 0.000 1.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1041 0.75002 0.000 0.964 0.000 0.032 0.004
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.3497 0.74690 0.020 0.828 0.012 0.140 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.5267 0.65047 0.032 0.704 0.044 0.216 0.004
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.2865 0.75748 0.008 0.856 0.000 0.132 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.1041 0.73899 0.000 0.964 0.000 0.032 0.004
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.2127 0.66432 0.000 0.000 0.892 0.108 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.7044 -0.17231 0.024 0.164 0.456 0.352 0.004
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.4025 0.72696 0.024 0.780 0.012 0.184 0.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.2672 0.76131 0.000 0.872 0.008 0.116 0.004
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.2722 0.76164 0.000 0.868 0.008 0.120 0.004
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.2068 0.76111 0.000 0.904 0.000 0.092 0.004
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0963 0.74661 0.964 0.000 0.000 0.036 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.2127 0.66432 0.000 0.000 0.892 0.108 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.4047 0.74342 0.676 0.004 0.000 0.320 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.6321 0.34254 0.028 0.544 0.092 0.336 0.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.5748 0.56088 0.044 0.636 0.048 0.272 0.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.4181 0.74784 0.676 0.004 0.004 0.316 0.000
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#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.5032 0.63655 0.076 0.228 0.000 0.692 0.004
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2597 0.76133 0.000 0.872 0.004 0.120 0.004
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.7274 0.39524 0.012 0.320 0.312 0.352 0.004
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.4056 0.72664 0.012 0.784 0.020 0.180 0.004
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1502 0.73842 0.000 0.940 0.004 0.056 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4445 0.73768 0.676 0.000 0.024 0.300 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.8039 -0.23447 0.032 0.348 0.404 0.164 0.052
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.2462 0.76460 0.008 0.900 0.008 0.080 0.004
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3239 0.75159 0.012 0.828 0.004 0.156 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4650 0.58043 0.032 0.684 0.000 0.280 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.4421 0.70205 0.020 0.748 0.024 0.208 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.5628 0.34365 0.004 0.556 0.072 0.368 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2982 0.75609 0.020 0.860 0.000 0.116 0.004
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4761 0.52629 0.008 0.080 0.740 0.172 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.2629 0.76782 0.012 0.880 0.000 0.104 0.004
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.4996 0.59560 0.704 0.060 0.000 0.224 0.012
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1571 0.74137 0.000 0.936 0.000 0.060 0.004
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0162 0.70191 0.000 0.000 0.996 0.004 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.3796 0.75348 0.700 0.000 0.000 0.300 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0162 0.70191 0.000 0.000 0.996 0.004 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.4886 0.51236 0.188 0.100 0.000 0.712 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.1365 0.75410 0.004 0.952 0.000 0.040 0.004
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4867 0.22886 0.024 0.544 0.000 0.432 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2396 0.76767 0.004 0.900 0.008 0.084 0.004
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6100 0.16651 0.016 0.496 0.080 0.408 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2756 0.75742 0.024 0.880 0.000 0.092 0.004
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0290 0.70015 0.000 0.000 0.992 0.008 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.7112 -0.25512 0.016 0.420 0.204 0.356 0.004
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2972 0.75640 0.024 0.864 0.000 0.108 0.004
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0451 0.71982 0.988 0.004 0.000 0.008 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4167 0.73931 0.032 0.792 0.024 0.152 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.2798 0.75819 0.000 0.852 0.008 0.140 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3387 0.74683 0.024 0.836 0.000 0.132 0.008
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.6790 0.24636 0.028 0.520 0.160 0.292 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2886 0.76303 0.016 0.864 0.000 0.116 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1197 0.75766 0.000 0.952 0.000 0.048 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5101 0.61256 0.060 0.676 0.000 0.256 0.008
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.7325 0.53087 0.028 0.276 0.240 0.452 0.004
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.5948 0.33284 0.572 0.092 0.000 0.324 0.012
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.6195 0.36576 0.028 0.552 0.080 0.340 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5058 0.67249 0.028 0.720 0.040 0.208 0.004
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2597 0.76629 0.004 0.872 0.000 0.120 0.004
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1571 0.72800 0.000 0.936 0.000 0.060 0.004
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0794 0.73975 0.972 0.000 0.000 0.028 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0955 0.74939 0.000 0.968 0.000 0.028 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.6065 0.28302 0.564 0.104 0.000 0.320 0.012
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5296 0.46048 0.012 0.100 0.696 0.192 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0865 0.74207 0.000 0.972 0.000 0.024 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6786 0.14147 0.016 0.500 0.200 0.284 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.5197 0.58201 0.684 0.068 0.000 0.236 0.012
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5328 0.45670 0.012 0.100 0.692 0.196 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4448 0.698137 0.032 0.748 0.004 0.176 0.004 0.036
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.5400 0.203147 0.032 0.424 0.000 0.496 0.000 0.048
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1793 0.747650 0.004 0.928 0.000 0.032 0.000 0.036
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3956 0.730245 0.028 0.784 0.008 0.156 0.000 0.024
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.5480 0.493069 0.592 0.012 0.000 0.296 0.008 0.092
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2911 0.748184 0.000 0.832 0.000 0.144 0.000 0.024
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1408 0.742460 0.000 0.944 0.000 0.020 0.000 0.036
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0146 0.754932 0.000 0.000 0.996 0.000 0.000 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1895 0.710248 0.000 0.912 0.000 0.016 0.000 0.072
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0547 0.750237 0.000 0.000 0.980 0.000 0.000 0.020
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2277 0.754384 0.000 0.892 0.000 0.076 0.000 0.032
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4763 0.644825 0.016 0.704 0.040 0.220 0.000 0.020
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2112 0.700901 0.000 0.896 0.000 0.016 0.000 0.088
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6722 0.380027 0.000 0.332 0.120 0.452 0.000 0.096
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.7000 0.402157 0.000 0.248 0.320 0.368 0.000 0.064
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2458 0.758925 0.008 0.888 0.004 0.084 0.000 0.016
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0891 0.685296 0.968 0.000 0.000 0.008 0.000 0.024
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.6909 -0.154481 0.008 0.404 0.164 0.364 0.000 0.060
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.1807 0.718706 0.000 0.920 0.000 0.020 0.000 0.060
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.6809 0.446117 0.000 0.276 0.236 0.432 0.000 0.056
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3606 0.745716 0.012 0.832 0.020 0.084 0.000 0.052
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.7148 0.364396 0.000 0.248 0.336 0.336 0.000 0.080
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3350 0.747292 0.032 0.836 0.000 0.100 0.000 0.032
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.6542 0.112071 0.008 0.476 0.152 0.324 0.000 0.040
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.7532 0.351110 0.000 0.204 0.256 0.360 0.000 0.180
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3402 0.751183 0.008 0.836 0.016 0.104 0.000 0.036
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3050 0.670966 0.004 0.856 0.000 0.016 0.028 0.096
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.4836 0.662121 0.012 0.704 0.028 0.212 0.000 0.044
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.5071 0.612055 0.564 0.004 0.000 0.356 0.000 0.076
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3062 0.740333 0.000 0.816 0.000 0.160 0.000 0.024
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.4585 0.669142 0.648 0.000 0.000 0.284 0.000 0.068
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6661 -0.008964 0.000 0.456 0.132 0.332 0.000 0.080
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2240 0.744803 0.008 0.904 0.000 0.032 0.000 0.056
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3200 0.755296 0.020 0.844 0.000 0.108 0.004 0.024
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.5457 0.392910 0.012 0.068 0.144 0.692 0.000 0.084
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4902 0.629442 0.040 0.684 0.000 0.232 0.004 0.040
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.5738 0.469658 0.008 0.596 0.076 0.280 0.000 0.040
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1938 0.749460 0.004 0.920 0.000 0.040 0.000 0.036
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3247 0.726987 0.000 0.808 0.000 0.156 0.000 0.036
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.4718 0.669238 0.632 0.000 0.000 0.292 0.000 0.076
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3947 0.745241 0.012 0.804 0.028 0.116 0.000 0.040
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.3815 0.717090 0.036 0.792 0.000 0.144 0.000 0.028
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.4317 0.414352 0.032 0.096 0.004 0.776 0.000 0.092
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0547 0.750237 0.000 0.000 0.980 0.000 0.000 0.020
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3999 0.715310 0.032 0.776 0.000 0.156 0.000 0.036
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1858 0.711606 0.000 0.912 0.000 0.012 0.000 0.076
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.7575 0.353448 0.000 0.228 0.220 0.356 0.000 0.196
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.3848 0.702327 0.736 0.000 0.000 0.224 0.000 0.040
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.3845 0.612617 0.768 0.004 0.000 0.172 0.000 0.056
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.6889 0.067261 0.004 0.104 0.472 0.292 0.000 0.128
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 6 0.7273 0.066921 0.012 0.348 0.076 0.104 0.024 0.436
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.6569 0.451345 0.000 0.320 0.140 0.472 0.000 0.068
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5055 0.296927 0.008 0.540 0.004 0.400 0.000 0.048
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5273 0.588904 0.012 0.652 0.048 0.252 0.000 0.036
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3692 0.744307 0.020 0.824 0.020 0.104 0.000 0.032
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.755093 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1584 0.706705 0.928 0.000 0.000 0.064 0.000 0.008
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 6 0.7267 0.078318 0.012 0.344 0.076 0.104 0.024 0.440
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.4823 0.637621 0.584 0.000 0.000 0.348 0.000 0.068
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.5396 0.213877 0.032 0.420 0.000 0.500 0.000 0.048
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2250 0.754242 0.000 0.896 0.000 0.064 0.000 0.040
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.7680 0.000721 0.048 0.424 0.080 0.260 0.000 0.188
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1777 0.685899 0.928 0.004 0.000 0.044 0.000 0.024
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.6208 0.012333 0.000 0.468 0.104 0.376 0.000 0.052
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.4957 0.414391 0.096 0.100 0.000 0.736 0.008 0.060
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.5119 0.561833 0.040 0.644 0.000 0.272 0.004 0.040
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2867 0.760045 0.016 0.872 0.004 0.076 0.000 0.032
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.5685 0.240789 0.000 0.504 0.060 0.392 0.000 0.044
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.6602 0.474704 0.004 0.224 0.176 0.528 0.000 0.068
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.2930 0.744705 0.000 0.840 0.000 0.124 0.000 0.036
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.4871 0.657811 0.616 0.004 0.000 0.308 0.000 0.072
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.6947 0.409329 0.000 0.220 0.308 0.404 0.000 0.068
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.5059 0.584602 0.528 0.000 0.000 0.392 0.000 0.080
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1257 0.743969 0.000 0.952 0.000 0.020 0.000 0.028
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5217 -0.116507 0.008 0.472 0.000 0.452 0.000 0.068
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.3697 0.744030 0.024 0.804 0.000 0.140 0.004 0.028
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2940 0.754731 0.004 0.848 0.000 0.112 0.000 0.036
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.5350 0.499164 0.000 0.636 0.016 0.200 0.000 0.148
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1951 0.758059 0.000 0.916 0.004 0.060 0.000 0.020
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.1951 0.758059 0.000 0.916 0.004 0.060 0.000 0.020
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.4587 0.666347 0.640 0.000 0.000 0.296 0.000 0.064
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.4418 0.632117 0.004 0.704 0.004 0.232 0.000 0.056
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0547 0.750237 0.000 0.000 0.980 0.000 0.000 0.020
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4657 0.619760 0.004 0.688 0.036 0.248 0.000 0.024
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.7739 -0.077444 0.012 0.132 0.324 0.296 0.000 0.236
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.6733 0.289534 0.024 0.516 0.152 0.264 0.000 0.044
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4676 0.686353 0.040 0.728 0.004 0.188 0.004 0.036
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4103 0.722029 0.012 0.752 0.004 0.192 0.000 0.040
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.3113 0.754493 0.024 0.856 0.000 0.072 0.000 0.048
#> F1099B84-FE2A-419C-9948-D0754C1AF902 6 0.6802 0.264168 0.352 0.004 0.072 0.076 0.024 0.472
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1498 0.743336 0.000 0.940 0.000 0.028 0.000 0.032
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2375 0.749766 0.008 0.896 0.000 0.060 0.000 0.036
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.1003 0.690888 0.964 0.000 0.000 0.020 0.000 0.016
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#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0146 0.754666 0.000 0.000 0.996 0.000 0.000 0.004
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.4033 0.716664 0.032 0.768 0.000 0.168 0.000 0.032
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.6433 0.326941 0.000 0.352 0.108 0.468 0.000 0.072
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.6508 0.318454 0.528 0.064 0.016 0.308 0.004 0.080
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.5259 0.532557 0.032 0.628 0.000 0.280 0.004 0.056
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.6617 0.196182 0.008 0.396 0.120 0.420 0.000 0.056
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.3462 0.727895 0.008 0.792 0.004 0.180 0.000 0.016
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#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.5452 0.414438 0.648 0.052 0.000 0.228 0.004 0.068
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.4675 0.517050 0.008 0.628 0.004 0.324 0.000 0.036
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4971 0.650479 0.032 0.684 0.012 0.232 0.000 0.040
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.3307 0.744907 0.012 0.828 0.000 0.120 0.000 0.040
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.4312 0.706053 0.036 0.756 0.004 0.168 0.000 0.036
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.1858 0.711606 0.000 0.912 0.000 0.012 0.000 0.076
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.2432 0.758824 0.008 0.888 0.000 0.080 0.000 0.024
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.755093 0.000 0.000 1.000 0.000 0.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.6100 0.311721 0.024 0.508 0.048 0.372 0.000 0.048
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#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.1895 0.716091 0.000 0.912 0.000 0.016 0.000 0.072
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#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.3127 0.759834 0.000 0.840 0.004 0.100 0.000 0.056
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.2009 0.732046 0.000 0.908 0.000 0.024 0.000 0.068
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.5930 0.375283 0.020 0.072 0.164 0.652 0.000 0.092
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#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.5071 0.612055 0.564 0.004 0.000 0.356 0.000 0.076
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#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.2744 0.734428 0.000 0.864 0.000 0.064 0.000 0.072
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#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0909 0.686785 0.968 0.000 0.000 0.012 0.000 0.020
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4088 0.706712 0.012 0.744 0.000 0.200 0.000 0.044
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#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 4 0.5377 -0.098530 0.268 0.020 0.004 0.620 0.000 0.088
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#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.4408 0.722423 0.020 0.768 0.036 0.144 0.000 0.032
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.5419 0.497461 0.016 0.604 0.044 0.308 0.000 0.028
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#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2599 0.727850 0.008 0.884 0.000 0.028 0.004 0.076
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 3 0.6675 -0.025778 0.000 0.140 0.468 0.312 0.000 0.080
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.1895 0.710248 0.000 0.912 0.000 0.016 0.000 0.072
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.5377 0.410915 0.024 0.108 0.056 0.712 0.000 0.100
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.4286 0.708847 0.020 0.760 0.020 0.172 0.000 0.028
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2436 0.709530 0.880 0.000 0.000 0.088 0.000 0.032
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 4 0.6716 0.229958 0.252 0.140 0.000 0.520 0.008 0.080
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1895 0.710248 0.000 0.912 0.000 0.016 0.000 0.072
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.2740 0.712761 0.852 0.000 0.000 0.120 0.000 0.028
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.4731 0.465216 0.016 0.232 0.000 0.684 0.000 0.068
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1594 0.721810 0.000 0.932 0.000 0.016 0.000 0.052
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.5566 0.292234 0.000 0.516 0.060 0.388 0.000 0.036
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.3695 0.603066 0.000 0.000 0.712 0.016 0.000 0.272
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4171 0.646327 0.008 0.716 0.000 0.236 0.000 0.040
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.2766 0.759462 0.012 0.868 0.000 0.092 0.000 0.028
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0260 0.754569 0.000 0.000 0.992 0.000 0.000 0.008
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.2240 0.744803 0.008 0.904 0.000 0.032 0.000 0.056
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 5 0.0935 0.987106 0.032 0.004 0.000 0.000 0.964 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.6124 0.404816 0.116 0.276 0.000 0.560 0.008 0.040
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.6104 0.372046 0.032 0.528 0.032 0.348 0.000 0.060
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1088 0.742953 0.000 0.960 0.000 0.016 0.000 0.024
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.3695 0.603066 0.000 0.000 0.712 0.016 0.000 0.272
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.755093 0.000 0.000 1.000 0.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 6 0.7185 0.286893 0.316 0.020 0.072 0.088 0.024 0.480
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.3980 0.428021 0.024 0.096 0.000 0.792 0.000 0.088
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.1124 0.736388 0.000 0.956 0.000 0.008 0.000 0.036
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0146 0.754608 0.000 0.000 0.996 0.004 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3040 0.755835 0.024 0.860 0.000 0.088 0.004 0.024
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4576 0.461348 0.012 0.192 0.000 0.712 0.000 0.084
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2867 0.751642 0.000 0.848 0.000 0.112 0.000 0.040
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.7846 -0.379714 0.008 0.312 0.204 0.268 0.000 0.208
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.4107 0.715915 0.008 0.768 0.016 0.168 0.000 0.040
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1909 0.731646 0.000 0.920 0.004 0.024 0.000 0.052
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.5096 0.652072 0.632 0.000 0.020 0.276 0.000 0.072
#> D021A258-8713-4383-9DCA-45E2F54A0411 6 0.7267 0.078318 0.012 0.344 0.076 0.104 0.024 0.440
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.2408 0.758026 0.008 0.896 0.004 0.068 0.000 0.024
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3043 0.747440 0.008 0.832 0.000 0.140 0.000 0.020
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4784 0.554387 0.028 0.660 0.000 0.272 0.000 0.040
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.4267 0.695985 0.016 0.744 0.020 0.200 0.000 0.020
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.5578 0.303523 0.000 0.524 0.068 0.376 0.000 0.032
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3245 0.748728 0.020 0.840 0.000 0.112 0.004 0.024
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4882 0.529331 0.000 0.064 0.708 0.180 0.000 0.048
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.2587 0.760453 0.004 0.868 0.000 0.108 0.000 0.020
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.5385 0.405671 0.664 0.056 0.000 0.208 0.004 0.068
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1926 0.734273 0.000 0.912 0.000 0.020 0.000 0.068
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0632 0.748842 0.000 0.000 0.976 0.000 0.000 0.024
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.4515 0.672727 0.656 0.000 0.000 0.280 0.000 0.064
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0632 0.748842 0.000 0.000 0.976 0.000 0.000 0.024
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.4556 0.372978 0.100 0.060 0.000 0.768 0.008 0.064
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.1844 0.751569 0.004 0.924 0.000 0.048 0.000 0.024
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4888 0.199395 0.004 0.536 0.000 0.408 0.000 0.052
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2350 0.761393 0.004 0.896 0.008 0.076 0.000 0.016
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6391 0.149751 0.012 0.476 0.060 0.372 0.000 0.080
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3014 0.750438 0.024 0.864 0.000 0.080 0.004 0.028
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0363 0.753573 0.000 0.000 0.988 0.000 0.000 0.012
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.6697 -0.274170 0.000 0.396 0.184 0.368 0.000 0.052
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.3140 0.749747 0.024 0.844 0.000 0.108 0.000 0.024
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0858 0.667583 0.968 0.000 0.000 0.004 0.000 0.028
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4189 0.733412 0.028 0.788 0.024 0.128 0.000 0.032
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3079 0.746839 0.000 0.836 0.008 0.128 0.000 0.028
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3566 0.736232 0.024 0.820 0.000 0.120 0.004 0.032
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.6315 0.224516 0.004 0.500 0.144 0.316 0.000 0.036
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2933 0.756608 0.016 0.860 0.000 0.092 0.000 0.032
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1225 0.751685 0.000 0.952 0.000 0.036 0.000 0.012
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5267 0.605440 0.056 0.660 0.000 0.236 0.008 0.040
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.6515 0.465048 0.000 0.236 0.220 0.496 0.000 0.048
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.6291 0.195799 0.524 0.072 0.000 0.320 0.008 0.076
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.5969 0.339417 0.012 0.532 0.064 0.348 0.000 0.044
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4907 0.658506 0.020 0.700 0.032 0.216 0.000 0.032
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2680 0.758462 0.004 0.856 0.000 0.124 0.000 0.016
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1807 0.718706 0.000 0.920 0.000 0.020 0.000 0.060
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1245 0.696669 0.952 0.000 0.000 0.032 0.000 0.016
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1176 0.743966 0.000 0.956 0.000 0.020 0.000 0.024
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.6407 0.166422 0.516 0.084 0.000 0.316 0.008 0.076
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5402 0.468647 0.000 0.076 0.656 0.208 0.000 0.060
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1265 0.735932 0.000 0.948 0.000 0.008 0.000 0.044
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.7081 0.162544 0.012 0.492 0.144 0.240 0.000 0.112
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.5640 0.399573 0.640 0.064 0.000 0.216 0.004 0.076
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5427 0.464221 0.000 0.076 0.652 0.212 0.000 0.060
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.510 0.861 0.905 0.3408 0.591 0.591
#> 3 3 0.747 0.882 0.924 0.4548 0.906 0.843
#> 4 4 0.753 0.849 0.919 0.3688 0.759 0.551
#> 5 5 0.643 0.546 0.726 0.1077 0.830 0.517
#> 6 6 0.657 0.613 0.732 0.0626 0.872 0.526
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9607 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.0000 0.9607 0.000 1.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9607 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9607 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.8608 0.8046 0.716 0.284
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9607 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9607 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.7528 0.7482 0.784 0.216
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9607 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.7528 0.7482 0.784 0.216
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9607 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9607 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9607 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9607 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0938 0.9452 0.012 0.988
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9607 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.8608 0.8046 0.716 0.284
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9607 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9607 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.9607 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9607 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.9775 0.4738 0.588 0.412
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9607 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0000 0.9607 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.1414 0.9366 0.020 0.980
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9607 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9607 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9607 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.8608 0.8046 0.716 0.284
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9607 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.8608 0.8046 0.716 0.284
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9607 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9607 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9607 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.9209 0.7010 0.664 0.336
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9607 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9607 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9607 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9607 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.8608 0.8046 0.716 0.284
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9607 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9607 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.8608 0.4397 0.284 0.716
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.7528 0.7482 0.784 0.216
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9607 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9607 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9607 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.8608 0.8046 0.716 0.284
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.8608 0.8046 0.716 0.284
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.7528 0.7482 0.784 0.216
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.0000 0.9607 0.000 1.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.9607 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9607 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9607 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9607 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.7528 0.7482 0.784 0.216
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.8608 0.8046 0.716 0.284
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.0000 0.9607 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.8608 0.8046 0.716 0.284
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0000 0.9607 0.000 1.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9607 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.0000 0.9607 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.8608 0.8046 0.716 0.284
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9607 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.6438 0.7030 0.164 0.836
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9607 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9607 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.9607 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.8327 0.4128 0.264 0.736
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9607 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.8608 0.8046 0.716 0.284
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.8813 0.2767 0.300 0.700
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.8608 0.8046 0.716 0.284
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9607 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.9607 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9607 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9607 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9607 0.000 1.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9607 0.000 1.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9607 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.8608 0.8046 0.716 0.284
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.9607 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.7528 0.7482 0.784 0.216
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9607 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.9522 0.5585 0.628 0.372
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9607 0.000 1.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9607 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9607 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9607 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.8608 0.8046 0.716 0.284
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9607 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9607 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.8608 0.8046 0.716 0.284
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9607 0.000 1.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.8608 0.8046 0.716 0.284
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9607 0.000 1.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.7528 0.7482 0.784 0.216
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.9607 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.7528 0.7482 0.784 0.216
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.8608 0.8046 0.716 0.284
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9607 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.7376 0.7473 0.792 0.208
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.7528 0.7482 0.784 0.216
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9607 0.000 1.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.8608 0.8046 0.716 0.284
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9607 0.000 1.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.8499 0.3745 0.276 0.724
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.8608 0.8046 0.716 0.284
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9607 0.000 1.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.0000 0.9607 0.000 1.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9607 0.000 1.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.0000 0.9607 0.000 1.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.9983 0.5375 0.524 0.476
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9607 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.9607 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.8608 0.8046 0.716 0.284
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.8608 0.8046 0.716 0.284
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9607 0.000 1.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0000 0.9607 0.000 1.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.5294 0.7748 0.120 0.880
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.8608 0.8046 0.716 0.284
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.7528 0.7482 0.784 0.216
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.8608 0.8046 0.716 0.284
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.7528 0.7482 0.784 0.216
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.9607 0.000 1.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9607 0.000 1.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0000 0.9607 0.000 1.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0000 0.9607 0.000 1.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.9607 0.000 1.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.7528 0.7482 0.784 0.216
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 1 0.7528 0.7482 0.784 0.216
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0000 0.9607 0.000 1.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0000 0.9607 0.000 1.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0000 0.9607 0.000 1.000
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0000 0.9607 0.000 1.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.8608 0.8046 0.716 0.284
#> B422FFF3-623B-419A-964E-046BAE3578B3 1 0.7528 0.7482 0.784 0.216
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.8608 0.8046 0.716 0.284
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.0000 0.9607 0.000 1.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.0000 0.9607 0.000 1.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.8608 0.8046 0.716 0.284
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.8608 0.8046 0.716 0.284
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.0000 0.9607 0.000 1.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.0000 0.9607 0.000 1.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0000 0.9607 0.000 1.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0000 0.9607 0.000 1.000
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.0000 0.9607 0.000 1.000
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 1 0.7528 0.7482 0.784 0.216
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.0672 0.9508 0.008 0.992
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 2 0.8327 0.4248 0.264 0.736
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.8608 0.8046 0.716 0.284
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.0000 0.9607 0.000 1.000
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0000 0.9607 0.000 1.000
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.0000 0.9607 0.000 1.000
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.0000 0.9607 0.000 1.000
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.0000 0.9607 0.000 1.000
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.0000 0.9607 0.000 1.000
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.0000 0.9607 0.000 1.000
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.0000 0.9607 0.000 1.000
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 2 0.9248 0.2743 0.340 0.660
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 1 0.7528 0.7482 0.784 0.216
#> 38FCA0B0-4399-4061-99AA-B886F54CA0DB 2 0.9993 -0.4559 0.484 0.516
#> C0DC6757-E0CD-4615-9543-A348500AAE84 2 0.0000 0.9607 0.000 1.000
#> 84B05220-4E28-44AE-B6EE-6018C0DBF0D2 2 0.0000 0.9607 0.000 1.000
#> AE8D8D83-D457-4164-861E-9329DB223561 1 0.7528 0.7482 0.784 0.216
#> 85853AF3-27B0-49E0-9E71-478019AE1FA6 2 0.0000 0.9607 0.000 1.000
#> D1B716E8-E4D4-4089-B46A-9892A8BE55F5 1 0.8608 0.8046 0.716 0.284
#> 4B1A0809-0B28-4993-893D-1B7EF099DE91 2 0.0000 0.9607 0.000 1.000
#> 842F6668-669F-4E7D-89F6-F6DA627297B8 1 0.8608 0.8046 0.716 0.284
#> B6E47B05-AFE9-41B5-B040-7FBCC62D4720 1 0.8608 0.8046 0.716 0.284
#> E43DADE2-3A54-4FC5-A94A-70752288DE94 2 0.0000 0.9607 0.000 1.000
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#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.9607 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9607 0.000 1.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0000 0.9607 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0000 0.9607 0.000 1.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.8608 0.8046 0.716 0.284
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.8608 0.8046 0.716 0.284
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9607 0.000 1.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0000 0.9607 0.000 1.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.9909 -0.3211 0.444 0.556
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.9170 0.7592 0.668 0.332
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.8608 0.8046 0.716 0.284
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9607 0.000 1.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.7528 0.7482 0.784 0.216
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0000 0.9607 0.000 1.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.6887 0.6642 0.184 0.816
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0376 0.9557 0.004 0.996
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.7528 0.7482 0.784 0.216
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.4022 0.8449 0.080 0.920
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9607 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 2 0.6801 0.6721 0.180 0.820
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.7528 0.7482 0.784 0.216
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.9607 0.000 1.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.9607 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.8608 0.8046 0.716 0.284
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.9607 0.000 1.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.9607 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9607 0.000 1.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.8608 0.8046 0.716 0.284
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.8608 0.8046 0.716 0.284
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0000 0.9607 0.000 1.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9607 0.000 1.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9607 0.000 1.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.9607 0.000 1.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9607 0.000 1.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9607 0.000 1.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.7528 0.7482 0.784 0.216
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9607 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.9607 0.000 1.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9607 0.000 1.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9607 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9607 0.000 1.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9607 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.9977 0.5448 0.528 0.472
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9607 0.000 1.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.8608 0.8046 0.716 0.284
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9607 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9607 0.000 1.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.9607 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.8608 0.8046 0.716 0.284
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9607 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9607 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.8608 0.8046 0.716 0.284
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.7528 0.7482 0.784 0.216
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9607 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9607 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9607 0.000 1.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.0000 0.9607 0.000 1.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.8608 0.8046 0.716 0.284
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9607 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9607 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9607 0.000 1.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9607 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9607 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.9323 0.0741 0.348 0.652
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9607 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.8608 0.8046 0.716 0.284
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.6973 0.6562 0.188 0.812
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9607 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.8608 0.8046 0.716 0.284
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9607 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9607 0.000 1.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9607 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.7528 0.7482 0.784 0.216
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9607 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9607 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.7528 0.7482 0.784 0.216
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9607 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9607 0.000 1.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.9607 0.000 1.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9607 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9607 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.7528 0.7482 0.784 0.216
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.7528 0.7482 0.784 0.216
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.9129 0.1663 0.328 0.672
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.6343 0.7106 0.160 0.840
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9607 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.7528 0.7482 0.784 0.216
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9607 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9607 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9607 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0000 0.9607 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9607 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9607 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.8555 0.8036 0.720 0.280
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.9607 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9607 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9607 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9607 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9607 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9607 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9607 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.7528 0.7482 0.784 0.216
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9607 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.8608 0.8046 0.716 0.284
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9607 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.7528 0.7482 0.784 0.216
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.8608 0.8046 0.716 0.284
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.7528 0.7482 0.784 0.216
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.7299 0.6302 0.204 0.796
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9607 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9607 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9607 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.9607 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9607 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.7528 0.7482 0.784 0.216
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9607 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9607 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.8608 0.8046 0.716 0.284
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9607 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9607 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9607 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.0000 0.9607 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9607 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9607 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9607 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.9977 0.5448 0.528 0.472
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.8763 0.7904 0.704 0.296
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.9607 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9607 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9607 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9607 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.8608 0.8046 0.716 0.284
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9607 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.6048 0.7187 0.148 0.852
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.7528 0.7482 0.784 0.216
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9607 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9607 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.8608 0.8046 0.716 0.284
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 1.0000 -0.4964 0.500 0.500
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0237 0.944 0.000 0.996 0.004
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.2959 0.916 0.000 0.900 0.100
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0424 0.943 0.000 0.992 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0237 0.944 0.000 0.996 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0592 0.884 0.988 0.012 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.944 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0424 0.943 0.000 0.992 0.008
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.3941 0.884 0.156 0.000 0.844
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0424 0.943 0.000 0.992 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3941 0.884 0.156 0.000 0.844
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.944 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.2356 0.927 0.000 0.928 0.072
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0424 0.943 0.000 0.992 0.008
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.3816 0.893 0.000 0.852 0.148
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3879 0.891 0.000 0.848 0.152
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.944 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0592 0.884 0.988 0.012 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3816 0.893 0.000 0.852 0.148
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.2448 0.927 0.000 0.924 0.076
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.3816 0.893 0.000 0.852 0.148
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3412 0.907 0.000 0.876 0.124
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.0983 0.752 0.004 0.016 0.980
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0424 0.943 0.000 0.992 0.008
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.3816 0.893 0.000 0.852 0.148
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.4235 0.872 0.000 0.824 0.176
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0237 0.944 0.000 0.996 0.004
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0424 0.943 0.000 0.992 0.008
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.3412 0.907 0.000 0.876 0.124
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0592 0.884 0.988 0.012 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3038 0.916 0.000 0.896 0.104
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0592 0.884 0.988 0.012 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3752 0.896 0.000 0.856 0.144
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0424 0.943 0.000 0.992 0.008
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1289 0.939 0.000 0.968 0.032
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4834 0.517 0.004 0.204 0.792
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.944 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3752 0.895 0.000 0.856 0.144
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0424 0.943 0.000 0.992 0.008
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.944 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0592 0.884 0.988 0.012 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0892 0.942 0.000 0.980 0.020
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.944 0.000 1.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.9146 0.213 0.472 0.380 0.148
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#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.3941 0.884 0.156 0.000 0.844
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.3686 0.898 0.000 0.860 0.140
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.1289 0.939 0.000 0.968 0.032
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0424 0.943 0.000 0.992 0.008
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0424 0.944 0.000 0.992 0.008
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0424 0.943 0.000 0.992 0.008
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0424 0.943 0.000 0.992 0.008
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.6126 0.284 0.004 0.352 0.644
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0237 0.944 0.000 0.996 0.004
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0592 0.884 0.988 0.012 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0424 0.943 0.000 0.992 0.008
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0424 0.943 0.000 0.992 0.008
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.3686 0.897 0.000 0.860 0.140
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0592 0.884 0.988 0.012 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.1031 0.941 0.000 0.976 0.024
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.944 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0592 0.884 0.988 0.012 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.4121 0.881 0.168 0.000 0.832
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0237 0.944 0.000 0.996 0.004
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.3551 0.901 0.000 0.868 0.132
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0747 0.942 0.000 0.984 0.016
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.3459 0.914 0.012 0.892 0.096
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0592 0.884 0.988 0.012 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.1289 0.939 0.000 0.968 0.032
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0424 0.943 0.000 0.992 0.008
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0424 0.943 0.000 0.992 0.008
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.3879 0.891 0.000 0.848 0.152
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0424 0.943 0.000 0.992 0.008
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.3816 0.893 0.000 0.852 0.148
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0424 0.943 0.000 0.992 0.008
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0592 0.884 0.988 0.012 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.7250 0.355 0.572 0.396 0.032
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0424 0.943 0.000 0.992 0.008
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0592 0.884 0.988 0.012 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.1643 0.936 0.000 0.956 0.044
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0424 0.943 0.000 0.992 0.008
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.3267 0.908 0.000 0.884 0.116
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.4121 0.881 0.168 0.000 0.832
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0424 0.943 0.000 0.992 0.008
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0424 0.943 0.000 0.992 0.008
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.3941 0.884 0.156 0.000 0.844
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0424 0.943 0.000 0.992 0.008
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0424 0.943 0.000 0.992 0.008
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.2711 0.921 0.000 0.912 0.088
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1289 0.939 0.000 0.968 0.032
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.944 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.4121 0.881 0.168 0.000 0.832
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.3941 0.884 0.156 0.000 0.844
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.6527 0.330 0.588 0.404 0.008
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.8920 0.324 0.324 0.532 0.144
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0237 0.944 0.000 0.996 0.004
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3941 0.884 0.156 0.000 0.844
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0424 0.943 0.000 0.992 0.008
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.3816 0.893 0.000 0.852 0.148
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.944 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.3816 0.893 0.000 0.852 0.148
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.2878 0.920 0.000 0.904 0.096
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0237 0.944 0.000 0.996 0.004
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0661 0.877 0.988 0.008 0.004
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.2261 0.930 0.000 0.932 0.068
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.1529 0.937 0.000 0.960 0.040
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0424 0.943 0.000 0.992 0.008
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.3267 0.909 0.000 0.884 0.116
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.944 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3816 0.893 0.000 0.852 0.148
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0424 0.943 0.000 0.992 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.3941 0.884 0.156 0.000 0.844
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.1643 0.936 0.000 0.956 0.044
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0592 0.884 0.988 0.012 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0424 0.943 0.000 0.992 0.008
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.3941 0.884 0.156 0.000 0.844
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0592 0.884 0.988 0.012 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.3941 0.884 0.156 0.000 0.844
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.8561 0.318 0.528 0.368 0.104
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0424 0.943 0.000 0.992 0.008
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3267 0.907 0.000 0.884 0.116
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0237 0.944 0.000 0.996 0.004
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.3816 0.893 0.000 0.852 0.148
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.944 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.3941 0.884 0.156 0.000 0.844
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.3816 0.893 0.000 0.852 0.148
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0424 0.943 0.000 0.992 0.008
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0592 0.884 0.988 0.012 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0424 0.943 0.000 0.992 0.008
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0892 0.942 0.000 0.980 0.020
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.944 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.3816 0.893 0.000 0.852 0.148
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0237 0.944 0.000 0.996 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.944 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0747 0.942 0.000 0.984 0.016
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.6169 0.260 0.004 0.360 0.636
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.1905 0.849 0.956 0.016 0.028
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.3816 0.893 0.000 0.852 0.148
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.1753 0.935 0.000 0.952 0.048
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.1529 0.938 0.000 0.960 0.040
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0424 0.943 0.000 0.992 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0592 0.884 0.988 0.012 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0424 0.943 0.000 0.992 0.008
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.5292 0.689 0.228 0.764 0.008
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.3038 0.843 0.104 0.000 0.896
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0424 0.943 0.000 0.992 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.3752 0.896 0.000 0.856 0.144
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0592 0.884 0.988 0.012 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.7474 0.707 0.128 0.696 0.176
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2466 0.8747 0.000 0.900 0.004 0.096
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.3933 0.7585 0.004 0.196 0.004 0.796
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0524 0.9141 0.000 0.988 0.008 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0592 0.9140 0.000 0.984 0.000 0.016
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0188 0.9627 0.996 0.000 0.004 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0817 0.9124 0.000 0.976 0.000 0.024
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0817 0.9124 0.000 0.976 0.000 0.024
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4877 0.4388 0.000 0.408 0.000 0.592
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1302 0.8692 0.000 0.044 0.000 0.956
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0817 0.9124 0.000 0.976 0.000 0.024
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4989 0.1285 0.000 0.472 0.000 0.528
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3688 0.7462 0.000 0.208 0.000 0.792
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3710 0.6774 0.000 0.004 0.192 0.804
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0376 0.9146 0.000 0.992 0.004 0.004
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.1211 0.8685 0.000 0.040 0.000 0.960
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.2589 0.8461 0.000 0.884 0.000 0.116
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2868 0.8228 0.000 0.136 0.000 0.864
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4543 0.5477 0.000 0.324 0.000 0.676
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.1474 0.8701 0.000 0.052 0.000 0.948
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3266 0.8113 0.000 0.832 0.000 0.168
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1356 0.8411 0.000 0.008 0.032 0.960
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2334 0.8817 0.000 0.908 0.004 0.088
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1716 0.8647 0.000 0.064 0.000 0.936
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0921 0.9115 0.000 0.972 0.000 0.028
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.2647 0.8609 0.000 0.880 0.000 0.120
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1389 0.9037 0.000 0.952 0.000 0.048
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.4696 0.7506 0.136 0.064 0.004 0.796
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0707 0.9137 0.000 0.980 0.000 0.020
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1211 0.8685 0.000 0.040 0.000 0.960
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1557 0.9291 0.000 0.000 0.944 0.056
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.3649 0.7632 0.000 0.204 0.000 0.796
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.1118 0.8669 0.000 0.036 0.000 0.964
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.1302 0.8702 0.000 0.044 0.000 0.956
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4500 0.6446 0.000 0.316 0.000 0.684
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4040 0.6599 0.000 0.752 0.000 0.248
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.4804 0.4319 0.000 0.384 0.000 0.616
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.2999 0.8204 0.000 0.132 0.004 0.864
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0524 0.9141 0.000 0.988 0.008 0.004
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.3448 0.7734 0.000 0.168 0.004 0.828
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.1389 0.8706 0.000 0.048 0.000 0.952
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#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.2266 0.8843 0.000 0.912 0.004 0.084
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0336 0.9150 0.000 0.992 0.000 0.008
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.2469 0.8394 0.000 0.108 0.000 0.892
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.3208 0.8317 0.000 0.848 0.004 0.148
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.3219 0.7841 0.000 0.836 0.000 0.164
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0524 0.9144 0.000 0.988 0.008 0.004
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0336 0.9144 0.000 0.992 0.000 0.008
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.0921 0.8361 0.000 0.000 0.028 0.972
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.2401 0.8765 0.000 0.904 0.004 0.092
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0672 0.9136 0.000 0.984 0.008 0.008
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.1867 0.8613 0.000 0.072 0.000 0.928
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.2888 0.8517 0.000 0.872 0.004 0.124
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.1557 0.9006 0.000 0.944 0.000 0.056
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1388 0.9638 0.012 0.000 0.960 0.028
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.2530 0.8474 0.000 0.888 0.000 0.112
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.2647 0.8369 0.000 0.120 0.000 0.880
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.2831 0.8575 0.000 0.876 0.004 0.120
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 4 0.5976 0.6620 0.184 0.112 0.004 0.700
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.3208 0.8304 0.000 0.848 0.004 0.148
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0672 0.9136 0.000 0.984 0.008 0.008
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.1022 0.8658 0.000 0.032 0.000 0.968
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9147 0.000 1.000 0.000 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.7127 0.3699 0.560 0.288 0.004 0.148
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.5119 0.1844 0.000 0.556 0.004 0.440
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.3052 0.8216 0.000 0.136 0.004 0.860
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1388 0.9638 0.012 0.000 0.960 0.028
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0524 0.9141 0.000 0.988 0.008 0.004
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0469 0.9128 0.000 0.988 0.000 0.012
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0524 0.9141 0.000 0.988 0.008 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0804 0.9120 0.000 0.980 0.008 0.012
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.4252 0.6920 0.000 0.252 0.004 0.744
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.3208 0.8317 0.000 0.848 0.004 0.148
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0817 0.9124 0.000 0.976 0.000 0.024
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1388 0.9638 0.012 0.000 0.960 0.028
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.6565 0.4291 0.600 0.304 0.004 0.092
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.5504 0.6671 0.204 0.068 0.004 0.724
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0188 0.9150 0.000 0.996 0.000 0.004
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0188 0.9149 0.000 0.996 0.004 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.1302 0.8702 0.000 0.044 0.000 0.956
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.1004 0.9137 0.000 0.972 0.004 0.024
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.1389 0.8698 0.000 0.048 0.000 0.952
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4477 0.5766 0.000 0.312 0.000 0.688
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0336 0.9150 0.000 0.992 0.000 0.008
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.4790 0.4500 0.000 0.380 0.000 0.620
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.4643 0.4583 0.000 0.656 0.000 0.344
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9147 0.000 1.000 0.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.4428 0.6562 0.000 0.276 0.004 0.720
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1867 0.8914 0.000 0.928 0.000 0.072
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0927 0.9098 0.000 0.976 0.008 0.016
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4697 0.4721 0.000 0.644 0.000 0.356
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9147 0.000 1.000 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0524 0.9684 0.008 0.000 0.988 0.004
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0469 0.9710 0.012 0.000 0.988 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.6676 0.2498 0.404 0.076 0.004 0.516
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0469 0.9143 0.000 0.988 0.000 0.012
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.3610 0.7699 0.000 0.200 0.000 0.800
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0707 0.9131 0.000 0.980 0.000 0.020
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.1389 0.9035 0.000 0.952 0.000 0.048
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0524 0.9684 0.008 0.000 0.988 0.004
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1474 0.8697 0.000 0.052 0.000 0.948
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0804 0.9120 0.000 0.980 0.008 0.012
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0524 0.9142 0.000 0.988 0.004 0.008
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4072 0.6449 0.000 0.748 0.000 0.252
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0707 0.9137 0.000 0.980 0.000 0.020
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0707 0.9137 0.000 0.980 0.000 0.020
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0921 0.9115 0.000 0.972 0.000 0.028
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.2888 0.8541 0.000 0.872 0.004 0.124
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1174 0.8564 0.000 0.020 0.012 0.968
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0524 0.9553 0.988 0.000 0.004 0.008
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1389 0.8706 0.000 0.048 0.000 0.952
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4933 0.1565 0.000 0.568 0.000 0.432
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.4483 0.6579 0.000 0.712 0.004 0.284
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9662 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9147 0.000 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.7338 0.2118 0.152 0.512 0.004 0.332
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4456 0.6095 0.004 0.000 0.716 0.280
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1474 0.8694 0.000 0.052 0.000 0.948
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0188 0.9627 0.996 0.000 0.004 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.1443 0.8411 0.004 0.008 0.028 0.960
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.0451 0.4138 0.000 0.008 0.000 0.004 0.988
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.5452 0.2885 0.000 0.200 0.000 0.144 0.656
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4150 0.7355 0.000 0.612 0.000 0.000 0.388
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.5271 -0.4473 0.000 0.432 0.000 0.048 0.520
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2228 0.8952 0.908 0.012 0.000 0.004 0.076
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5114 0.5465 0.000 0.488 0.000 0.036 0.476
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4196 0.7438 0.000 0.640 0.000 0.004 0.356
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9659 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4101 0.7479 0.000 0.664 0.000 0.004 0.332
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.5557 0.4806 0.000 0.472 0.000 0.068 0.460
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.5980 0.3842 0.000 0.176 0.000 0.584 0.240
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4166 0.7492 0.000 0.648 0.000 0.004 0.348
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1768 0.8026 0.000 0.072 0.000 0.924 0.004
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0290 0.8232 0.000 0.008 0.000 0.992 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 5 0.5542 -0.4332 0.000 0.432 0.000 0.068 0.500
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0451 0.9599 0.988 0.008 0.000 0.004 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.1012 0.8258 0.000 0.020 0.000 0.968 0.012
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5984 0.3638 0.000 0.208 0.000 0.588 0.204
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0912 0.8253 0.000 0.016 0.000 0.972 0.012
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4194 0.6894 0.000 0.132 0.000 0.780 0.088
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2522 0.7552 0.000 0.012 0.108 0.880 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 5 0.3452 0.1371 0.000 0.244 0.000 0.000 0.756
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1018 0.8262 0.000 0.016 0.000 0.968 0.016
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0798 0.8231 0.000 0.016 0.000 0.976 0.008
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.6589 0.2960 0.000 0.424 0.000 0.212 0.364
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4196 0.7467 0.000 0.640 0.000 0.004 0.356
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3994 0.6786 0.000 0.040 0.000 0.772 0.188
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3231 0.8199 0.800 0.196 0.000 0.004 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.5296 0.5418 0.000 0.180 0.000 0.676 0.144
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0290 0.9604 0.992 0.008 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.0912 0.8252 0.000 0.016 0.000 0.972 0.012
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4264 0.7469 0.000 0.620 0.000 0.004 0.376
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 5 0.6166 -0.3543 0.000 0.340 0.000 0.148 0.512
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1831 0.7959 0.000 0.076 0.000 0.920 0.004
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.0162 0.4079 0.000 0.004 0.000 0.000 0.996
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0693 0.8247 0.000 0.012 0.000 0.980 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4251 0.7476 0.000 0.624 0.000 0.004 0.372
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.5405 0.5168 0.000 0.484 0.000 0.056 0.460
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0671 0.9588 0.980 0.016 0.000 0.004 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 5 0.6322 -0.3571 0.000 0.408 0.000 0.156 0.436
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 5 0.3929 0.0813 0.000 0.208 0.000 0.028 0.764
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.6454 -0.0105 0.000 0.208 0.000 0.304 0.488
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 5 0.3783 -0.0212 0.000 0.252 0.000 0.008 0.740
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4166 0.7492 0.000 0.648 0.000 0.004 0.348
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.0693 0.8224 0.000 0.008 0.000 0.980 0.012
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0404 0.9604 0.988 0.012 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0566 0.9591 0.984 0.012 0.000 0.004 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2280 0.8702 0.000 0.000 0.880 0.120 0.000
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#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 4 0.0912 0.8255 0.000 0.016 0.000 0.972 0.012
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 4 0.6174 0.3135 0.000 0.192 0.000 0.552 0.256
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 5 0.5504 -0.4631 0.000 0.448 0.000 0.064 0.488
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 5 0.5329 -0.4441 0.000 0.432 0.000 0.052 0.516
#> DCD932D2-B708-487A-93C1-8485FBE9048A 4 0.0798 0.8250 0.000 0.016 0.000 0.976 0.008
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 5 0.4786 0.1590 0.000 0.040 0.000 0.308 0.652
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0162 0.9603 0.996 0.004 0.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0162 0.9603 0.996 0.004 0.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.4074 0.7408 0.000 0.636 0.000 0.000 0.364
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 5 0.0404 0.4035 0.000 0.012 0.000 0.000 0.988
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.0566 0.8207 0.000 0.004 0.000 0.984 0.012
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.4465 0.6496 0.000 0.212 0.000 0.732 0.056
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0566 0.9591 0.984 0.012 0.000 0.004 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.4135 0.7500 0.000 0.656 0.000 0.004 0.340
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.1732 0.9433 0.000 0.080 0.920 0.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 5 0.1082 0.4046 0.000 0.028 0.000 0.008 0.964
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 5 0.6809 0.0779 0.020 0.212 0.000 0.252 0.516
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 4 0.0579 0.8184 0.000 0.008 0.000 0.984 0.008
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.1082 0.8220 0.000 0.008 0.000 0.964 0.028
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 5 0.6637 0.0429 0.000 0.252 0.000 0.300 0.448
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 5 0.4614 0.4030 0.060 0.156 0.000 0.020 0.764
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 5 0.3635 0.0290 0.000 0.248 0.000 0.004 0.748
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.1830 0.8008 0.000 0.068 0.000 0.924 0.008
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.3953 0.8063 0.780 0.188 0.000 0.008 0.024
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 5 0.1211 0.4104 0.000 0.024 0.000 0.016 0.960
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.1892 0.7985 0.000 0.080 0.000 0.916 0.004
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 5 0.5646 -0.4361 0.000 0.444 0.000 0.076 0.480
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0290 0.9604 0.992 0.008 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0671 0.9588 0.980 0.016 0.000 0.004 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 4 0.5047 0.5348 0.000 0.064 0.000 0.652 0.284
#> BF128355-3E49-449D-A503-00E678E90DF8 5 0.3684 -0.0878 0.000 0.280 0.000 0.000 0.720
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.4196 0.7438 0.000 0.640 0.000 0.004 0.356
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 5 0.0451 0.4089 0.000 0.008 0.000 0.004 0.988
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4135 0.7500 0.000 0.656 0.000 0.004 0.340
#> 44047435-3E87-473A-9231-B61FB0D5045B 5 0.4743 -0.5627 0.000 0.472 0.000 0.016 0.512
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.2208 0.8108 0.000 0.020 0.000 0.908 0.072
#> 59C375B4-60FB-4598-A146-5B175C2B8079 5 0.0912 0.4140 0.000 0.012 0.000 0.016 0.972
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4321 0.7172 0.000 0.600 0.000 0.004 0.396
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.6626 0.2840 0.000 0.424 0.000 0.224 0.352
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4118 0.7482 0.000 0.660 0.000 0.004 0.336
#> A65773C1-18D0-4F48-85E1-380338B66C7D 5 0.4905 -0.5167 0.000 0.476 0.000 0.024 0.500
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.3550 0.7109 0.000 0.184 0.000 0.796 0.020
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 5 0.0566 0.4022 0.000 0.012 0.000 0.004 0.984
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2629 0.8750 0.860 0.136 0.000 0.004 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.4118 0.7452 0.000 0.660 0.000 0.004 0.336
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4182 0.7487 0.000 0.644 0.000 0.004 0.352
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.1216 0.8273 0.000 0.020 0.000 0.960 0.020
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0451 0.9599 0.988 0.008 0.000 0.004 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 5 0.3430 0.1221 0.000 0.220 0.000 0.004 0.776
#> 2356B998-0930-403F-9B04-57A18A150955 5 0.6069 -0.3892 0.000 0.432 0.000 0.120 0.448
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.3663 0.7948 0.776 0.208 0.000 0.016 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.2448 0.9345 0.000 0.088 0.892 0.020 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 5 0.5409 -0.1491 0.000 0.304 0.000 0.084 0.612
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.4164 0.7102 0.000 0.096 0.000 0.784 0.120
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 5 0.0703 0.4003 0.000 0.024 0.000 0.000 0.976
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 5 0.5644 0.3055 0.012 0.208 0.000 0.120 0.660
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9609 1.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 5 0.3596 0.1776 0.000 0.212 0.000 0.012 0.776
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4402 0.7321 0.000 0.636 0.000 0.012 0.352
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4341 0.7244 0.000 0.592 0.000 0.004 0.404
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.1012 0.8246 0.000 0.020 0.000 0.968 0.012
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4066 0.7446 0.000 0.672 0.000 0.004 0.324
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.3724 0.7019 0.000 0.204 0.000 0.776 0.020
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 5 0.5236 -0.3759 0.000 0.408 0.000 0.048 0.544
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9609 1.000 0.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 5 0.3427 0.4055 0.104 0.032 0.000 0.016 0.848
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4084 0.7461 0.000 0.668 0.000 0.004 0.328
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0451 0.9599 0.988 0.008 0.000 0.004 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 5 0.5004 0.3659 0.000 0.216 0.000 0.092 0.692
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4288 0.7444 0.000 0.612 0.000 0.004 0.384
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.5313 0.4220 0.000 0.056 0.000 0.556 0.388
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2448 0.9345 0.000 0.088 0.892 0.020 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 5 0.3949 0.0169 0.000 0.332 0.000 0.000 0.668
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 5 0.3366 0.0683 0.000 0.232 0.000 0.000 0.768
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9659 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4126 0.7440 0.000 0.620 0.000 0.000 0.380
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4101 0.7301 0.000 0.628 0.000 0.000 0.372
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.5365 0.3010 0.000 0.204 0.000 0.132 0.664
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 5 0.3102 0.3740 0.000 0.084 0.000 0.056 0.860
#> 29635F4D-3149-49BC-B960-FF863D10F747 5 0.5456 -0.4804 0.000 0.456 0.000 0.060 0.484
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2448 0.9345 0.000 0.088 0.892 0.020 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.4780 0.2713 0.280 0.048 0.000 0.000 0.672
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.6808 0.0444 0.016 0.212 0.000 0.272 0.500
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5049 0.5238 0.000 0.484 0.000 0.032 0.484
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4430 0.6779 0.000 0.540 0.000 0.004 0.456
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4193 0.7055 0.000 0.212 0.000 0.748 0.040
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.5088 0.6503 0.000 0.528 0.000 0.036 0.436
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.2236 0.8033 0.000 0.024 0.000 0.908 0.068
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4708 0.6049 0.000 0.068 0.000 0.712 0.220
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 5 0.5223 -0.4710 0.000 0.444 0.000 0.044 0.512
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0290 0.9604 0.992 0.008 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.6206 0.3127 0.000 0.200 0.000 0.548 0.252
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.6779 -0.2296 0.000 0.332 0.000 0.384 0.284
#> F5F7B591-062D-4FF0-AB68-73D678574318 5 0.4648 -0.5027 0.000 0.464 0.000 0.012 0.524
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.6319 0.0709 0.000 0.204 0.000 0.272 0.524
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.1502 0.3654 0.000 0.056 0.000 0.004 0.940
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1216 0.8259 0.000 0.020 0.000 0.960 0.020
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 5 0.3177 0.2299 0.000 0.208 0.000 0.000 0.792
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.6719 -0.2611 0.000 0.248 0.000 0.380 0.372
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0740 0.9566 0.980 0.008 0.000 0.004 0.008
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4627 0.6370 0.000 0.544 0.000 0.012 0.444
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0290 0.9604 0.992 0.008 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.6111 0.3007 0.040 0.212 0.000 0.108 0.640
#> 3C032234-C350-4170-B8F7-F8DE8269E713 5 0.5114 -0.5101 0.000 0.472 0.000 0.036 0.492
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.4430 0.7156 0.000 0.172 0.000 0.752 0.076
#> 981123DE-D55E-41D1-8850-1A41376F1DED 5 0.5334 -0.4588 0.000 0.436 0.000 0.052 0.512
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0566 0.8241 0.000 0.012 0.000 0.984 0.004
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 5 0.4930 -0.4863 0.000 0.424 0.000 0.028 0.548
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0162 0.9662 0.000 0.000 0.996 0.004 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0992 0.8241 0.000 0.024 0.000 0.968 0.008
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 5 0.3895 0.0639 0.000 0.320 0.000 0.000 0.680
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0162 0.9603 0.996 0.004 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 5 0.4288 -0.3456 0.000 0.384 0.000 0.004 0.612
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.6733 0.2144 0.000 0.416 0.000 0.288 0.296
#> C3E23136-7190-4D08-991C-93AFACC48E8D 5 0.4815 -0.5381 0.000 0.456 0.000 0.020 0.524
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0798 0.8250 0.000 0.016 0.000 0.976 0.008
#> 534B9E41-B731-4461-ABEA-30096148A493 5 0.3916 -0.0277 0.000 0.256 0.000 0.012 0.732
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 5 0.5346 -0.4784 0.000 0.452 0.000 0.052 0.496
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.0566 0.4022 0.000 0.012 0.000 0.004 0.984
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1894 0.7942 0.000 0.072 0.000 0.920 0.008
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.5033 0.4566 0.568 0.028 0.000 0.004 0.400
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0798 0.8250 0.000 0.016 0.000 0.976 0.008
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.6671 -0.0436 0.000 0.236 0.000 0.412 0.352
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 5 0.6108 0.2159 0.000 0.208 0.000 0.224 0.568
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4135 0.7471 0.000 0.656 0.000 0.004 0.340
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9609 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4437 0.6246 0.000 0.532 0.000 0.004 0.464
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.4490 0.4070 0.004 0.168 0.000 0.072 0.756
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4455 0.2947 0.000 0.008 0.404 0.588 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4151 0.7513 0.000 0.652 0.000 0.004 0.344
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.3321 0.7416 0.000 0.032 0.000 0.832 0.136
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0854 0.9553 0.976 0.012 0.000 0.004 0.008
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0566 0.8158 0.000 0.012 0.000 0.984 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.4158 0.70864 0.000 0.028 0.000 0.012 0.708 0.252
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.1714 0.70076 0.000 0.024 0.000 0.016 0.936 0.024
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4406 0.84704 0.000 0.500 0.000 0.000 0.024 0.476
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 6 0.3220 0.55370 0.000 0.016 0.000 0.088 0.052 0.844
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3551 0.72086 0.772 0.036 0.000 0.000 0.192 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.2932 0.42467 0.000 0.140 0.000 0.020 0.004 0.836
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4080 0.88849 0.000 0.536 0.000 0.000 0.008 0.456
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.94750 0.000 0.000 1.000 0.000 0.000 0.000
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#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.5945 0.64327 0.216 0.060 0.000 0.000 0.600 0.124
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.3730 0.58279 0.000 0.192 0.000 0.032 0.768 0.008
#> 5324E01D-69F5-4979-903B-7644F3236EE0 6 0.1701 0.45558 0.000 0.072 0.000 0.008 0.000 0.920
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0260 0.94802 0.000 0.000 0.992 0.008 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 6 0.3534 -0.10573 0.000 0.276 0.000 0.000 0.008 0.716
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.6172 0.54272 0.000 0.152 0.000 0.552 0.248 0.048
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.3401 0.31325 0.000 0.204 0.000 0.016 0.004 0.776
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.2261 0.77822 0.000 0.004 0.000 0.884 0.008 0.104
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4211 0.16428 0.000 0.008 0.000 0.532 0.004 0.456
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 6 0.0767 0.52341 0.000 0.004 0.000 0.012 0.008 0.976
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2118 0.90190 0.888 0.104 0.000 0.000 0.008 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 6 0.4462 0.14837 0.000 0.016 0.000 0.436 0.008 0.540
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 6 0.3833 0.40226 0.000 0.000 0.000 0.344 0.008 0.648
#> F5F7B591-062D-4FF0-AB68-73D678574318 6 0.1780 0.54431 0.000 0.000 0.000 0.048 0.028 0.924
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.3641 0.65544 0.000 0.120 0.000 0.028 0.812 0.040
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.4523 0.56800 0.000 0.032 0.000 0.004 0.592 0.372
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1644 0.79795 0.000 0.000 0.000 0.920 0.004 0.076
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 5 0.5989 0.06787 0.000 0.320 0.000 0.000 0.432 0.248
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0363 0.94631 0.000 0.000 0.988 0.012 0.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 6 0.4506 0.35676 0.000 0.004 0.000 0.344 0.036 0.616
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.2058 0.87574 0.908 0.036 0.000 0.000 0.056 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 6 0.1410 0.48524 0.000 0.044 0.000 0.004 0.008 0.944
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0260 0.94802 0.000 0.000 0.992 0.008 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2311 0.89970 0.880 0.104 0.000 0.000 0.016 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0260 0.94802 0.000 0.000 0.992 0.008 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.2076 0.67511 0.000 0.060 0.000 0.016 0.912 0.012
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.1732 0.46659 0.000 0.072 0.000 0.004 0.004 0.920
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.6092 0.61641 0.000 0.112 0.000 0.604 0.100 0.184
#> 981123DE-D55E-41D1-8850-1A41376F1DED 6 0.0862 0.52322 0.000 0.008 0.000 0.016 0.004 0.972
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1536 0.81390 0.000 0.020 0.000 0.944 0.012 0.024
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 6 0.4348 0.42615 0.000 0.104 0.000 0.004 0.160 0.732
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0260 0.94802 0.000 0.000 0.992 0.008 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1341 0.81235 0.000 0.028 0.000 0.948 0.000 0.024
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.5760 0.49925 0.000 0.508 0.000 0.000 0.268 0.224
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0363 0.91080 0.988 0.012 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 6 0.6054 -0.22981 0.000 0.348 0.000 0.000 0.260 0.392
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 6 0.3426 0.51070 0.000 0.000 0.000 0.276 0.004 0.720
#> C3E23136-7190-4D08-991C-93AFACC48E8D 6 0.2622 0.42041 0.000 0.104 0.000 0.004 0.024 0.868
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0935 0.81154 0.000 0.000 0.000 0.964 0.004 0.032
#> 534B9E41-B731-4461-ABEA-30096148A493 6 0.4524 0.24410 0.000 0.052 0.000 0.000 0.320 0.628
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 6 0.1418 0.52303 0.000 0.024 0.000 0.032 0.000 0.944
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.4110 0.69880 0.000 0.040 0.000 0.000 0.692 0.268
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2984 0.76684 0.000 0.104 0.000 0.848 0.044 0.004
#> D182D919-C57F-4004-93DB-FB1723A82072 5 0.4740 0.41801 0.300 0.064 0.000 0.000 0.632 0.004
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1003 0.81299 0.000 0.004 0.000 0.964 0.004 0.028
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 6 0.4868 0.37859 0.000 0.000 0.000 0.332 0.076 0.592
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.6549 0.15816 0.000 0.040 0.000 0.220 0.276 0.464
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 6 0.3659 -0.50391 0.000 0.364 0.000 0.000 0.000 0.636
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.91277 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.2362 0.34417 0.000 0.136 0.000 0.000 0.004 0.860
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.3194 0.72806 0.000 0.020 0.000 0.004 0.808 0.168
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.3956 0.57694 0.000 0.032 0.264 0.704 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3868 0.86307 0.000 0.508 0.000 0.000 0.000 0.492
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4490 0.39879 0.000 0.004 0.000 0.604 0.032 0.360
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1723 0.89465 0.928 0.036 0.000 0.000 0.036 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.1265 0.80546 0.000 0.044 0.000 0.948 0.008 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.875 0.916 0.966 0.4806 0.523 0.523
#> 3 3 0.887 0.919 0.967 0.2935 0.773 0.598
#> 4 4 0.786 0.797 0.907 0.1816 0.816 0.554
#> 5 5 0.769 0.758 0.877 0.0741 0.881 0.598
#> 6 6 0.753 0.719 0.826 0.0462 0.930 0.691
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9603 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.7139 0.7511 0.196 0.804
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9603 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9603 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9687 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9603 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9603 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9687 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9603 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9687 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9603 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9603 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9603 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.9732 0.3439 0.404 0.596
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.1184 0.9549 0.984 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9603 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9687 1.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.2423 0.9260 0.040 0.960
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.2603 0.9217 0.044 0.956
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.7056 0.7535 0.808 0.192
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9603 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.0000 0.9687 1.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9603 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.9608 0.3970 0.384 0.616
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.0000 0.9687 1.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9603 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9603 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9603 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9687 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9603 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9687 1.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9603 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9603 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9603 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.0000 0.9687 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9603 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.9552 0.4170 0.376 0.624
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9603 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9603 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9687 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9603 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9603 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.7139 0.7478 0.804 0.196
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.9687 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9603 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9603 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.9686 0.3353 0.604 0.396
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9687 1.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9687 1.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.9687 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.9710 0.3553 0.400 0.600
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.9044 0.5275 0.680 0.320
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.9286 0.4917 0.344 0.656
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9603 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9603 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.9687 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9687 1.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.5178 0.8495 0.116 0.884
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9687 1.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5408 0.8411 0.124 0.876
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9603 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.8267 0.6532 0.260 0.740
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9687 1.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.9129 0.5255 0.328 0.672
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7815 0.7004 0.232 0.768
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#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9687 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9603 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.9358 0.4738 0.352 0.648
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9603 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.5178 0.8477 0.116 0.884
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9603 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9603 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9687 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.5519 0.8359 0.128 0.872
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9603 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9603 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9603 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9603 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9603 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9603 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9687 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9603 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1633 0.9471 0.976 0.024
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9603 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9687 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9687 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9687 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9687 1.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9603 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9603 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9603 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.9580 0.4071 0.380 0.620
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9603 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9687 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0376 0.9571 0.004 0.996
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9603 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9687 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9603 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9603 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9603 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.0376 0.9653 0.996 0.004
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9603 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9603 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9603 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.0000 0.9687 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9687 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.9608 0.3970 0.384 0.616
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9603 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9603 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9603 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9687 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9603 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.7299 0.7362 0.796 0.204
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9687 1.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9603 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9603 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0376 0.9652 0.996 0.004
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9687 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9667 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4062 0.7759 0.836 0.164 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9667 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9667 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9635 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9667 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9667 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9512 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9667 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9512 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9667 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.2959 0.8687 0.000 0.900 0.100
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9667 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 3 0.0000 0.9512 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.9512 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9667 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9635 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.0000 0.9512 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3879 0.8132 0.000 0.848 0.152
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0000 0.9512 0.000 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.6008 0.4015 0.000 0.628 0.372
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.0000 0.9512 0.000 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9667 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.1289 0.9249 0.000 0.032 0.968
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.0000 0.9512 0.000 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9667 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9667 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.4504 0.7447 0.000 0.804 0.196
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9635 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9667 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9635 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 3 0.5810 0.5256 0.000 0.336 0.664
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9667 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9667 0.000 1.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.9512 0.000 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9667 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.0000 0.9512 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9667 0.000 1.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9667 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9635 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9667 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9667 0.000 1.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9635 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9512 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9667 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9667 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.0000 0.9512 0.000 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9635 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9635 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9512 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.6111 0.3769 0.000 0.396 0.604
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 3 0.0237 0.9481 0.000 0.004 0.996
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 3 0.5216 0.6745 0.000 0.260 0.740
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9667 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9667 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9512 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9635 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.6140 0.3062 0.000 0.596 0.404
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9635 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.4555 0.7311 0.800 0.200 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9667 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.0237 0.9480 0.000 0.004 0.996
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9635 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 3 0.4555 0.7548 0.000 0.200 0.800
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0000 0.9635 1.000 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9667 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9667 0.000 1.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 3 0.4555 0.7548 0.000 0.200 0.800
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 3 0.0000 0.9512 0.000 0.000 1.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9667 0.000 1.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9635 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.0000 0.9512 0.000 0.000 1.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9635 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9667 0.000 1.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.2165 0.9075 0.064 0.936 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9667 0.000 1.000 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9667 0.000 1.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9667 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9667 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9667 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9635 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.9667 0.000 1.000 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9512 0.000 0.000 1.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9667 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.9512 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4399 0.7576 0.000 0.812 0.188
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9667 0.000 1.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9667 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9667 0.000 1.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.9635 1.000 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9667 0.000 1.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9667 0.000 1.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9635 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9667 0.000 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9635 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9667 0.000 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9512 0.000 0.000 1.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.9667 0.000 1.000 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9512 0.000 0.000 1.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9635 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9667 0.000 1.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.0000 0.9512 0.000 0.000 1.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9512 0.000 0.000 1.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9667 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9635 1.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9667 0.000 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.0000 0.9512 0.000 0.000 1.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9635 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9667 0.000 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.6295 0.1030 0.528 0.472 0.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9667 0.000 1.000 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.6126 0.3341 0.600 0.400 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.0000 0.9512 0.000 0.000 1.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9667 0.000 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.9667 0.000 1.000 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9635 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9635 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9667 0.000 1.000 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0000 0.9667 0.000 1.000 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.9635 1.000 0.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9635 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9512 0.000 0.000 1.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9635 1.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9512 0.000 0.000 1.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.9667 0.000 1.000 0.000
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#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9667 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.9512 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9667 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9667 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9667 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.9512 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9635 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.3267 0.8461 0.000 0.116 0.884
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4555 0.7387 0.000 0.800 0.200
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9667 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9667 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9635 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9667 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9635 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9512 0.000 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9667 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.4842 0.7199 0.000 0.224 0.776
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9635 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.0000 0.9512 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1792 0.8436 0.000 0.932 0.000 0.068
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4595 0.7715 0.780 0.176 0.000 0.044
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.4382 0.5371 0.000 0.296 0.000 0.704
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1557 0.8655 0.000 0.944 0.000 0.056
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1118 0.8755 0.000 0.964 0.000 0.036
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4994 0.0173 0.000 0.480 0.000 0.520
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0817 0.8086 0.000 0.024 0.000 0.976
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4454 0.4885 0.000 0.000 0.308 0.692
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3444 0.7022 0.000 0.184 0.000 0.816
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0817 0.7986 0.000 0.000 0.024 0.976
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.1474 0.8029 0.000 0.052 0.000 0.948
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1356 0.8087 0.000 0.032 0.008 0.960
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0592 0.8765 0.000 0.984 0.000 0.016
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0817 0.8047 0.000 0.000 0.024 0.976
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.1022 0.8078 0.000 0.032 0.000 0.968
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.1716 0.7971 0.000 0.064 0.000 0.936
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.7777 0.2470 0.000 0.316 0.260 0.424
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3610 0.7311 0.000 0.800 0.000 0.200
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0188 0.9759 0.000 0.000 0.996 0.004
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.8688 0.000 1.000 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.4948 0.1817 0.000 0.000 0.440 0.560
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4331 0.6070 0.000 0.712 0.000 0.288
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4277 0.5679 0.000 0.280 0.000 0.720
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.3569 0.7371 0.000 0.804 0.000 0.196
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.2214 0.9197 0.928 0.044 0.000 0.028
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1792 0.8592 0.000 0.932 0.000 0.068
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1474 0.7931 0.000 0.000 0.052 0.948
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.5678 0.0878 0.000 0.024 0.452 0.524
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3444 0.6770 0.000 0.000 0.184 0.816
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.1389 0.8035 0.000 0.048 0.000 0.952
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.1022 0.8078 0.000 0.032 0.000 0.968
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.5006 0.7661 0.772 0.124 0.000 0.104
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.3196 0.8187 0.000 0.008 0.856 0.136
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.3801 0.6351 0.000 0.000 0.220 0.780
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.3718 0.8075 0.820 0.168 0.000 0.012
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2345 0.8201 0.000 0.900 0.000 0.100
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0000 0.8069 0.000 0.000 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 3 0.1022 0.9526 0.000 0.000 0.968 0.032
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1022 0.8773 0.000 0.968 0.000 0.032
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.2281 0.8321 0.000 0.904 0.000 0.096
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4985 0.2134 0.000 0.532 0.000 0.468
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4817 0.3275 0.000 0.388 0.000 0.612
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4996 0.1193 0.000 0.516 0.000 0.484
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4008 0.6252 0.000 0.244 0.000 0.756
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.0336 0.8072 0.000 0.008 0.000 0.992
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.3638 0.7808 0.000 0.848 0.120 0.032
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.1022 0.8654 0.000 0.968 0.000 0.032
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.4933 0.2703 0.000 0.432 0.000 0.568
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.8688 0.000 1.000 0.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4985 0.0592 0.000 0.468 0.000 0.532
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.0188 0.9756 0.000 0.000 0.996 0.004
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.5587 0.3267 0.372 0.028 0.000 0.600
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.1637 0.7990 0.000 0.060 0.000 0.940
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.7521 0.1040 0.368 0.188 0.000 0.444
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.2281 0.7865 0.000 0.096 0.000 0.904
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.4996 -0.0108 0.000 0.484 0.000 0.516
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0592 0.8764 0.000 0.984 0.000 0.016
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0469 0.9555 0.988 0.012 0.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.3726 0.6662 0.000 0.212 0.000 0.788
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.2081 0.7717 0.000 0.000 0.084 0.916
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.4961 0.2422 0.000 0.552 0.000 0.448
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.2345 0.7756 0.000 0.100 0.000 0.900
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.3123 0.7317 0.000 0.156 0.000 0.844
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.3172 0.7288 0.000 0.160 0.000 0.840
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 4 0.4989 0.0510 0.000 0.472 0.000 0.528
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 4 0.0000 0.8069 0.000 0.000 0.000 1.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 4 0.1489 0.8073 0.000 0.044 0.004 0.952
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.0000 0.8688 0.000 1.000 0.000 0.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.4514 0.7072 0.148 0.796 0.000 0.056
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#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0921 0.7972 0.000 0.000 0.028 0.972
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3123 0.7758 0.000 0.844 0.000 0.156
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3610 0.6799 0.000 0.000 0.200 0.800
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0336 0.8731 0.000 0.992 0.000 0.008
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0921 0.8085 0.000 0.028 0.000 0.972
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.2973 0.7966 0.000 0.856 0.000 0.144
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.3726 0.7250 0.000 0.000 0.788 0.212
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1118 0.8765 0.000 0.964 0.000 0.036
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4996 0.1179 0.000 0.516 0.000 0.484
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0921 0.8662 0.000 0.972 0.000 0.028
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0188 0.8063 0.000 0.000 0.004 0.996
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4222 0.5996 0.000 0.272 0.000 0.728
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.3172 0.7536 0.000 0.160 0.000 0.840
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2149 0.8427 0.000 0.912 0.000 0.088
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1022 0.8774 0.000 0.968 0.000 0.032
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.1940 0.9069 0.924 0.076 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9789 0.000 0.000 1.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0817 0.8789 0.000 0.976 0.000 0.024
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1411 0.8079 0.000 0.020 0.020 0.960
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9636 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.0000 0.9789 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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.5906 -0.0865 0.000 0.404 0.000 0.104 0.492
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.2179 0.6870 0.112 0.000 0.000 0.000 0.888
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.1430 0.7844 0.000 0.052 0.000 0.944 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5408 0.6383 0.000 0.664 0.000 0.180 0.156
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0290 0.8459 0.000 0.992 0.000 0.008 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1043 0.8331 0.000 0.960 0.000 0.040 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4238 0.6833 0.000 0.192 0.000 0.756 0.052
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0963 0.7725 0.000 0.000 0.000 0.964 0.036
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.4757 0.6258 0.000 0.000 0.080 0.204 0.716
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0609 0.9384 0.000 0.000 0.980 0.000 0.020
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0609 0.7867 0.000 0.020 0.000 0.980 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.1792 0.7464 0.000 0.000 0.000 0.916 0.084
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.1106 0.7877 0.000 0.024 0.000 0.964 0.012
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.1216 0.9254 0.000 0.000 0.960 0.020 0.020
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1357 0.7886 0.000 0.048 0.004 0.948 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.1270 0.9172 0.000 0.000 0.948 0.000 0.052
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0609 0.8412 0.000 0.980 0.000 0.000 0.020
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3536 0.6803 0.000 0.000 0.084 0.832 0.084
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.1544 0.9090 0.000 0.000 0.932 0.000 0.068
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0162 0.7847 0.000 0.004 0.000 0.996 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0404 0.7817 0.000 0.000 0.000 0.988 0.012
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0162 0.9616 0.996 0.000 0.000 0.000 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.2659 0.7649 0.000 0.060 0.000 0.888 0.052
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 3 0.7261 0.0706 0.000 0.388 0.408 0.048 0.156
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.3366 0.6476 0.000 0.768 0.000 0.232 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.2471 0.8292 0.000 0.000 0.864 0.000 0.136
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4801 0.6335 0.000 0.668 0.000 0.048 0.284
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.5199 0.4414 0.000 0.000 0.636 0.292 0.072
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.5267 0.2600 0.000 0.428 0.000 0.524 0.048
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.0794 0.7864 0.000 0.028 0.000 0.972 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4981 0.6512 0.000 0.704 0.000 0.188 0.108
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.1410 0.7109 0.060 0.000 0.000 0.000 0.940
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.5283 0.6519 0.000 0.676 0.000 0.136 0.188
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.1544 0.9090 0.000 0.000 0.932 0.000 0.068
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.4182 0.5279 0.000 0.000 0.004 0.352 0.644
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 5 0.5086 0.4086 0.000 0.000 0.304 0.060 0.636
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.4134 0.6101 0.000 0.004 0.008 0.284 0.704
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4404 0.6763 0.000 0.152 0.000 0.760 0.088
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0451 0.7838 0.000 0.004 0.000 0.988 0.008
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0404 0.7817 0.000 0.000 0.000 0.988 0.012
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.1792 0.7056 0.084 0.000 0.000 0.000 0.916
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.5916 0.4405 0.000 0.020 0.608 0.284 0.088
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 5 0.6483 0.3895 0.000 0.000 0.216 0.300 0.484
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.2690 0.6489 0.156 0.000 0.000 0.000 0.844
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.6071 0.5149 0.000 0.556 0.000 0.160 0.284
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.3586 0.6006 0.000 0.000 0.000 0.264 0.736
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 5 0.3884 0.4903 0.000 0.000 0.288 0.004 0.708
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.2588 0.7914 0.000 0.892 0.000 0.060 0.048
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.0880 0.9317 0.000 0.000 0.968 0.000 0.032
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0404 0.8461 0.000 0.988 0.000 0.012 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.3783 0.5912 0.000 0.252 0.000 0.008 0.740
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.4754 0.6072 0.000 0.052 0.000 0.264 0.684
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.5181 0.4757 0.000 0.360 0.000 0.588 0.052
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.2648 0.7402 0.000 0.152 0.000 0.848 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.0794 0.7864 0.000 0.028 0.000 0.972 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 5 0.3424 0.6282 0.000 0.000 0.000 0.240 0.760
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0290 0.7825 0.000 0.000 0.000 0.992 0.008
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0162 0.9477 0.000 0.000 0.996 0.000 0.004
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.5595 0.2384 0.000 0.560 0.084 0.356 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.5796 0.5493 0.000 0.588 0.000 0.128 0.284
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.3399 0.6566 0.000 0.020 0.000 0.812 0.168
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1043 0.8347 0.000 0.960 0.000 0.040 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.3759 0.7146 0.000 0.764 0.000 0.016 0.220
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4272 0.6764 0.000 0.196 0.000 0.752 0.052
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.0000 0.7838 0.000 0.000 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 3 0.1670 0.9092 0.000 0.000 0.936 0.012 0.052
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.1952 0.7061 0.004 0.000 0.000 0.084 0.912
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.2221 0.7726 0.000 0.036 0.000 0.912 0.052
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.1408 0.7056 0.008 0.000 0.000 0.044 0.948
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.2020 0.8711 0.000 0.000 0.900 0.000 0.100
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.3487 0.6585 0.000 0.212 0.000 0.780 0.008
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.4237 0.6747 0.000 0.200 0.000 0.752 0.048
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.1557 0.7748 0.000 0.008 0.000 0.940 0.052
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0404 0.8445 0.000 0.988 0.000 0.012 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.1408 0.7856 0.000 0.044 0.000 0.948 0.008
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.2659 0.7510 0.000 0.000 0.060 0.888 0.052
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#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.3770 0.6813 0.044 0.028 0.000 0.092 0.836
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.6450 0.2760 0.000 0.296 0.000 0.492 0.212
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.2074 0.7668 0.000 0.104 0.000 0.896 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.1732 0.7077 0.080 0.000 0.000 0.000 0.920
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.4030 0.5087 0.000 0.352 0.000 0.648 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 5 0.3395 0.6266 0.000 0.000 0.000 0.236 0.764
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2067 0.8136 0.000 0.920 0.000 0.032 0.048
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.4538 0.1121 0.000 0.000 0.452 0.540 0.008
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0510 0.7829 0.000 0.000 0.000 0.984 0.016
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 4 0.3143 0.6989 0.000 0.204 0.000 0.796 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.0609 0.7792 0.000 0.000 0.000 0.980 0.020
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0290 0.7825 0.000 0.000 0.000 0.992 0.008
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.3534 0.6485 0.000 0.256 0.000 0.744 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.2012 0.7089 0.060 0.020 0.000 0.000 0.920
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5877 0.5592 0.000 0.596 0.000 0.160 0.244
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.2230 0.7207 0.000 0.000 0.000 0.884 0.116
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2280 0.7940 0.000 0.880 0.000 0.000 0.120
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0000 0.7838 0.000 0.000 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.3895 0.5946 0.000 0.320 0.000 0.680 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.2891 0.6275 0.176 0.000 0.000 0.000 0.824
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4166 0.4406 0.000 0.648 0.000 0.348 0.004
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.3684 0.5789 0.000 0.000 0.000 0.280 0.720
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.4030 0.5079 0.000 0.352 0.000 0.648 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.4367 0.4233 0.000 0.000 0.004 0.416 0.580
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4855 0.6735 0.000 0.720 0.000 0.168 0.112
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.5630 0.3659 0.000 0.000 0.324 0.580 0.096
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0963 0.8321 0.000 0.964 0.000 0.000 0.036
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.1410 0.8191 0.000 0.940 0.000 0.060 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0290 0.7825 0.000 0.000 0.000 0.992 0.008
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3480 0.6253 0.000 0.752 0.000 0.248 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.2077 0.8727 0.000 0.000 0.908 0.084 0.008
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1670 0.8294 0.000 0.936 0.000 0.052 0.012
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.2605 0.7420 0.000 0.148 0.000 0.852 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4800 0.6431 0.000 0.676 0.000 0.052 0.272
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0703 0.9369 0.000 0.000 0.976 0.000 0.024
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.2563 0.7118 0.000 0.000 0.008 0.872 0.120
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.5008 0.5792 0.000 0.152 0.000 0.708 0.140
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4503 0.5685 0.000 0.036 0.000 0.696 0.268
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1197 0.8286 0.000 0.952 0.000 0.048 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1270 0.8334 0.000 0.948 0.000 0.052 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2471 0.8187 0.864 0.000 0.000 0.000 0.136
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9498 0.000 0.000 1.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8478 0.000 1.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0290 0.7825 0.000 0.000 0.000 0.992 0.008
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9653 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.1270 0.9172 0.000 0.000 0.948 0.000 0.052
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 6 0.3673 0.6977 0.000 0.100 0.000 0.008 0.088 0.804
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 6 0.3288 0.4668 0.000 0.000 0.000 0.000 0.276 0.724
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0713 0.8193 0.000 0.972 0.000 0.000 0.000 0.028
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.1245 0.7447 0.000 0.032 0.000 0.952 0.000 0.016
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.6150 0.4260 0.000 0.520 0.000 0.208 0.024 0.248
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1531 0.8111 0.000 0.928 0.000 0.000 0.004 0.068
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1951 0.8036 0.000 0.908 0.000 0.016 0.000 0.076
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.5324 0.6172 0.000 0.136 0.000 0.652 0.024 0.188
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1082 0.7353 0.000 0.000 0.000 0.956 0.040 0.004
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.8299 0.000 1.000 0.000 0.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.1806 0.6461 0.000 0.000 0.000 0.004 0.908 0.088
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.2636 0.8206 0.000 0.000 0.860 0.004 0.120 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.2491 0.7348 0.000 0.020 0.000 0.868 0.000 0.112
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2783 0.6729 0.000 0.000 0.000 0.836 0.148 0.016
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4628 0.7306 0.000 0.028 0.032 0.768 0.064 0.108
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.2975 0.8060 0.000 0.000 0.840 0.012 0.132 0.016
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4377 0.7366 0.000 0.048 0.004 0.776 0.072 0.100
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.2237 0.8472 0.000 0.000 0.896 0.004 0.020 0.080
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1765 0.7681 0.000 0.904 0.000 0.000 0.000 0.096
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3261 0.6356 0.000 0.000 0.000 0.780 0.204 0.016
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.4435 0.7410 0.000 0.000 0.720 0.004 0.176 0.100
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.1387 0.7458 0.000 0.000 0.000 0.932 0.000 0.068
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0363 0.8299 0.000 0.988 0.000 0.000 0.000 0.012
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2020 0.7187 0.000 0.000 0.000 0.896 0.096 0.008
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2212 0.8561 0.880 0.000 0.000 0.000 0.112 0.008
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4422 0.6816 0.000 0.036 0.000 0.728 0.036 0.200
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6730 0.3095 0.000 0.500 0.076 0.008 0.284 0.132
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0146 0.8301 0.000 0.996 0.000 0.000 0.000 0.004
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.5487 0.5790 0.000 0.656 0.000 0.192 0.064 0.088
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.3737 0.4086 0.000 0.000 0.608 0.000 0.392 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 6 0.3189 0.7422 0.000 0.184 0.000 0.020 0.000 0.796
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.6172 0.2325 0.000 0.000 0.472 0.312 0.200 0.016
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0458 0.8248 0.000 0.984 0.000 0.000 0.000 0.016
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6501 -0.0264 0.000 0.408 0.000 0.372 0.036 0.184
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2527 0.7357 0.000 0.024 0.000 0.868 0.000 0.108
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 6 0.5611 0.5511 0.000 0.200 0.000 0.212 0.008 0.580
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.3595 0.5549 0.008 0.000 0.000 0.000 0.704 0.288
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 6 0.5170 0.5959 0.000 0.176 0.000 0.204 0.000 0.620
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.8299 0.000 1.000 0.000 0.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.4506 0.7255 0.000 0.000 0.704 0.004 0.204 0.088
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.3717 0.4817 0.000 0.000 0.000 0.384 0.616 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 5 0.5379 0.5378 0.000 0.004 0.084 0.012 0.580 0.320
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.3156 0.6698 0.000 0.000 0.000 0.180 0.800 0.020
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.5671 0.5335 0.000 0.184 0.000 0.636 0.128 0.052
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0951 0.7416 0.000 0.004 0.000 0.968 0.020 0.008
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0603 0.7387 0.000 0.000 0.000 0.980 0.016 0.004
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.3817 0.3192 0.000 0.000 0.000 0.000 0.568 0.432
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0632 0.8213 0.000 0.976 0.000 0.000 0.000 0.024
#> C8D64135-1B75-428A-8C75-351D32009EAC 6 0.6303 0.4091 0.000 0.000 0.096 0.196 0.132 0.576
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 5 0.5681 0.5611 0.000 0.000 0.104 0.156 0.652 0.088
#> 12FD30FF-4D3A-4920-BF80-F44132824017 6 0.3050 0.5296 0.000 0.000 0.000 0.000 0.236 0.764
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 6 0.3279 0.7425 0.000 0.176 0.000 0.028 0.000 0.796
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2537 0.7877 0.000 0.888 0.000 0.016 0.068 0.028
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.2219 0.6713 0.000 0.000 0.000 0.136 0.864 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 5 0.4250 0.6080 0.000 0.000 0.176 0.004 0.736 0.084
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.3476 0.7301 0.000 0.792 0.000 0.016 0.016 0.176
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 3 0.2209 0.8584 0.000 0.000 0.904 0.004 0.052 0.040
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.2575 0.7885 0.000 0.872 0.000 0.024 0.004 0.100
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.4582 0.5706 0.000 0.216 0.000 0.000 0.684 0.100
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.5934 0.2713 0.000 0.000 0.000 0.216 0.420 0.364
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.8299 0.000 1.000 0.000 0.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6784 0.4533 0.000 0.516 0.000 0.120 0.172 0.192
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.3655 0.7085 0.000 0.096 0.000 0.792 0.000 0.112
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.2605 0.7345 0.000 0.028 0.000 0.864 0.000 0.108
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 5 0.4624 0.6130 0.000 0.000 0.000 0.192 0.688 0.120
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0790 0.7389 0.000 0.000 0.000 0.968 0.032 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.2219 0.8401 0.000 0.000 0.864 0.000 0.136 0.000
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#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.5406 0.3174 0.000 0.000 0.284 0.576 0.136 0.004
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#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.4734 0.4572 0.000 0.372 0.000 0.584 0.016 0.028
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#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 6 0.3050 0.5296 0.000 0.000 0.000 0.000 0.236 0.764
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.6000 0.2317 0.000 0.504 0.000 0.324 0.020 0.152
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.2915 0.6654 0.000 0.000 0.000 0.184 0.808 0.008
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.4941 0.3461 0.000 0.376 0.000 0.552 0.000 0.072
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.3348 0.5544 0.000 0.000 0.000 0.216 0.768 0.016
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 6 0.5983 0.2235 0.000 0.384 0.000 0.228 0.000 0.388
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.8966 0.000 0.000 1.000 0.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.7162 0.4214 0.000 0.008 0.148 0.488 0.200 0.156
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.1333 0.8038 0.000 0.944 0.000 0.000 0.008 0.048
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3377 0.6179 0.000 0.784 0.000 0.028 0.000 0.188
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0291 0.7407 0.000 0.000 0.000 0.992 0.004 0.004
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4428 0.5659 0.000 0.688 0.000 0.260 0.016 0.036
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.4855 0.5623 0.000 0.000 0.660 0.204 0.136 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4454 0.5130 0.000 0.704 0.000 0.048 0.016 0.232
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.3748 0.7025 0.000 0.108 0.000 0.784 0.000 0.108
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 6 0.3200 0.7407 0.000 0.196 0.000 0.016 0.000 0.788
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0993 0.8864 0.000 0.000 0.964 0.000 0.024 0.012
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3853 0.4890 0.000 0.000 0.000 0.680 0.304 0.016
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.3798 0.6557 0.000 0.076 0.000 0.796 0.012 0.116
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.4864 -0.0375 0.000 0.028 0.000 0.364 0.024 0.584
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2842 0.7750 0.000 0.852 0.000 0.044 0.000 0.104
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.3832 0.7183 0.000 0.776 0.000 0.120 0.000 0.104
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2912 0.6969 0.784 0.000 0.000 0.000 0.000 0.216
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0713 0.8853 0.000 0.000 0.972 0.000 0.028 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8299 0.000 1.000 0.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2573 0.6774 0.000 0.000 0.004 0.856 0.132 0.008
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9859 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.2814 0.8302 0.000 0.000 0.864 0.004 0.052 0.080
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 17581 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 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 0.966 0.977 0.2125 0.801 0.801
#> 3 3 0.549 0.773 0.877 1.2705 0.755 0.695
#> 4 4 0.475 0.688 0.825 0.3947 0.725 0.520
#> 5 5 0.486 0.534 0.738 0.1009 0.844 0.561
#> 6 6 0.509 0.497 0.720 0.0386 0.951 0.812
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9799 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.0000 0.9799 0.000 1.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9799 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9799 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.2043 0.9773 0.032 0.968
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0376 0.9800 0.004 0.996
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0376 0.9802 0.004 0.996
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9687 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9799 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9687 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9799 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0938 0.9810 0.012 0.988
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9799 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.2423 0.9741 0.040 0.960
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.2423 0.9741 0.040 0.960
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.1184 0.9806 0.016 0.984
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.1414 0.9785 0.020 0.980
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.2423 0.9741 0.040 0.960
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.1633 0.9799 0.024 0.976
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.2236 0.9762 0.036 0.964
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.1414 0.9804 0.020 0.980
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.9209 0.5255 0.336 0.664
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9799 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2236 0.9757 0.036 0.964
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.2043 0.9767 0.032 0.968
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.1184 0.9806 0.016 0.984
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9799 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.1184 0.9806 0.016 0.984
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.2423 0.9741 0.040 0.960
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0376 0.9800 0.004 0.996
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.2236 0.9760 0.036 0.964
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0938 0.9802 0.012 0.988
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9799 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1184 0.9806 0.016 0.984
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.2948 0.9662 0.052 0.948
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9799 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.1843 0.9789 0.028 0.972
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9799 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0376 0.9800 0.004 0.996
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.2236 0.9757 0.036 0.964
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.1414 0.9802 0.020 0.980
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9799 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.2236 0.9757 0.036 0.964
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.9687 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9799 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9799 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.2423 0.9741 0.040 0.960
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.2236 0.9760 0.036 0.964
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.2236 0.9760 0.036 0.964
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.9687 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.1414 0.9802 0.020 0.980
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.2423 0.9741 0.040 0.960
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.1414 0.9800 0.020 0.980
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.1184 0.9810 0.016 0.984
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0672 0.9808 0.008 0.992
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.9687 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.2236 0.9760 0.036 0.964
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.1414 0.9802 0.020 0.980
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.2236 0.9760 0.036 0.964
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0000 0.9799 0.000 1.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9799 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.2236 0.9757 0.036 0.964
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.1843 0.9781 0.028 0.972
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.2236 0.9762 0.036 0.964
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.1843 0.9787 0.028 0.972
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9799 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1184 0.9806 0.016 0.984
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.1843 0.9790 0.028 0.972
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.2423 0.9741 0.040 0.960
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9799 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.1184 0.9791 0.016 0.984
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.2423 0.9741 0.040 0.960
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.2043 0.9774 0.032 0.968
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9799 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.1414 0.9785 0.020 0.980
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9799 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9799 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9799 0.000 1.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9799 0.000 1.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9799 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.2043 0.9773 0.032 0.968
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.1414 0.9810 0.020 0.980
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.9687 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.1414 0.9802 0.020 0.980
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.9209 0.4849 0.664 0.336
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.2043 0.9777 0.032 0.968
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9799 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.1184 0.9806 0.016 0.984
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9799 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 2 0.2423 0.9740 0.040 0.960
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9799 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9799 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 2 0.2236 0.9760 0.036 0.964
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9799 0.000 1.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 2 0.2423 0.9741 0.040 0.960
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9799 0.000 1.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.0000 0.9687 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0376 0.9800 0.004 0.996
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.9687 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 2 0.1414 0.9795 0.020 0.980
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9799 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.9732 0.3069 0.596 0.404
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.9687 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.1414 0.9802 0.020 0.980
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 2 0.2236 0.9757 0.036 0.964
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0376 0.9802 0.004 0.996
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.2603 0.9720 0.044 0.956
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 2 0.2423 0.9741 0.040 0.960
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9799 0.000 1.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.2236 0.9757 0.036 0.964
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0376 0.9800 0.004 0.996
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.1843 0.9788 0.028 0.972
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.2778 0.9693 0.048 0.952
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.1184 0.9806 0.016 0.984
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0376 0.9800 0.004 0.996
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 2 0.1184 0.9791 0.016 0.984
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 2 0.1633 0.9796 0.024 0.976
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0672 0.9801 0.008 0.992
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0672 0.9808 0.008 0.992
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.2043 0.9775 0.032 0.968
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 2 0.1633 0.9785 0.024 0.976
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.0000 0.9687 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 2 0.2043 0.9773 0.032 0.968
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.0000 0.9687 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.9799 0.000 1.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0376 0.9805 0.004 0.996
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.2423 0.9741 0.040 0.960
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0000 0.9799 0.000 1.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.9799 0.000 1.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.0000 0.9687 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 2 0.6048 0.8579 0.148 0.852
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.1184 0.9806 0.016 0.984
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0376 0.9800 0.004 0.996
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0376 0.9800 0.004 0.996
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0376 0.9800 0.004 0.996
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 2 0.2423 0.9741 0.040 0.960
#> B422FFF3-623B-419A-964E-046BAE3578B3 1 0.0000 0.9687 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 2 0.1843 0.9784 0.028 0.972
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.2236 0.9757 0.036 0.964
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.1184 0.9806 0.016 0.984
#> FAA284CF-ABD4-4405-B847-AD06672BF451 2 0.2423 0.9741 0.040 0.960
#> 15C85716-4BE3-43A8-9F61-2929C600C828 2 0.5178 0.8989 0.116 0.884
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.1184 0.9806 0.016 0.984
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.0000 0.9799 0.000 1.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.1414 0.9804 0.020 0.980
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0376 0.9800 0.004 0.996
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.1414 0.9802 0.020 0.980
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 1 0.0000 0.9687 1.000 0.000
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.0000 0.9799 0.000 1.000
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 2 0.2423 0.9741 0.040 0.960
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 2 0.2043 0.9773 0.032 0.968
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.1414 0.9802 0.020 0.980
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0938 0.9811 0.012 0.988
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.0000 0.9799 0.000 1.000
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.0938 0.9813 0.012 0.988
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.0000 0.9799 0.000 1.000
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.1414 0.9804 0.020 0.980
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.1184 0.9806 0.016 0.984
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.1414 0.9802 0.020 0.980
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 2 0.2043 0.9773 0.032 0.968
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 1 0.8081 0.6601 0.752 0.248
#> 38FCA0B0-4399-4061-99AA-B886F54CA0DB 2 0.2423 0.9741 0.040 0.960
#> C0DC6757-E0CD-4615-9543-A348500AAE84 2 0.0000 0.9799 0.000 1.000
#> 84B05220-4E28-44AE-B6EE-6018C0DBF0D2 2 0.0672 0.9808 0.008 0.992
#> AE8D8D83-D457-4164-861E-9329DB223561 1 0.0000 0.9687 1.000 0.000
#> 85853AF3-27B0-49E0-9E71-478019AE1FA6 2 0.1633 0.9796 0.024 0.976
#> D1B716E8-E4D4-4089-B46A-9892A8BE55F5 2 0.2043 0.9773 0.032 0.968
#> 4B1A0809-0B28-4993-893D-1B7EF099DE91 2 0.1633 0.9796 0.024 0.976
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#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.0000 0.9687 1.000 0.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.2423 0.9741 0.040 0.960
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.2236 0.9763 0.036 0.964
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.1414 0.9802 0.020 0.980
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.9799 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9799 0.000 1.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.1843 0.9789 0.028 0.972
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.1843 0.9789 0.028 0.972
#> E6281A02-850B-405E-AF4D-E79967552F0A 2 0.0672 0.9804 0.008 0.992
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 2 0.2236 0.9760 0.036 0.964
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9799 0.000 1.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0000 0.9799 0.000 1.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.2423 0.9741 0.040 0.960
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.4431 0.9270 0.092 0.908
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 2 0.1843 0.9784 0.028 0.972
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9799 0.000 1.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.0000 0.9687 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0376 0.9805 0.004 0.996
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.1414 0.9785 0.020 0.980
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.2423 0.9741 0.040 0.960
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.0000 0.9687 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.2423 0.9741 0.040 0.960
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.1184 0.9808 0.016 0.984
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 2 0.1184 0.9812 0.016 0.984
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.0000 0.9687 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0376 0.9800 0.004 0.996
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.2423 0.9741 0.040 0.960
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 2 0.2423 0.9741 0.040 0.960
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0376 0.9802 0.004 0.996
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.2236 0.9763 0.036 0.964
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0938 0.9809 0.012 0.988
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 2 0.1843 0.9781 0.028 0.972
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 2 0.2423 0.9741 0.040 0.960
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0672 0.9804 0.008 0.992
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9799 0.000 1.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9799 0.000 1.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.9799 0.000 1.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9799 0.000 1.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9799 0.000 1.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.0000 0.9687 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.2423 0.9741 0.040 0.960
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.1414 0.9804 0.020 0.980
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9799 0.000 1.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0672 0.9808 0.008 0.992
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.1414 0.9808 0.020 0.980
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9799 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.2948 0.9663 0.052 0.948
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0672 0.9808 0.008 0.992
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 2 0.2603 0.9719 0.044 0.956
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0376 0.9800 0.004 0.996
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0376 0.9802 0.004 0.996
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.1633 0.9796 0.024 0.976
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 2 0.2043 0.9773 0.032 0.968
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0672 0.9808 0.008 0.992
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9799 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 2 0.2778 0.9693 0.048 0.952
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.0000 0.9687 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.2236 0.9757 0.036 0.964
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.1184 0.9809 0.016 0.984
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9799 0.000 1.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.2236 0.9757 0.036 0.964
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.2236 0.9760 0.036 0.964
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9799 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9799 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0672 0.9810 0.008 0.992
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.1633 0.9796 0.024 0.976
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9799 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.5059 0.9035 0.112 0.888
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0672 0.9808 0.008 0.992
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.2423 0.9741 0.040 0.960
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.2043 0.9773 0.032 0.968
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9799 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.2236 0.9760 0.036 0.964
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9799 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9799 0.000 1.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.1184 0.9809 0.016 0.984
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0000 0.9687 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9799 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9799 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.9687 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9799 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0376 0.9800 0.004 0.996
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.2043 0.9773 0.032 0.968
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.2236 0.9757 0.036 0.964
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9799 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.9687 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.9687 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.2043 0.9775 0.032 0.968
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0672 0.9803 0.008 0.992
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9799 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9687 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9799 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.1633 0.9801 0.024 0.976
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0376 0.9800 0.004 0.996
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.2236 0.9757 0.036 0.964
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0938 0.9811 0.012 0.988
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0672 0.9810 0.008 0.992
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.5519 0.8361 0.872 0.128
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.1414 0.9802 0.020 0.980
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.1184 0.9806 0.016 0.984
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9799 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.1633 0.9798 0.024 0.976
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1184 0.9806 0.016 0.984
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.1633 0.9796 0.024 0.976
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9799 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.1843 0.9441 0.972 0.028
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9799 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.2043 0.9779 0.032 0.968
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0938 0.9809 0.012 0.988
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9687 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.2236 0.9760 0.036 0.964
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9687 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.2043 0.9773 0.032 0.968
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9799 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9799 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9799 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.2423 0.9741 0.040 0.960
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9799 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9687 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0672 0.9808 0.008 0.992
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9799 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.2236 0.9760 0.036 0.964
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.1414 0.9804 0.020 0.980
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9799 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9799 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.2423 0.9741 0.040 0.960
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0672 0.9808 0.008 0.992
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9799 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9799 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.6887 0.8070 0.184 0.816
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.2236 0.9760 0.036 0.964
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.1633 0.9796 0.024 0.976
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.1414 0.9802 0.020 0.980
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0376 0.9800 0.004 0.996
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9799 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.1843 0.9781 0.028 0.972
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9799 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.2236 0.9757 0.036 0.964
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.9996 0.0138 0.512 0.488
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9799 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.2043 0.9776 0.032 0.968
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.1843 0.9788 0.028 0.972
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.2423 0.9741 0.040 0.960
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.82453 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.0000 0.82453 0.000 1.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.82453 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.82453 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3038 0.75678 0.896 0.104 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0592 0.82417 0.012 0.988 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0592 0.82417 0.012 0.988 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.92913 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.82453 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.92913 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0592 0.82417 0.012 0.988 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.3752 0.80355 0.144 0.856 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.82453 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.5560 0.74268 0.300 0.700 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.5529 0.74620 0.296 0.704 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4002 0.79826 0.160 0.840 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.5016 0.57869 0.760 0.240 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.5529 0.74620 0.296 0.704 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.5529 0.74620 0.296 0.704 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.5529 0.74620 0.296 0.704 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5363 0.75662 0.276 0.724 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.9929 0.15700 0.296 0.392 0.312
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.82453 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.5529 0.74620 0.296 0.704 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.5517 0.76006 0.268 0.728 0.004
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.5397 0.75379 0.280 0.720 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0237 0.82447 0.004 0.996 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.5497 0.74922 0.292 0.708 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0424 0.83928 0.992 0.008 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.1163 0.82269 0.028 0.972 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.83813 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.1289 0.82216 0.032 0.968 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0237 0.82447 0.004 0.996 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.5497 0.74922 0.292 0.708 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.6113 0.73258 0.300 0.688 0.012
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.82453 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.5529 0.74620 0.296 0.704 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.82453 0.000 1.000 0.000
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#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.82453 0.000 1.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.5431 0.75535 0.284 0.716 0.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.3340 0.80982 0.120 0.880 0.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.2796 0.77651 0.908 0.092 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0237 0.83945 0.996 0.004 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0892 0.82416 0.020 0.980 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.82453 0.000 1.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.82453 0.000 1.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.82453 0.000 1.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.82453 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.82453 0.000 1.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.92913 0.000 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.5529 0.74620 0.296 0.704 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.5397 0.75119 0.280 0.720 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0892 0.82415 0.020 0.980 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.2066 0.82164 0.060 0.940 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.5016 0.77534 0.240 0.760 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.82453 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.5958 0.73618 0.300 0.692 0.008
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.1753 0.82273 0.048 0.952 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0237 0.83945 0.996 0.004 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.1163 0.82269 0.028 0.972 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0592 0.82486 0.012 0.988 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.5363 0.75369 0.276 0.724 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0747 0.83715 0.984 0.016 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.1289 0.82414 0.032 0.968 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0592 0.82417 0.012 0.988 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.1643 0.81042 0.956 0.044 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0237 0.92639 0.004 0.000 0.996
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.5363 0.75293 0.276 0.724 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.4346 0.79250 0.184 0.816 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.82453 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.5431 0.74911 0.284 0.716 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0592 0.83713 0.988 0.012 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0592 0.82417 0.012 0.988 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.82453 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4235 0.79364 0.176 0.824 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.5497 0.74922 0.292 0.708 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0237 0.82447 0.004 0.996 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.6763 0.47967 0.436 0.552 0.012
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.1643 0.82287 0.044 0.956 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0237 0.83945 0.996 0.004 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.5431 0.74995 0.284 0.716 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0592 0.82417 0.012 0.988 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.83813 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.82453 0.000 1.000 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.82453 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.2165 0.82029 0.064 0.936 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0237 0.92639 0.004 0.000 0.996
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0237 0.82447 0.004 0.996 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.82453 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.92913 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.82453 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0237 0.82476 0.004 0.996 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.5397 0.75125 0.280 0.720 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.5529 0.74620 0.296 0.704 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0237 0.82447 0.004 0.996 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0237 0.92639 0.004 0.000 0.996
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.92913 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.5431 0.74911 0.284 0.716 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.6095 0.03348 0.392 0.608 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.82453 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.92913 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.82453 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.5397 0.75486 0.280 0.720 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0592 0.82417 0.012 0.988 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.5529 0.74620 0.296 0.704 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.5397 0.75616 0.280 0.720 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2711 0.81605 0.088 0.912 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.83813 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.5397 0.75179 0.280 0.720 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.5497 0.74922 0.292 0.708 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.82453 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.5327 0.75523 0.272 0.728 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5254 0.75756 0.264 0.736 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.5497 0.74922 0.292 0.708 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.82453 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.6546 0.48062 0.240 0.044 0.716
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.82453 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.5621 0.73479 0.308 0.692 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4121 0.79866 0.168 0.832 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.92913 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.83813 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.92913 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.5650 0.46037 0.688 0.312 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0592 0.82417 0.012 0.988 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3551 0.80524 0.132 0.868 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.82453 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.5529 0.74620 0.296 0.704 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.82453 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.92913 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.4796 0.78113 0.220 0.780 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0237 0.82476 0.004 0.996 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0424 0.83587 0.992 0.008 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5465 0.74819 0.288 0.712 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0237 0.82447 0.004 0.996 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.82453 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.5529 0.74620 0.296 0.704 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3192 0.81149 0.112 0.888 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0237 0.82447 0.004 0.996 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.82453 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.7970 0.64170 0.300 0.612 0.088
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.5968 0.21744 0.636 0.364 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.5497 0.74922 0.292 0.708 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5465 0.74974 0.288 0.712 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.1163 0.82269 0.028 0.972 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0592 0.82417 0.012 0.988 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.2537 0.78341 0.920 0.080 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0237 0.82447 0.004 0.996 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.5397 0.75733 0.280 0.720 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.9734 -0.03351 0.292 0.260 0.448
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.82453 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5465 0.74819 0.288 0.712 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.5138 0.55874 0.748 0.252 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.5785 0.73970 0.300 0.696 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1474 0.74497 0.000 0.948 0.000 0.052
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.2216 0.74025 0.000 0.908 0.000 0.092
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3486 0.69897 0.000 0.812 0.000 0.188
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2345 0.75405 0.000 0.900 0.000 0.100
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.6082 -0.11974 0.476 0.044 0.000 0.480
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2760 0.74646 0.000 0.872 0.000 0.128
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3873 0.68333 0.000 0.772 0.000 0.228
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1211 0.76562 0.000 0.960 0.000 0.040
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4776 0.47878 0.000 0.624 0.000 0.376
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4866 0.29835 0.000 0.596 0.000 0.404
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1792 0.76710 0.000 0.932 0.000 0.068
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1867 0.74292 0.000 0.072 0.000 0.928
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.2149 0.75655 0.000 0.088 0.000 0.912
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4907 0.25625 0.000 0.420 0.000 0.580
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2345 0.75951 0.000 0.100 0.000 0.900
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3123 0.75934 0.000 0.156 0.000 0.844
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.3486 0.75565 0.000 0.188 0.000 0.812
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4804 0.46801 0.000 0.384 0.000 0.616
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.4579 0.63876 0.000 0.032 0.200 0.768
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1474 0.75030 0.000 0.948 0.000 0.052
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2408 0.75849 0.000 0.104 0.000 0.896
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.2401 0.75649 0.000 0.092 0.004 0.904
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.4855 0.51526 0.000 0.400 0.000 0.600
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2216 0.76788 0.000 0.908 0.000 0.092
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3024 0.75122 0.000 0.148 0.000 0.852
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.1716 0.88110 0.936 0.000 0.000 0.064
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4933 0.28970 0.000 0.432 0.000 0.568
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4522 0.53151 0.000 0.680 0.000 0.320
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2281 0.75724 0.000 0.904 0.000 0.096
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.4040 0.73479 0.000 0.248 0.000 0.752
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1557 0.74793 0.000 0.056 0.000 0.944
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3907 0.62577 0.000 0.768 0.000 0.232
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.2760 0.75901 0.000 0.128 0.000 0.872
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0592 0.75866 0.000 0.984 0.000 0.016
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4072 0.68050 0.000 0.748 0.000 0.252
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0469 0.90734 0.988 0.000 0.000 0.012
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4955 0.40854 0.000 0.444 0.000 0.556
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1211 0.76250 0.000 0.960 0.000 0.040
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.7082 0.44643 0.564 0.184 0.000 0.252
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0921 0.75982 0.000 0.972 0.000 0.028
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0921 0.76374 0.000 0.972 0.000 0.028
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.3074 0.73257 0.000 0.152 0.000 0.848
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0592 0.90666 0.984 0.000 0.000 0.016
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.3528 0.78389 0.000 0.000 0.808 0.192
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4522 0.33995 0.000 0.680 0.000 0.320
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#> 421E2607-50FA-4260-BD10-C37FCB7D063F 2 0.5277 0.48647 0.028 0.668 0.000 0.304
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.2973 0.75017 0.000 0.856 0.000 0.144
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.2216 0.75984 0.000 0.092 0.000 0.908
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 4 0.3354 0.71988 0.044 0.084 0.000 0.872
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.2216 0.76459 0.000 0.908 0.000 0.092
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.3837 0.71403 0.000 0.224 0.000 0.776
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.4961 0.20450 0.000 0.552 0.000 0.448
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.1824 0.88188 0.936 0.004 0.000 0.060
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.4661 0.54892 0.000 0.652 0.000 0.348
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4522 0.53923 0.000 0.680 0.000 0.320
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.2469 0.75394 0.000 0.892 0.000 0.108
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.1302 0.75032 0.000 0.956 0.000 0.044
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.1302 0.74745 0.000 0.956 0.000 0.044
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.1940 0.76274 0.000 0.924 0.000 0.076
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.2868 0.76028 0.000 0.136 0.000 0.864
#> 59C375B4-60FB-4598-A146-5B175C2B8079 4 0.4996 0.27245 0.000 0.484 0.000 0.516
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4543 0.50188 0.000 0.676 0.000 0.324
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4624 0.45221 0.000 0.340 0.000 0.660
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 4 0.4134 0.65609 0.000 0.260 0.000 0.740
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4543 0.57044 0.000 0.676 0.000 0.324
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.2921 0.74481 0.000 0.140 0.000 0.860
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.4933 0.36388 0.000 0.568 0.000 0.432
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.1389 0.89028 0.952 0.000 0.000 0.048
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.4522 0.54297 0.000 0.680 0.000 0.320
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.3649 0.71981 0.000 0.796 0.000 0.204
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.4543 0.60793 0.000 0.324 0.000 0.676
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4907 0.30364 0.000 0.580 0.000 0.420
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.4761 0.43760 0.000 0.628 0.000 0.372
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.3051 0.84288 0.884 0.028 0.000 0.088
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1867 0.92852 0.000 0.000 0.928 0.072
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.4933 0.37941 0.000 0.432 0.000 0.568
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.4999 0.14945 0.000 0.492 0.000 0.508
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4040 0.62416 0.000 0.752 0.000 0.248
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 4 0.4134 0.67888 0.000 0.260 0.000 0.740
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4500 0.54717 0.000 0.684 0.000 0.316
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.2216 0.76446 0.000 0.908 0.000 0.092
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4941 0.24575 0.000 0.564 0.000 0.436
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.2814 0.75592 0.000 0.132 0.000 0.868
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.3024 0.74922 0.000 0.852 0.000 0.148
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.6514 0.57723 0.096 0.284 0.004 0.616
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.4998 -0.02534 0.000 0.488 0.000 0.512
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 4 0.4164 0.65024 0.000 0.264 0.000 0.736
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.3074 0.74343 0.000 0.848 0.000 0.152
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.1389 0.74695 0.000 0.952 0.000 0.048
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0707 0.75122 0.000 0.980 0.000 0.020
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4992 -0.01898 0.000 0.476 0.000 0.524
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1867 0.92852 0.000 0.000 0.928 0.072
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.1474 0.76192 0.000 0.948 0.000 0.052
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.1022 0.74566 0.000 0.968 0.000 0.032
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1022 0.74996 0.000 0.968 0.000 0.032
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.2868 0.76133 0.000 0.864 0.000 0.136
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.4624 0.58528 0.000 0.340 0.000 0.660
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.3444 0.74441 0.000 0.184 0.000 0.816
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4250 0.59109 0.000 0.724 0.000 0.276
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1867 0.92852 0.000 0.000 0.928 0.072
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.4925 0.02507 0.000 0.572 0.000 0.428
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.6303 0.55498 0.192 0.660 0.000 0.148
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.2704 0.76142 0.000 0.876 0.000 0.124
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1302 0.76695 0.000 0.956 0.000 0.044
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.4948 0.10526 0.000 0.560 0.000 0.440
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.3649 0.71505 0.000 0.796 0.000 0.204
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.2281 0.72172 0.000 0.096 0.000 0.904
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.2973 0.75150 0.000 0.144 0.000 0.856
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2345 0.74810 0.000 0.900 0.000 0.100
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.4967 0.46212 0.000 0.452 0.000 0.548
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.3024 0.75025 0.000 0.148 0.000 0.852
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.2530 0.75741 0.000 0.888 0.000 0.112
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4761 0.31406 0.000 0.628 0.000 0.372
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.5000 0.16835 0.000 0.500 0.000 0.500
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.4008 0.71423 0.000 0.244 0.000 0.756
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.1716 0.75938 0.000 0.936 0.000 0.064
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4950 0.37844 0.000 0.004 0.620 0.376
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4713 0.48646 0.000 0.640 0.000 0.360
#> 79A4EA16-B871-4932-B1F4-169004233CBA 4 0.4546 0.67050 0.012 0.256 0.000 0.732
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4999 0.03796 0.000 0.508 0.000 0.492
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0188 0.95956 0.000 0.000 0.996 0.004
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.7676 0.18537 0.452 0.240 0.000 0.308
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4222 0.66086 0.000 0.728 0.000 0.272
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4804 0.34355 0.000 0.616 0.000 0.384
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3356 0.69876 0.000 0.824 0.000 0.176
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.2081 0.74676 0.000 0.084 0.000 0.916
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.1118 0.76352 0.000 0.964 0.000 0.036
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.96204 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4382 0.65736 0.000 0.296 0.000 0.704
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2469 0.75674 0.000 0.892 0.000 0.108
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0336 0.90704 0.992 0.000 0.000 0.008
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.4605 0.60459 0.000 0.336 0.000 0.664
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4643 0.48957 0.000 0.656 0.000 0.344
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.2011 0.75415 0.000 0.920 0.000 0.080
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2469 0.75298 0.000 0.108 0.000 0.892
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3873 0.62276 0.000 0.772 0.000 0.228
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3764 0.72741 0.000 0.784 0.000 0.216
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4134 0.62852 0.000 0.740 0.000 0.260
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3542 0.73063 0.000 0.076 0.060 0.864
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.5678 0.59117 0.112 0.172 0.000 0.716
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3266 0.75555 0.000 0.168 0.000 0.832
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4331 0.68255 0.000 0.288 0.000 0.712
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4855 0.30066 0.000 0.400 0.000 0.600
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2216 0.75925 0.000 0.908 0.000 0.092
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.91030 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2530 0.75953 0.000 0.888 0.000 0.112
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.4866 0.39794 0.000 0.404 0.000 0.596
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4567 0.53890 0.000 0.008 0.276 0.716
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0707 0.76272 0.000 0.980 0.000 0.020
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4193 0.68263 0.000 0.268 0.000 0.732
#> C90142D8-F939-4FEA-BC48-073D2814F54E 4 0.6725 0.31368 0.348 0.104 0.000 0.548
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.1661 0.74737 0.000 0.052 0.004 0.944
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2193 0.69406 0.000 0.912 0.000 0.028 0.060
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.1907 0.69909 0.000 0.928 0.000 0.028 0.044
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3774 0.52102 0.000 0.704 0.000 0.296 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4847 0.58283 0.000 0.704 0.000 0.216 0.080
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.7269 -0.10820 0.408 0.100 0.000 0.408 0.084
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2570 0.69215 0.000 0.888 0.000 0.084 0.028
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2573 0.67996 0.000 0.880 0.000 0.104 0.016
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.92451 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2110 0.72544 0.000 0.912 0.000 0.072 0.016
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.92451 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4969 0.30485 0.000 0.376 0.000 0.588 0.036
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.6410 0.21977 0.000 0.284 0.000 0.504 0.212
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2193 0.72392 0.000 0.900 0.000 0.092 0.008
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.5427 0.55596 0.000 0.104 0.000 0.260 0.636
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.4787 0.48674 0.000 0.028 0.000 0.364 0.608
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3835 0.52309 0.000 0.156 0.000 0.796 0.048
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.93014 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.4413 0.33967 0.000 0.044 0.000 0.724 0.232
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4312 0.48829 0.000 0.104 0.000 0.772 0.124
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.6121 -0.04074 0.000 0.132 0.000 0.488 0.380
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.5327 0.50126 0.000 0.216 0.000 0.664 0.120
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.6525 0.04962 0.000 0.004 0.224 0.512 0.260
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1082 0.70227 0.000 0.964 0.000 0.028 0.008
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.5071 -0.30450 0.000 0.036 0.000 0.540 0.424
#> B013FB96-A517-46EC-8877-4AE84C01AE27 5 0.5551 0.41677 0.000 0.068 0.000 0.444 0.488
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.6323 0.18571 0.000 0.252 0.000 0.528 0.220
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2727 0.72428 0.000 0.868 0.000 0.116 0.016
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2983 0.47160 0.000 0.040 0.000 0.864 0.096
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2569 0.88683 0.896 0.004 0.000 0.032 0.068
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.5050 0.44385 0.000 0.120 0.000 0.700 0.180
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0510 0.92925 0.984 0.000 0.000 0.000 0.016
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6684 -0.26992 0.000 0.392 0.000 0.236 0.372
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2110 0.70351 0.000 0.912 0.000 0.072 0.016
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.4497 0.49289 0.000 0.208 0.000 0.732 0.060
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.4238 0.53280 0.000 0.004 0.000 0.368 0.628
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4961 -0.09954 0.000 0.524 0.000 0.448 0.028
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.5264 -0.24428 0.000 0.052 0.000 0.556 0.392
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1502 0.72202 0.000 0.940 0.000 0.056 0.004
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#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.5403 0.00917 0.000 0.036 0.016 0.580 0.368
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2207 0.70190 0.000 0.900 0.000 0.016 0.076 0.008
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.1149 0.72196 0.000 0.960 0.000 0.008 0.024 0.008
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4134 0.49620 0.000 0.640 0.000 0.340 0.016 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4792 0.60521 0.000 0.672 0.000 0.232 0.088 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.7353 -0.09717 0.320 0.068 0.000 0.340 0.260 0.012
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2361 0.70922 0.000 0.896 0.000 0.064 0.032 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2744 0.69522 0.000 0.864 0.000 0.072 0.064 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2182 0.74028 0.000 0.904 0.000 0.068 0.020 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4749 0.34855 0.000 0.332 0.000 0.612 0.048 0.008
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.6049 0.04121 0.000 0.200 0.000 0.460 0.332 0.008
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2060 0.74129 0.000 0.900 0.000 0.084 0.016 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.3500 0.49475 0.000 0.028 0.000 0.204 0.768 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.3081 0.47041 0.000 0.004 0.000 0.220 0.776 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3079 0.53576 0.000 0.092 0.000 0.848 0.052 0.008
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0717 0.77178 0.976 0.000 0.000 0.000 0.008 0.016
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.4090 0.19934 0.000 0.004 0.000 0.604 0.384 0.008
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4305 0.42235 0.000 0.052 0.000 0.712 0.228 0.008
#> A0A07F44-C51B-420C-92E8-65F464DB0442 5 0.4857 0.13004 0.000 0.060 0.000 0.408 0.532 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.5156 0.49155 0.000 0.188 0.000 0.648 0.156 0.008
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5586 0.11962 0.000 0.000 0.176 0.532 0.292 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1572 0.71426 0.000 0.936 0.000 0.036 0.028 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.4098 0.21463 0.000 0.008 0.000 0.496 0.496 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 5 0.4032 0.26218 0.000 0.008 0.000 0.420 0.572 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.6017 0.15566 0.000 0.224 0.000 0.492 0.276 0.008
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2996 0.73953 0.000 0.832 0.000 0.144 0.016 0.008
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1471 0.51681 0.000 0.004 0.000 0.932 0.064 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.5627 0.64395 0.544 0.004 0.000 0.000 0.164 0.288
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4093 0.44079 0.000 0.056 0.000 0.736 0.204 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.4151 0.72794 0.684 0.000 0.000 0.000 0.040 0.276
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 5 0.5928 0.25334 0.000 0.344 0.000 0.220 0.436 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2088 0.71834 0.000 0.904 0.000 0.068 0.028 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.4328 0.49130 0.000 0.164 0.000 0.724 0.112 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.2631 0.49463 0.000 0.000 0.000 0.180 0.820 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4983 -0.15933 0.000 0.484 0.000 0.460 0.048 0.008
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.4096 -0.19945 0.000 0.008 0.000 0.508 0.484 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1462 0.73847 0.000 0.936 0.000 0.056 0.008 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4165 0.36628 0.000 0.536 0.000 0.452 0.012 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.4747 0.70697 0.632 0.000 0.000 0.000 0.080 0.288
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4649 0.47878 0.000 0.280 0.000 0.656 0.056 0.008
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.2234 0.74014 0.000 0.872 0.000 0.124 0.004 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.7456 0.08207 0.156 0.116 0.000 0.020 0.432 0.276
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1584 0.74061 0.000 0.928 0.000 0.064 0.000 0.008
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1327 0.73808 0.000 0.936 0.000 0.064 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 5 0.3649 0.46543 0.000 0.040 0.000 0.196 0.764 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.4389 0.71785 0.660 0.000 0.000 0.000 0.052 0.288
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1251 0.76872 0.956 0.000 0.000 0.008 0.024 0.012
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 5 0.6499 -0.08615 0.000 0.000 0.388 0.136 0.420 0.056
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.5454 0.34792 0.000 0.252 0.000 0.180 0.568 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4300 0.17003 0.000 0.028 0.000 0.608 0.364 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.6012 0.22861 0.000 0.280 0.000 0.220 0.492 0.008
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.5508 -0.04682 0.000 0.140 0.000 0.508 0.352 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.1444 0.54313 0.000 0.072 0.000 0.928 0.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.5989 -0.04868 0.000 0.248 0.000 0.432 0.320 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.4552 0.71451 0.648 0.000 0.000 0.000 0.064 0.288
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4368 0.18839 0.000 0.592 0.000 0.016 0.384 0.008
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3481 0.69973 0.000 0.776 0.000 0.192 0.032 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.5930 0.34692 0.000 0.252 0.000 0.224 0.516 0.008
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1713 0.76999 0.928 0.000 0.000 0.000 0.044 0.028
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 5 0.5290 0.25746 0.000 0.104 0.000 0.392 0.504 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.8047 -0.31216 0.032 0.336 0.000 0.140 0.248 0.244
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4617 0.24112 0.000 0.624 0.000 0.328 0.040 0.008
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3275 0.61568 0.000 0.816 0.000 0.036 0.144 0.004
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.4756 -0.23593 0.000 0.048 0.000 0.488 0.464 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 5 0.3894 0.32627 0.000 0.004 0.000 0.324 0.664 0.008
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.3679 0.68732 0.000 0.724 0.000 0.260 0.012 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.5279 0.68859 0.596 0.008 0.000 0.000 0.108 0.288
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3944 0.15316 0.000 0.004 0.000 0.568 0.428 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.4652 0.71118 0.640 0.000 0.000 0.000 0.072 0.288
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0725 0.71810 0.000 0.976 0.000 0.012 0.012 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.7512 0.36608 0.000 0.240 0.000 0.240 0.360 0.160
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4655 0.63116 0.000 0.708 0.000 0.120 0.164 0.008
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2147 0.74740 0.000 0.896 0.000 0.084 0.020 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4011 0.68457 0.000 0.732 0.000 0.212 0.056 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4406 0.42703 0.000 0.624 0.000 0.344 0.024 0.008
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4645 0.32205 0.000 0.336 0.000 0.616 0.040 0.008
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.4079 0.72375 0.680 0.000 0.000 0.000 0.032 0.288
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4972 -0.00598 0.000 0.080 0.000 0.568 0.352 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.4747 0.43307 0.000 0.356 0.000 0.584 0.060 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 6 0.4191 0.21353 0.000 0.000 0.004 0.012 0.388 0.596
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.3857 0.50128 0.000 0.080 0.000 0.768 0.152 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4668 0.62224 0.000 0.652 0.000 0.284 0.056 0.008
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.1261 0.53810 0.000 0.024 0.000 0.952 0.024 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1700 0.74238 0.000 0.916 0.000 0.080 0.004 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.6526 0.45830 0.424 0.016 0.000 0.008 0.328 0.224
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1204 0.73843 0.000 0.944 0.000 0.056 0.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.4465 -0.04519 0.000 0.512 0.000 0.460 0.028 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3351 0.56752 0.000 0.712 0.000 0.288 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1757 0.74176 0.000 0.916 0.000 0.076 0.000 0.008
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.3867 -0.29614 0.000 0.000 0.512 0.000 0.000 0.488
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.3834 0.68008 0.000 0.708 0.000 0.268 0.024 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 6 0.3428 0.72899 0.000 0.000 0.304 0.000 0.000 0.696
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.5999 0.49160 0.612 0.036 0.000 0.240 0.080 0.032
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.3730 0.70922 0.000 0.768 0.000 0.192 0.032 0.008
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.4941 0.34252 0.000 0.000 0.648 0.212 0.140 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.3055 0.48308 0.000 0.096 0.000 0.840 0.064 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.5440 0.65350 0.556 0.000 0.000 0.000 0.156 0.288
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.3149 0.73384 0.000 0.824 0.000 0.132 0.044 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.3843 0.12455 0.000 0.000 0.000 0.548 0.452 0.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.2955 0.72774 0.000 0.816 0.000 0.172 0.004 0.008
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.5812 0.27585 0.000 0.192 0.000 0.264 0.536 0.008
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.1411 0.51480 0.000 0.004 0.000 0.936 0.060 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.5826 0.26347 0.000 0.400 0.000 0.144 0.448 0.008
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 5 0.2615 0.49143 0.000 0.004 0.000 0.136 0.852 0.008
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.3914 0.51445 0.000 0.104 0.000 0.768 0.128 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.2070 0.53064 0.000 0.100 0.000 0.892 0.008 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.4234 0.72466 0.676 0.000 0.000 0.000 0.044 0.280
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.2851 0.69563 0.868 0.036 0.000 0.016 0.080 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.2070 0.54177 0.000 0.048 0.000 0.908 0.044 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 4 0.4557 0.45837 0.000 0.268 0.000 0.660 0.072 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.5533 -0.01668 0.000 0.532 0.000 0.116 0.344 0.008
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.4173 0.72940 0.688 0.000 0.000 0.000 0.044 0.268
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.1807 0.73539 0.000 0.920 0.000 0.060 0.020 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.6105 0.02797 0.000 0.456 0.000 0.316 0.220 0.008
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.1957 0.46056 0.000 0.000 0.000 0.888 0.112 0.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.3261 0.69569 0.000 0.780 0.000 0.204 0.016 0.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.3313 0.73220 0.000 0.808 0.000 0.160 0.024 0.008
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 6 0.3428 0.72899 0.000 0.000 0.304 0.000 0.000 0.696
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 5 0.3081 0.46062 0.000 0.004 0.000 0.220 0.776 0.000
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.6130 0.02145 0.000 0.208 0.000 0.412 0.372 0.008
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.3358 0.54644 0.000 0.116 0.000 0.824 0.052 0.008
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.2817 0.72221 0.000 0.868 0.000 0.072 0.052 0.008
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 4 0.4514 0.46798 0.000 0.288 0.000 0.660 0.044 0.008
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 6 0.3428 0.72899 0.000 0.000 0.304 0.000 0.000 0.696
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.4499 0.71572 0.652 0.000 0.000 0.000 0.060 0.288
#> 64BA791A-C418-4507-BF64-B4B473C78834 5 0.5453 0.28842 0.000 0.108 0.000 0.340 0.544 0.008
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 4 0.3832 0.46530 0.000 0.120 0.000 0.776 0.104 0.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.5631 0.62436 0.528 0.000 0.000 0.000 0.188 0.284
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.0458 0.76503 0.984 0.000 0.000 0.000 0.016 0.000
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#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.2390 0.73957 0.000 0.888 0.000 0.056 0.056 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.1138 0.71430 0.000 0.960 0.000 0.004 0.024 0.012
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1003 0.71739 0.000 0.964 0.000 0.016 0.020 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.3845 0.65425 0.000 0.772 0.000 0.088 0.140 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.6047 0.28901 0.000 0.220 0.000 0.480 0.292 0.008
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.2629 0.53986 0.000 0.060 0.000 0.872 0.068 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.4735 0.26315 0.000 0.392 0.000 0.564 0.036 0.008
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 6 0.3428 0.72899 0.000 0.000 0.304 0.000 0.000 0.696
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.6288 0.25405 0.012 0.396 0.000 0.172 0.412 0.008
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.7683 0.23228 0.008 0.260 0.000 0.132 0.324 0.276
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.3390 0.72484 0.000 0.780 0.000 0.200 0.012 0.008
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1444 0.74080 0.000 0.928 0.000 0.072 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 5 0.6595 0.39783 0.000 0.132 0.000 0.176 0.548 0.144
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.3221 0.72669 0.000 0.792 0.000 0.188 0.020 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 5 0.5998 0.36146 0.000 0.016 0.000 0.360 0.472 0.152
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0508 0.52498 0.000 0.004 0.000 0.984 0.012 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3458 0.71666 0.000 0.820 0.000 0.104 0.068 0.008
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4416 0.72268 0.680 0.000 0.008 0.000 0.044 0.268
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.6187 -0.06961 0.000 0.268 0.000 0.392 0.336 0.004
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0291 0.52516 0.000 0.004 0.000 0.992 0.004 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4448 0.65191 0.000 0.708 0.000 0.216 0.068 0.008
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.6101 0.24888 0.000 0.252 0.000 0.268 0.472 0.008
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.5156 0.44388 0.000 0.272 0.000 0.600 0.128 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.3501 0.53189 0.000 0.080 0.000 0.804 0.116 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3168 0.72643 0.000 0.804 0.000 0.172 0.024 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.2680 0.67994 0.000 0.000 0.868 0.056 0.076 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.4756 0.42556 0.000 0.280 0.000 0.648 0.064 0.008
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.7537 -0.29390 0.312 0.144 0.000 0.280 0.264 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.2980 0.52485 0.000 0.180 0.000 0.808 0.012 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.4272 0.71983 0.668 0.000 0.000 0.000 0.044 0.288
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.8324 0.15412 0.128 0.156 0.000 0.088 0.344 0.284
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4118 0.58593 0.000 0.628 0.000 0.352 0.020 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.5607 0.27522 0.000 0.184 0.000 0.284 0.532 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4518 0.38284 0.000 0.624 0.000 0.336 0.032 0.008
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.3743 0.47796 0.000 0.024 0.000 0.252 0.724 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2613 0.72980 0.000 0.848 0.000 0.140 0.012 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.86635 0.000 0.000 1.000 0.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 5 0.4978 0.20626 0.000 0.068 0.000 0.432 0.500 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2994 0.71349 0.000 0.788 0.000 0.208 0.004 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.4277 0.50762 0.000 0.144 0.000 0.732 0.124 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.4039 0.51310 0.000 0.208 0.000 0.732 0.060 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1204 0.72250 0.000 0.944 0.000 0.056 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 5 0.4717 0.39485 0.000 0.056 0.000 0.364 0.580 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4617 0.41048 0.000 0.636 0.000 0.312 0.044 0.008
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3819 0.62769 0.000 0.700 0.000 0.280 0.020 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4282 0.32900 0.000 0.656 0.000 0.304 0.040 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.2442 0.48928 0.000 0.004 0.000 0.144 0.852 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 5 0.8216 0.29196 0.068 0.268 0.000 0.160 0.364 0.140
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.4824 0.25603 0.000 0.056 0.000 0.420 0.524 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.6140 0.24797 0.000 0.216 0.000 0.348 0.428 0.008
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.3863 0.43003 0.000 0.260 0.000 0.712 0.028 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2367 0.73827 0.000 0.888 0.000 0.088 0.016 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.77032 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2871 0.71833 0.000 0.804 0.000 0.192 0.004 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.5972 0.41413 0.000 0.260 0.000 0.208 0.520 0.012
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6014 0.05256 0.000 0.000 0.428 0.308 0.264 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2887 0.74055 0.000 0.856 0.000 0.104 0.032 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.6029 0.08228 0.000 0.188 0.000 0.356 0.448 0.008
#> C90142D8-F939-4FEA-BC48-073D2814F54E 4 0.7472 0.05752 0.268 0.112 0.000 0.408 0.200 0.012
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.4227 -0.05147 0.000 0.004 0.000 0.492 0.496 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["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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.805 0.912 0.960 0.4612 0.528 0.528
#> 3 3 0.774 0.865 0.943 0.0996 0.846 0.742
#> 4 4 0.694 0.819 0.891 0.3941 0.764 0.548
#> 5 5 0.683 0.704 0.840 0.0633 0.918 0.742
#> 6 6 0.633 0.603 0.758 0.0496 0.926 0.728
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9781 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.7815 0.6626 0.232 0.768
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9781 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9781 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9233 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9781 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9781 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9233 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9781 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9233 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9781 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9781 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9781 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.9393 0.5281 0.644 0.356
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0376 0.9743 0.004 0.996
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9781 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9233 1.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9781 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3274 0.9180 0.060 0.940
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.9781 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9781 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.7056 0.7860 0.808 0.192
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9781 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0000 0.9781 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.9248 0.4453 0.340 0.660
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9781 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9781 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9781 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9233 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9781 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9233 1.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9781 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9781 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9781 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.6623 0.8071 0.828 0.172
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9781 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9781 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9781 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9781 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9233 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9781 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9781 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.9491 0.5222 0.632 0.368
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.9233 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9781 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9781 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.7219 0.7304 0.200 0.800
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9233 1.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9233 1.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.9233 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.0000 0.9781 0.000 1.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.9781 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9781 0.000 1.000
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#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9781 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9781 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.9233 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9781 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.9522 0.5142 0.628 0.372
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.9781 0.000 1.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9781 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9781 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.9233 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.9233 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9233 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.8813 0.6432 0.700 0.300
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9781 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9233 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9781 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.9608 0.4881 0.616 0.384
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9781 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.7219 0.7304 0.200 0.800
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9781 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9781 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9233 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.9781 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9781 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9781 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.2043 0.9462 0.032 0.968
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9781 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9781 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9781 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9233 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9781 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9233 1.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9781 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9233 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9233 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9233 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.6623 0.8071 0.828 0.172
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9781 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9781 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9781 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.9781 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9781 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9233 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9781 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9781 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9233 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9781 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9781 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9781 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.0000 0.9781 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9781 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9781 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9781 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.6623 0.8071 0.828 0.172
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.6438 0.8137 0.836 0.164
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.9781 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9781 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9781 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9781 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9233 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9781 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.7139 0.7826 0.804 0.196
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.3879 0.8779 0.924 0.076
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9781 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.7219 0.7304 0.200 0.800
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9233 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.6623 0.8071 0.828 0.172
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0237 0.9362 0.000 0.996 0.004
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6228 0.3754 0.372 0.624 0.004
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9374 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9374 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9086 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9374 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3879 0.8152 0.000 0.848 0.152
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0424 0.9279 0.008 0.000 0.992
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9374 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0424 0.9279 0.008 0.000 0.992
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9374 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0237 0.9362 0.000 0.996 0.004
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9374 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.9162 0.3544 0.268 0.536 0.196
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.4555 0.7641 0.000 0.800 0.200
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9374 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9086 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0892 0.9289 0.000 0.980 0.020
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.4291 0.7885 0.000 0.820 0.180
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.1529 0.9157 0.000 0.960 0.040
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0592 0.9327 0.000 0.988 0.012
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.6448 0.4938 0.016 0.328 0.656
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9374 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0592 0.9333 0.000 0.988 0.012
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.4605 0.7593 0.000 0.796 0.204
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0892 0.9279 0.000 0.980 0.020
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9374 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0424 0.9351 0.000 0.992 0.008
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9086 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0237 0.9362 0.000 0.996 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9086 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3412 0.8454 0.000 0.876 0.124
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0237 0.9362 0.000 0.996 0.004
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0237 0.9362 0.000 0.996 0.004
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.5414 0.7344 0.016 0.772 0.212
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9374 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3038 0.8636 0.000 0.896 0.104
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0237 0.9362 0.000 0.996 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9374 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9086 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0237 0.9362 0.000 0.996 0.004
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9374 0.000 1.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6282 0.4042 0.612 0.384 0.004
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0424 0.9279 0.008 0.000 0.992
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9374 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9374 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.4504 0.7687 0.000 0.804 0.196
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9086 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9086 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0424 0.9279 0.008 0.000 0.992
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.0424 0.9351 0.000 0.992 0.008
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0424 0.9351 0.000 0.992 0.008
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0424 0.9351 0.000 0.992 0.008
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0424 0.9351 0.000 0.992 0.008
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0237 0.9362 0.000 0.996 0.004
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0424 0.9279 0.008 0.000 0.992
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9086 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.0424 0.9351 0.000 0.992 0.008
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9086 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6330 0.3079 0.396 0.600 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9374 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4733 0.7655 0.004 0.800 0.196
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9086 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0424 0.9351 0.000 0.992 0.008
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.6516 0.1221 0.516 0.480 0.004
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9374 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4399 0.7753 0.000 0.812 0.188
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.6047 0.5189 0.312 0.680 0.008
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.5728 0.7402 0.032 0.772 0.196
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9374 0.000 1.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9086 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.5541 0.6853 0.008 0.740 0.252
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9086 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9374 0.000 1.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.5815 0.5378 0.304 0.692 0.004
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0237 0.9362 0.000 0.996 0.004
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9374 0.000 1.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4452 0.7705 0.000 0.808 0.192
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9374 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9374 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9086 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0661 0.9321 0.008 0.988 0.004
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0424 0.9279 0.008 0.000 0.992
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9374 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.5597 0.7226 0.020 0.764 0.216
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4121 0.7980 0.000 0.832 0.168
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9374 0.000 1.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9374 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9374 0.000 1.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.3192 0.8099 0.888 0.000 0.112
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9374 0.000 1.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9374 0.000 1.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9086 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9374 0.000 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9086 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9374 0.000 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0424 0.9279 0.008 0.000 0.992
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0592 0.9327 0.000 0.988 0.012
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0424 0.9279 0.008 0.000 0.992
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9086 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9374 0.000 1.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.4399 0.7098 0.188 0.000 0.812
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0424 0.9279 0.008 0.000 0.992
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9374 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9086 1.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9374 0.000 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.5948 0.4836 0.000 0.640 0.360
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9086 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9374 0.000 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.1015 0.9288 0.012 0.980 0.008
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0237 0.9362 0.000 0.996 0.004
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.6057 0.4555 0.340 0.656 0.004
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#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9374 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0424 0.9279 0.008 0.000 0.992
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9086 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0424 0.9279 0.008 0.000 0.992
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.3500 0.7626 0.880 0.116 0.004
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9374 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4784 0.7237 0.200 0.796 0.004
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9374 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.3038 0.8635 0.000 0.896 0.104
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9374 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0424 0.9279 0.008 0.000 0.992
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.1031 0.9263 0.000 0.976 0.024
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0237 0.9362 0.000 0.996 0.004
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9086 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9374 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9374 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9374 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4733 0.7660 0.004 0.800 0.196
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9374 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9374 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9374 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.5414 0.7344 0.016 0.772 0.212
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0237 0.9052 0.996 0.000 0.004
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.1163 0.9236 0.000 0.972 0.028
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0237 0.9362 0.000 0.996 0.004
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9374 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9374 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9086 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9374 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.6373 0.3015 0.588 0.408 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.1751 0.8858 0.012 0.028 0.960
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9374 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.4504 0.7687 0.000 0.804 0.196
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9086 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.8233 0.4871 0.120 0.616 0.264
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2647 0.8654 0.000 0.880 0.000 0.120
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.7811 0.0412 0.380 0.252 0.000 0.368
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.2281 0.8759 0.000 0.904 0.000 0.096
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0336 0.8955 0.000 0.992 0.000 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0188 0.9439 0.996 0.000 0.000 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0336 0.8973 0.000 0.992 0.000 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3649 0.8202 0.000 0.796 0.000 0.204
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2345 0.8322 0.000 0.900 0.000 0.100
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4866 0.4779 0.000 0.404 0.000 0.596
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1474 0.8925 0.000 0.948 0.000 0.052
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0817 0.7989 0.000 0.000 0.024 0.976
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.2714 0.7862 0.000 0.004 0.112 0.884
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0188 0.8964 0.000 0.996 0.000 0.004
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2647 0.8126 0.000 0.120 0.000 0.880
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3667 0.8066 0.000 0.056 0.088 0.856
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.2530 0.8136 0.000 0.112 0.000 0.888
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.2868 0.8097 0.000 0.136 0.000 0.864
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3942 0.6949 0.000 0.000 0.236 0.764
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.2469 0.8692 0.000 0.892 0.000 0.108
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2647 0.8126 0.000 0.120 0.000 0.880
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.3583 0.7532 0.000 0.004 0.180 0.816
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.4898 0.0552 0.000 0.416 0.000 0.584
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0188 0.8967 0.000 0.996 0.000 0.004
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3123 0.8012 0.000 0.156 0.000 0.844
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0336 0.9428 0.992 0.000 0.000 0.008
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4500 0.6284 0.000 0.316 0.000 0.684
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.0336 0.7982 0.000 0.008 0.000 0.992
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3569 0.8268 0.000 0.804 0.000 0.196
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4661 0.4522 0.000 0.652 0.000 0.348
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.3444 0.7461 0.000 0.000 0.184 0.816
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2216 0.8773 0.000 0.908 0.000 0.092
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.3144 0.8057 0.000 0.044 0.072 0.884
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3569 0.8268 0.000 0.804 0.000 0.196
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1637 0.8755 0.000 0.940 0.000 0.060
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.1302 0.7955 0.000 0.044 0.000 0.956
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0592 0.8970 0.000 0.984 0.000 0.016
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5496 0.4376 0.604 0.024 0.000 0.372
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1302 0.8934 0.000 0.956 0.000 0.044
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2831 0.7852 0.000 0.004 0.120 0.876
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0592 0.9632 0.000 0.000 0.984 0.016
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1940 0.8173 0.000 0.076 0.000 0.924
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.2081 0.8176 0.000 0.084 0.000 0.916
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.0469 0.7998 0.000 0.012 0.000 0.988
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.3688 0.7700 0.000 0.208 0.000 0.792
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4843 0.1427 0.000 0.396 0.000 0.604
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.1302 0.8117 0.000 0.044 0.000 0.956
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.6562 0.2302 0.360 0.088 0.000 0.552
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3266 0.7717 0.000 0.832 0.000 0.168
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.3631 0.7606 0.004 0.004 0.168 0.824
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2647 0.8134 0.000 0.120 0.000 0.880
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.6010 0.6378 0.676 0.104 0.000 0.220
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2345 0.8735 0.000 0.900 0.000 0.100
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4564 0.6722 0.000 0.672 0.000 0.328
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2530 0.8136 0.000 0.112 0.000 0.888
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2760 0.7796 0.000 0.000 0.128 0.872
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0188 0.9439 0.996 0.000 0.000 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3356 0.7519 0.000 0.000 0.176 0.824
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1474 0.8956 0.000 0.948 0.000 0.052
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.1635 0.7925 0.008 0.044 0.000 0.948
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.4804 0.2812 0.000 0.384 0.000 0.616
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2760 0.8671 0.000 0.872 0.000 0.128
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.1474 0.7927 0.000 0.052 0.000 0.948
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0188 0.8964 0.000 0.996 0.000 0.004
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.3801 0.7620 0.000 0.220 0.000 0.780
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4843 0.2561 0.000 0.604 0.000 0.396
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.3649 0.7310 0.000 0.000 0.204 0.796
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.3547 0.8070 0.000 0.144 0.016 0.840
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.2530 0.8668 0.000 0.888 0.000 0.112
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.2647 0.8339 0.000 0.880 0.000 0.120
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1211 0.8939 0.000 0.960 0.000 0.040
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0469 0.9411 0.988 0.000 0.000 0.012
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.2011 0.8825 0.000 0.920 0.000 0.080
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2345 0.8739 0.000 0.900 0.000 0.100
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0188 0.8967 0.000 0.996 0.000 0.004
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.2081 0.8809 0.000 0.916 0.000 0.084
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.4477 0.6972 0.000 0.688 0.000 0.312
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5088 0.5540 0.288 0.000 0.688 0.024
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0188 0.8964 0.000 0.996 0.000 0.004
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0707 0.9368 0.980 0.000 0.000 0.020
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.3311 0.8484 0.000 0.828 0.000 0.172
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.3486 0.7430 0.000 0.000 0.188 0.812
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.2670 0.7628 0.072 0.024 0.000 0.904
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.3311 0.7926 0.000 0.172 0.000 0.828
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.4834 0.6867 0.120 0.096 0.000 0.784
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.3444 0.7461 0.000 0.000 0.184 0.816
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.3610 0.7735 0.000 0.200 0.000 0.800
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.1716 0.8725 0.000 0.936 0.000 0.064
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.4989 -0.0275 0.000 0.528 0.000 0.472
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1792 0.8918 0.000 0.932 0.000 0.068
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.2060 0.9076 0.932 0.016 0.000 0.052
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.3528 0.8280 0.000 0.808 0.000 0.192
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.1118 0.8964 0.000 0.964 0.000 0.036
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.2647 0.8126 0.000 0.120 0.000 0.880
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.2408 0.8798 0.000 0.896 0.000 0.104
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.8966 0.000 1.000 0.000 0.000
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#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.7394 0.4265 0.236 0.244 0.000 0.520
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1867 0.8853 0.000 0.928 0.000 0.072
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.2704 0.8122 0.000 0.124 0.000 0.876
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2469 0.8691 0.000 0.892 0.000 0.108
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0336 0.9676 0.000 0.000 0.992 0.008
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3975 0.6648 0.000 0.760 0.000 0.240
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0188 0.9439 0.996 0.000 0.000 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0188 0.8964 0.000 0.996 0.000 0.004
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.2111 0.9077 0.932 0.024 0.000 0.044
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.8966 0.000 1.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.3726 0.7708 0.000 0.212 0.000 0.788
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1211 0.8849 0.000 0.960 0.000 0.040
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0188 0.7974 0.000 0.004 0.000 0.996
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0469 0.8971 0.000 0.988 0.000 0.012
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9728 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.2859 0.8137 0.000 0.112 0.008 0.880
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2647 0.8671 0.000 0.880 0.000 0.120
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.1118 0.8968 0.000 0.964 0.000 0.036
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4866 0.2290 0.000 0.596 0.000 0.404
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0188 0.8971 0.000 0.996 0.000 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2861 0.7951 0.000 0.016 0.096 0.888
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1118 0.8857 0.000 0.964 0.000 0.036
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0592 0.8982 0.000 0.984 0.000 0.016
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3123 0.8525 0.000 0.844 0.000 0.156
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3172 0.7622 0.000 0.000 0.160 0.840
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.1004 0.9324 0.972 0.004 0.000 0.024
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0188 0.7974 0.000 0.004 0.000 0.996
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4977 0.2570 0.000 0.460 0.000 0.540
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.4877 0.4986 0.000 0.592 0.000 0.408
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0336 0.8961 0.000 0.992 0.000 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9452 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0469 0.8978 0.000 0.988 0.000 0.012
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2412 0.8854 0.908 0.008 0.000 0.084
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4605 0.4164 0.000 0.000 0.664 0.336
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0188 0.8964 0.000 0.996 0.000 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0672 0.7998 0.000 0.008 0.008 0.984
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0188 0.9439 0.996 0.000 0.000 0.004
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4121 0.7360 0.020 0.000 0.184 0.796
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1522 0.861118 0.000 0.944 0.000 0.012 0.044
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.6655 0.342044 0.060 0.392 0.000 0.068 0.480
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0579 0.866118 0.000 0.984 0.000 0.008 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3697 0.783998 0.000 0.820 0.000 0.080 0.100
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0794 0.873431 0.972 0.000 0.000 0.000 0.028
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1041 0.860076 0.000 0.964 0.000 0.032 0.004
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3602 0.723451 0.000 0.796 0.000 0.180 0.024
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1341 0.861358 0.000 0.944 0.000 0.000 0.056
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2172 0.835266 0.000 0.908 0.000 0.076 0.016
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4503 0.532330 0.000 0.256 0.000 0.704 0.040
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3269 0.807770 0.000 0.848 0.000 0.096 0.056
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4307 0.053888 0.000 0.000 0.000 0.504 0.496
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1197 0.743504 0.000 0.000 0.000 0.952 0.048
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.2676 0.825725 0.000 0.884 0.000 0.036 0.080
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0162 0.752148 0.000 0.000 0.000 0.996 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4127 0.543780 0.000 0.008 0.000 0.680 0.312
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0609 0.749558 0.000 0.000 0.000 0.980 0.020
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1704 0.744241 0.000 0.004 0.000 0.928 0.068
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.4386 0.620136 0.000 0.000 0.096 0.764 0.140
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1364 0.863391 0.000 0.952 0.000 0.012 0.036
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0404 0.750639 0.000 0.000 0.000 0.988 0.012
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.1818 0.746324 0.000 0.000 0.024 0.932 0.044
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3767 0.691041 0.000 0.068 0.000 0.812 0.120
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1197 0.861684 0.000 0.952 0.000 0.000 0.048
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2172 0.740272 0.000 0.016 0.000 0.908 0.076
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3752 0.641250 0.708 0.000 0.000 0.000 0.292
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.3216 0.707817 0.000 0.044 0.000 0.848 0.108
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1732 0.872441 0.920 0.000 0.000 0.000 0.080
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.1282 0.753680 0.000 0.004 0.000 0.952 0.044
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4204 0.704667 0.000 0.756 0.000 0.196 0.048
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.5604 0.061140 0.000 0.472 0.000 0.456 0.072
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.4650 0.141344 0.000 0.000 0.012 0.468 0.520
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0955 0.862734 0.000 0.968 0.000 0.004 0.028
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0609 0.749702 0.000 0.000 0.000 0.980 0.020
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4101 0.707867 0.000 0.768 0.000 0.184 0.048
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.5232 0.600256 0.000 0.648 0.000 0.268 0.084
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1732 0.871318 0.920 0.000 0.000 0.000 0.080
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.3085 0.719117 0.000 0.032 0.000 0.852 0.116
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1041 0.862104 0.000 0.964 0.000 0.004 0.032
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.4374 0.594579 0.092 0.032 0.000 0.076 0.800
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0703 0.862106 0.000 0.976 0.000 0.000 0.024
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1270 0.860925 0.000 0.948 0.000 0.000 0.052
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2389 0.717086 0.000 0.000 0.004 0.880 0.116
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1671 0.872784 0.924 0.000 0.000 0.000 0.076
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1043 0.940081 0.000 0.000 0.960 0.000 0.040
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1121 0.748032 0.000 0.000 0.000 0.956 0.044
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.1197 0.745569 0.000 0.000 0.000 0.952 0.048
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.2471 0.702300 0.000 0.000 0.000 0.864 0.136
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.2946 0.724694 0.000 0.044 0.000 0.868 0.088
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3814 0.688824 0.000 0.068 0.000 0.808 0.124
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0404 0.881378 0.988 0.000 0.000 0.000 0.012
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.2573 0.733329 0.000 0.016 0.000 0.880 0.104
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1732 0.871318 0.920 0.000 0.000 0.000 0.080
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.5807 0.551479 0.008 0.236 0.000 0.128 0.628
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.5122 0.511573 0.000 0.628 0.000 0.312 0.060
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.4494 0.427545 0.000 0.000 0.012 0.608 0.380
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.0290 0.752010 0.000 0.000 0.000 0.992 0.008
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.6419 0.506356 0.104 0.288 0.000 0.036 0.572
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0912 0.866112 0.000 0.972 0.000 0.012 0.016
#> C6FB2026-B740-459E-9831-93279BBF354E 4 0.6077 0.184828 0.000 0.396 0.000 0.480 0.124
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.4235 0.155868 0.000 0.000 0.000 0.576 0.424
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.4294 0.043380 0.000 0.000 0.000 0.532 0.468
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1907 0.847992 0.000 0.928 0.000 0.044 0.028
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.1671 0.873764 0.924 0.000 0.000 0.000 0.076
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.2771 0.693056 0.000 0.000 0.012 0.860 0.128
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.1732 0.871318 0.920 0.000 0.000 0.000 0.080
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1430 0.854731 0.000 0.944 0.000 0.052 0.004
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.5263 0.363403 0.000 0.056 0.000 0.368 0.576
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5066 0.439844 0.000 0.608 0.000 0.344 0.048
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1364 0.860518 0.000 0.952 0.000 0.012 0.036
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4167 0.650694 0.000 0.024 0.000 0.724 0.252
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0898 0.862653 0.000 0.972 0.000 0.008 0.020
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.3354 0.799002 0.000 0.844 0.000 0.068 0.088
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.1732 0.871451 0.920 0.000 0.000 0.000 0.080
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.5408 0.463981 0.000 0.228 0.000 0.652 0.120
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.5339 0.542402 0.000 0.224 0.000 0.660 0.116
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.5361 0.514964 0.000 0.000 0.188 0.668 0.144
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.4083 0.692443 0.000 0.080 0.000 0.788 0.132
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.1205 0.861768 0.000 0.956 0.000 0.004 0.040
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4649 0.678470 0.000 0.716 0.000 0.220 0.064
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0609 0.862583 0.000 0.980 0.000 0.000 0.020
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.4305 0.172445 0.512 0.000 0.000 0.000 0.488
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0510 0.863008 0.000 0.984 0.000 0.000 0.016
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.863401 0.000 1.000 0.000 0.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1478 0.860159 0.000 0.936 0.000 0.000 0.064
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1671 0.872784 0.924 0.000 0.000 0.000 0.076
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0703 0.862106 0.000 0.976 0.000 0.000 0.024
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.5736 0.230583 0.000 0.512 0.000 0.400 0.088
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.1270 0.861969 0.000 0.948 0.000 0.000 0.052
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5588 0.251139 0.052 0.000 0.560 0.012 0.376
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3812 0.775909 0.000 0.812 0.000 0.092 0.096
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.4030 0.590644 0.648 0.000 0.000 0.000 0.352
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.4305 0.706936 0.000 0.748 0.000 0.200 0.052
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.3146 0.685979 0.000 0.000 0.028 0.844 0.128
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0162 0.863637 0.000 0.996 0.000 0.000 0.004
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.4894 -0.016447 0.000 0.024 0.000 0.520 0.456
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#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.3197 0.723320 0.000 0.024 0.000 0.836 0.140
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.1300 0.753906 0.000 0.016 0.000 0.956 0.028
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.1205 0.861554 0.000 0.956 0.000 0.004 0.040
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 5 0.5425 0.374965 0.328 0.040 0.000 0.020 0.612
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.1845 0.854434 0.000 0.928 0.000 0.016 0.056
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1043 0.864367 0.000 0.960 0.000 0.000 0.040
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.5139 0.582143 0.000 0.648 0.000 0.280 0.072
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.1942 0.733977 0.000 0.000 0.012 0.920 0.068
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.1410 0.860436 0.000 0.940 0.000 0.000 0.060
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.4403 0.328517 0.000 0.000 0.008 0.384 0.608
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.3702 0.778582 0.000 0.820 0.000 0.096 0.084
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.4746 -0.034414 0.504 0.016 0.000 0.000 0.480
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1341 0.862514 0.000 0.944 0.000 0.000 0.056
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0404 0.881378 0.988 0.000 0.000 0.000 0.012
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 5 0.5795 0.521177 0.000 0.268 0.000 0.136 0.596
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1270 0.860627 0.000 0.948 0.000 0.000 0.052
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4712 0.478598 0.000 0.268 0.000 0.684 0.048
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0510 0.958642 0.000 0.000 0.984 0.000 0.016
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4168 0.719396 0.000 0.764 0.000 0.184 0.052
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.863401 0.000 1.000 0.000 0.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0955 0.864557 0.000 0.968 0.000 0.028 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.6823 -0.274189 0.372 0.388 0.000 0.004 0.236
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.6239 0.428380 0.004 0.172 0.000 0.268 0.556
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.6523 0.334495 0.000 0.248 0.000 0.484 0.268
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1251 0.861315 0.000 0.956 0.000 0.008 0.036
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0510 0.958642 0.000 0.000 0.984 0.000 0.016
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.4307 0.017498 0.496 0.000 0.000 0.000 0.504
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.5796 0.602183 0.076 0.148 0.000 0.080 0.696
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0451 0.864976 0.000 0.988 0.000 0.008 0.004
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0404 0.960202 0.000 0.000 0.988 0.000 0.012
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0404 0.864263 0.000 0.988 0.000 0.000 0.012
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 5 0.4060 0.406336 0.000 0.000 0.000 0.360 0.640
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.5083 0.554070 0.000 0.652 0.000 0.280 0.068
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.3280 0.665005 0.000 0.000 0.012 0.812 0.176
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4020 0.674639 0.000 0.096 0.000 0.796 0.108
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2569 0.833567 0.000 0.892 0.000 0.040 0.068
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4219 0.335989 0.584 0.000 0.000 0.000 0.416
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.2136 0.741583 0.000 0.008 0.000 0.904 0.088
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.5744 0.401415 0.000 0.332 0.000 0.564 0.104
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.1942 0.841683 0.000 0.920 0.000 0.068 0.012
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.6203 0.486503 0.004 0.296 0.000 0.152 0.548
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0771 0.864089 0.000 0.976 0.000 0.004 0.020
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.0510 0.751703 0.000 0.000 0.000 0.984 0.016
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0955 0.863140 0.000 0.968 0.000 0.004 0.028
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.2179 0.850691 0.000 0.000 0.888 0.000 0.112
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.5493 0.474214 0.000 0.264 0.000 0.628 0.108
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1197 0.862921 0.952 0.000 0.000 0.000 0.048
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2370 0.842921 0.000 0.904 0.000 0.040 0.056
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2329 0.851630 0.876 0.000 0.000 0.000 0.124
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.967307 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.5537 0.439596 0.256 0.084 0.000 0.012 0.648
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0290 0.864375 0.000 0.992 0.000 0.000 0.008
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.5411 0.496219 0.000 0.176 0.000 0.664 0.160
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.5107 0.655473 0.000 0.688 0.000 0.204 0.108
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1043 0.749965 0.000 0.000 0.000 0.960 0.040
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0510 0.863351 0.000 0.984 0.000 0.000 0.016
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0162 0.965299 0.000 0.000 0.996 0.000 0.004
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0609 0.751862 0.000 0.000 0.000 0.980 0.020
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.1205 0.861540 0.000 0.956 0.000 0.004 0.040
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2304 0.853936 0.000 0.908 0.000 0.044 0.048
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.5883 0.327513 0.000 0.368 0.000 0.524 0.108
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0290 0.863863 0.000 0.992 0.000 0.000 0.008
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0794 0.748825 0.000 0.000 0.000 0.972 0.028
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3657 0.783010 0.000 0.820 0.000 0.116 0.064
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1012 0.863281 0.000 0.968 0.000 0.012 0.020
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.2927 0.826614 0.000 0.872 0.000 0.068 0.060
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.4743 0.110353 0.000 0.000 0.016 0.472 0.512
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4811 0.120565 0.528 0.020 0.000 0.000 0.452
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0963 0.750086 0.000 0.000 0.000 0.964 0.036
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.5252 0.473522 0.000 0.292 0.000 0.632 0.076
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.5900 0.226312 0.000 0.376 0.000 0.516 0.108
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1943 0.857984 0.000 0.924 0.000 0.020 0.056
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.880837 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0404 0.864625 0.000 0.988 0.000 0.012 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.4777 0.322113 0.356 0.016 0.000 0.008 0.620
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6267 0.279937 0.000 0.000 0.540 0.224 0.236
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1043 0.862457 0.000 0.960 0.000 0.000 0.040
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2929 0.695371 0.000 0.000 0.000 0.820 0.180
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0880 0.871689 0.968 0.000 0.000 0.000 0.032
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.6056 0.420214 0.000 0.000 0.156 0.288 0.556
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2360 0.68691 0.000 0.900 0.000 0.012 0.044 0.044
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.5269 0.55645 0.024 0.268 0.000 0.024 0.644 0.040
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1897 0.72323 0.000 0.908 0.000 0.004 0.004 0.084
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 6 0.5254 0.57454 0.000 0.392 0.000 0.100 0.000 0.508
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2625 0.80692 0.872 0.000 0.000 0.000 0.056 0.072
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2300 0.69469 0.000 0.856 0.000 0.000 0.000 0.144
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.5059 0.42419 0.000 0.680 0.000 0.128 0.020 0.172
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0146 0.97239 0.000 0.000 0.996 0.000 0.004 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3314 0.65369 0.000 0.740 0.000 0.004 0.000 0.256
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0622 0.96559 0.000 0.000 0.980 0.000 0.008 0.012
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.3284 0.66553 0.000 0.784 0.000 0.020 0.000 0.196
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4669 0.42138 0.000 0.164 0.000 0.688 0.000 0.148
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.5012 0.27927 0.000 0.580 0.000 0.056 0.012 0.352
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.4949 0.16698 0.000 0.000 0.000 0.380 0.548 0.072
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0820 0.70672 0.000 0.000 0.000 0.972 0.016 0.012
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.3833 0.47029 0.000 0.648 0.000 0.008 0.000 0.344
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0790 0.84908 0.968 0.000 0.000 0.000 0.000 0.032
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0806 0.71114 0.000 0.000 0.000 0.972 0.008 0.020
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.6519 0.37738 0.000 0.080 0.000 0.528 0.152 0.240
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0717 0.70756 0.000 0.000 0.000 0.976 0.008 0.016
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3812 0.51390 0.000 0.016 0.000 0.712 0.004 0.268
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5544 0.48732 0.000 0.000 0.116 0.660 0.160 0.064
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1138 0.70808 0.000 0.960 0.000 0.004 0.012 0.024
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1010 0.71302 0.000 0.000 0.000 0.960 0.004 0.036
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.2555 0.69859 0.000 0.000 0.016 0.888 0.032 0.064
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 6 0.5976 0.56120 0.000 0.140 0.000 0.320 0.024 0.516
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3161 0.67771 0.000 0.776 0.000 0.008 0.000 0.216
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3680 0.58038 0.000 0.020 0.000 0.744 0.004 0.232
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.5549 0.55424 0.536 0.000 0.000 0.000 0.296 0.168
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.5479 0.39543 0.000 0.108 0.000 0.416 0.004 0.472
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.3248 0.83687 0.804 0.000 0.000 0.000 0.032 0.164
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.2221 0.70566 0.000 0.000 0.000 0.896 0.032 0.072
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.5996 0.05130 0.000 0.512 0.000 0.112 0.036 0.340
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.6217 -0.54869 0.000 0.384 0.000 0.316 0.004 0.296
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.4758 0.36960 0.000 0.000 0.016 0.356 0.596 0.032
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0551 0.71470 0.000 0.984 0.000 0.004 0.004 0.008
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0865 0.71302 0.000 0.000 0.000 0.964 0.000 0.036
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.5860 0.12147 0.000 0.548 0.000 0.136 0.024 0.292
#> 682C11E8-099C-466F-BC8A-B09A754205E3 6 0.5673 0.49244 0.000 0.396 0.000 0.156 0.000 0.448
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.2981 0.84001 0.820 0.000 0.000 0.000 0.020 0.160
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.5514 0.14782 0.000 0.080 0.000 0.520 0.020 0.380
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1080 0.71072 0.000 0.960 0.000 0.004 0.004 0.032
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.3264 0.64409 0.048 0.052 0.000 0.016 0.860 0.024
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0146 0.97239 0.000 0.000 0.996 0.000 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0260 0.71626 0.000 0.992 0.000 0.000 0.000 0.008
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.3081 0.67912 0.000 0.776 0.000 0.004 0.000 0.220
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2625 0.69936 0.000 0.000 0.000 0.872 0.056 0.072
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.3017 0.83904 0.816 0.000 0.000 0.000 0.020 0.164
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0790 0.84908 0.968 0.000 0.000 0.000 0.000 0.032
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2532 0.90945 0.000 0.000 0.892 0.020 0.052 0.036
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.2094 0.70818 0.000 0.000 0.000 0.900 0.020 0.080
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.1151 0.70077 0.000 0.000 0.000 0.956 0.032 0.012
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4254 0.57599 0.000 0.000 0.000 0.712 0.216 0.072
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4002 0.57739 0.000 0.036 0.000 0.736 0.008 0.220
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 6 0.5926 0.55221 0.000 0.140 0.000 0.328 0.020 0.512
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0146 0.97239 0.000 0.000 0.996 0.000 0.004 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1501 0.85662 0.924 0.000 0.000 0.000 0.000 0.076
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.3404 0.62057 0.000 0.000 0.000 0.760 0.016 0.224
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.3017 0.83904 0.816 0.000 0.000 0.000 0.020 0.164
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.4877 0.59309 0.008 0.232 0.000 0.040 0.688 0.032
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#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2653 0.71057 0.000 0.844 0.000 0.012 0.000 0.144
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.5403 0.57255 0.176 0.024 0.000 0.036 0.688 0.076
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 5 0.6539 0.18600 0.000 0.000 0.380 0.180 0.400 0.040
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2706 0.70591 0.000 0.832 0.000 0.008 0.000 0.160
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.3791 0.66543 0.000 0.004 0.000 0.768 0.048 0.180
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2625 0.80604 0.872 0.000 0.000 0.000 0.056 0.072
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.5419 0.49651 0.000 0.000 0.048 0.248 0.632 0.072
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 17581 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 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 0.962 0.945 0.978 0.4658 0.535 0.535
#> 3 3 0.932 0.925 0.971 0.2481 0.833 0.701
#> 4 4 0.633 0.731 0.831 0.1659 0.925 0.826
#> 5 5 0.631 0.697 0.798 0.1274 0.816 0.533
#> 6 6 0.725 0.536 0.762 0.0569 0.914 0.670
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9816 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.9754 0.2957 0.408 0.592
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9816 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9816 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9702 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9816 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9816 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9702 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9816 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9702 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9816 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9816 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9816 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9816 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0938 0.9705 0.012 0.988
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9816 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9702 1.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9816 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9816 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0376 0.9779 0.004 0.996
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9816 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.9087 0.5297 0.676 0.324
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9816 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0000 0.9816 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.7745 0.6969 0.228 0.772
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9816 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9816 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9816 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9702 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9816 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9702 1.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9816 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9816 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9816 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.0000 0.9702 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9816 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9816 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9816 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9816 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9702 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9816 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9816 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0376 0.9670 0.996 0.004
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.9702 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9816 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9816 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9816 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9702 1.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9702 1.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.9702 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.0000 0.9816 0.000 1.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0672 0.9743 0.008 0.992
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9816 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9816 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9816 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.9702 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9702 1.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.0000 0.9816 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9702 1.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.9977 0.0809 0.472 0.528
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9816 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.9522 0.4179 0.628 0.372
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9702 1.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9816 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.9661 0.3415 0.392 0.608
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9816 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9816 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.9816 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.0376 0.9670 0.996 0.004
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9816 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9702 1.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.0000 0.9702 1.000 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9702 1.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.9816 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.9816 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9816 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.9816 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9816 0.000 1.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9816 0.000 1.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9816 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9702 1.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.9816 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.9702 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9816 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.0000 0.9702 1.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9816 0.000 1.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9816 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9816 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9816 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.9702 1.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9816 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.9816 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9702 1.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9816 0.000 1.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9702 1.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9816 0.000 1.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.0000 0.9702 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.9816 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.9702 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9702 1.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9816 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.0000 0.9702 1.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.9702 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9816 0.000 1.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9702 1.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9816 0.000 1.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 1 0.8608 0.6099 0.716 0.284
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9702 1.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9816 0.000 1.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.9323 0.4546 0.348 0.652
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9816 0.000 1.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.7674 0.7012 0.224 0.776
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.0000 0.9702 1.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9816 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.9816 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9702 1.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9702 1.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9816 0.000 1.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0000 0.9816 0.000 1.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.9702 1.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9702 1.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.0000 0.9702 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9702 1.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.0000 0.9702 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.9816 0.000 1.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9816 0.000 1.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0376 0.9779 0.004 0.996
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0000 0.9816 0.000 1.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.9816 0.000 1.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.0000 0.9702 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 1 0.0000 0.9702 1.000 0.000
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#> D671E954-4CAC-4449-8EB1-163E478FE052 2 0.0000 0.9816 0.000 1.000
#> 33F20F2D-51A4-4038-B1C2-D5BE14BAB1CB 1 0.1184 0.9569 0.984 0.016
#> 9AF9E9CF-2D77-455E-8D47-10537BADD98F 2 0.0000 0.9816 0.000 1.000
#> 9E781A09-CBB2-496A-B3F6-B1B8B514836F 2 0.0000 0.9816 0.000 1.000
#> 4D112BD8-1A35-43CB-896A-16F48147811B 1 0.0000 0.9702 1.000 0.000
#> 0034ECFD-CA94-4615-94D2-E950A2B240ED 2 0.0000 0.9816 0.000 1.000
#> FBD43A48-C880-45FF-BB6A-08F922DE93B5 2 0.0000 0.9816 0.000 1.000
#> E5C1A89F-C3D9-4DC8-A35F-D2834B155843 2 0.0000 0.9816 0.000 1.000
#> 6A73B561-CF9C-49DD-8B8B-09036538CAA4 1 0.0000 0.9702 1.000 0.000
#> 795D478D-E1FE-49EB-92AD-8B1B145F944B 2 0.0000 0.9816 0.000 1.000
#> 6203B63E-6D3F-4399-B524-9573A9BD1E11 2 0.0000 0.9816 0.000 1.000
#> BDD03456-777B-4E94-8240-CD6B1D4EAC51 2 0.0000 0.9816 0.000 1.000
#> DE32121C-B7F5-4A94-9977-8F4B2D3BE976 2 0.0000 0.9816 0.000 1.000
#> 27C0EEBE-589F-41D9-8BF7-C7DA0ED87A3B 2 0.0000 0.9816 0.000 1.000
#> EE24DCB8-2927-42D4-AD8C-588EA01A64C7 2 0.0000 0.9816 0.000 1.000
#> A86D241D-FE25-40B7-A61C-B919D30FA545 2 0.0000 0.9816 0.000 1.000
#> 50A7A07E-B452-466D-97BF-978C4F9C47DA 2 0.8909 0.5510 0.308 0.692
#> 0E6AE036-64ED-4489-AE40-55F77089A890 2 0.0000 0.9816 0.000 1.000
#> BC9A5294-255F-47A4-8879-11C441093A3D 1 0.9775 0.3165 0.588 0.412
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.4022 0.8995 0.080 0.920
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 2 0.0000 0.9816 0.000 1.000
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 2 0.0000 0.9816 0.000 1.000
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 2 0.0000 0.9816 0.000 1.000
#> 3508F4B0-1ADA-4937-B924-424AC2596341 2 0.0000 0.9816 0.000 1.000
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 2 0.0000 0.9816 0.000 1.000
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 1 0.2603 0.9314 0.956 0.044
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.0000 0.9702 1.000 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.0000 0.9816 0.000 1.000
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.0000 0.9702 1.000 0.000
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 1 0.0000 0.9702 1.000 0.000
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.0000 0.9702 1.000 0.000
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.9702 1.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0000 0.9816 0.000 1.000
#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.0000 0.9702 1.000 0.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.0000 0.9816 0.000 1.000
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.0000 0.9816 0.000 1.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0000 0.9816 0.000 1.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.9816 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9816 0.000 1.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0000 0.9816 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0000 0.9816 0.000 1.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9702 1.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9702 1.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9816 0.000 1.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0000 0.9816 0.000 1.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 1 0.0000 0.9702 1.000 0.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.0000 0.9702 1.000 0.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9702 1.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9816 0.000 1.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.0000 0.9702 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0000 0.9816 0.000 1.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.8207 0.6629 0.744 0.256
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.9795 0.2737 0.416 0.584
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.0000 0.9702 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 1 0.0000 0.9702 1.000 0.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9816 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0376 0.9670 0.996 0.004
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.0000 0.9702 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.9816 0.000 1.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.9816 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.0000 0.9702 1.000 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0672 0.9743 0.008 0.992
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.9816 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9816 0.000 1.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9702 1.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9702 1.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0000 0.9816 0.000 1.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9816 0.000 1.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9816 0.000 1.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.9816 0.000 1.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9816 0.000 1.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9816 0.000 1.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.0000 0.9702 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9816 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.9816 0.000 1.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9816 0.000 1.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9816 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9816 0.000 1.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9816 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.0000 0.9702 1.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9816 0.000 1.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9702 1.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9816 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9816 0.000 1.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.9816 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9702 1.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9816 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9816 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9702 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.0000 0.9702 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9816 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9816 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9816 0.000 1.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9702 1.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9702 1.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9816 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9816 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9816 0.000 1.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9816 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9816 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.2043 0.9427 0.968 0.032
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9816 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9702 1.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9702 1.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9816 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9702 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9816 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9816 0.000 1.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9816 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0000 0.9702 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9816 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9816 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.9702 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9816 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9816 0.000 1.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.5059 0.8624 0.112 0.888
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1633 0.9589 0.024 0.976
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9816 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.9702 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.9702 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9702 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.9933 0.2022 0.548 0.452
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9816 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9702 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9816 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9816 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9816 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.1633 0.9589 0.024 0.976
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9816 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9816 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9702 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.9816 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9816 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9816 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9816 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9816 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9816 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9816 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9702 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9816 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9702 1.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9816 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9702 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9702 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9702 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1414 0.9534 0.980 0.020
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9816 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9816 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9816 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.2236 0.9468 0.036 0.964
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9816 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9702 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9816 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9816 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9702 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9816 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9816 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9816 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.5294 0.8534 0.880 0.120
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9816 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9816 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9816 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.0000 0.9702 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9702 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.9816 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9816 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9816 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9816 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9702 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9816 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9702 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9702 1.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9816 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9816 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9702 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9702 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9761 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.3619 0.7911 0.864 0.136 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9761 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9761 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9506 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9761 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9761 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9522 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9761 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9522 0.000 0.000 1.000
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#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9761 0.000 1.000 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0237 0.9726 0.004 0.996 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 3 0.0000 0.9522 0.000 0.000 1.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.2261 0.8888 0.932 0.000 0.068
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9506 1.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9761 0.000 1.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.9522 0.000 0.000 1.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0424 0.9691 0.008 0.992 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.0000 0.9506 1.000 0.000 0.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 3 0.0000 0.9522 0.000 0.000 1.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.9522 0.000 0.000 1.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 3 0.9106 0.4229 0.208 0.244 0.548
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9761 0.000 1.000 0.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0000 0.9506 1.000 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.9522 0.000 0.000 1.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.9761 0.000 1.000 0.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0592 0.9656 0.000 0.988 0.012
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.3116 0.8402 0.892 0.000 0.108
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 1 0.0000 0.9506 1.000 0.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.9761 0.000 1.000 0.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9761 0.000 1.000 0.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9506 1.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9506 1.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0000 0.9761 0.000 1.000 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9761 0.000 1.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0000 0.9761 0.000 1.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0892 0.9579 0.020 0.980 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9761 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9761 0.000 1.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9522 0.000 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9761 0.000 1.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0892 0.9580 0.020 0.980 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9761 0.000 1.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9761 0.000 1.000 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9761 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9761 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0000 0.9522 0.000 0.000 1.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9761 0.000 1.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9506 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9761 0.000 1.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9761 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.9761 0.000 1.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9506 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9761 0.000 1.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9761 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9506 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9522 0.000 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9761 0.000 1.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9761 0.000 1.000 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9761 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9506 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9506 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9761 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9761 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9761 0.000 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0237 0.9726 0.000 0.996 0.004
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9761 0.000 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.9522 0.000 0.000 1.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9761 0.000 1.000 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9506 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9506 1.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9761 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9506 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.6154 0.2891 0.408 0.592 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9761 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9761 0.000 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9522 0.000 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9761 0.000 1.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9761 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9522 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9761 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9761 0.000 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.5529 0.5666 0.704 0.296 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.3941 0.8036 0.156 0.844 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9761 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9522 0.000 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9522 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.2625 0.8670 0.916 0.000 0.084
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0000 0.9506 1.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9761 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0000 0.9522 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9761 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0237 0.9726 0.004 0.996 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9761 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.9522 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9761 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9761 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9506 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0747 0.9620 0.000 0.984 0.016
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9761 0.000 1.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9761 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.6252 0.2308 0.556 0.444 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9761 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9761 0.000 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9761 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0000 0.9522 0.000 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9761 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9506 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9761 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9522 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9506 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9522 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9506 1.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9761 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9761 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9761 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.1643 0.9063 0.000 0.044 0.956
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9761 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9522 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9761 0.000 1.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9761 0.000 1.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9506 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9761 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9761 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9761 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.9522 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9761 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9761 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9761 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.9522 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9506 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.9761 0.000 1.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9761 0.000 1.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9761 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9761 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9506 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9761 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9506 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9522 0.000 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9761 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6308 0.0156 0.000 0.508 0.492
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9506 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.0000 0.9522 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4431 0.4400 0.000 0.696 0.000 0.304
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.6702 0.6140 0.216 0.168 0.000 0.616
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4222 0.7458 0.000 0.728 0.000 0.272
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3024 0.7708 0.000 0.852 0.000 0.148
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2868 0.7353 0.000 0.864 0.000 0.136
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4331 0.7444 0.000 0.712 0.000 0.288
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1474 0.7643 0.000 0.948 0.000 0.052
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.2589 0.7515 0.000 0.884 0.000 0.116
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6774 0.5784 0.000 0.312 0.120 0.568
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1978 0.8230 0.000 0.068 0.928 0.004
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.1389 0.7650 0.000 0.952 0.000 0.048
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.2329 0.7411 0.000 0.916 0.012 0.072
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.4706 0.7546 0.000 0.732 0.020 0.248
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0469 0.8778 0.000 0.012 0.988 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5351 0.7041 0.000 0.744 0.152 0.104
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.1677 0.8545 0.000 0.012 0.948 0.040
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4304 0.7437 0.000 0.716 0.000 0.284
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.6500 0.0635 0.000 0.444 0.484 0.072
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.6113 0.4141 0.000 0.284 0.636 0.080
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.1022 0.7657 0.000 0.968 0.000 0.032
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4406 0.7428 0.000 0.700 0.000 0.300
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.2402 0.7533 0.000 0.912 0.012 0.076
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.4981 0.0669 0.536 0.000 0.000 0.464
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.1792 0.7621 0.000 0.932 0.000 0.068
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.5366 0.7331 0.000 0.684 0.040 0.276
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4382 0.7437 0.000 0.704 0.000 0.296
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4114 0.7184 0.000 0.828 0.112 0.060
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.2179 0.8398 0.000 0.012 0.924 0.064
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3356 0.6769 0.000 0.824 0.000 0.176
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.1305 0.8595 0.000 0.036 0.960 0.004
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4222 0.7462 0.000 0.728 0.000 0.272
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#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.4193 0.7457 0.000 0.732 0.000 0.268
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.6770 0.0844 0.292 0.580 0.000 0.128
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 3 0.0000 0.8816 0.000 0.000 1.000 0.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.6786 0.3840 0.344 0.020 0.064 0.572
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.4406 0.7422 0.000 0.700 0.000 0.300
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.1867 0.8631 0.000 0.000 0.928 0.072
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.5366 0.6892 0.040 0.684 0.000 0.276
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 4 0.5590 0.1735 0.456 0.020 0.000 0.524
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 3 0.5851 0.4979 0.000 0.236 0.680 0.084
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 3 0.8064 0.0216 0.032 0.360 0.460 0.148
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.2589 0.7241 0.000 0.884 0.000 0.116
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.2589 0.8025 0.884 0.000 0.000 0.116
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.2760 0.7212 0.000 0.872 0.000 0.128
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.5427 0.5562 0.000 0.416 0.016 0.568
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.5581 0.1526 0.532 0.000 0.448 0.020
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 1 0.5272 0.5693 0.752 0.136 0.000 0.112
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.5666 0.6345 0.000 0.348 0.036 0.616
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.1118 0.7666 0.000 0.964 0.000 0.036
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.2845 0.7811 0.028 0.896 0.000 0.076
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.2149 0.7562 0.000 0.912 0.000 0.088
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.4454 0.7424 0.000 0.692 0.000 0.308
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.4035 0.6463 0.020 0.804 0.000 0.176
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4193 0.7503 0.000 0.732 0.000 0.268
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.4406 0.7437 0.000 0.700 0.000 0.300
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.3528 0.6649 0.000 0.808 0.000 0.192
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.1637 0.7619 0.000 0.940 0.000 0.060
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4382 0.7434 0.000 0.704 0.000 0.296
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.3649 0.7729 0.000 0.796 0.000 0.204
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.2760 0.8133 0.000 0.000 0.872 0.128
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.2530 0.7323 0.000 0.888 0.000 0.112
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2469 0.8165 0.892 0.000 0.000 0.108
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.4331 0.7444 0.000 0.712 0.000 0.288
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.3636 0.6348 0.000 0.820 0.008 0.172
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.2814 0.7189 0.000 0.868 0.000 0.132
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.2149 0.7542 0.000 0.912 0.000 0.088
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.4977 0.0799 0.540 0.000 0.000 0.460
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1867 0.8631 0.000 0.000 0.928 0.072
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.4431 0.7407 0.000 0.696 0.000 0.304
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.2345 0.7299 0.000 0.900 0.000 0.100
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.3311 0.6816 0.000 0.828 0.000 0.172
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.5646 0.4212 0.672 0.056 0.000 0.272
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.2760 0.7212 0.000 0.872 0.000 0.128
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4331 0.7439 0.000 0.712 0.000 0.288
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4222 0.7458 0.000 0.728 0.000 0.272
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.4337 0.6470 0.000 0.808 0.140 0.052
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4406 0.7422 0.000 0.700 0.000 0.300
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.5496 0.1639 0.000 0.024 0.372 0.604
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.3356 0.7698 0.000 0.824 0.000 0.176
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.2149 0.8319 0.912 0.000 0.000 0.088
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4431 0.7420 0.000 0.696 0.000 0.304
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.6336 0.6840 0.088 0.304 0.000 0.608
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4222 0.7455 0.000 0.728 0.000 0.272
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.4008 0.5384 0.000 0.756 0.000 0.244
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1867 0.8631 0.000 0.000 0.928 0.072
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4454 0.7424 0.000 0.692 0.000 0.308
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4605 0.7162 0.000 0.664 0.000 0.336
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4193 0.7457 0.000 0.732 0.000 0.268
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.7780 -0.1025 0.428 0.300 0.000 0.272
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.6442 -0.3310 0.068 0.492 0.000 0.440
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.5416 0.6377 0.112 0.740 0.000 0.148
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1474 0.7663 0.000 0.948 0.000 0.052
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1867 0.8631 0.000 0.000 0.928 0.072
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.3133 0.8137 0.900 0.036 0.036 0.028
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.5894 0.3414 0.392 0.040 0.000 0.568
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.1389 0.7711 0.000 0.952 0.000 0.048
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4356 0.7431 0.000 0.708 0.000 0.292
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4643 0.6281 0.000 0.344 0.000 0.656
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.4331 0.7444 0.000 0.712 0.000 0.288
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.4236 0.7779 0.000 0.088 0.824 0.088
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.1474 0.7647 0.000 0.948 0.000 0.052
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2704 0.7851 0.000 0.876 0.000 0.124
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.3745 0.7084 0.000 0.852 0.060 0.088
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.1637 0.7633 0.000 0.940 0.000 0.060
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.2973 0.7683 0.000 0.856 0.000 0.144
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.6452 0.6734 0.116 0.260 0.000 0.624
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.2216 0.7504 0.000 0.908 0.000 0.092
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.2469 0.7404 0.000 0.892 0.000 0.108
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4713 0.7111 0.000 0.640 0.000 0.360
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.1940 0.7488 0.000 0.924 0.000 0.076
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0188 0.9196 0.996 0.000 0.000 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4164 0.7508 0.000 0.736 0.000 0.264
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.6000 0.4175 0.356 0.052 0.000 0.592
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.2530 0.7795 0.000 0.888 0.000 0.112
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3266 0.7671 0.000 0.832 0.000 0.168
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1557 0.7687 0.000 0.944 0.000 0.056
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.6764 0.3908 0.000 0.260 0.596 0.144
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2704 0.7425 0.000 0.876 0.000 0.124
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.8816 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.3383 0.7580 0.000 0.872 0.076 0.052
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4697 0.7412 0.008 0.696 0.000 0.296
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0188 0.9196 0.996 0.000 0.000 0.004
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4454 0.7394 0.000 0.692 0.000 0.308
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0921 0.7765 0.000 0.972 0.000 0.028
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1792 0.7741 0.000 0.932 0.000 0.068
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0927 0.8770 0.000 0.008 0.976 0.016
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4543 0.7324 0.000 0.676 0.000 0.324
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0921 0.7709 0.000 0.972 0.000 0.028
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.2760 0.7221 0.000 0.872 0.000 0.128
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.1302 0.8721 0.000 0.000 0.956 0.044
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.3463 0.7147 0.000 0.864 0.040 0.096
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.2345 0.7351 0.000 0.900 0.000 0.100
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2760 0.7212 0.000 0.872 0.000 0.128
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4304 0.7463 0.000 0.716 0.000 0.284
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2530 0.7804 0.000 0.888 0.000 0.112
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2376 0.8498 0.916 0.000 0.016 0.068
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0188 0.8819 0.000 0.000 0.996 0.004
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4193 0.7460 0.000 0.732 0.000 0.268
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.6919 0.1994 0.000 0.368 0.516 0.116
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9228 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.2002 0.8449 0.000 0.020 0.936 0.044
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.5379 0.4336 0.000 0.108 0.000 0.648 0.244
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.4867 0.6502 0.028 0.020 0.000 0.260 0.692
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3143 0.7396 0.000 0.796 0.000 0.204 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.3582 0.5921 0.000 0.224 0.000 0.768 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0963 0.9178 0.964 0.000 0.000 0.000 0.036
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4398 0.6282 0.000 0.240 0.000 0.720 0.040
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3048 0.6691 0.000 0.820 0.000 0.176 0.004
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9005 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2813 0.7731 0.000 0.832 0.000 0.168 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9005 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.3550 0.6512 0.000 0.236 0.000 0.760 0.004
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.3236 0.6563 0.000 0.152 0.000 0.828 0.020
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2127 0.7836 0.000 0.892 0.000 0.108 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.6741 0.2667 0.000 0.116 0.036 0.352 0.496
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1211 0.8881 0.000 0.000 0.960 0.024 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3266 0.6778 0.000 0.200 0.000 0.796 0.004
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9493 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.1484 0.7015 0.000 0.048 0.008 0.944 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4930 0.6114 0.000 0.268 0.052 0.676 0.004
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0290 0.8967 0.000 0.000 0.992 0.008 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.5528 0.6033 0.000 0.216 0.140 0.644 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.3120 0.7732 0.000 0.048 0.864 0.084 0.004
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.2377 0.7844 0.000 0.872 0.000 0.128 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.4347 0.6030 0.000 0.040 0.212 0.744 0.004
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.7551 -0.0126 0.000 0.228 0.396 0.328 0.048
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.1410 0.6992 0.000 0.060 0.000 0.940 0.000
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#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4269 0.5957 0.000 0.188 0.000 0.756 0.056
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4330 0.6541 0.000 0.204 0.008 0.752 0.036
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4015 0.3921 0.000 0.652 0.000 0.348 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9493 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.3990 0.5979 0.000 0.308 0.000 0.688 0.004
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.4082 0.7201 0.788 0.012 0.036 0.000 0.164
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.0000 0.9005 0.000 0.000 1.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2230 0.7822 0.000 0.884 0.000 0.116 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.5450 0.5234 0.000 0.044 0.176 0.708 0.072
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9493 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.5776 0.5767 0.076 0.060 0.700 0.160 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.4800 0.37047 0.000 0.008 0.000 0.680 0.212 0.100
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.5262 -0.13835 0.000 0.000 0.000 0.452 0.452 0.096
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0363 0.85007 0.000 0.988 0.000 0.012 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.0520 0.52180 0.000 0.008 0.000 0.984 0.000 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2402 0.78935 0.868 0.000 0.000 0.000 0.120 0.012
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.6187 0.36989 0.000 0.112 0.000 0.352 0.048 0.488
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3133 0.65533 0.000 0.780 0.000 0.008 0.000 0.212
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1984 0.80546 0.000 0.912 0.000 0.056 0.000 0.032
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.4807 0.27033 0.000 0.052 0.000 0.464 0.000 0.484
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0508 0.52160 0.000 0.004 0.000 0.984 0.000 0.012
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.6870 0.31601 0.000 0.012 0.036 0.216 0.312 0.424
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.3915 0.82315 0.000 0.000 0.584 0.000 0.004 0.412
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3961 -0.06620 0.000 0.004 0.000 0.556 0.000 0.440
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2178 0.49640 0.000 0.000 0.000 0.868 0.000 0.132
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.4399 0.38549 0.004 0.028 0.000 0.352 0.000 0.616
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> A4967738-7FC2-4270-A149-56E459EDB875 6 0.5481 0.04391 0.000 0.056 0.156 0.124 0.000 0.664
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.3126 -0.27326 0.000 0.000 0.248 0.000 0.000 0.752
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0146 0.85262 0.000 0.996 0.000 0.000 0.004 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1838 0.50131 0.000 0.000 0.068 0.916 0.000 0.016
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.6382 0.38223 0.000 0.048 0.344 0.140 0.000 0.468
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.2703 0.46597 0.000 0.004 0.000 0.824 0.000 0.172
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1765 0.50222 0.000 0.000 0.000 0.904 0.000 0.096
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 5 0.2883 0.63444 0.212 0.000 0.000 0.000 0.788 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.4757 0.26202 0.000 0.048 0.000 0.468 0.000 0.484
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.1820 0.81818 0.000 0.924 0.012 0.008 0.000 0.056
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.2972 0.41772 0.000 0.036 0.000 0.128 0.000 0.836
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4814 0.78651 0.000 0.000 0.532 0.056 0.000 0.412
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4841 0.37879 0.000 0.012 0.000 0.684 0.204 0.100
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4648 0.79418 0.000 0.000 0.548 0.044 0.000 0.408
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 6 0.5421 0.34064 0.000 0.116 0.000 0.432 0.000 0.452
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4136 -0.05089 0.000 0.012 0.000 0.560 0.000 0.428
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 4 0.2944 0.46503 0.092 0.028 0.000 0.860 0.000 0.020
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.0260 0.75680 0.008 0.000 0.000 0.000 0.992 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 4 0.0935 0.52029 0.000 0.004 0.000 0.964 0.000 0.032
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.4512 0.01171 0.000 0.456 0.520 0.004 0.004 0.016
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2362 0.71554 0.000 0.000 0.860 0.000 0.004 0.136
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1930 0.51394 0.000 0.036 0.012 0.924 0.000 0.028
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.5573 0.37622 0.000 0.012 0.000 0.304 0.124 0.560
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.5637 0.46905 0.000 0.204 0.004 0.232 0.560 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5361 0.26587 0.000 0.576 0.000 0.268 0.000 0.156
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.2100 0.49049 0.000 0.004 0.000 0.884 0.000 0.112
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0935 0.52006 0.000 0.004 0.000 0.964 0.000 0.032
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.1897 0.73245 0.004 0.000 0.000 0.004 0.908 0.084
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0363 0.85007 0.000 0.988 0.000 0.012 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.6383 0.10760 0.000 0.000 0.292 0.520 0.088 0.100
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 6 0.5940 0.34775 0.000 0.348 0.000 0.192 0.004 0.456
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.4403 0.60805 0.004 0.000 0.000 0.172 0.724 0.100
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.4747 0.38197 0.000 0.008 0.000 0.688 0.204 0.100
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0260 0.85172 0.000 0.992 0.000 0.008 0.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.3812 0.51297 0.000 0.000 0.000 0.264 0.712 0.024
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 5 0.4807 0.27974 0.000 0.012 0.024 0.008 0.588 0.368
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4136 0.19513 0.000 0.560 0.000 0.012 0.000 0.428
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 6 0.3741 -0.16345 0.000 0.000 0.208 0.032 0.004 0.756
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0405 0.92063 0.988 0.000 0.000 0.000 0.008 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.4929 0.04386 0.000 0.508 0.000 0.064 0.000 0.428
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.6008 0.10150 0.000 0.460 0.000 0.004 0.316 0.220
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.4263 0.00489 0.000 0.000 0.000 0.480 0.504 0.016
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0260 0.85198 0.000 0.992 0.000 0.000 0.000 0.008
#> 8751D026-849B-44ED-933B-FD9B80DE329E 6 0.5951 0.36818 0.000 0.200 0.004 0.332 0.000 0.464
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.2933 0.43741 0.000 0.004 0.000 0.796 0.000 0.200
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.3508 0.29617 0.000 0.004 0.000 0.704 0.000 0.292
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0260 0.92214 0.992 0.000 0.000 0.000 0.008 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.5016 -0.26127 0.000 0.012 0.000 0.488 0.044 0.456
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.2948 0.41807 0.000 0.008 0.000 0.804 0.000 0.188
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0146 0.64035 0.000 0.000 0.996 0.000 0.004 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 6 0.6569 -0.23756 0.000 0.308 0.064 0.132 0.004 0.492
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.4762 0.37987 0.008 0.000 0.000 0.688 0.200 0.104
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.2613 0.46631 0.000 0.000 0.000 0.848 0.140 0.012
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0146 0.85278 0.000 0.996 0.000 0.004 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0790 0.89831 0.968 0.000 0.000 0.032 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.5069 -0.05916 0.000 0.484 0.000 0.076 0.000 0.440
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.6770 0.30506 0.000 0.192 0.000 0.100 0.200 0.508
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0146 0.85278 0.000 0.996 0.000 0.004 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0458 0.84867 0.000 0.984 0.000 0.016 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0291 0.64299 0.000 0.000 0.992 0.000 0.004 0.004
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4804 -0.27708 0.000 0.052 0.000 0.492 0.000 0.456
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0146 0.64035 0.000 0.000 0.996 0.000 0.004 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0146 0.92480 0.996 0.000 0.000 0.000 0.000 0.004
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.4614 0.80210 0.032 0.000 0.548 0.000 0.004 0.416
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.2738 0.43559 0.000 0.004 0.000 0.820 0.000 0.176
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 5 0.3446 0.50203 0.308 0.000 0.000 0.000 0.692 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.85263 0.000 1.000 0.000 0.000 0.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 6 0.2801 0.28506 0.000 0.000 0.068 0.072 0.000 0.860
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0790 0.83646 0.000 0.968 0.000 0.032 0.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.1908 0.48885 0.000 0.000 0.000 0.900 0.096 0.004
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 6 0.4118 0.39583 0.000 0.020 0.000 0.352 0.000 0.628
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.1444 0.74390 0.000 0.000 0.000 0.072 0.928 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.4165 0.81579 0.000 0.000 0.568 0.004 0.008 0.420
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.4473 -0.06262 0.000 0.480 0.000 0.492 0.000 0.028
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.4804 -0.27708 0.000 0.052 0.000 0.492 0.000 0.456
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4804 -0.27673 0.000 0.052 0.000 0.492 0.000 0.456
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0935 0.83644 0.000 0.964 0.000 0.032 0.000 0.004
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.4446 0.31597 0.580 0.008 0.004 0.396 0.000 0.012
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.2212 0.77229 0.000 0.880 0.000 0.008 0.000 0.112
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.1531 0.51901 0.000 0.004 0.000 0.928 0.000 0.068
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 6 0.2664 0.40368 0.000 0.000 0.000 0.184 0.000 0.816
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0291 0.85326 0.000 0.992 0.000 0.004 0.000 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 6 0.4903 0.26071 0.000 0.060 0.000 0.468 0.000 0.472
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0146 0.64035 0.000 0.000 0.996 0.000 0.004 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.1471 0.67790 0.000 0.000 0.932 0.000 0.004 0.064
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.1370 0.51725 0.000 0.004 0.000 0.948 0.036 0.012
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#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.1908 0.80586 0.000 0.916 0.000 0.056 0.000 0.028
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.3456 0.65432 0.000 0.172 0.040 0.000 0.788 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.3253 0.40496 0.000 0.192 0.000 0.788 0.000 0.020
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.6328 0.36693 0.584 0.004 0.000 0.108 0.200 0.104
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0260 0.85198 0.000 0.992 0.000 0.000 0.000 0.008
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 5 0.1949 0.73058 0.004 0.000 0.000 0.004 0.904 0.088
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0806 0.84788 0.000 0.972 0.000 0.008 0.000 0.020
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4414 0.39108 0.000 0.000 0.000 0.704 0.204 0.092
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0146 0.64035 0.000 0.000 0.996 0.000 0.004 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0405 0.85076 0.000 0.988 0.000 0.004 0.000 0.008
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.5348 0.53181 0.000 0.676 0.000 0.052 0.156 0.116
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.3881 0.82142 0.000 0.000 0.600 0.000 0.004 0.396
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0146 0.85278 0.000 0.996 0.000 0.004 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0865 0.82795 0.036 0.964 0.000 0.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.4745 0.36261 0.000 0.004 0.000 0.676 0.220 0.100
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.4655 0.38540 0.000 0.004 0.000 0.692 0.200 0.104
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.4532 -0.20621 0.000 0.032 0.000 0.500 0.000 0.468
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0146 0.64035 0.000 0.000 0.996 0.000 0.004 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.1223 0.89908 0.960 0.012 0.000 0.016 0.004 0.008
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.1124 0.75283 0.008 0.000 0.000 0.000 0.956 0.036
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.4901 -0.24018 0.000 0.060 0.000 0.484 0.000 0.456
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0260 0.85198 0.000 0.992 0.000 0.000 0.000 0.008
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 5 0.3388 0.61635 0.000 0.000 0.000 0.172 0.792 0.036
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.5782 0.26274 0.000 0.400 0.000 0.176 0.000 0.424
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.3851 -0.04794 0.000 0.000 0.540 0.460 0.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3907 -0.04495 0.000 0.004 0.000 0.588 0.000 0.408
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 4 0.2311 0.50908 0.000 0.016 0.000 0.880 0.000 0.104
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.1049 0.51980 0.000 0.008 0.000 0.960 0.000 0.032
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.2772 0.43084 0.000 0.004 0.000 0.816 0.000 0.180
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.2553 0.48935 0.000 0.008 0.000 0.848 0.000 0.144
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.1933 0.74996 0.004 0.044 0.000 0.032 0.920 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.4132 0.41663 0.000 0.004 0.000 0.756 0.136 0.104
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.3314 0.37104 0.000 0.004 0.000 0.740 0.000 0.256
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2412 0.76653 0.000 0.880 0.000 0.000 0.092 0.028
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.2320 0.49775 0.000 0.004 0.000 0.864 0.000 0.132
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.3754 0.43743 0.000 0.152 0.000 0.776 0.000 0.072
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0146 0.92459 0.996 0.000 0.000 0.000 0.004 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.6352 0.42661 0.092 0.000 0.000 0.272 0.536 0.100
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.5034 -0.31158 0.000 0.072 0.000 0.472 0.000 0.456
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.4322 0.46696 0.000 0.016 0.000 0.280 0.680 0.024
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.3395 0.47355 0.000 0.060 0.000 0.808 0.000 0.132
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.3479 0.45388 0.000 0.000 0.088 0.820 0.008 0.084
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.5994 -0.07234 0.000 0.360 0.000 0.452 0.008 0.180
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.3915 0.82403 0.000 0.000 0.584 0.000 0.004 0.412
#> 05127463-A69A-42B3-9635-575A08EB980A 6 0.4552 0.38640 0.000 0.044 0.000 0.364 0.000 0.592
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0146 0.85219 0.000 0.996 0.000 0.000 0.000 0.004
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4109 0.32785 0.000 0.576 0.000 0.412 0.000 0.012
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.2882 0.46151 0.000 0.008 0.000 0.812 0.000 0.180
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.5916 -0.16544 0.000 0.336 0.000 0.444 0.000 0.220
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.6128 0.42265 0.000 0.000 0.344 0.316 0.000 0.340
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3470 0.61068 0.000 0.740 0.000 0.248 0.000 0.012
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.4109 -0.00565 0.000 0.012 0.000 0.576 0.000 0.412
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.4841 0.37940 0.000 0.012 0.000 0.684 0.204 0.100
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.3728 0.80598 0.000 0.000 0.652 0.000 0.004 0.344
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0520 0.91832 0.984 0.000 0.000 0.000 0.008 0.008
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.2700 0.48032 0.000 0.004 0.004 0.836 0.000 0.156
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2930 0.48420 0.000 0.072 0.004 0.868 0.044 0.012
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.5411 0.28341 0.000 0.012 0.000 0.420 0.080 0.488
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 6 0.5836 0.29817 0.000 0.392 0.000 0.188 0.000 0.420
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.5387 0.33336 0.000 0.112 0.000 0.424 0.000 0.464
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3922 0.69779 0.776 0.000 0.124 0.000 0.096 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.3950 0.81254 0.000 0.000 0.564 0.000 0.004 0.432
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0146 0.85280 0.000 0.996 0.000 0.000 0.000 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2145 0.50613 0.000 0.000 0.072 0.900 0.000 0.028
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.92684 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.2703 0.12581 0.016 0.000 0.116 0.008 0.000 0.860
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 17581 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 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 0.0991 0.577 0.750 0.3667 0.770 0.770
#> 3 3 0.1380 0.655 0.734 0.4434 0.755 0.685
#> 4 4 0.2534 0.479 0.717 0.1859 0.896 0.809
#> 5 5 0.3465 0.483 0.711 0.0861 0.962 0.915
#> 6 6 0.4079 0.408 0.655 0.0627 0.902 0.768
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.605 0.6665 0.148 0.852
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.936 0.2539 0.352 0.648
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.443 0.7072 0.092 0.908
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.689 0.6139 0.184 0.816
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.992 0.1248 0.448 0.552
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.850 0.6009 0.276 0.724
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.871 0.5888 0.292 0.708
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.876 0.8554 0.704 0.296
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.416 0.7060 0.084 0.916
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.891 0.8500 0.692 0.308
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.850 0.6009 0.276 0.724
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.574 0.6676 0.136 0.864
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.416 0.7053 0.084 0.916
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.808 0.6481 0.248 0.752
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.653 0.6355 0.168 0.832
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.416 0.7220 0.084 0.916
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.992 0.1523 0.448 0.552
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.634 0.6415 0.160 0.840
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.506 0.7242 0.112 0.888
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.781 0.6665 0.232 0.768
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.430 0.7203 0.088 0.912
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.861 0.6260 0.284 0.716
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.518 0.7223 0.116 0.884
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.644 0.6363 0.164 0.836
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.855 0.6114 0.280 0.720
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.388 0.7011 0.076 0.924
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.443 0.7062 0.092 0.908
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.760 0.6778 0.220 0.780
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.996 0.0832 0.464 0.536
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.814 0.6326 0.252 0.748
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.999 0.1320 0.484 0.516
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.689 0.6851 0.184 0.816
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.430 0.7149 0.088 0.912
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.753 0.6590 0.216 0.784
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.653 0.6325 0.168 0.832
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.605 0.6665 0.148 0.852
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.595 0.6600 0.144 0.856
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#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.980 0.1542 0.416 0.584
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.416 0.7064 0.084 0.916
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.402 0.7065 0.080 0.920
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.260 0.7116 0.044 0.956
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.821 0.6491 0.256 0.744
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.506 0.7037 0.112 0.888
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.966 0.0529 0.392 0.608
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.518 0.7059 0.116 0.884
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.992 0.1032 0.448 0.552
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.866 0.4162 0.288 0.712
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.506 0.7037 0.112 0.888
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.995 0.0987 0.460 0.540
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.839 0.6527 0.268 0.732
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.388 0.7096 0.076 0.924
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.574 0.6614 0.136 0.864
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.871 0.8528 0.708 0.292
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.814 0.6438 0.252 0.748
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.722 0.7089 0.200 0.800
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.876 0.8554 0.704 0.296
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.402 0.7079 0.080 0.920
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.936 0.3592 0.352 0.648
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.821 0.5428 0.256 0.744
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.402 0.7064 0.080 0.920
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.343 0.7160 0.064 0.936
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.871 0.8528 0.708 0.292
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.886 0.8543 0.696 0.304
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.981 0.6988 0.580 0.420
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.827 0.6403 0.260 0.740
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.760 0.6509 0.220 0.780
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.958 0.2943 0.620 0.380
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.644 0.6868 0.164 0.836
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.753 0.6732 0.216 0.784
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.802 0.6243 0.244 0.756
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.574 0.6647 0.136 0.864
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.443 0.7136 0.092 0.908
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.416 0.7189 0.084 0.916
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 2 1.000 -0.3817 0.500 0.500
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.998 -0.4181 0.472 0.528
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.388 0.7095 0.076 0.924
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.430 0.6930 0.088 0.912
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.730 0.6951 0.204 0.796
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.358 0.6985 0.068 0.932
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.584 0.6605 0.140 0.860
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.689 0.7037 0.184 0.816
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.891 0.6000 0.308 0.692
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.358 0.7175 0.068 0.932
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.995 0.2548 0.460 0.540
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.373 0.7152 0.072 0.928
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.886 0.8543 0.696 0.304
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.999 0.1320 0.484 0.516
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.886 0.8543 0.696 0.304
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.881 0.4476 0.300 0.700
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.795 0.6340 0.240 0.760
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.388 0.7174 0.076 0.924
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.430 0.7063 0.088 0.912
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.584 0.6626 0.140 0.860
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.584 0.7085 0.140 0.860
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.891 0.8520 0.692 0.308
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.775 0.6596 0.228 0.772
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.680 0.7108 0.180 0.820
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.980 0.1792 0.416 0.584
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.430 0.7117 0.088 0.912
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.358 0.7157 0.068 0.932
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.595 0.7150 0.144 0.856
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.653 0.6325 0.168 0.832
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.775 0.5320 0.228 0.772
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.358 0.7146 0.068 0.932
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.625 0.6648 0.156 0.844
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.839 0.6490 0.268 0.732
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.997 -0.0906 0.532 0.468
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.634 0.6584 0.160 0.840
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.605 0.6536 0.148 0.852
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.850 0.6200 0.276 0.724
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.541 0.7011 0.124 0.876
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.980 0.1542 0.416 0.584
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.855 0.5997 0.280 0.720
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.997 -0.0906 0.532 0.468
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.886 0.6039 0.304 0.696
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.402 0.7052 0.080 0.920
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.662 0.6162 0.172 0.828
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.995 0.2548 0.460 0.540
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.886 0.6039 0.304 0.696
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.632 0.68748 0.112 0.772 0.116
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.974 -0.04531 0.276 0.448 0.276
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.341 0.72440 0.080 0.900 0.020
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.706 0.65040 0.100 0.720 0.180
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.619 0.80349 0.744 0.216 0.040
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.708 0.54539 0.356 0.612 0.032
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.746 0.48828 0.400 0.560 0.040
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.486 0.85777 0.116 0.044 0.840
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.296 0.71996 0.080 0.912 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.509 0.85320 0.112 0.056 0.832
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.717 0.54321 0.352 0.612 0.036
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.627 0.69564 0.076 0.768 0.156
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.327 0.72068 0.080 0.904 0.016
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.709 0.60183 0.320 0.640 0.040
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.689 0.66045 0.088 0.728 0.184
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.377 0.75608 0.084 0.888 0.028
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.610 0.80316 0.740 0.228 0.032
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.676 0.66680 0.084 0.736 0.180
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.591 0.72801 0.156 0.784 0.060
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.748 0.62240 0.284 0.648 0.068
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.453 0.75323 0.088 0.860 0.052
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.790 0.57110 0.312 0.608 0.080
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.541 0.72896 0.156 0.804 0.040
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.684 0.66099 0.088 0.732 0.180
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.757 0.54960 0.356 0.592 0.052
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.385 0.74146 0.028 0.884 0.088
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.399 0.71885 0.108 0.872 0.020
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.726 0.65852 0.248 0.680 0.072
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.649 0.78582 0.752 0.172 0.076
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.716 0.58710 0.332 0.628 0.040
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.493 0.78636 0.820 0.156 0.024
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.577 0.69483 0.220 0.756 0.024
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.321 0.73603 0.092 0.900 0.008
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.623 0.63705 0.316 0.672 0.012
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.689 0.65714 0.088 0.728 0.184
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.632 0.68748 0.112 0.772 0.116
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.560 0.70530 0.060 0.804 0.136
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.321 0.72330 0.084 0.904 0.012
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.679 0.60301 0.292 0.672 0.036
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.896 0.51624 0.564 0.192 0.244
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.219 0.74660 0.024 0.948 0.028
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.498 0.74169 0.096 0.840 0.064
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.829 0.41394 0.512 0.408 0.080
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.499 0.85753 0.112 0.052 0.836
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.552 0.71188 0.120 0.812 0.068
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.327 0.72068 0.080 0.904 0.016
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.706 0.64872 0.264 0.680 0.056
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.493 0.78636 0.820 0.156 0.024
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.564 0.74420 0.752 0.232 0.016
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.949 -0.02626 0.184 0.424 0.392
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.828 0.11248 0.080 0.404 0.516
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.789 0.51348 0.372 0.564 0.064
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.398 0.75006 0.068 0.884 0.048
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.666 0.70671 0.120 0.752 0.128
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.566 0.73365 0.104 0.808 0.088
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.499 0.85753 0.112 0.052 0.836
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.541 0.79702 0.796 0.172 0.032
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.819 0.36340 0.104 0.292 0.604
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.518 0.78870 0.812 0.156 0.032
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.783 -0.06885 0.452 0.496 0.052
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.277 0.74149 0.048 0.928 0.024
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.698 0.64099 0.088 0.720 0.192
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.560 0.74461 0.756 0.228 0.016
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.754 0.63157 0.272 0.652 0.076
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.872 0.13624 0.324 0.548 0.128
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.581 0.69662 0.108 0.800 0.092
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.435 0.74961 0.128 0.852 0.020
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.767 0.63375 0.268 0.648 0.084
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.733 0.60131 0.312 0.636 0.052
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.672 0.60169 0.312 0.660 0.028
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.493 0.78636 0.820 0.156 0.024
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.751 0.63751 0.268 0.656 0.076
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.493 0.78636 0.820 0.156 0.024
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.745 0.49382 0.396 0.564 0.040
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.748 0.48266 0.404 0.556 0.040
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.524 0.74192 0.152 0.812 0.036
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.642 0.59663 0.324 0.660 0.016
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.520 0.71248 0.184 0.796 0.020
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.205 0.74682 0.020 0.952 0.028
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.205 0.74682 0.020 0.952 0.028
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.493 0.78636 0.820 0.156 0.024
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.710 0.54450 0.360 0.608 0.032
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.499 0.85753 0.112 0.052 0.836
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.498 0.73525 0.064 0.840 0.096
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.853 0.47106 0.156 0.604 0.240
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.398 0.75915 0.068 0.884 0.048
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.611 0.70807 0.140 0.780 0.080
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.241 0.74760 0.020 0.940 0.040
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.420 0.73674 0.112 0.864 0.024
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.777 0.48342 0.316 0.072 0.612
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.716 0.56726 0.332 0.628 0.040
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.733 0.51716 0.388 0.576 0.036
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.673 0.78000 0.680 0.284 0.036
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.327 0.72068 0.080 0.904 0.016
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.649 0.79965 0.732 0.216 0.052
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.337 0.74285 0.072 0.904 0.024
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.710 0.67445 0.280 0.052 0.668
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#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.524 0.71433 0.048 0.820 0.132
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.338 0.75264 0.044 0.908 0.048
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.290 0.74727 0.048 0.924 0.028
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.910 0.51197 0.548 0.204 0.248
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.815 0.36009 0.100 0.296 0.604
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.326 0.75066 0.040 0.912 0.048
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.473 0.73453 0.060 0.852 0.088
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.642 0.57347 0.304 0.676 0.020
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.406 0.73965 0.044 0.880 0.076
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.514 0.71439 0.044 0.824 0.132
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.613 0.61481 0.284 0.700 0.016
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.861 0.44245 0.364 0.528 0.108
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.315 0.75360 0.048 0.916 0.036
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.560 0.74461 0.756 0.228 0.016
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.298 0.73632 0.056 0.920 0.024
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.499 0.85753 0.112 0.052 0.836
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.493 0.78636 0.820 0.156 0.024
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.499 0.85753 0.112 0.052 0.836
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.872 0.13624 0.324 0.548 0.128
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.668 0.59851 0.324 0.652 0.024
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.408 0.74967 0.072 0.880 0.048
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.409 0.73946 0.068 0.880 0.052
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.582 0.70616 0.064 0.792 0.144
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.487 0.73024 0.144 0.828 0.028
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.547 0.83921 0.112 0.072 0.816
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.693 0.62085 0.296 0.664 0.040
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.560 0.71107 0.216 0.764 0.020
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.696 0.77082 0.660 0.300 0.040
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.464 0.74598 0.060 0.856 0.084
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.257 0.74737 0.032 0.936 0.032
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.501 0.72388 0.180 0.804 0.016
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.689 0.65714 0.088 0.728 0.184
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.742 0.56742 0.088 0.680 0.232
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.230 0.74304 0.036 0.944 0.020
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.617 0.68428 0.124 0.780 0.096
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.825 0.56653 0.292 0.600 0.108
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.437 0.71268 0.860 0.108 0.032
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.703 0.66830 0.104 0.724 0.172
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.618 0.68965 0.072 0.772 0.156
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.778 0.52245 0.364 0.576 0.060
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.500 0.70442 0.152 0.820 0.028
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.690 0.77446 0.668 0.292 0.040
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.718 0.53312 0.376 0.592 0.032
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.437 0.71268 0.860 0.108 0.032
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.850 0.46845 0.352 0.544 0.104
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.312 0.72013 0.080 0.908 0.012
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.686 0.65882 0.084 0.728 0.188
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.564 0.74420 0.752 0.232 0.016
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.861 0.44748 0.364 0.528 0.108
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.520 0.54932 0.124 0.788 0.048 0.040
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.871 -0.01514 0.340 0.400 0.212 0.048
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.454 0.39164 0.008 0.740 0.004 0.248
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.665 0.44036 0.084 0.704 0.076 0.136
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.320 0.80814 0.880 0.080 0.000 0.040
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.612 0.73410 0.064 0.336 0.000 0.600
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.525 0.69922 0.068 0.196 0.000 0.736
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.252 0.83880 0.064 0.024 0.912 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.458 0.35693 0.004 0.720 0.004 0.272
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.308 0.83603 0.064 0.028 0.896 0.012
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.630 0.72515 0.068 0.368 0.000 0.564
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.548 0.53646 0.084 0.776 0.104 0.036
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.446 0.37604 0.004 0.736 0.004 0.256
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.756 -0.02478 0.176 0.536 0.012 0.276
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.599 0.50790 0.084 0.740 0.136 0.040
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.427 0.51505 0.044 0.808 0.000 0.148
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.379 0.80669 0.844 0.112 0.000 0.044
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.589 0.51297 0.084 0.748 0.128 0.040
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.619 0.44061 0.124 0.712 0.020 0.144
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.765 0.20900 0.168 0.592 0.040 0.200
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.485 0.54901 0.072 0.812 0.028 0.088
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.826 -0.00112 0.180 0.516 0.048 0.256
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.586 0.48482 0.144 0.704 0.000 0.152
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.594 0.50938 0.084 0.744 0.132 0.040
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.772 -0.27504 0.168 0.484 0.012 0.336
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.340 0.57307 0.032 0.888 0.048 0.032
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.485 0.29811 0.004 0.676 0.004 0.316
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.707 0.29894 0.148 0.640 0.028 0.184
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.340 0.79642 0.884 0.068 0.024 0.024
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.720 -0.38888 0.124 0.488 0.004 0.384
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.293 0.79531 0.896 0.048 0.000 0.056
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.665 0.17691 0.116 0.616 0.004 0.264
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.460 0.40771 0.012 0.744 0.004 0.240
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.719 -0.45487 0.136 0.440 0.000 0.424
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.599 0.50595 0.084 0.740 0.136 0.040
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.520 0.54932 0.124 0.788 0.048 0.040
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.489 0.54865 0.048 0.812 0.096 0.044
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.446 0.38048 0.004 0.736 0.004 0.256
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.643 0.62395 0.056 0.440 0.004 0.500
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.647 0.60888 0.696 0.120 0.156 0.028
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.331 0.55742 0.016 0.880 0.016 0.088
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.487 0.55525 0.088 0.800 0.012 0.100
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.772 0.43048 0.560 0.288 0.056 0.096
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.295 0.83812 0.064 0.028 0.900 0.008
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.432 0.55685 0.128 0.824 0.016 0.032
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.446 0.37604 0.004 0.736 0.004 0.256
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.763 0.20759 0.180 0.584 0.032 0.204
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.300 0.79509 0.892 0.048 0.000 0.060
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.598 0.71165 0.704 0.128 0.004 0.164
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.835 0.12365 0.156 0.436 0.364 0.044
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.879 0.06278 0.076 0.336 0.428 0.160
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.707 0.68888 0.096 0.356 0.012 0.536
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.401 0.57061 0.064 0.848 0.008 0.080
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.618 0.51720 0.120 0.736 0.084 0.060
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.501 0.55091 0.076 0.808 0.044 0.072
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.295 0.83812 0.064 0.028 0.900 0.008
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.284 0.80218 0.900 0.056 0.000 0.044
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.890 0.37231 0.104 0.232 0.484 0.180
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.319 0.79849 0.888 0.052 0.004 0.056
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.757 0.14855 0.476 0.388 0.020 0.116
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.363 0.49808 0.008 0.832 0.004 0.156
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.592 0.50806 0.080 0.752 0.116 0.052
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.593 0.71449 0.708 0.124 0.004 0.164
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.758 0.22444 0.160 0.600 0.040 0.200
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.732 0.11240 0.412 0.488 0.044 0.056
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.503 0.55748 0.112 0.800 0.036 0.052
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.535 0.43332 0.048 0.720 0.004 0.228
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.777 0.24911 0.216 0.584 0.048 0.152
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.761 0.04973 0.172 0.556 0.020 0.252
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.629 0.66654 0.064 0.384 0.000 0.552
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.293 0.79531 0.896 0.048 0.000 0.056
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.746 0.24170 0.160 0.608 0.036 0.196
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.293 0.79531 0.896 0.048 0.000 0.056
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.514 0.69403 0.064 0.192 0.000 0.744
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.525 0.69730 0.068 0.196 0.000 0.736
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.528 0.47826 0.128 0.752 0.000 0.120
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.784 -0.26498 0.232 0.440 0.004 0.324
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.627 0.15222 0.068 0.612 0.004 0.316
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.325 0.54718 0.008 0.876 0.016 0.100
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.325 0.54718 0.008 0.876 0.016 0.100
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.293 0.79531 0.896 0.048 0.000 0.056
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.676 0.64224 0.096 0.400 0.000 0.504
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.295 0.83812 0.064 0.028 0.900 0.008
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.459 0.55840 0.056 0.832 0.060 0.052
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.767 0.36674 0.168 0.600 0.184 0.048
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.460 0.56140 0.052 0.824 0.028 0.096
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.536 0.54149 0.152 0.768 0.028 0.052
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.273 0.55744 0.012 0.900 0.004 0.084
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.538 0.38282 0.040 0.704 0.004 0.252
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.811 0.40825 0.304 0.032 0.492 0.172
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.549 0.69063 0.052 0.260 0.000 0.688
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.686 0.70925 0.116 0.348 0.000 0.536
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.386 0.79273 0.824 0.152 0.000 0.024
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.449 0.37394 0.004 0.732 0.004 0.260
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.273 0.80434 0.900 0.084 0.004 0.012
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.410 0.51095 0.028 0.820 0.004 0.148
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.591 0.69362 0.176 0.020 0.724 0.080
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.651 0.67594 0.076 0.408 0.000 0.516
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.286 0.83031 0.052 0.016 0.908 0.024
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.593 0.71640 0.708 0.124 0.004 0.164
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.466 0.35217 0.004 0.708 0.004 0.284
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.893 -0.12301 0.248 0.448 0.076 0.228
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.262 0.83923 0.064 0.028 0.908 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.320 0.56340 0.032 0.888 0.008 0.072
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.340 0.79642 0.884 0.068 0.024 0.024
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.451 0.50089 0.024 0.788 0.008 0.180
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.776 0.05350 0.176 0.544 0.024 0.256
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.266 0.80256 0.904 0.080 0.004 0.012
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.373 0.49069 0.008 0.824 0.004 0.164
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.854 0.01912 0.320 0.420 0.224 0.036
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.735 -0.04396 0.136 0.544 0.012 0.308
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.818 0.19671 0.212 0.500 0.256 0.032
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.914 0.11326 0.220 0.456 0.208 0.116
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.302 0.57002 0.024 0.900 0.016 0.060
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.684 -0.52707 0.100 0.464 0.000 0.436
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.415 0.78523 0.808 0.160 0.000 0.032
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.593 0.71449 0.708 0.124 0.004 0.164
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#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.691 0.64653 0.108 0.408 0.000 0.484
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.444 0.55667 0.040 0.836 0.084 0.040
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.352 0.56237 0.032 0.876 0.016 0.076
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.352 0.52936 0.004 0.856 0.020 0.120
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.660 0.60079 0.680 0.128 0.168 0.024
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.890 0.36370 0.104 0.236 0.484 0.176
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.280 0.55918 0.012 0.900 0.008 0.080
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.373 0.57733 0.060 0.872 0.028 0.040
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.738 0.11634 0.276 0.516 0.000 0.208
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.377 0.57895 0.044 0.872 0.036 0.048
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.452 0.55782 0.036 0.832 0.084 0.048
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.741 0.11554 0.252 0.516 0.000 0.232
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.893 -0.12301 0.248 0.448 0.076 0.228
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.366 0.55745 0.024 0.860 0.012 0.104
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.593 0.71449 0.708 0.124 0.004 0.164
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.395 0.46593 0.004 0.804 0.008 0.184
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.295 0.83812 0.064 0.028 0.900 0.008
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.293 0.79531 0.896 0.048 0.000 0.056
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.295 0.83812 0.064 0.028 0.900 0.008
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.732 0.11240 0.412 0.488 0.044 0.056
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.653 0.64581 0.076 0.420 0.000 0.504
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.408 0.56988 0.064 0.844 0.008 0.084
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.436 0.46338 0.004 0.780 0.016 0.200
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.513 0.54698 0.064 0.800 0.092 0.044
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.526 0.30537 0.020 0.672 0.004 0.304
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.341 0.82430 0.064 0.048 0.880 0.008
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.755 0.06429 0.172 0.552 0.016 0.260
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.670 0.26060 0.136 0.600 0.000 0.264
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.469 0.77289 0.780 0.176 0.004 0.040
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.454 0.57261 0.056 0.832 0.036 0.076
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.289 0.54892 0.004 0.896 0.020 0.080
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.648 0.33924 0.116 0.656 0.008 0.220
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.599 0.50595 0.084 0.740 0.136 0.040
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.707 0.33223 0.068 0.672 0.120 0.140
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.289 0.52124 0.000 0.872 0.004 0.124
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.551 0.52839 0.148 0.760 0.024 0.068
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.837 0.18620 0.188 0.548 0.084 0.180
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.432 0.76151 0.824 0.048 0.008 0.120
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.606 0.50952 0.112 0.736 0.116 0.036
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.511 0.54039 0.064 0.796 0.108 0.032
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.726 0.67570 0.112 0.356 0.012 0.520
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.565 0.05544 0.020 0.580 0.004 0.396
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.399 0.79020 0.820 0.156 0.004 0.020
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.604 0.73156 0.072 0.292 0.000 0.636
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.432 0.76151 0.824 0.048 0.008 0.120
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.885 -0.10814 0.236 0.460 0.072 0.232
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.458 0.35887 0.004 0.720 0.004 0.272
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.616 0.51336 0.084 0.732 0.136 0.048
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.598 0.71165 0.704 0.128 0.004 0.164
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.890 -0.13103 0.248 0.448 0.072 0.232
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.5217 0.54647 0.072 0.772 0.040 0.036 0.080
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.8812 0.02300 0.312 0.352 0.180 0.040 0.116
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.5308 0.41460 0.004 0.664 0.004 0.256 0.072
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.6108 0.44719 0.024 0.668 0.028 0.080 0.200
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2353 0.73415 0.916 0.028 0.004 0.008 0.044
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4054 0.65654 0.008 0.236 0.000 0.744 0.012
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.1911 0.46580 0.004 0.036 0.000 0.932 0.028
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0451 0.89149 0.000 0.008 0.988 0.000 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.5343 0.38333 0.000 0.640 0.004 0.280 0.076
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0740 0.88574 0.000 0.008 0.980 0.008 0.004
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4159 0.65926 0.008 0.268 0.000 0.716 0.008
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.5174 0.53364 0.036 0.768 0.096 0.024 0.076
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.5287 0.40175 0.000 0.656 0.004 0.260 0.080
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.7421 -0.06368 0.116 0.500 0.012 0.304 0.068
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.5500 0.50096 0.032 0.736 0.128 0.020 0.084
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4015 0.53347 0.024 0.788 0.000 0.172 0.016
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3708 0.72672 0.836 0.056 0.000 0.016 0.092
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.5356 0.50802 0.032 0.748 0.120 0.020 0.080
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.6263 0.42534 0.072 0.676 0.020 0.168 0.064
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.7628 0.17890 0.120 0.564 0.040 0.196 0.080
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5094 0.53700 0.040 0.772 0.024 0.108 0.056
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.8285 -0.05920 0.116 0.476 0.068 0.264 0.076
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.6500 0.45860 0.132 0.624 0.000 0.180 0.064
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.5345 0.50659 0.032 0.748 0.124 0.020 0.076
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.7457 -0.29469 0.116 0.444 0.012 0.368 0.060
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3644 0.57679 0.012 0.860 0.044 0.044 0.040
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.5569 0.33105 0.000 0.588 0.004 0.332 0.076
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.6958 0.28513 0.100 0.624 0.028 0.176 0.072
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2330 0.71981 0.920 0.020 0.020 0.004 0.036
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.6841 0.39017 0.084 0.432 0.004 0.432 0.048
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1386 0.71868 0.952 0.000 0.000 0.016 0.032
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6704 0.16887 0.076 0.560 0.004 0.296 0.064
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.5296 0.44031 0.008 0.676 0.004 0.244 0.068
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.6753 0.42821 0.104 0.352 0.000 0.500 0.044
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.5389 0.50362 0.032 0.744 0.128 0.020 0.076
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.5217 0.54647 0.072 0.772 0.040 0.036 0.080
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.4229 0.54868 0.012 0.820 0.088 0.024 0.056
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.5234 0.40717 0.000 0.660 0.004 0.260 0.076
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.4838 0.57338 0.004 0.364 0.004 0.612 0.016
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6002 0.53600 0.692 0.072 0.116 0.004 0.116
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3762 0.56355 0.004 0.828 0.012 0.120 0.036
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.5022 0.56427 0.084 0.760 0.004 0.116 0.036
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.7530 0.39768 0.556 0.236 0.048 0.060 0.100
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4424 0.55470 0.108 0.804 0.012 0.024 0.052
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.5287 0.40175 0.000 0.656 0.004 0.260 0.080
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.7598 0.16248 0.116 0.552 0.028 0.216 0.088
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1469 0.71849 0.948 0.000 0.000 0.016 0.036
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.6040 0.60814 0.672 0.060 0.000 0.116 0.152
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 2 0.7697 0.09684 0.072 0.412 0.376 0.012 0.128
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.7795 0.29193 0.000 0.304 0.240 0.068 0.388
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.6123 0.63780 0.052 0.288 0.012 0.612 0.036
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.4319 0.57552 0.044 0.812 0.008 0.100 0.036
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.6070 0.50775 0.068 0.720 0.076 0.052 0.084
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4780 0.54475 0.040 0.800 0.040 0.076 0.044
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1372 0.72349 0.956 0.004 0.000 0.016 0.024
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.7192 0.57357 0.000 0.192 0.244 0.052 0.512
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1812 0.72308 0.940 0.008 0.004 0.012 0.036
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.7464 0.14680 0.480 0.340 0.020 0.076 0.084
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4318 0.51881 0.004 0.772 0.008 0.176 0.040
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.5542 0.51936 0.036 0.728 0.096 0.012 0.128
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.6113 0.59926 0.664 0.060 0.000 0.116 0.160
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.7472 0.21090 0.112 0.580 0.040 0.192 0.076
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7426 0.12101 0.368 0.456 0.028 0.040 0.108
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.5155 0.55442 0.072 0.776 0.032 0.044 0.076
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.5705 0.44021 0.048 0.644 0.000 0.264 0.044
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.7744 0.21862 0.180 0.556 0.048 0.148 0.068
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.7424 0.02820 0.112 0.532 0.020 0.268 0.068
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.4260 0.59956 0.008 0.308 0.000 0.680 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.1386 0.71868 0.952 0.000 0.000 0.016 0.032
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.7481 0.20650 0.108 0.580 0.040 0.192 0.080
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.1386 0.71868 0.952 0.000 0.000 0.016 0.032
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.1493 0.44681 0.000 0.024 0.000 0.948 0.028
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.1914 0.45802 0.004 0.032 0.000 0.932 0.032
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5417 0.48170 0.100 0.716 0.000 0.148 0.036
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.7688 -0.24359 0.220 0.368 0.000 0.352 0.060
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6438 0.20360 0.052 0.524 0.004 0.368 0.052
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4052 0.55567 0.004 0.808 0.012 0.132 0.044
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.4052 0.55567 0.004 0.808 0.012 0.132 0.044
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.1386 0.71868 0.952 0.000 0.000 0.016 0.032
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.5613 0.59078 0.052 0.352 0.000 0.580 0.016
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4499 0.54629 0.024 0.816 0.056 0.056 0.048
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.7357 0.35381 0.124 0.580 0.184 0.020 0.092
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4590 0.56501 0.028 0.800 0.028 0.108 0.036
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.5543 0.54030 0.112 0.744 0.024 0.064 0.056
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.2934 0.57013 0.004 0.880 0.004 0.076 0.036
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.6113 0.38398 0.032 0.612 0.004 0.276 0.076
#> F1099B84-FE2A-419C-9948-D0754C1AF902 5 0.5946 0.76359 0.140 0.008 0.240 0.000 0.612
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.2416 0.53320 0.000 0.100 0.000 0.888 0.012
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.5821 0.65683 0.068 0.244 0.000 0.648 0.040
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.4254 0.70970 0.796 0.096 0.000 0.012 0.096
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.5339 0.39819 0.000 0.652 0.004 0.260 0.084
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.2459 0.73116 0.904 0.040 0.004 0.000 0.052
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4760 0.52788 0.020 0.764 0.008 0.156 0.052
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.4734 0.65850 0.104 0.008 0.776 0.016 0.096
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.5460 0.62803 0.044 0.320 0.000 0.616 0.020
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.1697 0.86927 0.000 0.008 0.932 0.000 0.060
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.6077 0.60743 0.668 0.060 0.000 0.116 0.156
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.5455 0.37738 0.000 0.624 0.004 0.292 0.080
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.9167 -0.16449 0.192 0.404 0.100 0.192 0.112
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0290 0.89158 0.000 0.008 0.992 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.2760 0.57263 0.020 0.896 0.008 0.064 0.012
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.2330 0.71981 0.920 0.020 0.020 0.004 0.036
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#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1697 0.86927 0.000 0.008 0.932 0.000 0.060
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.4579 0.56895 0.016 0.788 0.016 0.128 0.052
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.5321 0.53176 0.044 0.760 0.096 0.024 0.076
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.5950 0.48913 0.108 0.708 0.016 0.056 0.112
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.7248 0.14897 0.356 0.476 0.028 0.028 0.112
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.4462 0.70830 0.788 0.100 0.004 0.012 0.096
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.5572 0.37291 0.004 0.620 0.004 0.296 0.076
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.5387 0.36777 0.000 0.624 0.004 0.300 0.072
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.3705 0.55107 0.004 0.832 0.008 0.112 0.044
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.7900 -0.00954 0.116 0.504 0.040 0.264 0.076
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.5394 0.24180 0.000 0.540 0.000 0.400 0.060
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.8825 0.02842 0.228 0.372 0.248 0.036 0.116
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.4721 0.54625 0.040 0.804 0.040 0.072 0.044
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2688 0.72986 0.896 0.036 0.012 0.000 0.056
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.7413 0.20926 0.292 0.508 0.040 0.024 0.136
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.5394 0.24180 0.000 0.540 0.000 0.400 0.060
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.2128 0.72718 0.928 0.020 0.012 0.004 0.036
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.8016 -0.28373 0.344 0.336 0.000 0.228 0.092
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.5243 0.41370 0.000 0.668 0.004 0.244 0.084
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.4565 0.54915 0.020 0.804 0.080 0.024 0.072
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1697 0.86927 0.000 0.008 0.932 0.000 0.060
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.7117 0.49229 0.176 0.320 0.000 0.468 0.036
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.6940 0.21106 0.108 0.524 0.000 0.304 0.064
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0579 0.89126 0.000 0.008 0.984 0.000 0.008
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.5156 0.41570 0.000 0.668 0.004 0.256 0.072
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.7007 0.44452 0.544 0.228 0.000 0.052 0.176
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.6606 0.36932 0.228 0.620 0.032 0.028 0.092
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4539 0.56482 0.048 0.800 0.008 0.100 0.044
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4686 0.49429 0.000 0.740 0.012 0.192 0.056
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1697 0.86927 0.000 0.008 0.932 0.000 0.060
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.5946 0.76359 0.140 0.008 0.240 0.000 0.612
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.7704 -0.17579 0.384 0.368 0.000 0.164 0.084
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.4734 0.40262 0.000 0.372 0.000 0.604 0.024
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.8530 0.08790 0.188 0.064 0.484 0.152 0.112
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.6060 0.04326 0.028 0.484 0.000 0.432 0.056
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.7421 0.03170 0.168 0.516 0.008 0.248 0.060
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.6013 0.61711 0.072 0.316 0.000 0.584 0.028
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.3977 0.55825 0.012 0.836 0.080 0.024 0.048
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.3013 0.57036 0.020 0.888 0.016 0.060 0.016
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4221 0.54362 0.000 0.800 0.016 0.112 0.072
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.5952 0.53735 0.696 0.072 0.124 0.004 0.104
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.7216 0.56895 0.000 0.196 0.244 0.052 0.508
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.2744 0.56774 0.004 0.896 0.008 0.052 0.040
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3775 0.58332 0.032 0.856 0.024 0.044 0.044
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.7607 0.08271 0.264 0.452 0.000 0.216 0.068
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.4238 0.58122 0.020 0.828 0.032 0.064 0.056
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.4064 0.55915 0.012 0.832 0.080 0.028 0.048
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.7605 0.07367 0.240 0.448 0.000 0.248 0.064
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.9167 -0.16449 0.192 0.404 0.100 0.192 0.112
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4266 0.56681 0.020 0.812 0.012 0.108 0.048
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.6113 0.59926 0.664 0.060 0.000 0.116 0.160
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4589 0.49241 0.000 0.752 0.008 0.172 0.068
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.1386 0.71868 0.952 0.000 0.000 0.016 0.032
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0613 0.88986 0.000 0.008 0.984 0.004 0.004
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.7426 0.12101 0.368 0.456 0.028 0.040 0.108
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.5273 0.59473 0.024 0.344 0.000 0.608 0.024
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4442 0.57569 0.048 0.804 0.008 0.104 0.036
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4981 0.47539 0.004 0.708 0.008 0.224 0.056
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.4650 0.54403 0.024 0.800 0.084 0.024 0.068
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.5602 0.35800 0.016 0.608 0.000 0.316 0.060
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1116 0.86467 0.000 0.028 0.964 0.004 0.004
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.7492 0.03317 0.116 0.512 0.016 0.284 0.072
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6563 0.27030 0.120 0.560 0.000 0.284 0.036
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.5368 0.66279 0.708 0.120 0.004 0.012 0.156
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4614 0.57308 0.032 0.804 0.028 0.092 0.044
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3556 0.55724 0.000 0.840 0.012 0.104 0.044
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.6535 0.36911 0.120 0.600 0.000 0.228 0.052
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.5389 0.50362 0.032 0.744 0.128 0.020 0.076
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.6303 0.35476 0.008 0.636 0.056 0.072 0.228
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3609 0.53738 0.000 0.816 0.004 0.148 0.032
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5624 0.51846 0.104 0.736 0.016 0.064 0.080
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.8457 0.13911 0.136 0.508 0.088 0.164 0.104
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3642 0.66463 0.824 0.004 0.000 0.048 0.124
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.5527 0.50532 0.056 0.744 0.108 0.020 0.072
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4600 0.53850 0.020 0.796 0.096 0.016 0.072
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.6422 0.63097 0.060 0.284 0.012 0.596 0.048
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5739 0.16183 0.012 0.500 0.000 0.432 0.056
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.4409 0.70926 0.792 0.100 0.004 0.012 0.092
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.3852 0.61991 0.008 0.168 0.000 0.796 0.028
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3642 0.66463 0.824 0.004 0.000 0.048 0.124
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9058 -0.14525 0.180 0.420 0.096 0.196 0.108
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.5396 0.38185 0.000 0.636 0.004 0.280 0.080
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5907 0.50661 0.036 0.716 0.132 0.040 0.076
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.6040 0.60814 0.672 0.060 0.000 0.116 0.152
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.9131 -0.16443 0.192 0.404 0.092 0.200 0.112
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.4764 0.446177 0.032 0.100 0.024 0.776 0.024 0.044
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.8563 0.048481 0.276 0.076 0.144 0.384 0.068 0.052
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4429 0.736836 0.000 0.548 0.000 0.424 0.000 0.028
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.6024 0.085300 0.012 0.216 0.012 0.592 0.160 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3021 0.688988 0.868 0.080 0.008 0.024 0.016 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.5352 0.639636 0.008 0.168 0.000 0.204 0.000 0.620
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.2586 0.440595 0.004 0.096 0.000 0.020 0.004 0.876
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0520 0.903796 0.000 0.000 0.984 0.008 0.008 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4533 0.790296 0.000 0.588 0.000 0.376 0.004 0.032
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0603 0.899243 0.000 0.000 0.980 0.016 0.000 0.004
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.4807 0.648740 0.008 0.076 0.000 0.260 0.000 0.656
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.3921 0.512701 0.028 0.044 0.072 0.828 0.012 0.016
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4006 0.781726 0.000 0.600 0.000 0.392 0.004 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6718 0.034904 0.088 0.092 0.004 0.524 0.012 0.280
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3639 0.502801 0.016 0.036 0.096 0.832 0.004 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4781 0.373489 0.004 0.176 0.000 0.696 0.004 0.120
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.4947 0.653096 0.720 0.168 0.004 0.028 0.072 0.008
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3560 0.504671 0.016 0.036 0.088 0.840 0.008 0.012
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5862 0.435806 0.048 0.124 0.016 0.668 0.008 0.136
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.6708 0.255197 0.092 0.092 0.024 0.604 0.016 0.172
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4720 0.453516 0.024 0.120 0.016 0.756 0.004 0.080
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.7510 0.044449 0.088 0.096 0.060 0.508 0.012 0.236
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.6745 0.215913 0.096 0.208 0.004 0.568 0.020 0.104
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3258 0.503326 0.016 0.036 0.092 0.848 0.000 0.008
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.6628 -0.214891 0.076 0.064 0.012 0.464 0.008 0.376
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3081 0.474384 0.000 0.100 0.032 0.852 0.004 0.012
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4905 0.778834 0.000 0.580 0.000 0.344 0.000 0.076
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.5835 0.348024 0.076 0.076 0.020 0.672 0.004 0.152
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2189 0.674707 0.916 0.020 0.016 0.040 0.008 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.6215 -0.339336 0.064 0.044 0.008 0.448 0.008 0.428
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1608 0.670612 0.940 0.036 0.000 0.004 0.016 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.6696 0.183468 0.056 0.224 0.000 0.512 0.008 0.200
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.5443 -0.546279 0.004 0.436 0.000 0.468 0.004 0.088
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.7443 0.385542 0.080 0.260 0.004 0.268 0.008 0.380
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.3307 0.502602 0.016 0.036 0.096 0.844 0.000 0.008
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4764 0.446177 0.032 0.100 0.024 0.776 0.024 0.044
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.2375 0.502073 0.000 0.036 0.060 0.896 0.000 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4453 0.764022 0.000 0.568 0.000 0.400 0.000 0.032
#> 682C11E8-099C-466F-BC8A-B09A754205E3 6 0.5967 0.554094 0.004 0.176 0.004 0.288 0.004 0.524
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6047 0.529727 0.668 0.048 0.088 0.108 0.088 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.3872 0.179836 0.000 0.264 0.004 0.712 0.000 0.020
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 4 0.5088 0.246672 0.052 0.244 0.004 0.668 0.004 0.028
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.7793 0.347228 0.480 0.168 0.040 0.220 0.040 0.052
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0508 0.902545 0.000 0.000 0.984 0.012 0.000 0.004
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 4 0.4991 0.393217 0.072 0.160 0.004 0.724 0.016 0.024
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4006 0.781726 0.000 0.600 0.000 0.392 0.004 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.6745 0.237959 0.092 0.100 0.016 0.588 0.016 0.188
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1722 0.671095 0.936 0.036 0.000 0.004 0.016 0.008
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.7213 0.474699 0.520 0.216 0.004 0.028 0.124 0.108
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 4 0.6784 0.156500 0.036 0.044 0.348 0.496 0.052 0.024
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.6608 0.358105 0.000 0.152 0.076 0.240 0.528 0.004
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.4906 0.614403 0.028 0.024 0.012 0.284 0.000 0.652
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4383 0.326380 0.024 0.196 0.000 0.736 0.004 0.040
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4337 0.519598 0.032 0.080 0.048 0.796 0.000 0.044
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3536 0.512350 0.020 0.056 0.020 0.848 0.004 0.052
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0508 0.902545 0.000 0.000 0.984 0.012 0.000 0.004
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2146 0.678982 0.916 0.052 0.004 0.012 0.012 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.5557 0.665020 0.000 0.116 0.076 0.128 0.676 0.004
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.2126 0.674930 0.920 0.040 0.004 0.012 0.020 0.004
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#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3515 0.510345 0.024 0.052 0.076 0.840 0.004 0.004
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2742 0.504639 0.008 0.028 0.068 0.884 0.008 0.004
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.5333 0.611013 0.036 0.032 0.012 0.288 0.004 0.628
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.6085 0.632296 0.012 0.504 0.000 0.300 0.004 0.180
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.5442 0.641576 0.676 0.196 0.008 0.056 0.060 0.004
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.4657 0.580359 0.008 0.132 0.000 0.124 0.008 0.728
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.5086 0.546496 0.716 0.132 0.000 0.004 0.088 0.060
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.8239 -0.051754 0.136 0.096 0.088 0.460 0.024 0.196
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4456 0.790323 0.000 0.596 0.000 0.372 0.004 0.028
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.3910 0.503513 0.020 0.032 0.100 0.820 0.016 0.012
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.7213 0.474699 0.520 0.216 0.004 0.028 0.124 0.108
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.8429 -0.081125 0.140 0.096 0.084 0.444 0.036 0.200
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 17581 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 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 0.313 0.735 0.842 0.4105 0.573 0.573
#> 3 3 0.857 0.888 0.952 0.2511 0.892 0.818
#> 4 4 0.682 0.801 0.866 0.3540 0.752 0.527
#> 5 5 0.728 0.605 0.783 0.1070 0.886 0.641
#> 6 6 0.721 0.674 0.803 0.0446 0.874 0.531
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2948 0.82702 0.052 0.948
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.8661 0.41750 0.288 0.712
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1843 0.82783 0.028 0.972
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.6531 0.79818 0.168 0.832
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.8555 0.74442 0.720 0.280
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2236 0.82274 0.036 0.964
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2236 0.82274 0.036 0.964
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.8555 0.54471 0.720 0.280
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1843 0.82783 0.028 0.972
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.8555 0.54471 0.720 0.280
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.1633 0.83701 0.024 0.976
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.7376 0.76679 0.208 0.792
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1414 0.83124 0.020 0.980
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.5946 0.81065 0.144 0.856
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.8267 0.70747 0.260 0.740
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4431 0.83053 0.092 0.908
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.8555 0.74442 0.720 0.280
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.8016 0.72765 0.244 0.756
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.5629 0.81604 0.132 0.868
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.7528 0.75876 0.216 0.784
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5842 0.81241 0.140 0.860
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6712 0.79167 0.176 0.824
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.2236 0.82274 0.036 0.964
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.8267 0.70747 0.260 0.740
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.5629 0.81900 0.132 0.868
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.7376 0.76679 0.208 0.792
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1843 0.82783 0.028 0.972
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.5946 0.81045 0.144 0.856
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.8555 0.74442 0.720 0.280
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.4161 0.83245 0.084 0.916
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.8555 0.74442 0.720 0.280
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4815 0.82690 0.104 0.896
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0938 0.83374 0.012 0.988
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1843 0.82843 0.028 0.972
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.9996 0.19143 0.488 0.512
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1843 0.82783 0.028 0.972
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.8267 0.70747 0.260 0.740
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1843 0.82783 0.028 0.972
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0376 0.83658 0.004 0.996
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6801 0.72286 0.820 0.180
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.7376 0.76640 0.208 0.792
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.2423 0.81894 0.040 0.960
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.8555 0.74442 0.720 0.280
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.8555 0.54471 0.720 0.280
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2043 0.82539 0.032 0.968
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1843 0.82783 0.028 0.972
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.6247 0.80364 0.156 0.844
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.8555 0.74442 0.720 0.280
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.8555 0.74442 0.720 0.280
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.8555 0.54471 0.720 0.280
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.9170 0.60433 0.332 0.668
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.4939 0.82955 0.108 0.892
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.7056 0.78066 0.192 0.808
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5842 0.81241 0.140 0.860
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.7299 0.77015 0.204 0.796
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.8555 0.54471 0.720 0.280
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.8555 0.74442 0.720 0.280
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.9170 0.60433 0.332 0.668
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.8555 0.74442 0.720 0.280
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.2236 0.82274 0.036 0.964
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1843 0.82783 0.028 0.972
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.9881 0.35295 0.436 0.564
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.8555 0.74442 0.720 0.280
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.5946 0.81045 0.144 0.856
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.9988 -0.32436 0.480 0.520
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2043 0.83269 0.032 0.968
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1633 0.82963 0.024 0.976
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.5737 0.81444 0.136 0.864
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.5946 0.81065 0.144 0.856
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.1184 0.83267 0.016 0.984
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.8555 0.74442 0.720 0.280
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.6343 0.80121 0.160 0.840
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.8555 0.74442 0.720 0.280
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.2236 0.82274 0.036 0.964
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.2236 0.82274 0.036 0.964
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.83603 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.2236 0.82274 0.036 0.964
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4161 0.83243 0.084 0.916
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4431 0.83066 0.092 0.908
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.5842 0.81241 0.140 0.860
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.8555 0.74442 0.720 0.280
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.3879 0.83527 0.076 0.924
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.8555 0.54471 0.720 0.280
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.7376 0.76640 0.208 0.792
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.9087 0.62062 0.324 0.676
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4022 0.83323 0.080 0.920
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.2236 0.82274 0.036 0.964
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4022 0.83323 0.080 0.920
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.2043 0.82539 0.032 0.968
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.5519 0.70635 0.872 0.128
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.2043 0.82539 0.032 0.968
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2236 0.82274 0.036 0.964
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.8555 0.74442 0.720 0.280
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1843 0.82783 0.028 0.972
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.8555 0.74442 0.720 0.280
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.2043 0.82539 0.032 0.968
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.8327 0.56048 0.736 0.264
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.1633 0.83704 0.024 0.976
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.8386 0.55807 0.732 0.268
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.8555 0.74442 0.720 0.280
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0938 0.83374 0.012 0.988
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.9850 0.42326 0.572 0.428
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.8555 0.54471 0.720 0.280
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.5842 0.81241 0.140 0.860
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.8081 0.73992 0.752 0.248
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.83603 0.000 1.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.6343 0.80121 0.160 0.840
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.8555 0.74442 0.720 0.280
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0938 0.83376 0.012 0.988
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.9993 0.00254 0.516 0.484
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.4562 0.82943 0.096 0.904
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.7376 0.76574 0.208 0.792
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.7883 0.74314 0.236 0.764
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.6973 0.78373 0.188 0.812
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0672 0.83483 0.008 0.992
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.8555 0.74442 0.720 0.280
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.8555 0.74442 0.720 0.280
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.5629 0.81604 0.132 0.868
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1184 0.83290 0.016 0.984
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.6887 0.72338 0.816 0.184
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.8555 0.74442 0.720 0.280
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.8555 0.54471 0.720 0.280
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#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1414 0.83129 0.020 0.980
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.8555 0.74442 0.720 0.280
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2236 0.82274 0.036 0.964
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.8327 0.74291 0.736 0.264
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.6712 0.79167 0.176 0.824
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1843 0.82783 0.028 0.972
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.7674 0.75049 0.224 0.776
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.8555 0.74442 0.720 0.280
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.7745 0.74705 0.228 0.772
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9487 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.5178 0.6362 0.256 0.744 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9487 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9487 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9751 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0892 0.9441 0.000 0.980 0.020
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0892 0.9441 0.000 0.980 0.020
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0892 0.8743 0.020 0.000 0.980
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9487 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0892 0.8743 0.020 0.000 0.980
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0892 0.9441 0.000 0.980 0.020
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9487 0.000 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9487 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0892 0.9441 0.000 0.980 0.020
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.4887 0.7098 0.000 0.772 0.228
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0892 0.9441 0.000 0.980 0.020
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9751 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3879 0.8119 0.000 0.848 0.152
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0892 0.9441 0.000 0.980 0.020
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.2711 0.8904 0.000 0.912 0.088
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9487 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6204 0.2788 0.000 0.576 0.424
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9487 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.6274 0.1720 0.000 0.544 0.456
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.1289 0.9385 0.000 0.968 0.032
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9487 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0237 0.9481 0.000 0.996 0.004
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0892 0.9441 0.000 0.980 0.020
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9751 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0892 0.9441 0.000 0.980 0.020
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9751 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0237 0.9481 0.000 0.996 0.004
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0424 0.9473 0.000 0.992 0.008
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0892 0.9441 0.000 0.980 0.020
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4755 0.6913 0.008 0.184 0.808
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9487 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.4931 0.7039 0.000 0.768 0.232
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0237 0.9481 0.000 0.996 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0892 0.9441 0.000 0.980 0.020
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9751 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9487 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.9487 0.000 1.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9751 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0892 0.8743 0.020 0.000 0.980
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9487 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9487 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.1031 0.9427 0.000 0.976 0.024
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9751 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9751 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0892 0.8743 0.020 0.000 0.980
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.5926 0.4408 0.000 0.644 0.356
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.1860 0.9243 0.000 0.948 0.052
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9487 0.000 1.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9487 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9487 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0892 0.8743 0.020 0.000 0.980
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9751 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.5926 0.4408 0.000 0.644 0.356
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9751 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0000 0.9487 0.000 1.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9487 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.5948 0.4322 0.000 0.640 0.360
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9751 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0892 0.9441 0.000 0.980 0.020
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.1753 0.9092 0.952 0.048 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9487 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9487 0.000 1.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0892 0.9441 0.000 0.980 0.020
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.1753 0.9274 0.000 0.952 0.048
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0892 0.9441 0.000 0.980 0.020
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9751 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.2625 0.8984 0.000 0.916 0.084
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9751 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0892 0.9441 0.000 0.980 0.020
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0892 0.9441 0.000 0.980 0.020
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.9487 0.000 1.000 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0424 0.9473 0.000 0.992 0.008
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0892 0.9441 0.000 0.980 0.020
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9487 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9487 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9751 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0892 0.9441 0.000 0.980 0.020
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0892 0.8743 0.020 0.000 0.980
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9487 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.6295 0.1143 0.000 0.528 0.472
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9487 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.9487 0.000 1.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9487 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9487 0.000 1.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.5431 0.5780 0.716 0.000 0.284
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0892 0.9441 0.000 0.980 0.020
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0892 0.9441 0.000 0.980 0.020
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9751 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9487 0.000 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9751 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9487 0.000 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0892 0.8743 0.020 0.000 0.980
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0892 0.9441 0.000 0.980 0.020
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0892 0.8743 0.020 0.000 0.980
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9751 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0424 0.9473 0.000 0.992 0.008
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.6295 0.0971 0.000 0.472 0.528
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0892 0.8743 0.020 0.000 0.980
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9487 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9751 1.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9487 0.000 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.3686 0.8409 0.000 0.860 0.140
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9751 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9487 0.000 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.4591 0.8179 0.032 0.848 0.120
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0892 0.9441 0.000 0.980 0.020
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.0424 0.9463 0.008 0.992 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.6111 0.3935 0.000 0.604 0.396
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9487 0.000 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0892 0.9441 0.000 0.980 0.020
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9751 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9751 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0892 0.9441 0.000 0.980 0.020
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0000 0.9487 0.000 1.000 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0747 0.9608 0.984 0.000 0.016
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9751 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0892 0.8743 0.020 0.000 0.980
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9751 1.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0892 0.8743 0.020 0.000 0.980
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0892 0.9441 0.000 0.980 0.020
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9487 0.000 1.000 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.2625 0.8984 0.000 0.916 0.084
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0000 0.9487 0.000 1.000 0.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0424 0.9473 0.000 0.992 0.008
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0892 0.8743 0.020 0.000 0.980
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.1015 0.8686 0.012 0.008 0.980
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0000 0.9487 0.000 1.000 0.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0892 0.9441 0.000 0.980 0.020
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0892 0.9441 0.000 0.980 0.020
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0892 0.9441 0.000 0.980 0.020
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9751 1.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0892 0.8743 0.020 0.000 0.980
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9751 1.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.2625 0.8835 0.000 0.916 0.084
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.0000 0.9487 0.000 1.000 0.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0000 0.9751 1.000 0.000 0.000
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.0000 0.9751 1.000 0.000 0.000
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.2537 0.8763 0.080 0.920 0.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.0237 0.9481 0.000 0.996 0.004
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0000 0.9487 0.000 1.000 0.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0892 0.9441 0.000 0.980 0.020
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.0424 0.9453 0.000 0.992 0.008
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.0237 0.8626 0.004 0.000 0.996
#> 679EE059-DDD9-4138-9973-51A583941B71 1 0.0892 0.9543 0.980 0.000 0.020
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.0000 0.9751 1.000 0.000 0.000
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0000 0.9751 1.000 0.000 0.000
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.2261 0.9001 0.000 0.932 0.068
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0892 0.9441 0.000 0.980 0.020
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.0892 0.9441 0.000 0.980 0.020
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.0592 0.9464 0.000 0.988 0.012
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.0000 0.9487 0.000 1.000 0.000
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.0000 0.9487 0.000 1.000 0.000
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.0592 0.9465 0.000 0.988 0.012
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.0000 0.9487 0.000 1.000 0.000
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 1 0.0000 0.9751 1.000 0.000 0.000
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 3 0.4452 0.6673 0.000 0.192 0.808
#> 38FCA0B0-4399-4061-99AA-B886F54CA0DB 3 0.3965 0.7678 0.132 0.008 0.860
#> C0DC6757-E0CD-4615-9543-A348500AAE84 2 0.0000 0.9487 0.000 1.000 0.000
#> 84B05220-4E28-44AE-B6EE-6018C0DBF0D2 2 0.0000 0.9487 0.000 1.000 0.000
#> AE8D8D83-D457-4164-861E-9329DB223561 3 0.0892 0.8743 0.020 0.000 0.980
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#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.3941 0.8220 0.000 0.844 0.156
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 2 0.0000 0.9487 0.000 1.000 0.000
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 2 0.0000 0.9487 0.000 1.000 0.000
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 2 0.0892 0.9441 0.000 0.980 0.020
#> 3508F4B0-1ADA-4937-B924-424AC2596341 2 0.0000 0.9487 0.000 1.000 0.000
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 2 0.0000 0.9487 0.000 1.000 0.000
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 1 0.0892 0.9543 0.980 0.000 0.020
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.0000 0.9751 1.000 0.000 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.0000 0.9487 0.000 1.000 0.000
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.0000 0.9751 1.000 0.000 0.000
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 3 0.0892 0.8743 0.020 0.000 0.980
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 3 0.5178 0.6062 0.256 0.000 0.744
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0424 0.9671 0.992 0.000 0.008
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0892 0.9441 0.000 0.980 0.020
#> A5572139-03CA-4299-98B6-13A2945649D0 3 0.0892 0.8743 0.020 0.000 0.980
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.4974 0.7064 0.000 0.764 0.236
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.2625 0.8984 0.000 0.916 0.084
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.3116 0.8580 0.000 0.892 0.108
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0892 0.9441 0.000 0.980 0.020
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9487 0.000 1.000 0.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.4887 0.7098 0.000 0.772 0.228
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0892 0.9379 0.000 0.980 0.020
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9751 1.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9751 1.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0000 0.9487 0.000 1.000 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.0000 0.9487 0.000 1.000 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.5058 0.7080 0.000 0.756 0.244
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.8144 0.3042 0.084 0.572 0.344
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9751 1.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0747 0.9453 0.000 0.984 0.016
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0892 0.8743 0.020 0.000 0.980
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.0000 0.9487 0.000 1.000 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.6501 0.3957 0.664 0.316 0.020
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.3752 0.8219 0.000 0.856 0.144
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0892 0.8743 0.020 0.000 0.980
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.2165 0.9034 0.000 0.936 0.064
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9487 0.000 1.000 0.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0000 0.9751 1.000 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0892 0.8743 0.020 0.000 0.980
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0237 0.9481 0.000 0.996 0.004
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.1031 0.9427 0.000 0.976 0.024
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.5733 0.4887 0.324 0.000 0.676
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.9487 0.000 1.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.2625 0.8984 0.000 0.916 0.084
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9487 0.000 1.000 0.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9751 1.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9751 1.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0000 0.9487 0.000 1.000 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9487 0.000 1.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0892 0.9441 0.000 0.980 0.020
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.9487 0.000 1.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9487 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9487 0.000 1.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0892 0.8743 0.020 0.000 0.980
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0892 0.9441 0.000 0.980 0.020
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.9487 0.000 1.000 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9487 0.000 1.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0892 0.9441 0.000 0.980 0.020
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9487 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9487 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.5493 0.6371 0.012 0.232 0.756
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9487 0.000 1.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9751 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0892 0.9441 0.000 0.980 0.020
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9487 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.3879 0.8119 0.000 0.848 0.152
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9751 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0747 0.9453 0.000 0.984 0.016
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9487 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9751 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0892 0.8743 0.020 0.000 0.980
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9487 0.000 1.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9487 0.000 1.000 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9487 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9751 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9751 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9487 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9487 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9487 0.000 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.1411 0.9359 0.000 0.964 0.036
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0747 0.9453 0.000 0.984 0.016
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.6754 0.2236 0.012 0.432 0.556
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9487 0.000 1.000 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9751 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9751 1.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0592 0.9464 0.000 0.988 0.012
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9751 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0592 0.9465 0.000 0.988 0.012
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9487 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9487 0.000 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0892 0.8743 0.020 0.000 0.980
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0892 0.9441 0.000 0.980 0.020
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9487 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0892 0.8743 0.020 0.000 0.980
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9487 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9487 0.000 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.9487 0.000 1.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9487 0.000 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9487 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0892 0.8743 0.020 0.000 0.980
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0892 0.8743 0.020 0.000 0.980
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0747 0.9608 0.984 0.000 0.016
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.1129 0.9425 0.004 0.976 0.020
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0424 0.9473 0.000 0.992 0.008
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.4399 0.6715 0.000 0.188 0.812
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0592 0.9464 0.000 0.988 0.012
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0892 0.9441 0.000 0.980 0.020
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0892 0.9441 0.000 0.980 0.020
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.6291 0.1293 0.000 0.532 0.468
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0892 0.9441 0.000 0.980 0.020
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9487 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9751 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.5926 0.4408 0.000 0.644 0.356
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0424 0.9475 0.000 0.992 0.008
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9487 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9487 0.000 1.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9487 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3267 0.8499 0.000 0.884 0.116
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0424 0.9473 0.000 0.992 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.5016 0.6133 0.000 0.240 0.760
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9487 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0237 0.9711 0.996 0.000 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9487 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1015 0.8686 0.012 0.008 0.980
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9751 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0892 0.8743 0.020 0.000 0.980
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0592 0.9604 0.988 0.012 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0892 0.9441 0.000 0.980 0.020
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9487 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9487 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.2165 0.9034 0.000 0.936 0.064
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0892 0.9441 0.000 0.980 0.020
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1015 0.8686 0.012 0.008 0.980
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0892 0.9441 0.000 0.980 0.020
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0892 0.9441 0.000 0.980 0.020
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9751 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9487 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9487 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0237 0.9481 0.000 0.996 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.6260 0.1818 0.000 0.448 0.552
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9487 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9487 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9487 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.5098 0.7018 0.000 0.752 0.248
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0747 0.9587 0.984 0.000 0.016
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.4887 0.7098 0.000 0.772 0.228
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3816 0.8164 0.000 0.852 0.148
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0892 0.9441 0.000 0.980 0.020
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0892 0.9441 0.000 0.980 0.020
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9751 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0892 0.9441 0.000 0.980 0.020
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9751 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6299 0.0821 0.000 0.476 0.524
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9487 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.1289 0.9294 0.000 0.968 0.032
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9751 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.6168 0.3176 0.000 0.588 0.412
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.1211 0.79448 0.000 0.040 0.000 0.960
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.1610 0.80064 0.016 0.032 0.000 0.952
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.0592 0.81238 0.000 0.016 0.000 0.984
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.1474 0.72844 0.000 0.948 0.000 0.052
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1474 0.72844 0.000 0.948 0.000 0.052
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.2281 0.69664 0.000 0.904 0.000 0.096
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4356 0.70852 0.000 0.292 0.000 0.708
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#> BC9A5294-255F-47A4-8879-11C441093A3D 4 0.0672 0.81619 0.000 0.008 0.008 0.984
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 4 0.4482 0.72575 0.000 0.264 0.008 0.728
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#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.4605 0.79868 0.000 0.664 0.000 0.336
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#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4643 0.79192 0.000 0.656 0.000 0.344
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#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.1004 0.81704 0.000 0.024 0.004 0.972
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 4 0.0000 0.81789 0.000 0.000 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0336 0.96094 0.992 0.008 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 4 0.3873 0.74928 0.000 0.228 0.000 0.772
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#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 4 0.0592 0.81238 0.000 0.016 0.000 0.984
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#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4564 0.80468 0.000 0.672 0.000 0.328
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.4564 0.68090 0.000 0.328 0.000 0.672
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4730 0.76775 0.000 0.636 0.000 0.364
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4103 0.73297 0.000 0.256 0.000 0.744
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4746 0.76249 0.000 0.632 0.000 0.368
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.4008 0.65012 0.000 0.000 0.244 0.756
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.1716 0.76759 0.000 0.064 0.000 0.936
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.1474 0.72844 0.000 0.948 0.000 0.052
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4564 0.80468 0.000 0.672 0.000 0.328
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.0657 0.81491 0.000 0.012 0.004 0.984
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.3172 0.77097 0.000 0.840 0.000 0.160
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.0000 0.81789 0.000 0.000 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0188 0.93576 0.000 0.004 0.996 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.0000 0.81789 0.000 0.000 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4585 0.80126 0.000 0.668 0.000 0.332
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0469 0.96087 0.988 0.012 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0817 0.95944 0.976 0.024 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4304 0.82439 0.000 0.716 0.000 0.284
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 4 0.4955 -0.36630 0.000 0.444 0.000 0.556
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.4343 0.72697 0.000 0.264 0.004 0.732
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.2345 0.77722 0.000 0.900 0.000 0.100
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.2053 0.78725 0.000 0.004 0.072 0.924
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0469 0.81848 0.000 0.012 0.000 0.988
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0336 0.96100 0.992 0.008 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.3117 0.85004 0.880 0.028 0.000 0.092
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.2345 0.77722 0.000 0.900 0.000 0.100
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.2530 0.78415 0.000 0.888 0.000 0.112
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.0000 0.81789 0.000 0.000 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0188 0.93576 0.000 0.004 0.996 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.1474 0.72844 0.000 0.948 0.000 0.052
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4406 0.82371 0.000 0.700 0.000 0.300
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4331 0.81998 0.000 0.712 0.000 0.288
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.0817 0.80775 0.000 0.024 0.000 0.976
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4624 0.79750 0.000 0.660 0.000 0.340
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0188 0.93576 0.000 0.004 0.996 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.2111 0.70389 0.044 0.932 0.000 0.024
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.2345 0.77722 0.000 0.900 0.000 0.100
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.5463 0.64090 0.000 0.256 0.692 0.052
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.2281 0.77512 0.000 0.904 0.000 0.096
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4164 0.72762 0.000 0.264 0.000 0.736
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2408 0.68988 0.000 0.896 0.000 0.104
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.0804 0.81458 0.000 0.012 0.008 0.980
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4134 0.73045 0.000 0.260 0.000 0.740
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4967 0.62873 0.000 0.548 0.000 0.452
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.1706 0.79547 0.000 0.016 0.036 0.948
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.3975 0.74220 0.000 0.240 0.000 0.760
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4817 0.73620 0.000 0.612 0.000 0.388
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.0000 0.81789 0.000 0.000 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2760 0.78915 0.000 0.872 0.000 0.128
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.6943 0.48054 0.000 0.264 0.576 0.160
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0592 0.81238 0.000 0.016 0.000 0.984
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4730 0.76692 0.000 0.636 0.000 0.364
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.3300 0.77080 0.848 0.008 0.000 0.144
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4193 0.39968 0.000 0.732 0.000 0.268
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.0592 0.81238 0.000 0.016 0.000 0.984
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4746 0.76249 0.000 0.632 0.000 0.368
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1004 0.81704 0.000 0.024 0.004 0.972
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.1302 0.74201 0.000 0.956 0.000 0.044
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.93683 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4222 0.72298 0.000 0.272 0.000 0.728
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.1474 0.72844 0.000 0.948 0.000 0.052
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.0469 0.81446 0.000 0.012 0.000 0.988
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0592 0.81238 0.000 0.016 0.000 0.984
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3837 0.81626 0.000 0.776 0.000 0.224
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0707 0.81456 0.000 0.000 0.020 0.980
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4730 0.76692 0.000 0.636 0.000 0.364
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4522 0.81092 0.000 0.680 0.000 0.320
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4916 0.67991 0.000 0.576 0.000 0.424
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.4511 0.72425 0.000 0.268 0.008 0.724
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2081 0.87930 0.916 0.084 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1151 0.81649 0.000 0.024 0.008 0.968
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0188 0.81820 0.000 0.000 0.004 0.996
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4564 0.68090 0.000 0.328 0.000 0.672
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1389 0.73008 0.000 0.952 0.000 0.048
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0817 0.95944 0.976 0.024 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1211 0.73424 0.000 0.960 0.000 0.040
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0188 0.96091 0.996 0.004 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.7834 0.12088 0.000 0.320 0.404 0.276
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4382 0.82393 0.000 0.704 0.000 0.296
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0188 0.81700 0.000 0.004 0.000 0.996
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0921 0.95883 0.972 0.028 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.5047 0.68609 0.000 0.316 0.016 0.668
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
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#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3409 0.7296 0.000 0.824 0.000 0.144 0.032
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.5049 0.2013 0.000 0.000 0.488 0.032 0.480
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.3999 0.6548 0.000 0.000 0.000 0.656 0.344
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1484 0.9020 0.944 0.008 0.000 0.000 0.048
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2953 0.7295 0.000 0.844 0.000 0.144 0.012
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9519 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0451 0.9058 0.988 0.008 0.000 0.000 0.004
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9519 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4928 0.5021 0.548 0.020 0.000 0.428 0.004
#> 3C032234-C350-4170-B8F7-F8DE8269E713 5 0.4219 0.4879 0.000 0.156 0.000 0.072 0.772
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.3612 0.6188 0.000 0.000 0.000 0.732 0.268
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2674 0.7333 0.000 0.856 0.000 0.140 0.004
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.4210 0.6518 0.000 0.000 0.000 0.588 0.412
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3116 0.7358 0.000 0.860 0.000 0.064 0.076
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9519 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 5 0.4192 -0.2319 0.000 0.000 0.000 0.404 0.596
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6793 0.3219 0.000 0.376 0.000 0.332 0.292
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.1484 0.9020 0.944 0.008 0.000 0.000 0.048
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.3551 0.5852 0.000 0.008 0.000 0.772 0.220
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.4264 0.6605 0.000 0.004 0.000 0.620 0.376
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1195 0.7697 0.000 0.960 0.000 0.028 0.012
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.4201 0.6555 0.000 0.000 0.000 0.592 0.408
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4249 0.6563 0.000 0.688 0.000 0.296 0.016
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1121 0.7689 0.000 0.956 0.000 0.044 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4297 0.5419 0.000 0.528 0.000 0.472 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.4297 -0.4215 0.000 0.000 0.000 0.472 0.528
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4067 0.5844 0.692 0.008 0.000 0.000 0.300
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.4210 0.6518 0.000 0.000 0.000 0.588 0.412
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4201 0.6555 0.000 0.000 0.000 0.592 0.408
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 5 0.2193 0.5424 0.000 0.008 0.000 0.092 0.900
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4161 0.4036 0.000 0.608 0.000 0.000 0.392
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1484 0.9020 0.944 0.008 0.000 0.000 0.048
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4171 0.4011 0.000 0.604 0.000 0.000 0.396
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0579 0.9053 0.984 0.008 0.000 0.000 0.008
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 5 0.4425 0.3852 0.000 0.000 0.244 0.040 0.716
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0865 0.7695 0.000 0.972 0.000 0.024 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4150 0.6605 0.000 0.000 0.000 0.612 0.388
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1484 0.9020 0.944 0.008 0.000 0.000 0.048
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.2124 0.5383 0.000 0.000 0.004 0.096 0.900
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.3784 0.5386 0.000 0.012 0.000 0.308 0.680 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.3421 0.5815 0.000 0.008 0.000 0.256 0.736 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0520 0.8379 0.000 0.984 0.000 0.000 0.008 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.5225 0.5386 0.000 0.064 0.000 0.672 0.204 0.060
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1989 0.8968 0.916 0.000 0.000 0.004 0.028 0.052
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.3528 0.5806 0.000 0.296 0.000 0.000 0.004 0.700
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.3847 0.5525 0.000 0.348 0.000 0.000 0.008 0.644
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9259 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1196 0.8352 0.000 0.952 0.000 0.000 0.008 0.040
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.3628 0.6570 0.000 0.168 0.000 0.044 0.004 0.784
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.2737 0.7707 0.000 0.004 0.000 0.868 0.084 0.044
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0363 0.8385 0.000 0.988 0.000 0.000 0.000 0.012
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.4274 0.3575 0.000 0.004 0.000 0.432 0.012 0.552
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.1565 0.8055 0.000 0.004 0.000 0.940 0.028 0.028
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.1946 0.8053 0.000 0.004 0.000 0.912 0.012 0.072
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1367 0.9025 0.944 0.000 0.000 0.000 0.012 0.044
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0777 0.8094 0.000 0.004 0.000 0.972 0.024 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.2572 0.7291 0.000 0.000 0.000 0.852 0.012 0.136
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.2019 0.7674 0.000 0.000 0.000 0.900 0.012 0.088
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.2103 0.7904 0.000 0.012 0.000 0.912 0.020 0.056
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.5336 0.4374 0.000 0.004 0.060 0.376 0.016 0.544
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4952 0.0812 0.000 0.524 0.000 0.000 0.408 0.068
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0858 0.8089 0.000 0.004 0.000 0.968 0.028 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.4048 0.5387 0.000 0.004 0.000 0.340 0.012 0.644
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.2706 0.7862 0.000 0.016 0.000 0.880 0.044 0.060
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0363 0.8385 0.000 0.988 0.000 0.000 0.000 0.012
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1225 0.7991 0.000 0.000 0.000 0.952 0.012 0.036
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.1643 0.9012 0.924 0.000 0.000 0.000 0.068 0.008
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.3827 0.5733 0.000 0.004 0.000 0.308 0.008 0.680
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1387 0.9028 0.932 0.000 0.000 0.000 0.068 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.2844 0.7511 0.000 0.020 0.000 0.860 0.016 0.104
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0458 0.8359 0.000 0.984 0.000 0.000 0.000 0.016
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.3927 0.5550 0.000 0.344 0.000 0.000 0.012 0.644
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1003 0.8094 0.000 0.000 0.004 0.964 0.028 0.004
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.4832 0.6049 0.000 0.108 0.000 0.244 0.648 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1003 0.8099 0.000 0.004 0.000 0.964 0.028 0.004
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0260 0.8374 0.000 0.992 0.000 0.000 0.000 0.008
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.2558 0.7133 0.000 0.840 0.000 0.000 0.004 0.156
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.2504 0.8623 0.856 0.000 0.000 0.004 0.136 0.004
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2123 0.8067 0.000 0.012 0.000 0.912 0.024 0.052
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 5 0.4101 0.3398 0.000 0.408 0.000 0.000 0.580 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.3808 0.4427 0.284 0.000 0.000 0.012 0.700 0.004
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 5 0.4859 0.4771 0.000 0.324 0.000 0.040 0.616 0.020
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0713 0.8386 0.000 0.972 0.000 0.000 0.000 0.028
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2783 0.7149 0.000 0.000 0.000 0.836 0.016 0.148
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0865 0.9080 0.964 0.000 0.000 0.000 0.036 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1461 0.9017 0.940 0.000 0.000 0.000 0.016 0.044
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1757 0.8592 0.000 0.000 0.916 0.076 0.000 0.008
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.7695 0.1982 0.000 0.264 0.012 0.232 0.360 0.132
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.3972 0.5561 0.000 0.004 0.000 0.320 0.012 0.664
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4471 0.4669 0.000 0.008 0.000 0.660 0.292 0.040
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.1219 0.8104 0.000 0.004 0.000 0.948 0.000 0.048
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.1442 0.8068 0.000 0.004 0.000 0.944 0.012 0.040
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1349 0.9054 0.940 0.000 0.000 0.000 0.056 0.004
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.7661 0.1623 0.000 0.200 0.012 0.312 0.344 0.132
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1387 0.9028 0.932 0.000 0.000 0.000 0.068 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.3767 0.5730 0.008 0.004 0.000 0.268 0.716 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1265 0.8211 0.000 0.948 0.000 0.000 0.044 0.008
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.4495 0.3678 0.000 0.004 0.000 0.388 0.580 0.028
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1594 0.8984 0.932 0.000 0.000 0.000 0.016 0.052
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2450 0.7459 0.000 0.000 0.000 0.868 0.016 0.116
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.3558 0.5657 0.160 0.004 0.000 0.044 0.792 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 5 0.4092 0.4951 0.000 0.020 0.000 0.344 0.636 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0146 0.8380 0.000 0.996 0.000 0.000 0.000 0.004
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2218 0.7579 0.000 0.000 0.000 0.884 0.012 0.104
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3967 0.3222 0.000 0.000 0.000 0.632 0.012 0.356
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 6 0.3728 0.5405 0.000 0.344 0.000 0.004 0.000 0.652
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.1387 0.9028 0.932 0.000 0.000 0.000 0.068 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3534 0.5727 0.000 0.000 0.000 0.740 0.016 0.244
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.1387 0.9028 0.932 0.000 0.000 0.000 0.068 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 6 0.3695 0.4948 0.000 0.376 0.000 0.000 0.000 0.624
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.4121 0.6371 0.000 0.220 0.000 0.000 0.060 0.720
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.5050 0.0245 0.000 0.012 0.000 0.512 0.428 0.048
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1204 0.8183 0.000 0.944 0.000 0.000 0.000 0.056
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4078 0.4016 0.000 0.676 0.000 0.016 0.008 0.300
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.4696 0.6221 0.000 0.152 0.000 0.728 0.032 0.088
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.1820 0.8065 0.000 0.012 0.000 0.924 0.008 0.056
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.1531 0.9023 0.928 0.000 0.000 0.000 0.068 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 6 0.3812 0.6057 0.000 0.004 0.000 0.268 0.016 0.712
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.1933 0.8063 0.000 0.012 0.000 0.924 0.032 0.032
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.2587 0.7611 0.000 0.004 0.000 0.868 0.108 0.020
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.5532 0.1658 0.000 0.408 0.000 0.500 0.032 0.060
#> 21821B38-6786-4078-9918-EC0E877C1533 5 0.3998 0.5088 0.000 0.016 0.000 0.340 0.644 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.2255 0.7995 0.000 0.024 0.000 0.908 0.024 0.044
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0260 0.8381 0.000 0.992 0.000 0.000 0.000 0.008
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.5753 0.5196 0.524 0.000 0.012 0.004 0.344 0.116
#> 8865E079-D8AB-406C-8886-C854F1A26201 6 0.3737 0.4469 0.000 0.392 0.000 0.000 0.000 0.608
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.4349 0.5603 0.000 0.084 0.000 0.000 0.208 0.708
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.2007 0.8976 0.916 0.000 0.000 0.004 0.036 0.044
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0146 0.8382 0.000 0.996 0.000 0.000 0.000 0.004
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1555 0.9071 0.932 0.000 0.000 0.004 0.060 0.004
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4312 0.2789 0.000 0.604 0.000 0.000 0.368 0.028
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 6 0.3790 0.6149 0.000 0.004 0.000 0.264 0.016 0.716
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.2912 0.8701 0.000 0.000 0.852 0.000 0.076 0.072
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.1594 0.8984 0.932 0.000 0.000 0.000 0.016 0.052
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0790 0.8368 0.000 0.968 0.000 0.000 0.000 0.032
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 6 0.5325 0.3034 0.000 0.000 0.364 0.080 0.012 0.544
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.1453 0.8096 0.000 0.008 0.000 0.944 0.008 0.040
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.1866 0.9020 0.908 0.000 0.000 0.000 0.084 0.008
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0146 0.8380 0.000 0.996 0.000 0.000 0.000 0.004
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#> 59C375B4-60FB-4598-A146-5B175C2B8079 5 0.4196 0.4694 0.000 0.332 0.000 0.028 0.640 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0717 0.8387 0.000 0.976 0.000 0.000 0.008 0.016
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.1398 0.8087 0.000 0.000 0.000 0.940 0.008 0.052
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0260 0.8376 0.000 0.992 0.000 0.000 0.000 0.008
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.3405 0.7479 0.000 0.832 0.000 0.068 0.016 0.084
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 4 0.3693 0.5496 0.000 0.000 0.004 0.708 0.280 0.008
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 5 0.4012 0.5032 0.000 0.016 0.000 0.344 0.640 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.1643 0.9012 0.924 0.000 0.000 0.000 0.068 0.008
#> A4CECC77-3764-4F27-BD37-D7E76E436944 6 0.3531 0.5467 0.000 0.328 0.000 0.000 0.000 0.672
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0767 0.8375 0.000 0.976 0.000 0.008 0.004 0.012
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.1401 0.8098 0.000 0.004 0.000 0.948 0.028 0.020
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.2138 0.8953 0.908 0.000 0.000 0.004 0.036 0.052
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 6 0.5829 0.1522 0.000 0.192 0.000 0.000 0.360 0.448
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.2015 0.8016 0.000 0.012 0.000 0.916 0.016 0.056
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.1643 0.9012 0.924 0.000 0.000 0.000 0.068 0.008
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.2912 0.8701 0.000 0.000 0.852 0.000 0.076 0.072
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.4613 0.4812 0.000 0.028 0.000 0.676 0.264 0.032
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.1624 0.8050 0.000 0.004 0.000 0.936 0.040 0.020
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 5 0.4078 0.4570 0.000 0.340 0.000 0.020 0.640 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 5 0.3394 0.4774 0.236 0.000 0.000 0.012 0.752 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.1642 0.9025 0.936 0.000 0.000 0.004 0.032 0.028
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.1333 0.8329 0.000 0.944 0.000 0.000 0.008 0.048
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1333 0.8329 0.000 0.944 0.000 0.000 0.008 0.048
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.5697 0.4012 0.000 0.632 0.000 0.196 0.116 0.056
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.3457 0.5939 0.000 0.000 0.000 0.752 0.016 0.232
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0790 0.8368 0.000 0.968 0.000 0.000 0.000 0.032
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.4946 -0.0452 0.000 0.012 0.008 0.496 0.460 0.024
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.2009 0.7994 0.000 0.004 0.000 0.916 0.040 0.040
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.1232 0.9069 0.956 0.000 0.000 0.004 0.024 0.016
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 5 0.3886 0.4557 0.264 0.000 0.000 0.000 0.708 0.028
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1049 0.8358 0.000 0.960 0.000 0.000 0.008 0.032
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.1606 0.9055 0.932 0.000 0.000 0.004 0.056 0.008
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 5 0.4793 0.4574 0.000 0.288 0.000 0.000 0.628 0.084
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0713 0.8375 0.000 0.972 0.000 0.000 0.000 0.028
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.3183 0.7345 0.000 0.004 0.000 0.828 0.128 0.040
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2744 0.8758 0.000 0.000 0.864 0.000 0.064 0.072
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.4740 0.5229 0.000 0.108 0.000 0.000 0.228 0.664
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 5 0.4460 0.2167 0.000 0.452 0.000 0.000 0.520 0.028
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9259 0.000 0.000 1.000 0.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0260 0.8380 0.000 0.992 0.000 0.000 0.000 0.008
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0777 0.8330 0.000 0.972 0.000 0.000 0.024 0.004
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.3784 0.5386 0.000 0.012 0.000 0.308 0.680 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.5916 0.3743 0.000 0.204 0.000 0.596 0.156 0.044
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.2207 0.8097 0.000 0.900 0.000 0.016 0.008 0.076
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2912 0.8701 0.000 0.000 0.852 0.000 0.076 0.072
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.5501 0.5658 0.552 0.000 0.008 0.000 0.320 0.120
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.5560 0.4547 0.120 0.044 0.000 0.004 0.656 0.176
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.2234 0.8123 0.000 0.872 0.000 0.000 0.004 0.124
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.4628 0.2310 0.000 0.000 0.572 0.024 0.012 0.392
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1204 0.8183 0.000 0.944 0.000 0.000 0.000 0.056
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.4026 0.2627 0.000 0.000 0.000 0.612 0.012 0.376
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.4641 0.6301 0.000 0.124 0.000 0.036 0.100 0.740
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.1194 0.8094 0.000 0.004 0.000 0.956 0.032 0.008
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.1760 0.8019 0.000 0.004 0.000 0.928 0.020 0.048
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4980 0.5859 0.000 0.712 0.000 0.148 0.052 0.088
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2009 0.9021 0.904 0.000 0.000 0.004 0.084 0.008
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.7640 0.1472 0.000 0.192 0.012 0.320 0.344 0.132
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.1307 0.8091 0.000 0.008 0.000 0.952 0.008 0.032
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.2706 0.7850 0.000 0.016 0.000 0.880 0.044 0.060
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.5171 0.6028 0.000 0.072 0.000 0.248 0.648 0.032
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.4642 0.2543 0.000 0.012 0.000 0.452 0.516 0.020
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1478 0.8091 0.000 0.004 0.000 0.944 0.032 0.020
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4414 0.4879 0.000 0.676 0.000 0.000 0.260 0.064
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.6224 -0.0865 0.000 0.000 0.424 0.216 0.012 0.348
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.3238 0.7640 0.000 0.016 0.000 0.844 0.080 0.060
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1594 0.8984 0.932 0.000 0.000 0.000 0.016 0.052
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3539 0.7519 0.000 0.828 0.000 0.052 0.032 0.088
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.1387 0.9028 0.932 0.000 0.000 0.000 0.068 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.3283 0.5585 0.160 0.000 0.000 0.036 0.804 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.4267 0.6547 0.000 0.080 0.000 0.132 0.024 0.764
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.3918 0.6835 0.000 0.016 0.000 0.776 0.160 0.048
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2620 0.8044 0.000 0.888 0.000 0.024 0.040 0.048
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0653 0.8057 0.000 0.004 0.000 0.980 0.004 0.012
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3307 0.7056 0.000 0.808 0.000 0.000 0.044 0.148
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0260 0.9280 0.000 0.000 0.992 0.008 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3673 0.5646 0.000 0.004 0.000 0.736 0.016 0.244
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 5 0.5984 0.1346 0.000 0.236 0.000 0.000 0.420 0.344
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2138 0.8953 0.908 0.000 0.000 0.004 0.036 0.052
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.4373 0.5365 0.000 0.008 0.000 0.688 0.260 0.044
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.2964 0.7819 0.000 0.036 0.000 0.868 0.036 0.060
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1196 0.8272 0.000 0.952 0.000 0.000 0.008 0.040
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0858 0.8089 0.000 0.004 0.000 0.968 0.028 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4468 0.3512 0.000 0.604 0.000 0.008 0.364 0.024
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2315 0.8042 0.000 0.892 0.000 0.016 0.008 0.084
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.4642 0.4341 0.000 0.356 0.000 0.052 0.592 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2531 0.7313 0.000 0.000 0.000 0.856 0.012 0.132
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4774 0.4876 0.600 0.000 0.000 0.000 0.068 0.332
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.1053 0.8075 0.000 0.004 0.000 0.964 0.020 0.012
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0858 0.8089 0.000 0.004 0.000 0.968 0.028 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.3878 0.5586 0.000 0.004 0.000 0.320 0.008 0.668
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4048 0.2420 0.000 0.644 0.000 0.012 0.004 0.340
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1562 0.9033 0.940 0.000 0.000 0.004 0.032 0.024
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.3717 0.4824 0.000 0.384 0.000 0.000 0.000 0.616
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2277 0.8985 0.892 0.000 0.000 0.000 0.076 0.032
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.5874 0.5114 0.000 0.000 0.196 0.252 0.012 0.540
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0790 0.8368 0.000 0.968 0.000 0.000 0.000 0.032
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2007 0.7984 0.000 0.004 0.000 0.916 0.036 0.044
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1594 0.8984 0.932 0.000 0.000 0.000 0.016 0.052
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.4606 0.5736 0.000 0.004 0.032 0.300 0.012 0.652
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", "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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.477 0.853 0.907 0.4768 0.530 0.530
#> 3 3 0.824 0.874 0.945 0.3713 0.689 0.476
#> 4 4 0.753 0.706 0.871 0.1322 0.817 0.539
#> 5 5 0.806 0.771 0.887 0.0705 0.872 0.571
#> 6 6 0.769 0.665 0.814 0.0445 0.914 0.630
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.7453 0.82270 0.212 0.788
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.1633 0.89555 0.976 0.024
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.6048 0.88509 0.148 0.852
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.89235 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.89822 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.6048 0.88509 0.148 0.852
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.6048 0.88509 0.148 0.852
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#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.5737 0.88829 0.136 0.864
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.89235 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.5946 0.87125 0.856 0.144
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.9922 0.40755 0.448 0.552
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.89235 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.89235 0.000 1.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.89822 1.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.89822 1.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.5178 0.81849 0.116 0.884
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.6048 0.88509 0.148 0.852
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.6048 0.88509 0.148 0.852
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.8713 0.48717 0.708 0.292
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.5946 0.88637 0.144 0.856
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.6048 0.88509 0.148 0.852
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.6048 0.87024 0.852 0.148
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.1633 0.89540 0.024 0.976
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.7883 0.80540 0.236 0.764
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.6048 0.88509 0.148 0.852
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.89235 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.1184 0.89467 0.016 0.984
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.89235 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.6048 0.87024 0.852 0.148
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.6048 0.88509 0.148 0.852
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.89822 1.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.6048 0.88509 0.148 0.852
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4161 0.89534 0.084 0.916
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.4939 0.80227 0.108 0.892
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.89822 1.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.6048 0.88509 0.148 0.852
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.89235 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.89822 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.6048 0.87024 0.852 0.148
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.89235 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.89235 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.6048 0.88509 0.148 0.852
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.89822 1.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.89822 1.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.5946 0.88637 0.144 0.856
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.5946 0.88637 0.144 0.856
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4690 0.89265 0.100 0.900
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.89235 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.6048 0.88509 0.148 0.852
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.6048 0.87024 0.852 0.148
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.89235 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0938 0.89707 0.988 0.012
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.89822 1.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.5629 0.88927 0.132 0.868
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.89822 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.7602 0.82387 0.220 0.780
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.6048 0.88509 0.148 0.852
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.2043 0.87476 0.032 0.968
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.6048 0.87024 0.852 0.148
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.6048 0.88509 0.148 0.852
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.6048 0.88509 0.148 0.852
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.6048 0.87024 0.852 0.148
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.6048 0.88509 0.148 0.852
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.6712 0.86598 0.176 0.824
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.2778 0.89279 0.952 0.048
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.89235 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.89235 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.6048 0.87024 0.852 0.148
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.6048 0.87024 0.852 0.148
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.89822 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.9170 0.37032 0.668 0.332
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5946 0.88637 0.144 0.856
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.6048 0.87024 0.852 0.148
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.6048 0.88509 0.148 0.852
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.89235 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.6048 0.88509 0.148 0.852
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0376 0.89073 0.004 0.996
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.89235 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.89235 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.1843 0.89511 0.972 0.028
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.9209 0.34721 0.336 0.664
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.89235 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.89235 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.9944 -0.06775 0.544 0.456
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.6048 0.88509 0.148 0.852
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.89235 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6048 0.88509 0.148 0.852
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.6048 0.87024 0.852 0.148
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.89235 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.89822 1.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.89235 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.6048 0.87024 0.852 0.148
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.89822 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.6048 0.87024 0.852 0.148
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.89822 1.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.5842 0.88738 0.140 0.860
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.89235 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0376 0.89328 0.004 0.996
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.89235 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.6048 0.88509 0.148 0.852
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.6048 0.87024 0.852 0.148
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.89235 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6048 0.88509 0.148 0.852
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.89822 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0938 0.89483 0.012 0.988
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.89235 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.6048 0.88509 0.148 0.852
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.9996 0.29872 0.512 0.488
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.9944 0.32164 0.456 0.544
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2603 0.89755 0.044 0.956
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6048 0.88509 0.148 0.852
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.6048 0.87024 0.852 0.148
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.89822 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.2423 0.86882 0.040 0.960
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3431 0.84866 0.064 0.936
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2236 0.89611 0.036 0.964
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.6048 0.88509 0.148 0.852
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.89822 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.6048 0.88509 0.148 0.852
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.89822 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9323 0.31886 0.348 0.652
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.6048 0.88509 0.148 0.852
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5842 0.76075 0.140 0.860
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.89822 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.7453 0.81476 0.788 0.212
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.6859 0.24976 0.564 0.420 0.016
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.96634 1.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.93279 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2878 0.86641 0.000 0.904 0.096
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.96634 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.93279 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.93279 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.92716 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.93279 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.92716 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.93279 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.4555 0.75018 0.000 0.200 0.800
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.93279 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 3 0.3619 0.84258 0.000 0.136 0.864
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.92716 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.93279 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.96634 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.0000 0.92716 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 3 0.2878 0.87480 0.000 0.096 0.904
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0000 0.92716 0.000 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.6204 0.22326 0.000 0.576 0.424
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 3 0.2959 0.87230 0.000 0.100 0.900
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0592 0.92573 0.012 0.988 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0000 0.92716 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 3 0.5882 0.50791 0.000 0.348 0.652
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 3 0.4346 0.77213 0.000 0.184 0.816
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.93279 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 3 0.2878 0.87480 0.000 0.096 0.904
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.96634 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.4452 0.73757 0.000 0.808 0.192
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.96634 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.2261 0.88271 0.000 0.932 0.068
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.93279 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.93279 0.000 1.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.92716 0.000 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2878 0.86233 0.096 0.904 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.0000 0.92716 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.93279 0.000 1.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.93279 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.96634 1.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 3 0.1411 0.91042 0.000 0.036 0.964
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.5926 0.44008 0.644 0.356 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.96634 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.92716 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2959 0.85889 0.100 0.900 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.93279 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 3 0.2878 0.87480 0.000 0.096 0.904
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.96634 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.96634 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.92716 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.6126 0.34452 0.000 0.400 0.600
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 3 0.5859 0.51687 0.000 0.344 0.656
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 3 0.4178 0.78687 0.000 0.172 0.828
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 3 0.6295 0.21675 0.000 0.472 0.528
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 3 0.1753 0.90312 0.000 0.048 0.952
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.92716 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.96634 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.5291 0.64489 0.000 0.268 0.732
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.96634 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.96634 1.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.93279 0.000 1.000 0.000
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#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.93279 0.000 1.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.93279 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.96634 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.92716 0.000 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 3 0.5465 0.60755 0.000 0.288 0.712
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 3 0.3340 0.84529 0.000 0.120 0.880
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.2959 0.85921 0.100 0.900 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.96634 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.96634 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.93279 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.93279 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2878 0.86641 0.000 0.904 0.096
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 3 0.2959 0.87230 0.000 0.100 0.900
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.93279 0.000 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.92716 0.000 0.000 1.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 3 0.3116 0.85715 0.000 0.108 0.892
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.96634 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.96634 1.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.93279 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.96634 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.6295 0.13234 0.472 0.528 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.93279 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 3 0.3267 0.84933 0.000 0.116 0.884
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.92716 0.000 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.93279 0.000 1.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.93279 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.92716 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.93279 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.3116 0.85253 0.108 0.892 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.0747 0.95209 0.984 0.000 0.016
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.2959 0.86398 0.000 0.900 0.100
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.93279 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.92716 0.000 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.92716 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.96634 1.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0000 0.96634 1.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.93279 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.2796 0.87738 0.000 0.092 0.908
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.93279 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 3 0.3816 0.83561 0.000 0.148 0.852
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.93279 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.92716 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 3 0.6307 0.11653 0.000 0.488 0.512
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2878 0.86641 0.000 0.904 0.096
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.96634 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.5178 0.66560 0.000 0.256 0.744
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.6168 0.25688 0.000 0.588 0.412
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.93279 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.0424 0.95917 0.992 0.008 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.93279 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 3 0.0000 0.92716 0.000 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.93279 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.1031 0.91646 0.000 0.024 0.976
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.2711 0.87307 0.000 0.912 0.088
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.96634 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2878 0.86641 0.000 0.904 0.096
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.92716 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.96634 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.92716 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.96634 1.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.93279 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.2878 0.86641 0.000 0.904 0.096
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2878 0.86641 0.000 0.904 0.096
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.0000 0.92716 0.000 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.93279 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.92716 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 3 0.6062 0.42059 0.000 0.384 0.616
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.93279 0.000 1.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.96634 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2959 0.86311 0.000 0.900 0.100
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.2878 0.86641 0.000 0.904 0.096
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.93279 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.92716 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3886 0.85388 0.024 0.880 0.096
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.93279 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.93279 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.92716 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.96634 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.0000 0.92716 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.92716 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.6299 0.05134 0.000 0.524 0.476
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.93279 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.96634 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.93279 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.96634 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.2878 0.87480 0.000 0.096 0.904
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.93279 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0424 0.92375 0.000 0.008 0.992
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.96634 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.2878 0.87480 0.000 0.096 0.904
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.7221 0.200053 0.140 0.424 0.000 0.436
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.4985 0.270843 0.000 0.468 0.000 0.532
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4981 0.384995 0.000 0.536 0.000 0.464
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.5000 0.218440 0.000 0.000 0.496 0.504
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.4790 0.444636 0.000 0.000 0.380 0.620
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4898 0.384838 0.000 0.416 0.000 0.584
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.4866 0.091521 0.000 0.000 0.404 0.596
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0817 0.688594 0.000 0.000 0.024 0.976
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.5172 0.416213 0.000 0.008 0.404 0.588
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4277 0.334745 0.000 0.280 0.000 0.720
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.3528 0.642896 0.000 0.000 0.808 0.192
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0469 0.833908 0.000 0.988 0.000 0.012
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4989 -0.138917 0.000 0.000 0.528 0.472
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4877 0.480702 0.000 0.592 0.000 0.408
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.6729 0.475358 0.000 0.128 0.284 0.588
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4304 0.549650 0.284 0.716 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.0188 0.699679 0.000 0.000 0.004 0.996
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.4830 0.342359 0.000 0.392 0.608 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.2149 0.636898 0.000 0.000 0.088 0.912
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.7006 0.457402 0.000 0.340 0.132 0.528
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0336 0.700053 0.000 0.000 0.008 0.992
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.4959 0.595809 0.000 0.052 0.752 0.196
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.3569 0.638050 0.000 0.000 0.804 0.196
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4994 -0.133293 0.000 0.520 0.000 0.480
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.0817 0.688594 0.000 0.000 0.024 0.976
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.0817 0.688594 0.000 0.000 0.024 0.976
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.4817 0.505190 0.000 0.612 0.000 0.388
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.3569 0.505519 0.000 0.196 0.000 0.804
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#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.4907 0.396831 0.000 0.000 0.420 0.580
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4741 0.570814 0.004 0.668 0.000 0.328
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.0336 0.700547 0.000 0.008 0.000 0.992
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.6815 0.502624 0.000 0.284 0.136 0.580
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.4804 0.440562 0.000 0.000 0.384 0.616
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0336 0.837341 0.008 0.992 0.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0707 0.827822 0.000 0.980 0.000 0.020
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0469 0.699075 0.000 0.000 0.012 0.988
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.5138 0.335439 0.392 0.600 0.000 0.008
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.3219 0.760448 0.836 0.000 0.164 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4804 0.193243 0.000 0.616 0.000 0.384
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0707 0.827867 0.000 0.980 0.000 0.020
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0921 0.932821 0.972 0.028 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.4866 0.305786 0.000 0.000 0.596 0.404
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.4888 0.475597 0.000 0.588 0.000 0.412
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.4925 0.381318 0.000 0.000 0.428 0.572
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.5762 0.210285 0.000 0.040 0.608 0.352
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.4888 0.393079 0.000 0.412 0.000 0.588
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.3528 0.738349 0.808 0.192 0.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.0188 0.701165 0.000 0.004 0.000 0.996
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.4898 0.404160 0.000 0.000 0.416 0.584
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4866 0.305786 0.000 0.000 0.596 0.404
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.4888 0.393079 0.000 0.412 0.000 0.588
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.4843 -0.027787 0.000 0.396 0.000 0.604
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.4925 0.365701 0.000 0.428 0.000 0.572
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0817 0.828925 0.000 0.976 0.000 0.024
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.880459 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4817 0.505190 0.000 0.612 0.000 0.388
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.4888 0.393079 0.000 0.412 0.000 0.588
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.4888 0.393079 0.000 0.412 0.000 0.588
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.4406 0.413643 0.000 0.000 0.700 0.300
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.1716 0.789310 0.000 0.936 0.000 0.064
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1940 0.651087 0.000 0.000 0.076 0.924
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2704 0.829984 0.876 0.000 0.000 0.124
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.701571 0.000 0.000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4877 0.480702 0.000 0.592 0.000 0.408
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4761 0.522935 0.000 0.628 0.000 0.372
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4888 0.292064 0.000 0.000 0.588 0.412
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.842385 0.000 1.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4888 0.411294 0.000 0.000 0.412 0.588
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.960381 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4933 0.019903 0.000 0.000 0.432 0.568
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.0000 0.75321 0.000 0.000 0.000 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.2813 0.82568 0.832 0.000 0.000 0.000 0.168
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.2291 0.74912 0.000 0.056 0.000 0.036 0.908
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4045 0.46858 0.000 0.356 0.000 0.644 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.4150 0.40929 0.000 0.388 0.000 0.612 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.2813 0.69697 0.000 0.168 0.000 0.832 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.1341 0.77781 0.000 0.000 0.000 0.056 0.944
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.6674 0.35453 0.000 0.000 0.324 0.248 0.428
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 5 0.4307 -0.00269 0.000 0.000 0.000 0.496 0.504
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.3480 0.73881 0.000 0.000 0.000 0.248 0.752
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0963 0.76343 0.000 0.000 0.000 0.964 0.036
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.4015 0.20717 0.000 0.000 0.000 0.652 0.348
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4448 -0.24099 0.000 0.004 0.000 0.516 0.480
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2732 0.67498 0.000 0.000 0.160 0.840 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1410 0.86583 0.000 0.940 0.000 0.000 0.060
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.3635 0.73771 0.000 0.000 0.004 0.248 0.748
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 5 0.1732 0.78257 0.000 0.000 0.000 0.080 0.920
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4030 0.23832 0.000 0.000 0.000 0.648 0.352
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.1270 0.75834 0.000 0.052 0.000 0.948 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4300 -0.02206 0.000 0.524 0.000 0.476 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.6588 0.31873 0.000 0.000 0.348 0.216 0.436
#> 775E9758-CBA2-4B87-844A-120E56FE2141 5 0.4249 0.01346 0.000 0.432 0.000 0.000 0.568
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 5 0.3635 0.73771 0.000 0.000 0.004 0.248 0.748
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4242 0.12970 0.000 0.572 0.000 0.428 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 5 0.3480 0.73881 0.000 0.000 0.000 0.248 0.752
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.2344 0.85029 0.032 0.904 0.000 0.000 0.064
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0794 0.95778 0.972 0.000 0.000 0.000 0.028
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3636 0.69711 0.000 0.728 0.000 0.000 0.272
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.0880 0.76492 0.000 0.000 0.000 0.968 0.032
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.2513 0.71007 0.000 0.116 0.008 0.000 0.876
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.3904 0.75409 0.000 0.052 0.000 0.156 0.792
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4210 -0.01420 0.000 0.000 0.000 0.588 0.412
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 5 0.1965 0.78225 0.000 0.000 0.000 0.096 0.904
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.2856 0.71923 0.000 0.104 0.016 0.008 0.872
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.1197 0.94540 0.952 0.000 0.000 0.000 0.048
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.0404 0.75174 0.000 0.000 0.012 0.000 0.988
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#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.3480 0.72499 0.000 0.752 0.000 0.000 0.248
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 4 0.5377 0.08532 0.456 0.004 0.000 0.496 0.044
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 5 0.6680 0.29089 0.000 0.000 0.348 0.240 0.412
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 5 0.3561 0.72942 0.000 0.000 0.000 0.260 0.740
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 5 0.1410 0.77918 0.000 0.000 0.000 0.060 0.940
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.1121 0.94808 0.956 0.000 0.000 0.000 0.044
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 4 0.4383 0.39483 0.000 0.004 0.000 0.572 0.424
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.0162 0.95088 0.004 0.000 0.996 0.000 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0162 0.88951 0.000 0.996 0.000 0.000 0.004
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.1478 0.74649 0.000 0.000 0.000 0.936 0.064
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 5 0.1608 0.78213 0.000 0.000 0.000 0.072 0.928
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 5 0.2970 0.77176 0.004 0.000 0.000 0.168 0.828
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.3143 0.76594 0.000 0.796 0.000 0.000 0.204
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.4163 0.63494 0.000 0.740 0.000 0.228 0.032
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 5 0.4210 0.16699 0.412 0.000 0.000 0.000 0.588
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.0162 0.77324 0.000 0.004 0.000 0.996 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.3757 0.75144 0.020 0.772 0.000 0.000 0.208
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 5 0.4262 0.17452 0.000 0.000 0.000 0.440 0.560
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4287 0.11469 0.000 0.540 0.000 0.000 0.460
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.3895 0.49443 0.000 0.000 0.680 0.000 0.320
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 5 0.4572 0.02136 0.452 0.004 0.000 0.004 0.540
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.4150 0.40929 0.000 0.388 0.000 0.612 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 5 0.3480 0.73881 0.000 0.000 0.000 0.248 0.752
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.5619 0.61105 0.000 0.636 0.000 0.156 0.208
#> 2356B998-0930-403F-9B04-57A18A150955 5 0.3039 0.76609 0.000 0.000 0.000 0.192 0.808
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 5 0.0609 0.76376 0.000 0.000 0.000 0.020 0.980
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 5 0.3039 0.76560 0.000 0.000 0.000 0.192 0.808
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.3508 0.72323 0.000 0.748 0.000 0.000 0.252
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.1121 0.94808 0.956 0.000 0.000 0.000 0.044
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 5 0.4182 0.20146 0.000 0.400 0.000 0.000 0.600
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.1270 0.75506 0.000 0.000 0.000 0.948 0.052
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 5 0.1608 0.78156 0.000 0.000 0.000 0.072 0.928
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.1043 0.95056 0.960 0.000 0.000 0.000 0.040
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.3886 0.80041 0.028 0.832 0.000 0.072 0.068
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 5 0.1478 0.78057 0.000 0.000 0.000 0.064 0.936
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.5129 0.45509 0.000 0.328 0.000 0.616 0.056
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.1043 0.87650 0.000 0.960 0.000 0.000 0.040
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0162 0.88993 0.000 0.996 0.000 0.000 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.0880 0.74379 0.032 0.000 0.000 0.000 0.968
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 5 0.6341 0.25941 0.000 0.396 0.000 0.160 0.444
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0880 0.87926 0.000 0.968 0.000 0.000 0.032
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.2955 0.87787 0.876 0.060 0.000 0.004 0.060
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.1341 0.86406 0.000 0.944 0.000 0.000 0.056
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3661 0.57476 0.000 0.000 0.724 0.276 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.4000 0.62255 0.000 0.228 0.000 0.748 0.024
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 5 0.3480 0.73881 0.000 0.000 0.000 0.248 0.752
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3913 0.31611 0.000 0.000 0.000 0.676 0.324
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 5 0.2773 0.67218 0.000 0.164 0.000 0.000 0.836
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.3053 0.74480 0.000 0.076 0.008 0.044 0.872
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4114 0.15953 0.000 0.000 0.000 0.624 0.376
#> F5F7B591-062D-4FF0-AB68-73D678574318 5 0.1544 0.78144 0.000 0.000 0.000 0.068 0.932
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.4078 0.76183 0.784 0.148 0.000 0.000 0.068
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.1341 0.73354 0.000 0.000 0.000 0.056 0.944
#> DB7FD043-2A8F-480A-A208-912D99CE8848 5 0.3480 0.73881 0.000 0.000 0.000 0.248 0.752
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0290 0.88858 0.000 0.992 0.000 0.000 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.3074 0.71776 0.000 0.000 0.804 0.196 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 5 0.1608 0.78213 0.000 0.000 0.000 0.072 0.928
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1341 0.86462 0.000 0.944 0.000 0.000 0.056
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1197 0.94540 0.952 0.000 0.000 0.000 0.048
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.4094 0.67453 0.000 0.084 0.000 0.788 0.128
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.4133 0.74687 0.000 0.052 0.000 0.180 0.768
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0963 0.87277 0.000 0.964 0.000 0.000 0.036
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.3586 0.72546 0.000 0.000 0.000 0.264 0.736
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0290 0.88662 0.000 0.992 0.000 0.008 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.95419 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0880 0.76496 0.000 0.000 0.000 0.968 0.032
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.3705 0.77426 0.000 0.816 0.000 0.120 0.064
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 5 0.1484 0.77350 0.000 0.008 0.000 0.048 0.944
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 5 0.1608 0.78213 0.000 0.000 0.000 0.072 0.928
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 5 0.4210 0.73469 0.000 0.000 0.036 0.224 0.740
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1270 0.86936 0.000 0.948 0.000 0.000 0.052
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1965 0.83767 0.000 0.904 0.000 0.000 0.096
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3480 0.72499 0.000 0.752 0.000 0.000 0.248
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1836 0.75759 0.000 0.000 0.036 0.932 0.032
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2852 0.76081 0.828 0.000 0.000 0.172 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.3586 0.72559 0.000 0.000 0.000 0.264 0.736
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.3607 0.74060 0.000 0.000 0.004 0.244 0.752
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.77370 0.000 0.000 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4219 0.18616 0.000 0.584 0.000 0.416 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2773 0.74053 0.000 0.836 0.000 0.164 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4219 0.27938 0.000 0.000 0.416 0.584 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.89001 0.000 1.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.1831 0.78264 0.000 0.000 0.004 0.076 0.920
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.97299 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.2471 0.69526 0.000 0.000 0.136 0.864 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.3464 0.48745 0.000 0.000 0.000 0.312 0.688 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.4613 0.64380 0.196 0.000 0.000 0.116 0.688 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0146 0.86704 0.000 0.996 0.000 0.000 0.004 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.2999 0.65510 0.000 0.124 0.000 0.836 0.040 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.3468 0.38060 0.000 0.284 0.000 0.000 0.004 0.712
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.3619 0.33071 0.000 0.316 0.000 0.000 0.004 0.680
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.90525 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0260 0.86609 0.000 0.992 0.000 0.008 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.90525 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.2134 0.52082 0.000 0.052 0.000 0.044 0.000 0.904
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0717 0.78153 0.000 0.000 0.000 0.976 0.016 0.008
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.86813 0.000 1.000 0.000 0.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.3952 0.57845 0.000 0.000 0.000 0.020 0.308 0.672
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.4764 0.63937 0.000 0.000 0.040 0.712 0.060 0.188
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4593 0.35913 0.000 0.000 0.000 0.620 0.056 0.324
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2218 0.77254 0.000 0.000 0.000 0.884 0.012 0.104
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.5451 0.49641 0.000 0.000 0.000 0.148 0.308 0.544
#> A0A07F44-C51B-420C-92E8-65F464DB0442 6 0.6109 0.19381 0.000 0.000 0.000 0.316 0.308 0.376
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#> F5F7B591-062D-4FF0-AB68-73D678574318 4 0.0260 0.78055 0.000 0.000 0.000 0.992 0.008 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.4979 0.60478 0.276 0.012 0.000 0.000 0.636 0.076
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.3564 0.43285 0.000 0.000 0.000 0.264 0.724 0.012
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.2020 0.77549 0.000 0.000 0.000 0.896 0.008 0.096
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3469 0.73008 0.000 0.808 0.000 0.000 0.088 0.104
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4332 0.55399 0.000 0.000 0.672 0.000 0.276 0.052
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0146 0.78153 0.000 0.000 0.000 0.996 0.004 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3534 0.59358 0.000 0.716 0.000 0.276 0.008 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.90525 0.000 0.000 1.000 0.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.90525 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.3547 0.56146 0.332 0.000 0.000 0.000 0.668 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.2526 0.50199 0.000 0.024 0.000 0.096 0.004 0.876
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.3299 0.74281 0.000 0.012 0.000 0.820 0.028 0.140
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2020 0.79779 0.000 0.896 0.000 0.096 0.008 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.5667 0.34246 0.000 0.000 0.000 0.520 0.288 0.192
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3601 0.52436 0.000 0.684 0.000 0.000 0.004 0.312
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.90525 0.000 0.000 1.000 0.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 6 0.5507 0.48952 0.000 0.000 0.000 0.156 0.308 0.536
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 6 0.5608 -0.16388 0.000 0.148 0.000 0.000 0.380 0.472
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.1970 0.73975 0.000 0.000 0.000 0.900 0.092 0.008
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0146 0.78153 0.000 0.000 0.000 0.996 0.004 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1349 0.83696 0.000 0.940 0.000 0.000 0.004 0.056
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2165 0.77154 0.000 0.000 0.000 0.884 0.008 0.108
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2801 0.76753 0.000 0.860 0.000 0.072 0.068 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2562 0.72411 0.000 0.828 0.000 0.172 0.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 5 0.3874 0.46866 0.000 0.356 0.000 0.008 0.636 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 6 0.6123 0.50710 0.000 0.000 0.096 0.060 0.320 0.524
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3390 0.53091 0.704 0.000 0.000 0.000 0.000 0.296
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3483 0.67319 0.000 0.000 0.000 0.764 0.024 0.212
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2020 0.77646 0.000 0.000 0.000 0.896 0.008 0.096
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.1829 0.57558 0.000 0.000 0.000 0.024 0.056 0.920
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.3840 0.52835 0.000 0.696 0.000 0.000 0.020 0.284
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.3999 -0.13171 0.000 0.496 0.000 0.000 0.004 0.500
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5975 0.04066 0.000 0.000 0.444 0.000 0.300 0.256
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.86813 0.000 1.000 0.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0405 0.78346 0.000 0.000 0.000 0.988 0.004 0.008
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.96429 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.4616 0.58383 0.000 0.000 0.072 0.000 0.280 0.648
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 17581 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 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 0.247 0.529 0.700 0.3812 0.503 0.503
#> 3 3 0.367 0.644 0.763 0.4583 0.546 0.379
#> 4 4 0.743 0.760 0.901 0.2649 0.729 0.494
#> 5 5 0.704 0.719 0.844 0.0944 0.857 0.562
#> 6 6 0.690 0.614 0.811 0.0399 0.940 0.746
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.8813 0.67079 0.700 0.300
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.9686 0.54999 0.604 0.396
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.9552 0.60882 0.376 0.624
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 1 0.8813 0.67079 0.700 0.300
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.0000 0.49237 0.000 1.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.9552 0.60882 0.376 0.624
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.9427 0.60686 0.360 0.640
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.8081 0.32398 0.752 0.248
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.9552 0.60882 0.376 0.624
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.5629 0.39504 0.868 0.132
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.9552 0.60882 0.376 0.624
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.8813 0.67079 0.700 0.300
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.9552 0.60882 0.376 0.624
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.8813 0.67079 0.700 0.300
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.7674 0.62189 0.776 0.224
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.8813 0.67079 0.700 0.300
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.0000 0.49237 0.000 1.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.8813 0.67079 0.700 0.300
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 1 0.8813 0.67079 0.700 0.300
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.8813 0.67079 0.700 0.300
#> A4967738-7FC2-4270-A149-56E459EDB875 1 0.8813 0.67079 0.700 0.300
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.7815 0.62674 0.768 0.232
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.9087 0.59614 0.324 0.676
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.7815 0.62726 0.768 0.232
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.9896 0.43862 0.440 0.560
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.8813 0.67079 0.700 0.300
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.9552 0.60882 0.376 0.624
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 1 0.8813 0.67079 0.700 0.300
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.3733 0.40971 0.072 0.928
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.9552 0.60882 0.376 0.624
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.0000 0.49237 0.000 1.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.9710 0.55643 0.400 0.600
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.9552 0.60882 0.376 0.624
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.9552 0.60882 0.376 0.624
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.6343 0.57400 0.840 0.160
#> 775E9758-CBA2-4B87-844A-120E56FE2141 1 0.9775 0.29543 0.588 0.412
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 1 0.8813 0.67079 0.700 0.300
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.9552 0.60882 0.376 0.624
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.9552 0.60882 0.376 0.624
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.9087 -0.15237 0.324 0.676
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 1 0.8813 0.67079 0.700 0.300
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.9460 0.60572 0.364 0.636
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.8763 -0.04496 0.296 0.704
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.7376 0.35012 0.792 0.208
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.9552 0.60882 0.376 0.624
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.9552 0.60882 0.376 0.624
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.8813 0.67079 0.700 0.300
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.0000 0.49237 0.000 1.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.0000 0.49237 0.000 1.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.4690 0.41305 0.900 0.100
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 1 0.6531 0.51787 0.832 0.168
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.9922 0.41028 0.448 0.552
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 1 0.8955 0.64269 0.688 0.312
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 1 0.8813 0.67079 0.700 0.300
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 1 0.8813 0.67079 0.700 0.300
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.5737 0.39258 0.864 0.136
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.0000 0.49237 0.000 1.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.5842 0.53546 0.860 0.140
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.0000 0.49237 0.000 1.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.7376 0.55765 0.208 0.792
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.9552 0.60882 0.376 0.624
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.9248 0.62747 0.660 0.340
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.0000 0.49237 0.000 1.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 1 0.8813 0.67079 0.700 0.300
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.9552 -0.11973 0.376 0.624
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 1 0.8813 0.67079 0.700 0.300
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.9552 0.60882 0.376 0.624
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 1 0.8813 0.67079 0.700 0.300
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.8813 0.67079 0.700 0.300
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.9552 0.60882 0.376 0.624
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.0000 0.49237 0.000 1.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.8813 0.67079 0.700 0.300
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.0000 0.49237 0.000 1.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.8909 0.59120 0.308 0.692
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.8608 0.58491 0.284 0.716
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.9686 0.56673 0.396 0.604
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.9209 0.60098 0.336 0.664
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.9552 0.60882 0.376 0.624
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 1 0.8813 0.67079 0.700 0.300
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 1 0.8813 0.67079 0.700 0.300
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.0000 0.49237 0.000 1.000
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#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 1 0.8813 0.67079 0.700 0.300
#> F5F7B591-062D-4FF0-AB68-73D678574318 1 0.8813 0.67079 0.700 0.300
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.9522 0.60860 0.372 0.628
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 1 0.8813 0.67079 0.700 0.300
#> DB7FD043-2A8F-480A-A208-912D99CE8848 1 0.8813 0.67079 0.700 0.300
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.9393 0.60586 0.356 0.644
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.8555 0.47628 0.720 0.280
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 1 0.8813 0.67079 0.700 0.300
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.0376 0.49372 0.004 0.996
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 1 0.8813 0.67079 0.700 0.300
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0376 0.45847 0.996 0.004
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.0000 0.49237 0.000 1.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.5408 0.40050 0.876 0.124
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.9129 -0.14186 0.328 0.672
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.9552 0.60882 0.376 0.624
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 1 0.8813 0.67079 0.700 0.300
#> 981123DE-D55E-41D1-8850-1A41376F1DED 1 0.8813 0.67079 0.700 0.300
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 1 0.8813 0.67079 0.700 0.300
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.9552 0.60882 0.376 0.624
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.1843 0.44980 0.972 0.028
#> 05127463-A69A-42B3-9635-575A08EB980A 1 0.8813 0.67079 0.700 0.300
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.9552 0.60882 0.376 0.624
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.0000 0.49237 0.000 1.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 1 0.8813 0.67079 0.700 0.300
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 1 0.8813 0.67079 0.700 0.300
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.9552 0.60882 0.376 0.624
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.7883 0.63013 0.764 0.236
#> 534B9E41-B731-4461-ABEA-30096148A493 1 1.0000 -0.18976 0.500 0.500
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.9552 0.60882 0.376 0.624
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.9552 0.60882 0.376 0.624
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.7745 0.52662 0.772 0.228
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.0000 0.49237 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.8813 0.67079 0.700 0.300
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 1 0.8813 0.67079 0.700 0.300
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.9686 0.56665 0.396 0.604
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.9552 0.60882 0.376 0.624
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.0000 0.49237 0.000 1.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.9552 0.60882 0.376 0.624
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.9963 -0.22425 0.464 0.536
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.7674 0.62091 0.776 0.224
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.9552 0.60882 0.376 0.624
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 1 0.8813 0.67079 0.700 0.300
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.0000 0.49237 0.000 1.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.8443 0.59013 0.728 0.272
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4346 0.65461 0.000 0.816 0.184
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6091 0.68481 0.092 0.784 0.124
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.5678 0.60546 0.316 0.684 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3965 0.67870 0.008 0.860 0.132
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3038 0.77028 0.896 0.104 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5678 0.60546 0.316 0.684 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.5706 0.60104 0.320 0.680 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.86980 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.7613 0.60865 0.316 0.620 0.064
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.86980 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4702 0.64299 0.212 0.788 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4346 0.65461 0.000 0.816 0.184
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.5678 0.60546 0.316 0.684 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.3412 0.67648 0.000 0.876 0.124
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.5327 0.53931 0.000 0.728 0.272
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.3340 0.67750 0.000 0.880 0.120
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.77810 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.4346 0.65461 0.000 0.816 0.184
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.4346 0.65461 0.000 0.816 0.184
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.4346 0.65461 0.000 0.816 0.184
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.4002 0.66563 0.000 0.840 0.160
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6274 -0.10012 0.000 0.544 0.456
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.5706 0.60104 0.320 0.680 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.4452 0.64709 0.000 0.808 0.192
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.3192 0.67634 0.000 0.888 0.112
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4346 0.65461 0.000 0.816 0.184
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.5678 0.60546 0.316 0.684 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.4346 0.65461 0.000 0.816 0.184
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.6757 0.64700 0.736 0.180 0.084
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.2050 0.69160 0.028 0.952 0.020
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.2796 0.77464 0.908 0.092 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3607 0.68183 0.112 0.880 0.008
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.5363 0.62675 0.276 0.724 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.5678 0.60546 0.316 0.684 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.5178 0.67207 0.000 0.256 0.744
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1585 0.69420 0.008 0.964 0.028
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.4796 0.61667 0.000 0.780 0.220
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.5678 0.60546 0.316 0.684 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4931 0.64639 0.232 0.768 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6796 0.60065 0.708 0.236 0.056
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4346 0.65461 0.000 0.816 0.184
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.5678 0.60546 0.316 0.684 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5560 0.55822 0.700 0.300 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.86980 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.5363 0.62598 0.276 0.724 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.5678 0.60546 0.316 0.684 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.4346 0.65461 0.000 0.816 0.184
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.77810 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.77810 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.86980 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.6235 0.25452 0.000 0.564 0.436
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.5835 0.63924 0.052 0.784 0.164
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5710 0.68664 0.080 0.804 0.116
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.4346 0.65461 0.000 0.816 0.184
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4346 0.65461 0.000 0.816 0.184
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.86980 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.4178 0.73562 0.828 0.172 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.5465 0.59177 0.000 0.712 0.288
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.2959 0.77183 0.900 0.100 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4750 0.59629 0.216 0.784 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.7164 0.61003 0.316 0.640 0.044
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4346 0.65461 0.000 0.816 0.184
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.77810 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.4346 0.65461 0.000 0.816 0.184
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.8082 0.40254 0.296 0.608 0.096
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4346 0.65461 0.000 0.816 0.184
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.5397 0.62668 0.280 0.720 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.4346 0.65461 0.000 0.816 0.184
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.4235 0.64190 0.000 0.824 0.176
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.5678 0.60546 0.316 0.684 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.77810 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.4452 0.63911 0.000 0.808 0.192
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2537 0.77802 0.920 0.080 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.5706 0.60104 0.320 0.680 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.6180 0.06761 0.584 0.416 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5760 0.67734 0.140 0.796 0.064
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.5810 0.58182 0.336 0.664 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.5397 0.62697 0.280 0.720 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.3192 0.68010 0.000 0.888 0.112
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.3879 0.66827 0.000 0.848 0.152
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0424 0.77950 0.992 0.008 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.2448 0.68795 0.000 0.924 0.076
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.86980 0.000 0.000 1.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4346 0.65461 0.000 0.816 0.184
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.6302 0.23237 0.000 0.480 0.520
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.2772 0.68370 0.080 0.916 0.004
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.1289 0.69448 0.000 0.968 0.032
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4504 0.65861 0.196 0.804 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.5678 0.60546 0.316 0.684 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.5431 0.50024 0.284 0.000 0.716
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.5678 0.60546 0.316 0.684 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.5678 0.60546 0.316 0.684 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.77810 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.5678 0.60546 0.316 0.684 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.4178 0.73562 0.828 0.172 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.5678 0.60546 0.316 0.684 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.86980 0.000 0.000 1.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.5678 0.60546 0.316 0.684 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.86980 0.000 0.000 1.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.77810 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.5678 0.60546 0.316 0.684 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.9021 0.42867 0.184 0.264 0.552
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.86980 0.000 0.000 1.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3482 0.67534 0.000 0.872 0.128
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.7297 0.60706 0.708 0.172 0.120
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.5902 0.60752 0.316 0.680 0.004
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.4842 0.61191 0.000 0.776 0.224
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.4291 0.72867 0.820 0.180 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.6793 0.67782 0.160 0.740 0.100
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.5397 0.52345 0.000 0.720 0.280
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.6613 0.67440 0.188 0.740 0.072
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.4346 0.65461 0.000 0.816 0.184
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.5785 0.58726 0.000 0.332 0.668
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.4346 0.65461 0.000 0.816 0.184
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.5678 0.60546 0.316 0.684 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.77810 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.77810 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.3340 0.67750 0.000 0.880 0.120
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.2804 0.68805 0.060 0.924 0.016
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.8710 -0.10147 0.508 0.380 0.112
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.4178 0.73562 0.828 0.172 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.86980 0.000 0.000 1.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.77810 1.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.86980 0.000 0.000 1.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.5678 0.60546 0.316 0.684 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.4346 0.65461 0.000 0.816 0.184
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.4002 0.65442 0.000 0.840 0.160
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.5431 0.62237 0.284 0.716 0.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.5138 0.63751 0.252 0.748 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.86980 0.000 0.000 1.000
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#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4346 0.65461 0.000 0.816 0.184
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.5678 0.60546 0.316 0.684 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.5988 0.32995 0.000 0.632 0.368
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.7562 0.61368 0.308 0.628 0.064
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4931 0.64442 0.232 0.768 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4605 0.64688 0.204 0.796 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.5968 0.52831 0.000 0.364 0.636
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.3192 0.76689 0.888 0.112 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.4346 0.65461 0.000 0.816 0.184
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4346 0.65461 0.000 0.816 0.184
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2955 0.68908 0.008 0.912 0.080
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5678 0.60546 0.316 0.684 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.77810 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.5678 0.60546 0.316 0.684 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.7525 0.56965 0.684 0.208 0.108
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5760 0.52859 0.000 0.328 0.672
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.5678 0.60546 0.316 0.684 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.4346 0.65461 0.000 0.816 0.184
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0237 0.77889 0.996 0.004 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.8744 0.31561 0.108 0.444 0.448
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.4996 -0.0194 0.000 0.484 0.000 0.516
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0336 0.8738 0.000 0.992 0.000 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.3311 0.6913 0.000 0.172 0.000 0.828
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0592 0.8706 0.000 0.984 0.000 0.016
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4746 0.3866 0.000 0.632 0.000 0.368
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0592 0.8706 0.000 0.984 0.000 0.016
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0336 0.8173 0.000 0.008 0.000 0.992
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.1389 0.7984 0.000 0.048 0.000 0.952
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.7851 -0.1177 0.000 0.376 0.268 0.356
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0188 0.8194 0.000 0.004 0.000 0.996
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0336 0.8191 0.000 0.008 0.000 0.992
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4843 0.4316 0.000 0.396 0.000 0.604
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4998 -0.1224 0.000 0.512 0.000 0.488
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0817 0.8663 0.000 0.976 0.000 0.024
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.1637 0.7786 0.000 0.000 0.060 0.940
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4888 0.3959 0.000 0.412 0.000 0.588
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3528 0.6825 0.000 0.808 0.000 0.192
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0188 0.9480 0.996 0.000 0.000 0.004
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0188 0.8748 0.000 0.996 0.000 0.004
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2868 0.8134 0.000 0.000 0.864 0.136
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.0592 0.8091 0.000 0.000 0.016 0.984
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.4998 0.1072 0.000 0.512 0.000 0.488
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0592 0.8706 0.000 0.984 0.000 0.016
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4304 0.5414 0.000 0.716 0.000 0.284
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.7688 0.1231 0.284 0.260 0.000 0.456
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2921 0.7482 0.000 0.860 0.000 0.140
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0592 0.8706 0.000 0.984 0.000 0.016
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.4624 0.5232 0.000 0.340 0.000 0.660
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0188 0.8745 0.004 0.996 0.000 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.1389 0.8464 0.000 0.952 0.000 0.048
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.1637 0.8376 0.000 0.940 0.000 0.060
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.4941 0.3458 0.000 0.436 0.000 0.564
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4040 0.6395 0.000 0.248 0.000 0.752
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.0592 0.8091 0.000 0.000 0.016 0.984
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4605 0.3829 0.000 0.664 0.000 0.336
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.4790 0.4594 0.000 0.380 0.000 0.620
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4855 0.2195 0.000 0.600 0.000 0.400
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 4 0.7880 -0.2453 0.284 0.000 0.344 0.372
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0592 0.8706 0.000 0.984 0.000 0.016
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.3612 0.7993 0.144 0.004 0.840 0.012
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 4 0.4898 0.1891 0.000 0.416 0.000 0.584
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.1302 0.7986 0.000 0.044 0.000 0.956
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4877 0.4072 0.000 0.408 0.000 0.592
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.0469 0.8139 0.000 0.012 0.000 0.988
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.0707 0.8078 0.000 0.000 0.020 0.980
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0336 0.8738 0.000 0.992 0.000 0.008
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.4972 -0.0011 0.000 0.544 0.000 0.456
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.8845 0.2296 0.180 0.444 0.076 0.300
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0188 0.8748 0.000 0.996 0.000 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.1302 0.8517 0.000 0.956 0.000 0.044
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 4 0.4356 0.4707 0.000 0.000 0.292 0.708
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.4989 -0.0521 0.000 0.528 0.000 0.472
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.2081 0.8520 0.916 0.000 0.000 0.084
#> 15C85716-4BE3-43A8-9F61-2929C600C828 3 0.7143 0.2306 0.380 0.000 0.484 0.136
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.0000 0.8761 0.000 1.000 0.000 0.000
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#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9427 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1211 0.8031 0.000 0.040 0.000 0.960
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.1557 0.7992 0.000 0.056 0.000 0.944
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0336 0.8148 0.000 0.000 0.008 0.992
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4776 0.3752 0.000 0.624 0.000 0.376
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0707 0.8687 0.000 0.980 0.000 0.020
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3569 0.6792 0.000 0.804 0.000 0.196
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.2469 0.7415 0.000 0.000 0.108 0.892
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0000 0.8193 0.000 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4776 0.4704 0.000 0.376 0.000 0.624
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0188 0.9480 0.996 0.000 0.000 0.004
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.5307 0.6585 0.000 0.188 0.736 0.076
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8761 0.000 1.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0188 0.8200 0.000 0.004 0.000 0.996
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9519 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.7945 0.1536 0.376 0.008 0.404 0.212
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.2929 0.8467 0.000 0.000 0.000 0.180 0.820
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.4318 0.4915 0.000 0.292 0.000 0.020 0.688
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3010 0.7038 0.000 0.824 0.000 0.172 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.4467 0.6596 0.000 0.164 0.000 0.084 0.752
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4171 0.2535 0.000 0.396 0.000 0.604 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0290 0.8414 0.000 0.992 0.000 0.008 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2520 0.7907 0.000 0.896 0.000 0.048 0.056
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.3274 0.5592 0.000 0.220 0.000 0.780 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.2773 0.8515 0.000 0.000 0.000 0.164 0.836
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0162 0.8430 0.000 0.996 0.000 0.000 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.3305 0.5754 0.000 0.000 0.000 0.776 0.224
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.2852 0.8513 0.000 0.000 0.000 0.172 0.828
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.2983 0.7135 0.000 0.056 0.000 0.868 0.076
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.2852 0.8513 0.000 0.000 0.000 0.172 0.828
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 5 0.4165 0.7454 0.000 0.008 0.000 0.320 0.672
#> A0A07F44-C51B-420C-92E8-65F464DB0442 5 0.3837 0.7356 0.000 0.000 0.000 0.308 0.692
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.2388 0.7136 0.000 0.028 0.000 0.900 0.072
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3612 0.5296 0.000 0.000 0.228 0.764 0.008
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0671 0.7184 0.000 0.004 0.000 0.980 0.016
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 5 0.3636 0.7833 0.000 0.000 0.000 0.272 0.728
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2230 0.7106 0.000 0.000 0.000 0.884 0.116
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0404 0.7196 0.000 0.012 0.000 0.988 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4168 0.6564 0.000 0.200 0.000 0.756 0.044
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4305 0.0997 0.000 0.512 0.000 0.488 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.2970 0.8516 0.000 0.000 0.004 0.168 0.828
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4010 0.7239 0.000 0.088 0.000 0.796 0.116
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 5 0.2891 0.8509 0.000 0.000 0.000 0.176 0.824
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.2732 0.6396 0.000 0.160 0.000 0.840 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.3857 0.3854 0.000 0.000 0.000 0.688 0.312
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.1478 0.8989 0.936 0.000 0.000 0.064 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0162 0.8430 0.000 0.996 0.000 0.000 0.004
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0162 0.8430 0.000 0.996 0.000 0.000 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.3395 0.5355 0.000 0.000 0.000 0.764 0.236
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.5261 0.1019 0.000 0.000 0.528 0.048 0.424
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.2773 0.8515 0.000 0.000 0.000 0.164 0.836
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.1851 0.7180 0.000 0.000 0.000 0.912 0.088
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 5 0.3857 0.4622 0.000 0.312 0.000 0.000 0.688
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 5 0.4210 0.5129 0.000 0.000 0.000 0.412 0.588
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 5 0.4297 0.1639 0.000 0.000 0.000 0.472 0.528
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.2813 0.8513 0.000 0.000 0.000 0.168 0.832
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4273 0.2533 0.000 0.552 0.000 0.448 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1043 0.8209 0.000 0.960 0.000 0.000 0.040
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.2773 0.8515 0.000 0.000 0.000 0.164 0.836
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2074 0.7134 0.000 0.000 0.000 0.896 0.104
#> 12FD30FF-4D3A-4920-BF80-F44132824017 5 0.6004 0.4205 0.256 0.168 0.000 0.000 0.576
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.3837 0.5053 0.000 0.000 0.000 0.692 0.308
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3671 0.6317 0.000 0.756 0.000 0.236 0.008
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.4305 0.3741 0.000 0.000 0.000 0.488 0.512
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2127 0.7130 0.000 0.000 0.000 0.892 0.108
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4235 0.2890 0.000 0.576 0.000 0.424 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.2074 0.7134 0.000 0.000 0.000 0.896 0.104
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0609 0.8371 0.000 0.980 0.000 0.020 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4734 0.6321 0.000 0.728 0.000 0.176 0.096
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.3612 0.4908 0.000 0.268 0.000 0.732 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.5335 0.4953 0.000 0.096 0.000 0.644 0.260
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4599 0.4626 0.000 0.040 0.000 0.688 0.272
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.1894 0.7254 0.000 0.008 0.000 0.920 0.072
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.4171 0.3188 0.000 0.000 0.000 0.604 0.396
#> EB9FCAC4-2937-46BC-A560-E506412F8966 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.3487 0.6003 0.000 0.212 0.000 0.780 0.008
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.3506 0.7222 0.000 0.064 0.000 0.832 0.104
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.3479 0.7290 0.000 0.084 0.000 0.836 0.080
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 5 0.5886 0.3908 0.272 0.000 0.144 0.000 0.584
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.4045 0.4546 0.000 0.644 0.000 0.356 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.1041 0.8285 0.000 0.964 0.000 0.032 0.004
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.1484 0.8752 0.000 0.000 0.944 0.048 0.008
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.3814 0.5796 0.000 0.720 0.000 0.276 0.004
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.2773 0.8504 0.000 0.000 0.836 0.000 0.164
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.4060 0.4606 0.000 0.640 0.000 0.360 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.4297 0.1087 0.000 0.000 0.528 0.472 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.3289 0.7228 0.000 0.048 0.000 0.844 0.108
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0451 0.8413 0.000 0.988 0.000 0.008 0.004
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.2179 0.7120 0.000 0.000 0.000 0.888 0.112
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.6500 -0.1364 0.000 0.412 0.000 0.400 0.188
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.3098 0.8443 0.000 0.016 0.000 0.148 0.836
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.3090 0.7278 0.000 0.052 0.000 0.860 0.088
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.2891 0.8500 0.000 0.000 0.000 0.176 0.824
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 5 0.3671 0.7994 0.000 0.000 0.008 0.236 0.756
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 5 0.2891 0.8495 0.000 0.000 0.000 0.176 0.824
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.3143 0.6777 0.000 0.796 0.000 0.204 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.0404 0.7203 0.000 0.012 0.000 0.988 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 4 0.5264 0.3337 0.000 0.392 0.000 0.556 0.052
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.6689 0.4171 0.060 0.544 0.088 0.000 0.308
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 5 0.3508 0.7944 0.000 0.000 0.000 0.252 0.748
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.2074 0.7149 0.000 0.000 0.000 0.896 0.104
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#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0162 0.8430 0.000 0.996 0.000 0.000 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0162 0.8430 0.000 0.996 0.000 0.000 0.004
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.3816 0.7272 0.000 0.000 0.000 0.304 0.696
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4275 0.5292 0.000 0.696 0.000 0.284 0.020
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.4665 0.4843 0.000 0.048 0.000 0.692 0.260
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2773 0.8504 0.000 0.000 0.836 0.000 0.164
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.7049 0.3842 0.068 0.556 0.212 0.000 0.164
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4304 0.1585 0.000 0.516 0.000 0.484 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3508 0.6332 0.000 0.000 0.748 0.252 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3636 0.3116 0.000 0.000 0.000 0.728 0.272
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0794 0.8312 0.000 0.972 0.000 0.028 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 5 0.2852 0.8513 0.000 0.000 0.000 0.172 0.828
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.2074 0.7134 0.000 0.000 0.000 0.896 0.104
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 5 0.4395 0.7351 0.000 0.064 0.000 0.188 0.748
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.2773 0.8515 0.000 0.000 0.000 0.164 0.836
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4369 0.6594 0.000 0.052 0.000 0.740 0.208
#> F5F7B591-062D-4FF0-AB68-73D678574318 5 0.5548 0.2660 0.000 0.068 0.000 0.440 0.492
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0510 0.8377 0.000 0.984 0.000 0.016 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.3527 0.7201 0.000 0.056 0.000 0.828 0.116
#> DB7FD043-2A8F-480A-A208-912D99CE8848 5 0.3876 0.6681 0.000 0.000 0.000 0.316 0.684
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4283 0.1628 0.000 0.000 0.544 0.456 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.4210 0.2893 0.000 0.000 0.000 0.588 0.412
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 5 0.3767 0.7954 0.000 0.068 0.000 0.120 0.812
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.5086 0.4550 0.304 0.060 0.000 0.000 0.636
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.3048 0.7083 0.000 0.820 0.000 0.176 0.004
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.3596 0.6030 0.000 0.212 0.000 0.012 0.776
#> 981123DE-D55E-41D1-8850-1A41376F1DED 5 0.4717 0.6534 0.000 0.120 0.000 0.144 0.736
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9019 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3409 0.6296 0.000 0.024 0.000 0.816 0.160
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 5 0.4617 0.3316 0.000 0.012 0.000 0.436 0.552
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 5 0.3242 0.8268 0.000 0.000 0.000 0.216 0.784
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4182 0.3626 0.000 0.600 0.000 0.000 0.400
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.4818 0.0568 0.000 0.460 0.000 0.520 0.020
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.3615 0.7037 0.000 0.156 0.000 0.808 0.036
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.4653 0.3931 0.000 0.000 0.012 0.472 0.516
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.2813 0.8517 0.000 0.000 0.000 0.168 0.832
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.2067 0.7327 0.000 0.032 0.000 0.920 0.048
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0162 0.8428 0.000 0.996 0.000 0.004 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3242 0.8335 0.852 0.000 0.000 0.076 0.072
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.3707 0.4693 0.000 0.000 0.284 0.716 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8437 0.000 1.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.3305 0.8222 0.000 0.000 0.000 0.224 0.776
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9583 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.3305 0.5559 0.000 0.000 0.224 0.776 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.1075 0.774872 0.000 0.000 0.000 0.952 0.000 0.048
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.4087 0.473563 0.000 0.276 0.000 0.688 0.000 0.036
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3927 0.601481 0.000 0.712 0.000 0.004 0.024 0.260
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.3992 0.620242 0.000 0.136 0.000 0.760 0.000 0.104
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.5647 0.297403 0.000 0.296 0.000 0.000 0.184 0.520
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3312 0.721930 0.000 0.792 0.000 0.000 0.180 0.028
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.862946 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3013 0.747055 0.000 0.832 0.000 0.004 0.024 0.140
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.862946 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.3806 0.360323 0.000 0.048 0.000 0.000 0.200 0.752
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0363 0.780993 0.000 0.000 0.000 0.988 0.000 0.012
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0777 0.838345 0.000 0.972 0.000 0.004 0.000 0.024
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.5962 0.078245 0.000 0.000 0.000 0.300 0.448 0.252
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0603 0.780184 0.000 0.000 0.000 0.980 0.004 0.016
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 6 0.2740 0.572277 0.000 0.028 0.000 0.120 0.000 0.852
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0458 0.780529 0.000 0.000 0.000 0.984 0.000 0.016
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5624 0.383155 0.000 0.000 0.000 0.536 0.264 0.200
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.5048 0.414120 0.000 0.000 0.000 0.616 0.264 0.120
#> A4967738-7FC2-4270-A149-56E459EDB875 6 0.1829 0.554677 0.000 0.000 0.000 0.056 0.024 0.920
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 5 0.5907 0.012766 0.000 0.000 0.368 0.004 0.448 0.180
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0363 0.844389 0.000 0.988 0.000 0.000 0.000 0.012
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0146 0.781868 0.000 0.000 0.000 0.996 0.000 0.004
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.4979 0.002967 0.000 0.004 0.000 0.056 0.448 0.492
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3126 0.612530 0.000 0.000 0.000 0.752 0.000 0.248
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 6 0.3841 0.565637 0.000 0.000 0.000 0.244 0.032 0.724
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.4332 0.198236 0.000 0.008 0.000 0.020 0.344 0.628
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 6 0.7033 0.300799 0.000 0.172 0.000 0.120 0.248 0.460
#> 839EC959-1497-45DC-8E46-B5C285215603 6 0.3854 0.097409 0.000 0.464 0.000 0.000 0.000 0.536
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.0146 0.781868 0.000 0.000 0.000 0.996 0.000 0.004
#> 775E9758-CBA2-4B87-844A-120E56FE2141 6 0.3954 0.584980 0.000 0.056 0.000 0.204 0.000 0.740
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0363 0.781380 0.000 0.000 0.000 0.988 0.000 0.012
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 6 0.1364 0.545508 0.000 0.020 0.000 0.016 0.012 0.952
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 6 0.3151 0.496040 0.000 0.000 0.000 0.252 0.000 0.748
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.845788 0.000 1.000 0.000 0.000 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.3126 0.643878 0.752 0.000 0.000 0.000 0.248 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.862946 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1124 0.841588 0.000 0.956 0.000 0.008 0.000 0.036
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0777 0.838345 0.000 0.972 0.000 0.004 0.000 0.024
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 6 0.5992 0.224860 0.000 0.000 0.000 0.292 0.268 0.440
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 4 0.4352 0.501535 0.000 0.000 0.280 0.668 0.052 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.1636 0.770360 0.000 0.004 0.000 0.936 0.024 0.036
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 5 0.5855 -0.009156 0.000 0.000 0.000 0.200 0.448 0.352
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3934 0.440080 0.000 0.304 0.000 0.676 0.000 0.020
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.2730 0.614033 0.000 0.000 0.000 0.808 0.000 0.192
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3774 -0.022072 0.000 0.000 0.000 0.592 0.000 0.408
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.862946 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.1562 0.771558 0.000 0.004 0.000 0.940 0.024 0.032
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4666 0.151950 0.000 0.536 0.000 0.000 0.044 0.420
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0777 0.838345 0.000 0.972 0.000 0.004 0.000 0.024
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.1082 0.773664 0.000 0.004 0.000 0.956 0.000 0.040
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 6 0.5770 0.365922 0.000 0.000 0.000 0.240 0.252 0.508
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.5792 0.347087 0.248 0.172 0.000 0.564 0.000 0.016
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 6 0.3489 0.560287 0.000 0.004 0.000 0.288 0.000 0.708
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3748 0.531512 0.000 0.688 0.000 0.012 0.000 0.300
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 5 0.5855 0.065090 0.000 0.000 0.000 0.352 0.448 0.200
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 6 0.5905 0.316481 0.000 0.000 0.000 0.244 0.288 0.468
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4224 0.197338 0.000 0.552 0.000 0.000 0.016 0.432
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 6 0.5829 0.344299 0.000 0.000 0.000 0.240 0.268 0.492
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.3714 0.692898 0.000 0.760 0.000 0.000 0.196 0.044
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4904 0.494956 0.000 0.644 0.000 0.120 0.000 0.236
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> 8751D026-849B-44ED-933B-FD9B80DE329E 6 0.5640 0.266337 0.000 0.200 0.000 0.000 0.268 0.532
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 6 0.3141 0.504645 0.000 0.012 0.000 0.200 0.000 0.788
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 6 0.3404 0.508617 0.000 0.016 0.000 0.224 0.000 0.760
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.942930 1.000 0.000 0.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 5 0.5970 -0.000849 0.000 0.004 0.000 0.196 0.444 0.356
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.862946 0.000 0.000 1.000 0.000 0.000 0.000
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#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0363 0.844389 0.000 0.988 0.000 0.000 0.000 0.012
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#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0146 0.845919 0.000 0.996 0.000 0.000 0.000 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1501 0.752191 0.000 0.000 0.000 0.924 0.000 0.076
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#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.6280 0.141247 0.000 0.000 0.180 0.024 0.448 0.348
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 17581 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 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 0.608 0.877 0.936 0.4028 0.603 0.603
#> 3 3 0.943 0.933 0.972 0.1795 0.916 0.863
#> 4 4 0.731 0.831 0.924 0.4731 0.757 0.546
#> 5 5 0.678 0.695 0.818 0.0650 0.962 0.875
#> 6 6 0.648 0.549 0.753 0.0486 0.905 0.676
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4690 0.900 0.100 0.900
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6343 0.845 0.160 0.840
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4690 0.900 0.100 0.900
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.938 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.906 1.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.938 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4431 0.905 0.092 0.908
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.7745 0.811 0.772 0.228
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4690 0.900 0.100 0.900
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.9933 0.370 0.548 0.452
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.938 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.938 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3274 0.920 0.060 0.940
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.938 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0000 0.938 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.938 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.906 1.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.938 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.938 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.938 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.938 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0000 0.938 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4690 0.900 0.100 0.900
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0000 0.938 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.938 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.938 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1414 0.933 0.020 0.980
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.938 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.906 1.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.938 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.906 1.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.938 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.938 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4690 0.900 0.100 0.900
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.0000 0.938 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4690 0.900 0.100 0.900
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.938 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4431 0.905 0.092 0.908
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.938 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.906 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.938 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4690 0.900 0.100 0.900
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.8555 0.640 0.720 0.280
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 2 1.0000 -0.220 0.500 0.500
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4690 0.900 0.100 0.900
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4161 0.909 0.084 0.916
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.938 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.906 1.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.906 1.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.7745 0.811 0.772 0.228
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.0000 0.938 0.000 1.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.938 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.938 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.938 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.938 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 2 1.0000 -0.206 0.496 0.504
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.906 1.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.0000 0.938 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.906 1.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4690 0.900 0.100 0.900
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.4690 0.900 0.100 0.900
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.0000 0.938 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.906 1.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.938 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.7139 0.799 0.196 0.804
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.3431 0.918 0.064 0.936
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3431 0.918 0.064 0.936
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.938 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0000 0.938 0.000 1.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.938 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.906 1.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0000 0.938 0.000 1.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.906 1.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.2043 0.930 0.032 0.968
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.3879 0.913 0.076 0.924
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.3431 0.918 0.064 0.936
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.4690 0.900 0.100 0.900
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.938 0.000 1.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.938 0.000 1.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.938 0.000 1.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.906 1.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.938 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.7745 0.811 0.772 0.228
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.938 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.0000 0.938 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.938 0.000 1.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4690 0.900 0.100 0.900
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.938 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4690 0.900 0.100 0.900
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0376 0.905 0.996 0.004
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.938 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.2948 0.923 0.052 0.948
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.906 1.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.4431 0.905 0.092 0.908
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.906 1.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4690 0.900 0.100 0.900
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.7745 0.811 0.772 0.228
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.938 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.7745 0.811 0.772 0.228
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.906 1.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.938 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.9686 0.192 0.396 0.604
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.7745 0.811 0.772 0.228
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.938 0.000 1.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0000 0.906 1.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0672 0.936 0.008 0.992
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.0000 0.938 0.000 1.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.906 1.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.3584 0.917 0.068 0.932
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.9129 0.562 0.328 0.672
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.938 0.000 1.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.2236 0.929 0.036 0.964
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.0000 0.938 0.000 1.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.938 0.000 1.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.938 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.906 1.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.906 1.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.938 0.000 1.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.2603 0.926 0.044 0.956
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.906 1.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.906 1.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.7745 0.811 0.772 0.228
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.906 1.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.7745 0.811 0.772 0.228
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.2948 0.923 0.052 0.948
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.938 0.000 1.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0000 0.938 0.000 1.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.4690 0.900 0.100 0.900
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.938 0.000 1.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.7745 0.811 0.772 0.228
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 2 0.0000 0.938 0.000 1.000
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0000 0.938 0.000 1.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0000 0.938 0.000 1.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0000 0.938 0.000 1.000
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0000 0.938 0.000 1.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.906 1.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 1 0.7745 0.811 0.772 0.228
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.906 1.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.0000 0.938 0.000 1.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.0000 0.938 0.000 1.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0000 0.906 1.000 0.000
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.6973 0.832 0.812 0.188
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.4690 0.900 0.100 0.900
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.4690 0.900 0.100 0.900
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0000 0.938 0.000 1.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0000 0.938 0.000 1.000
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.0000 0.938 0.000 1.000
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 2 0.9996 -0.176 0.488 0.512
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.5408 0.880 0.124 0.876
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.0000 0.906 1.000 0.000
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0000 0.906 1.000 0.000
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.0000 0.938 0.000 1.000
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0000 0.938 0.000 1.000
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.4690 0.900 0.100 0.900
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.0000 0.938 0.000 1.000
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.4690 0.900 0.100 0.900
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 2 0.4161 0.909 0.084 0.916
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 2 0.0000 0.938 0.000 1.000
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 2 0.0000 0.938 0.000 1.000
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 1 0.0000 0.906 1.000 0.000
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 2 0.0000 0.938 0.000 1.000
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#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.7745 0.811 0.772 0.228
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.906 1.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0000 0.938 0.000 1.000
#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.7745 0.811 0.772 0.228
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.0000 0.938 0.000 1.000
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.0000 0.938 0.000 1.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0000 0.938 0.000 1.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.938 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.938 0.000 1.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0000 0.938 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.0000 0.938 0.000 1.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.906 1.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.906 1.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.4690 0.900 0.100 0.900
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.4690 0.900 0.100 0.900
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.0000 0.938 0.000 1.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.9608 0.242 0.384 0.616
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.906 1.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.1633 0.932 0.024 0.976
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.7745 0.811 0.772 0.228
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4690 0.900 0.100 0.900
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.4690 0.900 0.100 0.900
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0000 0.938 0.000 1.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.8763 0.716 0.704 0.296
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.0000 0.938 0.000 1.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.938 0.000 1.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.3584 0.867 0.932 0.068
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 2 1.0000 -0.206 0.496 0.504
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0000 0.938 0.000 1.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.938 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.7745 0.811 0.772 0.228
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.4690 0.900 0.100 0.900
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.938 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.938 0.000 1.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.906 1.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.906 1.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.1414 0.933 0.020 0.980
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4690 0.900 0.100 0.900
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.4690 0.900 0.100 0.900
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.4690 0.900 0.100 0.900
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.2778 0.925 0.048 0.952
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.4690 0.900 0.100 0.900
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.8327 0.764 0.736 0.264
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.938 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4690 0.900 0.100 0.900
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4690 0.900 0.100 0.900
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.938 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.938 0.000 1.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.938 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.9996 0.265 0.512 0.488
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.4690 0.900 0.100 0.900
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.906 1.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.938 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.938 0.000 1.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.938 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.906 1.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.4690 0.900 0.100 0.900
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.938 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.906 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.7745 0.811 0.772 0.228
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.938 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.938 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4690 0.900 0.100 0.900
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.5629 0.836 0.868 0.132
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.906 1.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.938 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.3274 0.920 0.060 0.940
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2948 0.923 0.052 0.948
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.938 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.938 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.9710 0.178 0.400 0.600
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.938 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.906 1.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.1414 0.897 0.980 0.020
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.938 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.906 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4690 0.900 0.100 0.900
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4690 0.900 0.100 0.900
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.938 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.7745 0.811 0.772 0.228
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4562 0.902 0.096 0.904
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4690 0.900 0.100 0.900
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.7745 0.811 0.772 0.228
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4690 0.900 0.100 0.900
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4690 0.900 0.100 0.900
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.3879 0.913 0.076 0.924
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.938 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.938 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.7745 0.811 0.772 0.228
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.9833 0.449 0.576 0.424
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.906 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.4690 0.900 0.100 0.900
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.938 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.9710 0.177 0.400 0.600
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3431 0.918 0.064 0.936
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.938 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0672 0.936 0.008 0.992
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0000 0.938 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.938 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.938 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.906 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.938 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.938 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.938 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4690 0.900 0.100 0.900
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.938 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.938 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4690 0.900 0.100 0.900
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.7674 0.650 0.224 0.776
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.938 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0672 0.903 0.992 0.008
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2948 0.923 0.052 0.948
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 2 0.9710 0.177 0.400 0.600
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.906 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.9661 0.528 0.608 0.392
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.7219 0.730 0.800 0.200
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.938 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.938 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.938 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.938 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4690 0.900 0.100 0.900
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 2 0.9996 -0.176 0.488 0.512
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.938 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4690 0.900 0.100 0.900
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.906 1.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2043 0.929 0.032 0.968
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.938 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4690 0.900 0.100 0.900
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.0000 0.938 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4690 0.900 0.100 0.900
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.938 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4690 0.900 0.100 0.900
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.0000 0.938 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.906 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.938 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.938 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.938 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.938 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.906 1.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.2603 0.926 0.044 0.956
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.906 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.5408 0.815 0.124 0.876
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3584 0.917 0.068 0.932
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.938 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.906 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0672 0.933 0.008 0.992
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.9761 0.000 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3816 0.8196 0.148 0.852 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9761 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9761 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9436 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9761 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9761 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9425 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9761 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9425 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9761 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0747 0.9695 0.000 0.984 0.016
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9761 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0747 0.9698 0.000 0.984 0.016
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.2878 0.9027 0.000 0.904 0.096
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9761 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9436 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.1031 0.9649 0.000 0.976 0.024
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9761 0.000 1.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.1289 0.9593 0.000 0.968 0.032
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0592 0.9714 0.000 0.988 0.012
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.4654 0.7608 0.000 0.792 0.208
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.9761 0.000 1.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.3619 0.8601 0.000 0.864 0.136
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.1643 0.9460 0.000 0.956 0.044
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0747 0.9695 0.000 0.984 0.016
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9761 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0592 0.9714 0.000 0.988 0.012
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9436 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9761 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9436 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0592 0.9714 0.000 0.988 0.012
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9761 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.9761 0.000 1.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.5327 0.5674 0.000 0.272 0.728
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9761 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.2796 0.9065 0.000 0.908 0.092
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9761 0.000 1.000 0.000
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#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.9761 0.000 1.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9761 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.9761 0.000 1.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9425 0.000 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9761 0.000 1.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.9761 0.000 1.000 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9761 0.000 1.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0424 0.9731 0.000 0.992 0.008
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9761 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9761 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.4399 0.6882 0.000 0.188 0.812
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.0000 0.9761 0.000 1.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9436 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.9761 0.000 1.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9761 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0892 0.9673 0.000 0.980 0.020
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9436 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.9761 0.000 1.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9761 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9436 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0237 0.9401 0.004 0.000 0.996
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0237 0.9747 0.000 0.996 0.004
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0424 0.9731 0.000 0.992 0.008
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9761 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.2537 0.8308 0.920 0.080 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9436 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9761 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9761 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.9761 0.000 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0892 0.9673 0.000 0.980 0.020
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9761 0.000 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.5968 0.4378 0.000 0.636 0.364
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0592 0.9714 0.000 0.988 0.012
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9436 1.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.1753 0.8792 0.952 0.048 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9761 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9436 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9761 0.000 1.000 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9761 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0592 0.9714 0.000 0.988 0.012
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0237 0.9401 0.004 0.000 0.996
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9761 0.000 1.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9761 0.000 1.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9425 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9761 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9761 0.000 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.9761 0.000 1.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9761 0.000 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0237 0.9747 0.000 0.996 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0237 0.9401 0.004 0.000 0.996
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9425 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9436 1.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0000 0.9761 0.000 1.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9761 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.6079 0.3450 0.000 0.388 0.612
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9761 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9761 0.000 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9761 0.000 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.2796 0.9065 0.000 0.908 0.092
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0892 0.9673 0.000 0.980 0.020
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9761 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9436 1.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0747 0.9695 0.000 0.984 0.016
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0592 0.9714 0.000 0.988 0.012
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9761 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9761 0.000 1.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9761 0.000 1.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0892 0.9673 0.000 0.980 0.020
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9761 0.000 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.6062 0.4126 0.000 0.616 0.384
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9761 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0892 0.9178 0.980 0.020 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9761 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2261 0.8628 0.000 0.068 0.932
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9436 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9425 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4002 0.7023 0.840 0.160 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9761 0.000 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9761 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9761 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.1643 0.9500 0.000 0.956 0.044
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9761 0.000 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9425 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0747 0.9695 0.000 0.984 0.016
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9761 0.000 1.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9436 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9761 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0747 0.9695 0.000 0.984 0.016
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9761 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4605 0.7705 0.000 0.796 0.204
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9761 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9761 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9761 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.2711 0.9098 0.000 0.912 0.088
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9436 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.2796 0.9063 0.000 0.908 0.092
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.1163 0.9622 0.000 0.972 0.028
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9761 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9761 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9436 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9761 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9436 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.4887 0.7297 0.000 0.772 0.228
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9761 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0747 0.9695 0.000 0.984 0.016
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9436 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.3192 0.8793 0.000 0.888 0.112
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2760 0.8429 0.000 0.872 0.000 0.128
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.7009 0.0256 0.444 0.440 0.000 0.116
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4661 0.5311 0.000 0.652 0.000 0.348
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0336 0.8828 0.000 0.992 0.000 0.008
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.1022 0.8802 0.000 0.968 0.000 0.032
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4790 0.5127 0.000 0.620 0.000 0.380
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4605 0.4018 0.000 0.336 0.000 0.664
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.2216 0.8377 0.000 0.092 0.000 0.908
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2704 0.8035 0.000 0.000 0.124 0.876
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0817 0.8816 0.000 0.976 0.000 0.024
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.2921 0.7853 0.000 0.140 0.000 0.860
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.2973 0.7779 0.000 0.144 0.000 0.856
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0707 0.8812 0.000 0.980 0.000 0.020
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0469 0.8836 0.000 0.988 0.000 0.012
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4877 0.3033 0.000 0.000 0.592 0.408
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2704 0.8462 0.000 0.876 0.000 0.124
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1716 0.8676 0.000 0.936 0.000 0.064
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.0707 0.9058 0.000 0.020 0.000 0.980
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6548 0.4863 0.608 0.276 0.000 0.116
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0336 0.8829 0.000 0.992 0.000 0.008
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.3528 0.7468 0.000 0.000 0.808 0.192
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4624 0.5097 0.000 0.660 0.000 0.340
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.4999 -0.1456 0.000 0.492 0.000 0.508
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.4961 0.1994 0.000 0.552 0.000 0.448
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.2281 0.8379 0.000 0.096 0.000 0.904
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#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.3123 0.8247 0.000 0.844 0.000 0.156
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.2760 0.8288 0.000 0.872 0.000 0.128
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.3311 0.7842 0.000 0.828 0.000 0.172
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.4843 0.3350 0.000 0.000 0.604 0.396
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.2760 0.8429 0.000 0.872 0.000 0.128
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.1792 0.8654 0.000 0.932 0.000 0.068
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0921 0.8823 0.000 0.972 0.000 0.028
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.4222 0.5565 0.000 0.272 0.000 0.728
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.3123 0.7646 0.000 0.156 0.000 0.844
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.5998 0.5762 0.684 0.200 0.000 0.116
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1474 0.8731 0.000 0.948 0.000 0.052
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 4 0.3636 0.7365 0.000 0.172 0.008 0.820
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.3610 0.6961 0.800 0.200 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1118 0.8773 0.000 0.964 0.000 0.036
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.8807 0.000 1.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.4356 0.6602 0.000 0.708 0.000 0.292
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4999 0.2270 0.000 0.508 0.000 0.492
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1940 0.8618 0.000 0.924 0.000 0.076
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.3569 0.7487 0.000 0.804 0.000 0.196
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.3975 0.6698 0.000 0.000 0.760 0.240
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2760 0.8429 0.000 0.872 0.000 0.128
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.2081 0.8583 0.000 0.916 0.000 0.084
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.4961 0.1975 0.000 0.448 0.000 0.552
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4972 0.3347 0.000 0.544 0.000 0.456
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.3569 0.7936 0.000 0.804 0.000 0.196
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.3444 0.7284 0.000 0.000 0.184 0.816
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4877 0.4579 0.000 0.592 0.000 0.408
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0188 0.9271 0.996 0.004 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2647 0.8348 0.000 0.880 0.000 0.120
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.6548 0.4869 0.608 0.276 0.000 0.116
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.4564 0.6016 0.000 0.672 0.000 0.328
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4998 0.2362 0.000 0.512 0.000 0.488
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3074 0.8050 0.000 0.848 0.000 0.152
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0188 0.8821 0.000 0.996 0.000 0.004
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9306 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.2589 0.8495 0.000 0.884 0.000 0.116
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4967 0.3491 0.000 0.548 0.000 0.452
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.2704 0.7907 0.000 0.124 0.000 0.876
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1389 0.8735 0.000 0.952 0.000 0.048
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0469 0.8836 0.000 0.988 0.000 0.012
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0336 0.8827 0.000 0.992 0.000 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.8807 0.000 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.3266 0.7504 0.000 0.000 0.168 0.832
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0188 0.8826 0.000 0.996 0.000 0.004
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.0000 0.9190 0.000 0.000 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9311 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0000 0.9190 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4045 0.5982 0.000 0.644 0.000 0.000 0.356
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.6043 0.3925 0.168 0.264 0.000 0.000 0.568
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.2127 0.6654 0.000 0.892 0.000 0.000 0.108
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2674 0.6496 0.000 0.856 0.000 0.140 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.2864 0.7075 0.000 0.864 0.000 0.024 0.112
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.3857 0.6346 0.000 0.688 0.000 0.000 0.312
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2127 0.6654 0.000 0.892 0.000 0.000 0.108
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.4170 0.5738 0.000 0.760 0.000 0.192 0.048
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.2193 0.8305 0.000 0.028 0.000 0.912 0.060
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2074 0.6680 0.000 0.896 0.000 0.000 0.104
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1341 0.8426 0.000 0.000 0.000 0.944 0.056
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0609 0.8485 0.000 0.000 0.000 0.980 0.020
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4886 0.2062 0.000 0.528 0.000 0.448 0.024
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0290 0.8477 0.000 0.000 0.000 0.992 0.008
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.1638 0.8407 0.000 0.004 0.000 0.932 0.064
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0963 0.8461 0.000 0.000 0.000 0.964 0.036
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3427 0.7514 0.000 0.108 0.000 0.836 0.056
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3102 0.7807 0.000 0.000 0.084 0.860 0.056
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4045 0.5974 0.000 0.644 0.000 0.000 0.356
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.1270 0.8421 0.000 0.000 0.000 0.948 0.052
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.2260 0.8307 0.000 0.028 0.000 0.908 0.064
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.2209 0.8297 0.000 0.032 0.000 0.912 0.056
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1121 0.7109 0.000 0.956 0.000 0.000 0.044
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0880 0.8473 0.000 0.000 0.000 0.968 0.032
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.5117 0.4554 0.000 0.276 0.000 0.652 0.072
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4010 0.7058 0.000 0.136 0.000 0.792 0.072
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0703 0.7099 0.000 0.976 0.000 0.000 0.024
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.2773 0.7010 0.000 0.836 0.000 0.000 0.164
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4974 0.2228 0.000 0.000 0.560 0.408 0.032
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3895 0.6256 0.000 0.680 0.000 0.000 0.320
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1043 0.8432 0.000 0.000 0.000 0.960 0.040
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1544 0.6864 0.000 0.932 0.000 0.000 0.068
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.1211 0.7104 0.000 0.960 0.000 0.024 0.016
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0162 0.9107 0.996 0.000 0.000 0.000 0.004
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.3075 0.7737 0.000 0.092 0.000 0.860 0.048
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4030 0.5998 0.000 0.648 0.000 0.000 0.352
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.5908 0.3328 0.380 0.108 0.000 0.000 0.512
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3932 0.6214 0.000 0.672 0.000 0.000 0.328
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2127 0.6654 0.000 0.892 0.000 0.000 0.108
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1121 0.8449 0.000 0.000 0.000 0.956 0.044
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.3779 0.6370 0.000 0.000 0.776 0.200 0.024
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.6121 0.3218 0.000 0.380 0.000 0.132 0.488
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#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.4040 0.4876 0.000 0.724 0.000 0.260 0.016
#> DCD932D2-B708-487A-93C1-8485FBE9048A 4 0.0794 0.8479 0.000 0.000 0.000 0.972 0.028
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 4 0.2660 0.7962 0.000 0.008 0.000 0.864 0.128
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.4088 0.6097 0.000 0.632 0.000 0.000 0.368
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 2 0.4030 0.5998 0.000 0.648 0.000 0.000 0.352
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.1197 0.8442 0.000 0.000 0.000 0.952 0.048
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.5326 0.4902 0.004 0.024 0.020 0.612 0.340
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.1908 0.6758 0.000 0.908 0.000 0.000 0.092
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4030 0.5998 0.000 0.648 0.000 0.000 0.352
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.4821 0.3633 0.020 0.516 0.000 0.000 0.464
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 4 0.0794 0.8453 0.000 0.000 0.000 0.972 0.028
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.0510 0.8483 0.000 0.000 0.000 0.984 0.016
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 4 0.1907 0.8363 0.000 0.028 0.000 0.928 0.044
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.6017 -0.1782 0.480 0.116 0.000 0.000 0.404
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.3942 0.5749 0.000 0.748 0.000 0.232 0.020
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.1197 0.8442 0.000 0.000 0.000 0.952 0.048
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.6938 0.0946 0.348 0.000 0.356 0.004 0.292
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.4161 0.5922 0.000 0.608 0.000 0.000 0.392
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.1341 0.8426 0.000 0.000 0.000 0.944 0.056
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 4 0.3359 0.7645 0.000 0.108 0.000 0.840 0.052
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.5896 0.4046 0.000 0.564 0.000 0.308 0.128
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.3579 0.6715 0.000 0.756 0.000 0.004 0.240
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.3983 0.6094 0.000 0.660 0.000 0.000 0.340
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.5498 0.5617 0.000 0.612 0.000 0.096 0.292
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.2020 0.6704 0.000 0.900 0.000 0.000 0.100
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.2020 0.7129 0.000 0.900 0.000 0.000 0.100
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.3412 0.7181 0.000 0.152 0.000 0.820 0.028
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.4030 0.5998 0.000 0.648 0.000 0.000 0.352
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.2020 0.6704 0.000 0.900 0.000 0.000 0.100
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.1582 0.8421 0.000 0.028 0.000 0.944 0.028
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.2491 0.6732 0.000 0.896 0.000 0.036 0.068
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.2300 0.6765 0.000 0.904 0.000 0.024 0.072
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.5793 0.2908 0.000 0.000 0.536 0.364 0.100
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.4074 0.5935 0.000 0.636 0.000 0.000 0.364
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.1908 0.6882 0.000 0.908 0.000 0.000 0.092
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.1774 0.6898 0.000 0.932 0.000 0.016 0.052
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.1410 0.8374 0.000 0.000 0.000 0.940 0.060
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.3796 0.6397 0.000 0.700 0.000 0.000 0.300
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.4713 0.2406 0.000 0.544 0.000 0.440 0.016
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.2329 0.8161 0.876 0.000 0.000 0.000 0.124
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 4 0.4017 0.7073 0.000 0.148 0.000 0.788 0.064
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.1907 0.8385 0.000 0.028 0.000 0.928 0.044
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.3983 0.6103 0.000 0.660 0.000 0.000 0.340
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 5 0.5673 0.2399 0.420 0.080 0.000 0.000 0.500
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.2338 0.6620 0.000 0.884 0.000 0.004 0.112
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1792 0.6792 0.000 0.916 0.000 0.000 0.084
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1764 0.7150 0.000 0.928 0.000 0.008 0.064
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.1197 0.8449 0.000 0.000 0.000 0.952 0.048
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.1851 0.6777 0.000 0.912 0.000 0.000 0.088
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.6994 -0.0671 0.000 0.072 0.084 0.416 0.428
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0671 0.8478 0.000 0.004 0.000 0.980 0.016
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0290 0.9084 0.992 0.000 0.000 0.000 0.008
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.5603 -0.0962 0.476 0.072 0.000 0.000 0.452
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.1892 0.6813 0.000 0.916 0.000 0.004 0.080
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4045 0.5974 0.000 0.644 0.000 0.000 0.356
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1121 0.6965 0.000 0.956 0.000 0.000 0.044
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.1444 0.8441 0.000 0.012 0.000 0.948 0.040
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.4060 0.5953 0.000 0.640 0.000 0.000 0.360
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3730 0.6488 0.000 0.712 0.000 0.000 0.288
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1410 0.6894 0.000 0.940 0.000 0.000 0.060
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4171 0.5992 0.000 0.604 0.000 0.000 0.396
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.5816 0.5243 0.000 0.608 0.000 0.164 0.228
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4794 0.4233 0.000 0.624 0.000 0.344 0.032
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.2423 0.6705 0.000 0.896 0.000 0.024 0.080
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.3039 0.7489 0.808 0.000 0.000 0.000 0.192
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.4114 0.5787 0.000 0.624 0.000 0.000 0.376
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.5016 0.6056 0.000 0.704 0.000 0.176 0.120
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.5990 0.4661 0.000 0.000 0.568 0.152 0.280
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.1121 0.7121 0.000 0.956 0.000 0.000 0.044
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3863 0.7042 0.000 0.152 0.000 0.796 0.052
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.4141 0.6705 0.000 0.736 0.000 0.028 0.236
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.1197 0.8410 0.000 0.000 0.000 0.952 0.048
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.0963 0.8490 0.000 0.000 0.000 0.964 0.036
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1117 0.7065 0.000 0.964 0.000 0.016 0.020
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2891 0.7594 0.824 0.000 0.000 0.000 0.176
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.6693 0.3363 0.000 0.320 0.000 0.256 0.424
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0794 0.8483 0.000 0.000 0.000 0.972 0.028
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3934 0.5005 0.000 0.716 0.000 0.276 0.008
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4088 0.5899 0.000 0.632 0.000 0.000 0.368
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.4334 0.6613 0.000 0.768 0.000 0.140 0.092
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1197 0.8417 0.000 0.000 0.000 0.952 0.048
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4060 0.5947 0.000 0.640 0.000 0.000 0.360
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.4686 0.6430 0.000 0.000 0.160 0.736 0.104
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3003 0.6063 0.000 0.812 0.000 0.188 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1732 0.8278 0.920 0.000 0.000 0.000 0.080
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2248 0.6736 0.000 0.900 0.000 0.012 0.088
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1478 0.8223 0.000 0.000 0.936 0.064 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 5 0.6032 0.2292 0.424 0.116 0.000 0.000 0.460
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.3970 0.6366 0.000 0.788 0.000 0.156 0.056
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4576 0.3569 0.000 0.608 0.000 0.376 0.016
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1981 0.6837 0.000 0.920 0.000 0.016 0.064
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0404 0.8480 0.000 0.000 0.000 0.988 0.012
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3796 0.6428 0.000 0.700 0.000 0.000 0.300
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.8890 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.0963 0.8486 0.000 0.000 0.000 0.964 0.036
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4045 0.5974 0.000 0.644 0.000 0.000 0.356
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5425 0.5043 0.000 0.632 0.000 0.268 0.100
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.5583 0.1811 0.000 0.424 0.000 0.504 0.072
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.2605 0.7021 0.000 0.852 0.000 0.000 0.148
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.1410 0.8392 0.000 0.000 0.000 0.940 0.060
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.3274 0.6686 0.000 0.780 0.000 0.000 0.220
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1408 0.6952 0.000 0.948 0.000 0.008 0.044
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3210 0.6849 0.000 0.788 0.000 0.000 0.212
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3796 0.6275 0.000 0.000 0.000 0.700 0.300
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0510 0.9034 0.984 0.000 0.000 0.000 0.016
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0963 0.8481 0.000 0.000 0.000 0.964 0.036
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.1043 0.8434 0.000 0.000 0.000 0.960 0.040
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4303 0.6261 0.000 0.192 0.000 0.752 0.056
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.1544 0.6873 0.000 0.932 0.000 0.000 0.068
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1478 0.7114 0.000 0.936 0.000 0.000 0.064
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3661 0.6381 0.724 0.000 0.000 0.000 0.276
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4098 0.6879 0.000 0.000 0.156 0.780 0.064
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1908 0.6758 0.000 0.908 0.000 0.000 0.092
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1270 0.8399 0.000 0.000 0.000 0.948 0.052
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9131 1.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.3857 0.6118 0.000 0.000 0.000 0.688 0.312
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 6 0.3823 0.58435 0.000 0.436 0.000 0.000 0.000 0.564
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 6 0.5648 0.46592 0.068 0.172 0.000 0.000 0.112 0.648
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0935 0.55398 0.000 0.964 0.000 0.000 0.032 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4074 0.50376 0.000 0.656 0.000 0.324 0.004 0.016
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.92918 1.000 0.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.5114 0.15700 0.000 0.492 0.000 0.052 0.012 0.444
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.3867 0.31601 0.000 0.296 0.000 0.004 0.012 0.688
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.87846 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0935 0.55398 0.000 0.964 0.000 0.000 0.032 0.004
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.87846 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.6291 -0.16864 0.000 0.340 0.000 0.216 0.016 0.428
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1719 0.67432 0.000 0.016 0.000 0.924 0.060 0.000
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#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.2455 0.66918 0.000 0.012 0.000 0.872 0.112 0.004
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.5424 0.12099 0.000 0.292 0.000 0.112 0.012 0.584
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.1765 0.67317 0.000 0.000 0.000 0.904 0.096 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.1913 0.67679 0.000 0.012 0.000 0.908 0.080 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3062 0.58590 0.000 0.816 0.000 0.160 0.000 0.024
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2942 0.82093 0.836 0.000 0.000 0.000 0.132 0.032
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.6365 0.36421 0.000 0.268 0.000 0.340 0.380 0.012
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0363 0.67645 0.000 0.000 0.000 0.988 0.012 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3993 0.44585 0.000 0.592 0.000 0.400 0.008 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 6 0.3782 0.60888 0.000 0.412 0.000 0.000 0.000 0.588
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5158 0.47050 0.000 0.632 0.000 0.220 0.004 0.144
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.1010 0.67114 0.000 0.004 0.000 0.960 0.036 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 6 0.4366 0.52899 0.000 0.428 0.000 0.024 0.000 0.548
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.6290 -0.07039 0.000 0.000 0.112 0.440 0.396 0.052
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3804 0.49645 0.000 0.656 0.000 0.336 0.008 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1644 0.87048 0.932 0.012 0.000 0.000 0.004 0.052
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1116 0.57726 0.000 0.960 0.000 0.028 0.008 0.004
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2030 0.80386 0.000 0.000 0.908 0.028 0.064 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.92918 1.000 0.000 0.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.87846 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 6 0.5754 -0.20207 0.436 0.020 0.000 0.000 0.100 0.444
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.6038 0.28028 0.000 0.416 0.000 0.268 0.000 0.316
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4305 0.40879 0.000 0.544 0.000 0.436 0.020 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2146 0.59321 0.000 0.880 0.000 0.116 0.004 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.2219 0.63993 0.000 0.000 0.000 0.864 0.136 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3986 -0.36904 0.000 0.532 0.000 0.004 0.000 0.464
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0458 0.86977 0.000 0.000 0.984 0.000 0.016 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.1584 0.67607 0.000 0.008 0.000 0.928 0.064 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 6 0.3774 0.60942 0.000 0.408 0.000 0.000 0.000 0.592
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0146 0.92784 0.996 0.000 0.000 0.000 0.000 0.004
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.6052 0.27842 0.000 0.464 0.000 0.324 0.008 0.204
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.4264 0.28335 0.000 0.332 0.000 0.636 0.032 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3659 -0.06734 0.000 0.636 0.000 0.000 0.000 0.364
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3309 0.50684 0.000 0.000 0.000 0.720 0.280 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.5682 -0.00598 0.000 0.512 0.000 0.000 0.300 0.188
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2165 0.59483 0.000 0.884 0.000 0.108 0.000 0.008
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4929 -0.26983 0.000 0.508 0.000 0.064 0.000 0.428
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.4594 -0.10680 0.000 0.000 0.000 0.476 0.488 0.036
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0692 0.91820 0.976 0.000 0.000 0.000 0.004 0.020
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3109 0.59423 0.000 0.004 0.000 0.772 0.224 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.2048 0.65285 0.000 0.000 0.000 0.880 0.120 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.5557 0.42748 0.000 0.016 0.000 0.596 0.248 0.140
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.2520 0.59532 0.000 0.872 0.000 0.108 0.012 0.008
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.92918 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4029 0.34047 0.000 0.680 0.000 0.028 0.000 0.292
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.2852 0.83071 0.856 0.000 0.000 0.000 0.064 0.080
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4957 0.34940 0.000 0.000 0.084 0.584 0.332 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0891 0.55775 0.000 0.968 0.000 0.000 0.024 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.1663 0.67579 0.000 0.000 0.000 0.912 0.088 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.92918 1.000 0.000 0.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.5440 0.16757 0.000 0.000 0.000 0.348 0.520 0.132
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 17581 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 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 0.553 0.721 0.874 0.4461 0.529 0.529
#> 3 3 0.774 0.849 0.937 0.3552 0.803 0.648
#> 4 4 0.693 0.754 0.839 0.2059 0.789 0.512
#> 5 5 0.636 0.613 0.802 0.0602 0.881 0.603
#> 6 6 0.641 0.569 0.743 0.0467 0.916 0.667
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4022 0.84391 0.080 0.920
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.8813 0.57136 0.700 0.300
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.90261 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.90261 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.9970 0.34480 0.532 0.468
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0938 0.89816 0.012 0.988
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.2043 0.88573 0.032 0.968
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.4022 0.74742 0.920 0.080
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.90261 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.4022 0.74742 0.920 0.080
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.90261 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.7219 0.64722 0.200 0.800
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.90261 0.000 1.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.90261 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.9970 0.01044 0.468 0.532
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.90261 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.9977 0.33559 0.528 0.472
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.9170 0.37972 0.332 0.668
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.5059 0.77627 0.112 0.888
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.6438 0.70691 0.164 0.836
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.90261 0.000 1.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0672 0.89815 0.008 0.992
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4022 0.84391 0.080 0.920
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 1.0000 0.08733 0.500 0.500
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.90261 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.5408 0.76569 0.124 0.876
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.90261 0.000 1.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.90261 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0376 0.73684 0.996 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.90261 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.9686 0.46829 0.604 0.396
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.90261 0.000 1.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.90261 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1184 0.89606 0.016 0.984
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.4161 0.74597 0.916 0.084
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2236 0.88276 0.036 0.964
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.9933 0.06052 0.452 0.548
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0376 0.90140 0.004 0.996
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.90261 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.73633 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.90261 0.000 1.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4022 0.84391 0.080 0.920
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.9963 0.35439 0.536 0.464
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.4022 0.74742 0.920 0.080
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2423 0.87964 0.040 0.960
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.90261 0.000 1.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.90261 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.9795 0.43887 0.584 0.416
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.9970 0.34433 0.532 0.468
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.4022 0.74742 0.920 0.080
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.9754 0.18834 0.408 0.592
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.4161 0.82002 0.084 0.916
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5178 0.77647 0.116 0.884
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.90261 0.000 1.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.90261 0.000 1.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.4022 0.74742 0.920 0.080
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.9909 0.39211 0.556 0.444
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.9954 0.03575 0.460 0.540
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.7674 0.64969 0.776 0.224
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 1.0000 0.27135 0.504 0.496
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.90261 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.8861 0.53871 0.696 0.304
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.9977 0.33559 0.528 0.472
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.90261 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.9988 0.31633 0.520 0.480
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.90261 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.90261 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.7528 0.57076 0.216 0.784
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.9635 -0.00118 0.388 0.612
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0376 0.90140 0.004 0.996
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.9963 0.35318 0.536 0.464
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#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0376 0.90140 0.004 0.996
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.4022 0.74742 0.920 0.080
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0938 0.89816 0.012 0.988
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.90261 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.2603 0.87642 0.044 0.956
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.9977 -0.00247 0.472 0.528
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.90261 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.90261 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0000 0.73633 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.9732 0.19927 0.404 0.596
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.90261 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.90261 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.7056 0.69689 0.192 0.808
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0672 0.89992 0.008 0.992
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.8386 0.51953 0.268 0.732
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4022 0.84391 0.080 0.920
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.5842 0.73425 0.860 0.140
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.90261 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.9988 0.31633 0.520 0.480
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2603 0.86394 0.044 0.956
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.4161 0.74597 0.916 0.084
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.9460 0.51130 0.636 0.364
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.4022 0.74742 0.920 0.080
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.9044 0.55341 0.680 0.320
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.1184 0.89606 0.016 0.984
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.90261 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.90261 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6801 0.68143 0.180 0.820
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2778 0.87311 0.048 0.952
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.4022 0.74742 0.920 0.080
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.90261 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4022 0.84391 0.080 0.920
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.8661 0.59638 0.712 0.288
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.90261 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.1184 0.89063 0.016 0.984
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0938 0.89816 0.012 0.988
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.8327 0.59216 0.736 0.264
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.7219 0.64722 0.200 0.800
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.90261 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0938 0.89816 0.012 0.988
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.4298 0.74749 0.912 0.088
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.9710 0.46241 0.600 0.400
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.9896 0.26257 0.560 0.440
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.9963 0.02284 0.464 0.536
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.90261 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.90261 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.9896 0.39972 0.560 0.440
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.1184 0.89606 0.016 0.984
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.73633 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.9754 -0.05731 0.408 0.592
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.90261 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.9427 0.31287 0.360 0.640
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.9944 0.36924 0.544 0.456
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.9988 0.39768 0.520 0.480
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2356 0.8853 0.072 0.928 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.3816 0.7849 0.852 0.000 0.148
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9439 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9439 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9290 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0747 0.9347 0.016 0.984 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4346 0.7688 0.184 0.816 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.8681 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9439 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.8681 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0747 0.9347 0.016 0.984 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4002 0.7825 0.000 0.840 0.160
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9439 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0424 0.9395 0.008 0.992 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.2165 0.8372 0.000 0.064 0.936
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9439 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9290 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.2448 0.8817 0.000 0.924 0.076
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.3267 0.8471 0.116 0.884 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.4452 0.7388 0.000 0.808 0.192
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9439 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.5988 0.3870 0.000 0.632 0.368
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.3816 0.7725 0.852 0.148 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.4555 0.7329 0.000 0.200 0.800
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.2152 0.9124 0.036 0.948 0.016
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9439 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9439 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9439 0.000 1.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9290 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9439 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9290 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9439 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9439 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.1529 0.9175 0.040 0.960 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.8681 0.000 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9439 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.3941 0.7776 0.000 0.156 0.844
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.9439 0.000 1.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9439 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1860 0.8906 0.948 0.000 0.052
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9439 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.4504 0.7039 0.804 0.196 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9290 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.8681 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9439 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9439 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9439 0.000 1.000 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9290 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9290 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.8681 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.6215 0.3152 0.000 0.428 0.572
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.8748 0.4058 0.172 0.584 0.244
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.2165 0.8933 0.000 0.936 0.064
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9439 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9439 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.8681 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9290 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.6168 0.3619 0.000 0.412 0.588
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9290 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.9290 1.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9439 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.4654 0.7257 0.000 0.208 0.792
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9290 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9439 0.000 1.000 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0000 0.9290 1.000 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9439 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.9439 0.000 1.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.5016 0.6920 0.240 0.760 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.6192 0.7016 0.060 0.764 0.176
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9439 0.000 1.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9290 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.6140 0.2911 0.000 0.596 0.404
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9290 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.1643 0.9143 0.044 0.956 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.5254 0.6052 0.736 0.264 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0237 0.9418 0.004 0.996 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1753 0.9124 0.048 0.952 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9439 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9439 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9439 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9290 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.5968 0.4463 0.364 0.636 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.8681 0.000 0.000 1.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9439 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.2356 0.8293 0.000 0.072 0.928
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9439 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.3941 0.7577 0.844 0.156 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9439 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.9439 0.000 1.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.3686 0.7593 0.140 0.000 0.860
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9439 0.000 1.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.1643 0.9143 0.044 0.956 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9290 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9439 0.000 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9290 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9439 0.000 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.8681 0.000 0.000 1.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.4931 0.7043 0.232 0.768 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.8681 0.000 0.000 1.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9290 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9439 0.000 1.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5397 0.5419 0.280 0.000 0.720
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.8681 0.000 0.000 1.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9439 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0592 0.9214 0.988 0.000 0.012
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9439 0.000 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.6168 0.2686 0.000 0.588 0.412
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9290 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9439 0.000 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 3 0.8637 0.5132 0.236 0.168 0.596
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9439 0.000 1.000 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.4682 0.7075 0.804 0.192 0.004
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.0000 0.8681 0.000 0.000 1.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9439 0.000 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0592 0.9371 0.012 0.988 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9290 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9290 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9439 0.000 1.000 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.0000 0.9439 0.000 1.000 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.6126 0.3370 0.400 0.000 0.600
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9290 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0000 0.8681 0.000 0.000 1.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9290 1.000 0.000 0.000
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#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 1 0.5859 0.4728 0.656 0.344 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9290 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.9439 0.000 1.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9439 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9439 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.8681 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0747 0.9336 0.000 0.984 0.016
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9439 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9439 0.000 1.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.3816 0.7304 0.148 0.000 0.852
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9290 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.4702 0.7219 0.000 0.212 0.788
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.5497 0.6208 0.000 0.292 0.708
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.3134 0.8872 0.052 0.916 0.032
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9439 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9290 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0592 0.9371 0.012 0.988 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.1964 0.8890 0.944 0.000 0.056
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6467 0.3744 0.008 0.388 0.604
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9439 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6305 -0.0227 0.000 0.516 0.484
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9290 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 3 0.6126 0.2693 0.400 0.000 0.600
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.5546 0.6291 0.052 0.680 0.000 0.268
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.3372 0.8531 0.868 0.036 0.000 0.096
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0336 0.7874 0.000 0.992 0.000 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.1867 0.7742 0.000 0.928 0.000 0.072
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.4277 0.8336 0.000 0.280 0.000 0.720
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.4250 0.8323 0.000 0.276 0.000 0.724
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0592 0.7852 0.000 0.984 0.000 0.016
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4164 0.6692 0.000 0.736 0.000 0.264
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0817 0.7812 0.000 0.976 0.000 0.024
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0188 0.9056 0.000 0.004 0.996 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4761 0.7859 0.000 0.372 0.000 0.628
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0592 0.9312 0.984 0.000 0.000 0.016
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.4793 0.6117 0.000 0.756 0.204 0.040
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.3908 0.6501 0.000 0.212 0.784 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3688 0.5147 0.000 0.792 0.000 0.208
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.4621 0.5306 0.000 0.008 0.284 0.708
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.2662 0.8584 0.900 0.084 0.000 0.016
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.5553 0.7243 0.000 0.100 0.724 0.176
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.5581 0.7328 0.000 0.140 0.132 0.728
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.1302 0.7852 0.000 0.956 0.000 0.044
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.4996 0.5797 0.000 0.484 0.000 0.516
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1792 0.6043 0.000 0.068 0.000 0.932
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0817 0.9278 0.976 0.000 0.000 0.024
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4830 0.7570 0.000 0.392 0.000 0.608
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.4804 0.7685 0.000 0.384 0.000 0.616
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.4331 0.8339 0.000 0.288 0.000 0.712
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4295 0.6837 0.008 0.752 0.000 0.240
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.3873 0.6831 0.000 0.228 0.772 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4661 0.0208 0.000 0.652 0.000 0.348
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.4776 0.7775 0.000 0.376 0.000 0.624
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0188 0.9331 0.996 0.000 0.000 0.004
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3688 0.5115 0.000 0.792 0.000 0.208
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.4391 0.6569 0.740 0.252 0.000 0.008
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0469 0.9328 0.988 0.000 0.000 0.012
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2271 0.7717 0.008 0.916 0.000 0.076
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0707 0.7836 0.000 0.980 0.000 0.020
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.4454 0.8302 0.000 0.308 0.000 0.692
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0469 0.9322 0.988 0.000 0.000 0.012
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1118 0.9226 0.964 0.000 0.000 0.036
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.3088 0.7481 0.000 0.864 0.008 0.128
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.4690 0.5437 0.004 0.008 0.268 0.720
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0188 0.7882 0.000 0.996 0.000 0.004
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.4730 -0.0776 0.000 0.636 0.000 0.364
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4713 0.7393 0.000 0.360 0.000 0.640
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0469 0.9321 0.988 0.000 0.000 0.012
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.4690 0.6616 0.000 0.724 0.016 0.260
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0188 0.9331 0.996 0.000 0.000 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0336 0.7874 0.000 0.992 0.000 0.008
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.5462 0.6367 0.004 0.692 0.040 0.264
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0469 0.9322 0.988 0.000 0.000 0.012
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.4522 0.8271 0.000 0.320 0.000 0.680
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0336 0.9322 0.992 0.000 0.000 0.008
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.3873 0.6937 0.000 0.772 0.000 0.228
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4304 0.2747 0.000 0.716 0.000 0.284
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.1792 0.6498 0.000 0.068 0.000 0.932
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.4986 0.5788 0.004 0.024 0.248 0.724
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.4543 0.8228 0.000 0.324 0.000 0.676
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0469 0.9321 0.988 0.000 0.000 0.012
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.5310 0.3164 0.000 0.012 0.412 0.576
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0188 0.9333 0.996 0.000 0.000 0.004
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.5657 0.7373 0.120 0.160 0.000 0.720
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.4134 0.5617 0.000 0.260 0.000 0.740
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 4 0.7068 0.6956 0.156 0.296 0.000 0.548
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4605 0.8156 0.000 0.336 0.000 0.664
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0817 0.7805 0.000 0.976 0.000 0.024
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.5000 -0.5339 0.000 0.504 0.000 0.496
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4193 0.8290 0.000 0.268 0.000 0.732
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0707 0.7829 0.000 0.980 0.000 0.020
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.1042 0.8969 0.000 0.008 0.972 0.020
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.1022 0.7759 0.000 0.968 0.000 0.032
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.5393 0.6825 0.688 0.044 0.000 0.268
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.1302 0.7648 0.000 0.956 0.000 0.044
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1022 0.7763 0.000 0.968 0.000 0.032
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.9167 0.1549 0.240 0.320 0.364 0.076
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.4406 0.8321 0.000 0.300 0.000 0.700
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.4277 0.8336 0.000 0.280 0.000 0.720
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0469 0.9322 0.988 0.000 0.000 0.012
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0592 0.7852 0.000 0.984 0.000 0.016
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0524 0.7884 0.004 0.988 0.000 0.008
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.4250 0.8323 0.000 0.276 0.000 0.724
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0592 0.9310 0.984 0.000 0.000 0.016
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 4 0.4790 0.7725 0.000 0.380 0.000 0.620
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.5039 0.2934 0.004 0.000 0.592 0.404
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4072 0.6576 0.000 0.252 0.000 0.748
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0188 0.9331 0.996 0.000 0.000 0.004
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1302 0.7664 0.000 0.956 0.000 0.044
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.5250 0.2383 0.000 0.008 0.440 0.552
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0469 0.9322 0.988 0.000 0.000 0.012
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0188 0.7879 0.000 0.996 0.000 0.004
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.7701 0.3733 0.240 0.488 0.004 0.268
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.4718 0.7062 0.708 0.012 0.000 0.280
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0188 0.7879 0.000 0.996 0.000 0.004
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0592 0.9314 0.984 0.000 0.000 0.016
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.4477 0.8287 0.000 0.312 0.000 0.688
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.2868 0.6532 0.000 0.864 0.000 0.136
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 2 0.9707 0.1571 0.244 0.344 0.148 0.264
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0469 0.9321 0.988 0.000 0.000 0.012
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0188 0.9331 0.996 0.000 0.000 0.004
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 4 0.4277 0.8336 0.000 0.280 0.000 0.720
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.1716 0.7768 0.000 0.936 0.000 0.064
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.4920 0.3963 0.000 0.004 0.368 0.628
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0188 0.7879 0.000 0.996 0.000 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.4933 -0.3353 0.000 0.568 0.000 0.432
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.3726 0.7039 0.000 0.788 0.000 0.212
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.4522 0.8250 0.000 0.320 0.000 0.680
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0188 0.9331 0.996 0.000 0.000 0.004
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.3626 0.7196 0.000 0.812 0.004 0.184
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#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0921 0.9258 0.972 0.000 0.000 0.028
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0188 0.9071 0.000 0.000 0.996 0.004
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1059 0.9236 0.972 0.016 0.000 0.012
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.4304 0.8342 0.000 0.284 0.000 0.716
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0469 0.7866 0.000 0.988 0.000 0.012
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0469 0.7866 0.000 0.988 0.000 0.012
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.4088 0.6150 0.000 0.232 0.764 0.004
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.4624 0.8135 0.000 0.340 0.000 0.660
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9074 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4661 0.8065 0.000 0.348 0.000 0.652
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.7393 0.2937 0.400 0.164 0.000 0.436
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0469 0.9322 0.988 0.000 0.000 0.012
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3975 0.6860 0.000 0.760 0.000 0.240
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0188 0.7885 0.000 0.996 0.000 0.004
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4994 -0.4902 0.000 0.520 0.000 0.480
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0376 0.9046 0.000 0.004 0.992 0.004
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1902 0.7769 0.004 0.932 0.000 0.064
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0817 0.7812 0.000 0.976 0.000 0.024
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.1792 0.7788 0.000 0.932 0.000 0.068
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0336 0.9043 0.000 0.000 0.992 0.008
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.4605 0.5290 0.664 0.000 0.000 0.336
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.4452 0.7428 0.000 0.008 0.732 0.260
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.4690 0.7380 0.000 0.016 0.724 0.260
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.3067 0.6887 0.004 0.084 0.024 0.888
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.4522 0.8250 0.000 0.320 0.000 0.680
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9336 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.4454 0.8301 0.000 0.308 0.000 0.692
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 3 0.6897 0.5720 0.180 0.000 0.592 0.228
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.5105 0.2350 0.004 0.000 0.432 0.564
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1867 0.7391 0.000 0.928 0.000 0.072
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.7630 0.2492 0.000 0.312 0.460 0.228
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0707 0.9300 0.980 0.000 0.000 0.020
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4483 0.5103 0.004 0.000 0.284 0.712
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.4921 0.51916 0.040 0.340 0.000 0.000 0.620
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.7034 -0.39222 0.360 0.288 0.000 0.008 0.344
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0162 0.67980 0.000 0.996 0.000 0.000 0.004
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2561 0.60185 0.000 0.856 0.000 0.000 0.144
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1915 0.89055 0.928 0.000 0.000 0.040 0.032
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.2127 0.81592 0.000 0.108 0.000 0.892 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.2909 0.79303 0.012 0.140 0.000 0.848 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0324 0.86143 0.000 0.000 0.992 0.004 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0404 0.68232 0.000 0.988 0.000 0.012 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.2536 0.83751 0.004 0.000 0.900 0.052 0.044
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.1908 0.81559 0.000 0.092 0.000 0.908 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.4088 0.48747 0.000 0.368 0.000 0.000 0.632
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0609 0.68107 0.000 0.980 0.000 0.020 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.2077 0.81524 0.000 0.084 0.008 0.908 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1197 0.83666 0.000 0.048 0.952 0.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3039 0.78867 0.000 0.152 0.000 0.836 0.012
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1661 0.89377 0.940 0.000 0.000 0.024 0.036
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.5997 0.32743 0.000 0.608 0.020 0.100 0.272
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.2678 0.81648 0.000 0.100 0.004 0.880 0.016
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.4288 0.68761 0.000 0.072 0.784 0.136 0.008
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.3430 0.60374 0.000 0.776 0.004 0.220 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5844 0.43303 0.000 0.084 0.352 0.556 0.008
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.4995 0.62012 0.728 0.140 0.000 0.124 0.008
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.6697 0.34119 0.000 0.408 0.148 0.016 0.428
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.2036 0.80722 0.000 0.056 0.024 0.920 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.5045 0.49966 0.000 0.696 0.000 0.108 0.196
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3932 0.27260 0.000 0.672 0.000 0.328 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4574 0.36642 0.000 0.012 0.000 0.576 0.412
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2300 0.86208 0.904 0.000 0.000 0.024 0.072
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.2074 0.81479 0.000 0.104 0.000 0.896 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0451 0.89747 0.988 0.000 0.000 0.008 0.004
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4268 -0.09829 0.000 0.556 0.000 0.444 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4273 -0.11108 0.000 0.552 0.000 0.448 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.3300 0.77943 0.004 0.204 0.000 0.792 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.2513 0.77748 0.000 0.000 0.876 0.008 0.116
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4846 0.08471 0.028 0.588 0.000 0.000 0.384
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4449 0.04492 0.000 0.484 0.512 0.004 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3508 0.45649 0.000 0.748 0.000 0.252 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.4300 0.23403 0.000 0.476 0.000 0.524 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0404 0.89638 0.988 0.000 0.000 0.000 0.012
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4832 0.55057 0.000 0.712 0.088 0.200 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.3835 0.59145 0.744 0.244 0.000 0.000 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.5744 0.37036 0.528 0.000 0.000 0.092 0.380
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.2695 0.83634 0.004 0.004 0.896 0.052 0.044
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3534 0.47403 0.000 0.744 0.000 0.000 0.256
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0510 0.68126 0.000 0.984 0.000 0.016 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.4038 0.79582 0.000 0.128 0.080 0.792 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1124 0.89750 0.960 0.000 0.000 0.004 0.036
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2074 0.88705 0.920 0.000 0.000 0.036 0.044
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0290 0.86076 0.000 0.000 0.992 0.000 0.008
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.3480 0.46271 0.000 0.752 0.000 0.000 0.248
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.2152 0.79408 0.000 0.032 0.044 0.920 0.004
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.1270 0.66798 0.000 0.948 0.000 0.000 0.052
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5083 0.53580 0.000 0.696 0.000 0.184 0.120
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.6142 0.26439 0.000 0.132 0.000 0.472 0.396
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.2695 0.83634 0.004 0.004 0.896 0.052 0.044
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.89764 1.000 0.000 0.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.4489 0.03808 0.000 0.572 0.000 0.008 0.420
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0162 0.89680 0.996 0.000 0.000 0.000 0.004
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.4452 0.64487 0.696 0.000 0.000 0.032 0.272
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0324 0.67996 0.004 0.992 0.000 0.000 0.004
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4708 -0.08239 0.000 0.548 0.016 0.000 0.436
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.2230 0.88350 0.912 0.000 0.000 0.044 0.044
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2127 0.81660 0.000 0.108 0.000 0.892 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.1788 0.87726 0.932 0.004 0.000 0.008 0.056
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4074 0.23203 0.000 0.636 0.000 0.000 0.364
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2773 0.61189 0.000 0.836 0.000 0.164 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.5730 0.29449 0.000 0.040 0.024 0.524 0.412
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2228 0.79741 0.000 0.040 0.048 0.912 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.3876 0.65076 0.000 0.316 0.000 0.684 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0162 0.89680 0.996 0.000 0.000 0.000 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.4522 0.62462 0.000 0.044 0.248 0.708 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0798 0.89424 0.976 0.000 0.000 0.016 0.008
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.3160 0.78974 0.004 0.188 0.000 0.808 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.2331 0.76042 0.080 0.020 0.000 0.900 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 5 0.5571 0.05208 0.000 0.084 0.000 0.348 0.568
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.6475 -0.17248 0.184 0.428 0.000 0.388 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4278 0.38168 0.000 0.452 0.000 0.548 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.3898 0.62653 0.000 0.804 0.000 0.116 0.080
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.4835 0.34263 0.000 0.592 0.000 0.380 0.028
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0162 0.89680 0.996 0.000 0.000 0.000 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.2584 0.79475 0.008 0.052 0.000 0.900 0.040
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.2390 0.84100 0.004 0.000 0.908 0.044 0.044
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4002 0.61736 0.000 0.796 0.000 0.120 0.084
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.4686 0.65253 0.000 0.124 0.756 0.008 0.112
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0671 0.68200 0.000 0.980 0.000 0.016 0.004
#> 21821B38-6786-4078-9918-EC0E877C1533 5 0.5235 0.43823 0.312 0.068 0.000 0.000 0.620
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4133 0.61679 0.000 0.768 0.000 0.180 0.052
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1043 0.67939 0.000 0.960 0.000 0.040 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.9123 -0.27372 0.200 0.180 0.308 0.036 0.276
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.3561 0.70686 0.000 0.260 0.000 0.740 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.1908 0.81582 0.000 0.092 0.000 0.908 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.68020 0.000 1.000 0.000 0.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1211 0.89856 0.960 0.000 0.000 0.024 0.016
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1399 0.66852 0.020 0.952 0.000 0.000 0.028
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.0579 0.85995 0.000 0.000 0.984 0.008 0.008
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 4 0.1830 0.81158 0.008 0.068 0.000 0.924 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0451 0.86066 0.000 0.000 0.988 0.008 0.004
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0880 0.89801 0.968 0.000 0.000 0.000 0.032
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.4227 -0.02907 0.000 0.580 0.000 0.420 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 3 0.3113 0.82677 0.008 0.000 0.868 0.080 0.044
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.1469 0.85343 0.000 0.000 0.948 0.016 0.036
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.5066 0.59848 0.000 0.084 0.000 0.676 0.240
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.1117 0.89111 0.964 0.000 0.000 0.016 0.020
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0794 0.68093 0.000 0.972 0.000 0.028 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.5383 0.27446 0.000 0.048 0.408 0.540 0.004
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0703 0.67640 0.000 0.976 0.000 0.000 0.024
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 5 0.3921 0.60469 0.044 0.172 0.000 0.000 0.784
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.2304 0.81563 0.000 0.100 0.008 0.892 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 5 0.2722 0.55571 0.028 0.000 0.020 0.056 0.896
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 3 0.0955 0.85272 0.000 0.000 0.968 0.028 0.004
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.1168 0.67736 0.000 0.960 0.000 0.008 0.032
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.2280 0.81109 0.000 0.120 0.000 0.880 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0162 0.89680 0.996 0.000 0.000 0.000 0.004
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.2424 0.80633 0.000 0.132 0.000 0.868 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.3980 0.62592 0.000 0.796 0.000 0.128 0.076
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 5 0.6765 0.55511 0.140 0.100 0.148 0.000 0.612
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#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4302 -0.15934 0.000 0.520 0.000 0.480 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0609 0.89965 0.980 0.000 0.000 0.020 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.7198 0.23302 0.476 0.044 0.000 0.304 0.176
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0404 0.68081 0.000 0.988 0.000 0.012 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 5 0.3741 0.57588 0.000 0.264 0.004 0.000 0.732
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0579 0.85995 0.000 0.000 0.984 0.008 0.008
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.3710 0.75939 0.048 0.144 0.000 0.808 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3019 0.63715 0.016 0.864 0.000 0.012 0.108
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0324 0.86143 0.000 0.000 0.992 0.004 0.004
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0451 0.68082 0.000 0.988 0.000 0.008 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4114 0.27040 0.376 0.624 0.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 5 0.4972 0.52255 0.044 0.336 0.000 0.000 0.620
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1041 0.67652 0.000 0.964 0.000 0.004 0.032
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.2280 0.65978 0.000 0.880 0.000 0.120 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0579 0.85995 0.000 0.000 0.984 0.008 0.008
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.2536 0.83751 0.004 0.000 0.900 0.052 0.044
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.5952 0.05280 0.500 0.020 0.060 0.000 0.420
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.2707 0.83798 0.876 0.000 0.000 0.024 0.100
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4306 -0.13525 0.000 0.508 0.000 0.492 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.2369 0.84488 0.004 0.000 0.908 0.056 0.032
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4249 -0.06013 0.000 0.568 0.000 0.432 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3180 0.77964 0.000 0.068 0.000 0.856 0.076
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.2771 0.80470 0.012 0.128 0.000 0.860 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.7831 -0.20142 0.000 0.348 0.380 0.088 0.184
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3563 0.74126 0.000 0.208 0.000 0.780 0.012
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.1408 0.67263 0.000 0.948 0.000 0.008 0.044
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.4564 0.19241 0.000 0.612 0.000 0.016 0.372
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4394 0.69051 0.000 0.220 0.000 0.732 0.048
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3582 0.52174 0.000 0.768 0.000 0.008 0.224
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.4883 0.71371 0.748 0.072 0.000 0.024 0.156
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 5 0.4812 0.46892 0.000 0.372 0.000 0.028 0.600
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.4768 0.60392 0.000 0.776 0.048 0.104 0.072
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6540 0.06602 0.268 0.480 0.000 0.252 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.2605 0.83699 0.004 0.000 0.896 0.056 0.044
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3535 0.63906 0.000 0.832 0.000 0.088 0.080
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.2446 0.87850 0.900 0.000 0.000 0.056 0.044
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1300 0.67807 0.000 0.956 0.000 0.016 0.028
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2150 0.84743 0.004 0.004 0.924 0.028 0.040
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.1310 0.88823 0.956 0.000 0.000 0.020 0.024
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1997 0.84691 0.000 0.000 0.924 0.036 0.040
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.3101 0.81771 0.864 0.024 0.000 0.012 0.100
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.2280 0.81242 0.000 0.120 0.000 0.880 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.2409 0.66781 0.000 0.900 0.000 0.032 0.068
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0865 0.67872 0.000 0.972 0.000 0.004 0.024
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.8350 -0.00292 0.000 0.152 0.228 0.352 0.268
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4533 -0.13259 0.008 0.544 0.000 0.448 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.86132 0.000 0.000 1.000 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4138 0.46993 0.000 0.384 0.000 0.616 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.4493 0.71231 0.108 0.136 0.000 0.756 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4430 -0.12503 0.000 0.540 0.000 0.004 0.456
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3003 0.65815 0.000 0.864 0.000 0.092 0.044
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4114 0.17779 0.000 0.624 0.000 0.376 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.3145 0.75314 0.000 0.008 0.844 0.012 0.136
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2074 0.63538 0.000 0.896 0.000 0.000 0.104
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2280 0.65551 0.000 0.880 0.000 0.120 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4491 0.31693 0.000 0.652 0.000 0.020 0.328
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.6232 0.27595 0.000 0.000 0.492 0.356 0.152
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.6491 0.21105 0.228 0.000 0.000 0.488 0.284
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.4567 0.60415 0.000 0.092 0.084 0.036 0.788
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.6645 0.52001 0.000 0.272 0.052 0.108 0.568
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.2302 0.77936 0.000 0.016 0.020 0.916 0.048
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.4088 0.53432 0.000 0.368 0.000 0.632 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0880 0.89801 0.968 0.000 0.000 0.000 0.032
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.3074 0.78245 0.000 0.196 0.000 0.804 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.5819 0.37997 0.032 0.000 0.100 0.204 0.664
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.4419 0.71563 0.004 0.000 0.740 0.212 0.044
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1608 0.66798 0.000 0.928 0.000 0.072 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.5303 0.47134 0.000 0.372 0.048 0.004 0.576
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2376 0.87962 0.904 0.000 0.000 0.052 0.044
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.1430 0.76032 0.004 0.000 0.052 0.944 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.3203 0.6060 0.004 0.160 0.000 0.812 0.024 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.7246 -0.0504 0.268 0.116 0.000 0.444 0.164 0.008
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0976 0.6571 0.000 0.968 0.000 0.016 0.008 0.008
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.2810 0.5830 0.000 0.832 0.000 0.156 0.008 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2234 0.8187 0.872 0.000 0.000 0.000 0.124 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.1082 0.7469 0.000 0.040 0.000 0.000 0.004 0.956
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.1787 0.7264 0.004 0.068 0.000 0.000 0.008 0.920
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0458 0.8095 0.000 0.000 0.984 0.000 0.016 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3809 0.5781 0.000 0.756 0.000 0.020 0.208 0.016
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3819 0.7051 0.064 0.000 0.764 0.000 0.172 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.1196 0.7476 0.000 0.040 0.000 0.000 0.008 0.952
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.1845 0.6135 0.000 0.072 0.000 0.916 0.008 0.004
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1082 0.6651 0.000 0.956 0.000 0.004 0.000 0.040
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.1623 0.7459 0.000 0.032 0.004 0.004 0.020 0.940
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.2964 0.7225 0.000 0.100 0.856 0.024 0.020 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 6 0.5121 0.6365 0.000 0.064 0.000 0.080 0.156 0.700
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2118 0.8149 0.888 0.000 0.000 0.000 0.104 0.008
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.6905 0.3383 0.000 0.288 0.004 0.440 0.208 0.060
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.4222 0.6858 0.004 0.032 0.020 0.012 0.160 0.772
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.5316 0.5072 0.000 0.072 0.644 0.016 0.016 0.252
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.5136 0.5469 0.000 0.656 0.000 0.020 0.224 0.100
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.6186 0.5387 0.004 0.052 0.212 0.004 0.136 0.592
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.6314 0.2904 0.232 0.564 0.000 0.004 0.064 0.136
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.7192 0.3802 0.000 0.288 0.068 0.444 0.180 0.020
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.1049 0.7464 0.000 0.032 0.000 0.000 0.008 0.960
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.6523 0.2006 0.000 0.500 0.000 0.280 0.156 0.064
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2823 0.5984 0.000 0.796 0.000 0.000 0.000 0.204
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.4110 0.2154 0.000 0.000 0.000 0.608 0.016 0.376
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.4528 -0.0763 0.544 0.000 0.000 0.020 0.428 0.008
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.1720 0.7466 0.000 0.040 0.000 0.000 0.032 0.928
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1480 0.8208 0.940 0.000 0.000 0.000 0.040 0.020
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3515 0.4305 0.000 0.676 0.000 0.000 0.000 0.324
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4006 0.2576 0.000 0.600 0.000 0.004 0.004 0.392
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.2871 0.6751 0.000 0.192 0.000 0.000 0.004 0.804
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.6579 0.3666 0.000 0.080 0.568 0.172 0.168 0.012
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4504 0.3199 0.004 0.432 0.000 0.540 0.024 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.7173 0.1649 0.000 0.416 0.276 0.072 0.228 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.2699 0.6531 0.008 0.864 0.000 0.000 0.020 0.108
#> 682C11E8-099C-466F-BC8A-B09A754205E3 6 0.5737 0.0442 0.000 0.380 0.000 0.004 0.148 0.468
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.2134 0.8080 0.904 0.000 0.000 0.044 0.052 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.6639 0.4219 0.000 0.552 0.016 0.080 0.232 0.120
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.3442 0.7154 0.824 0.100 0.000 0.004 0.068 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 5 0.6558 0.6208 0.252 0.000 0.000 0.124 0.524 0.100
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.3763 0.7078 0.060 0.000 0.768 0.000 0.172 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4379 0.2007 0.004 0.600 0.000 0.376 0.016 0.004
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0790 0.6648 0.000 0.968 0.000 0.000 0.000 0.032
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 6 0.4091 0.6282 0.000 0.052 0.212 0.000 0.004 0.732
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0713 0.8329 0.972 0.000 0.000 0.000 0.028 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2302 0.8069 0.872 0.000 0.000 0.000 0.120 0.008
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.8097 0.000 0.000 1.000 0.000 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4763 0.1375 0.000 0.576 0.000 0.372 0.048 0.004
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.1026 0.7403 0.000 0.008 0.008 0.004 0.012 0.968
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.1511 0.6494 0.000 0.940 0.000 0.044 0.012 0.004
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.5359 0.2287 0.000 0.520 0.000 0.100 0.004 0.376
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3651 0.4759 0.000 0.016 0.000 0.752 0.008 0.224
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.3175 0.7379 0.028 0.000 0.808 0.000 0.164 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.1168 0.8316 0.956 0.000 0.000 0.000 0.028 0.016
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.5381 0.5065 0.000 0.280 0.000 0.568 0.152 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1333 0.8200 0.944 0.000 0.000 0.000 0.048 0.008
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 5 0.5165 0.4519 0.396 0.000 0.000 0.068 0.528 0.008
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2715 0.6362 0.044 0.888 0.000 0.012 0.044 0.012
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.4194 0.5653 0.000 0.308 0.008 0.664 0.020 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1908 0.8193 0.900 0.000 0.000 0.000 0.096 0.004
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 6 0.1149 0.7473 0.000 0.024 0.000 0.008 0.008 0.960
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.5116 0.5164 0.696 0.040 0.000 0.068 0.188 0.008
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.4544 0.3521 0.000 0.416 0.000 0.548 0.036 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2278 0.6529 0.000 0.868 0.000 0.004 0.000 0.128
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 6 0.5374 0.3219 0.000 0.004 0.000 0.136 0.276 0.584
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 6 0.1251 0.7462 0.000 0.024 0.008 0.000 0.012 0.956
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 6 0.3725 0.5006 0.000 0.316 0.000 0.000 0.008 0.676
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.1657 0.8182 0.928 0.000 0.000 0.000 0.056 0.016
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 6 0.4669 0.6572 0.004 0.016 0.108 0.004 0.128 0.740
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2825 0.7412 0.844 0.000 0.000 0.012 0.136 0.008
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 6 0.2558 0.6982 0.000 0.156 0.000 0.000 0.004 0.840
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#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 3 0.5607 0.1377 0.376 0.000 0.528 0.008 0.068 0.020
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.2333 0.8223 0.872 0.004 0.000 0.004 0.120 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.3802 0.4566 0.000 0.676 0.000 0.000 0.012 0.312
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0603 0.8076 0.000 0.000 0.980 0.000 0.016 0.004
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 4 0.3957 0.5654 0.004 0.140 0.000 0.788 0.048 0.020
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 6 0.2936 0.6575 0.060 0.004 0.000 0.000 0.080 0.856
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 3 0.5825 0.2763 0.000 0.352 0.532 0.016 0.084 0.016
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.2981 0.7432 0.020 0.000 0.820 0.000 0.160 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 6 0.8334 0.0762 0.000 0.060 0.276 0.208 0.144 0.312
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#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.3032 0.7535 0.840 0.000 0.000 0.104 0.056 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.2805 0.7505 0.012 0.000 0.828 0.000 0.160 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 6 0.3992 0.4402 0.000 0.012 0.000 0.364 0.000 0.624
#> C6F4EF8F-353C-463E-8069-FDEACF556176 6 0.3534 0.7117 0.000 0.068 0.004 0.004 0.108 0.816
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#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.7138 0.0514 0.216 0.476 0.000 0.148 0.156 0.004
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.1963 0.6637 0.016 0.924 0.000 0.012 0.004 0.044
#> F694D119-BF58-4449-A811-CB7A2165D8C0 6 0.5400 0.2046 0.080 0.408 0.000 0.000 0.012 0.500
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 4 0.1480 0.5412 0.000 0.000 0.000 0.940 0.020 0.040
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#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 6 0.3301 0.6534 0.000 0.216 0.000 0.004 0.008 0.772
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#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0976 0.6604 0.000 0.968 0.000 0.008 0.016 0.008
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4249 0.1474 0.000 0.004 0.000 0.568 0.012 0.416
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.1610 0.6645 0.000 0.916 0.000 0.000 0.000 0.084
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4958 0.5169 0.000 0.680 0.000 0.068 0.220 0.032
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.5484 0.1569 0.000 0.052 0.512 0.400 0.036 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.2986 0.5388 0.004 0.020 0.000 0.856 0.016 0.104
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2349 0.7928 0.892 0.000 0.000 0.020 0.080 0.008
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#> A664B550-4B77-4B1E-BD11-62C4F73073DF 4 0.4933 0.5089 0.024 0.324 0.000 0.612 0.040 0.000
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#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4670 0.5598 0.000 0.692 0.000 0.012 0.220 0.076
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.3672 0.4005 0.000 0.712 0.000 0.276 0.004 0.008
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 6 0.6609 0.4915 0.000 0.128 0.052 0.028 0.236 0.556
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4148 0.5857 0.000 0.724 0.000 0.000 0.068 0.208
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.7333 -0.2285 0.000 0.364 0.244 0.092 0.296 0.004
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.2234 0.5306 0.000 0.000 0.000 0.872 0.004 0.124
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2006 0.8253 0.892 0.000 0.000 0.004 0.104 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.4372 0.6704 0.772 0.040 0.000 0.116 0.068 0.004
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.5586 0.4242 0.000 0.552 0.000 0.004 0.160 0.284
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.1918 0.8258 0.904 0.000 0.000 0.000 0.088 0.008
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 5 0.7398 0.5590 0.180 0.164 0.000 0.020 0.480 0.156
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1426 0.6623 0.000 0.948 0.000 0.008 0.016 0.028
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.1806 0.5991 0.000 0.044 0.000 0.928 0.020 0.008
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0603 0.8076 0.000 0.000 0.980 0.000 0.016 0.004
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.3890 0.6298 0.016 0.200 0.000 0.004 0.020 0.760
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3361 0.6393 0.004 0.848 0.000 0.060 0.032 0.056
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0260 0.8098 0.000 0.000 0.992 0.000 0.008 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1426 0.6571 0.000 0.948 0.000 0.008 0.028 0.016
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.5371 0.0710 0.384 0.536 0.000 0.008 0.060 0.012
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.2376 0.6110 0.008 0.096 0.000 0.884 0.012 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1340 0.6502 0.000 0.948 0.000 0.040 0.008 0.004
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.5461 0.4924 0.000 0.640 0.000 0.052 0.228 0.080
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0603 0.8076 0.000 0.000 0.980 0.000 0.016 0.004
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.3819 0.7049 0.064 0.000 0.764 0.000 0.172 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 4 0.6478 0.0622 0.368 0.064 0.012 0.480 0.072 0.004
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 5 0.5697 0.4693 0.384 0.016 0.000 0.020 0.520 0.060
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4664 0.3972 0.000 0.596 0.000 0.004 0.044 0.356
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 3 0.2990 0.7572 0.036 0.000 0.860 0.000 0.020 0.084
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3468 0.4930 0.000 0.712 0.000 0.000 0.004 0.284
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 6 0.4485 0.5068 0.000 0.020 0.000 0.032 0.268 0.680
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.2001 0.7300 0.012 0.068 0.000 0.000 0.008 0.912
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.8171 0.3903 0.000 0.180 0.180 0.372 0.220 0.048
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 6 0.6407 0.4216 0.000 0.084 0.000 0.136 0.232 0.548
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3952 0.5795 0.000 0.780 0.000 0.104 0.108 0.008
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2092 0.8062 0.876 0.000 0.000 0.000 0.124 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.5805 0.3646 0.000 0.344 0.000 0.484 0.168 0.004
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 6 0.6079 0.3511 0.000 0.024 0.000 0.276 0.176 0.524
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3487 0.5684 0.000 0.776 0.000 0.200 0.012 0.012
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 5 0.6875 0.4983 0.192 0.300 0.000 0.040 0.452 0.016
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.2765 0.5996 0.000 0.056 0.000 0.872 0.008 0.064
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.6852 0.3639 0.000 0.540 0.032 0.128 0.232 0.068
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.5066 0.5312 0.100 0.696 0.000 0.000 0.040 0.164
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 3 0.4475 0.6818 0.076 0.000 0.728 0.000 0.180 0.016
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.5936 0.4258 0.000 0.600 0.000 0.144 0.204 0.052
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.2653 0.7870 0.844 0.000 0.000 0.000 0.144 0.012
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4321 0.5527 0.000 0.732 0.000 0.064 0.192 0.012
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1829 0.7972 0.004 0.012 0.920 0.000 0.064 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.1693 0.8184 0.932 0.000 0.000 0.004 0.044 0.020
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1643 0.7966 0.008 0.000 0.924 0.000 0.068 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.5775 0.1935 0.580 0.044 0.000 0.096 0.280 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.1471 0.7417 0.000 0.064 0.000 0.000 0.004 0.932
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3674 0.6203 0.000 0.804 0.000 0.044 0.132 0.020
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1777 0.6528 0.000 0.928 0.000 0.024 0.044 0.004
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 6 0.8522 0.0731 0.000 0.092 0.236 0.200 0.144 0.328
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4353 0.2601 0.020 0.588 0.000 0.000 0.004 0.388
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0363 0.8096 0.000 0.000 0.988 0.000 0.012 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.6038 0.1315 0.000 0.412 0.000 0.004 0.208 0.376
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 6 0.5847 0.2334 0.108 0.380 0.000 0.000 0.024 0.488
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2416 0.7842 0.844 0.000 0.000 0.000 0.156 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.3761 0.5697 0.000 0.228 0.000 0.744 0.008 0.020
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.5938 0.4092 0.000 0.588 0.000 0.144 0.224 0.044
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3240 0.5703 0.000 0.752 0.000 0.000 0.004 0.244
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.7219 0.1335 0.000 0.092 0.460 0.228 0.208 0.012
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2940 0.6017 0.000 0.848 0.000 0.112 0.036 0.004
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.5834 0.4620 0.000 0.612 0.000 0.076 0.224 0.088
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.4808 0.5538 0.016 0.200 0.000 0.708 0.012 0.064
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.4537 0.4182 0.000 0.000 0.640 0.012 0.032 0.316
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.5035 0.5003 0.052 0.000 0.000 0.084 0.160 0.704
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.2783 0.5923 0.000 0.012 0.024 0.884 0.020 0.060
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4663 0.5938 0.000 0.080 0.000 0.748 0.108 0.064
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.1542 0.7267 0.000 0.000 0.004 0.052 0.008 0.936
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 6 0.5714 0.1683 0.000 0.340 0.000 0.000 0.176 0.484
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0146 0.8322 0.996 0.000 0.000 0.000 0.004 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.2871 0.6774 0.000 0.192 0.000 0.000 0.004 0.804
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.7427 0.3603 0.016 0.000 0.088 0.332 0.372 0.192
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 3 0.6894 0.3217 0.064 0.000 0.428 0.000 0.248 0.260
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1663 0.6642 0.000 0.912 0.000 0.000 0.000 0.088
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.2921 0.6281 0.000 0.080 0.004 0.868 0.032 0.016
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2513 0.7923 0.852 0.000 0.000 0.000 0.140 0.008
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.2443 0.7120 0.040 0.000 0.024 0.008 0.024 0.904
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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.274 0.622 0.824 0.4294 0.507 0.507
#> 3 3 0.314 0.548 0.776 0.3891 0.609 0.394
#> 4 4 0.373 0.626 0.680 0.1278 0.758 0.471
#> 5 5 0.435 0.595 0.741 0.0702 0.939 0.803
#> 6 6 0.507 0.579 0.730 0.0583 0.928 0.757
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.3274 0.79525 0.940 0.060
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.1843 0.80144 0.972 0.028
#> 300D7F74-A627-4738-91A9-62778D98C5AD 1 0.0000 0.79852 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 1 0.0000 0.79852 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.9044 0.61853 0.320 0.680
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.71348 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.71348 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.79852 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 1 0.0672 0.80044 0.992 0.008
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.79852 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.71348 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.1633 0.80153 0.976 0.024
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 1 0.5737 0.75172 0.864 0.136
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.8608 0.66004 0.284 0.716
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.0376 0.79948 0.996 0.004
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.6438 0.71373 0.164 0.836
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.0376 0.71473 0.004 0.996
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.1633 0.80184 0.976 0.024
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.8016 0.68705 0.244 0.756
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.9661 0.28255 0.608 0.392
#> A4967738-7FC2-4270-A149-56E459EDB875 1 0.6801 0.71252 0.820 0.180
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.4939 0.71998 0.108 0.892
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.9580 0.54514 0.380 0.620
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.0000 0.79852 1.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.71348 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.1414 0.80184 0.980 0.020
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 1 0.8909 0.51601 0.692 0.308
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.9580 0.54691 0.380 0.620
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.0376 0.71468 0.004 0.996
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.5737 0.71786 0.136 0.864
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.0000 0.71348 0.000 1.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 1 0.9983 -0.09623 0.524 0.476
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.9944 0.35985 0.456 0.544
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.71348 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.0000 0.79852 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 1 0.4939 0.77296 0.892 0.108
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 1 0.0000 0.79852 1.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.8955 0.63836 0.312 0.688
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.9635 0.53194 0.388 0.612
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1843 0.80144 0.972 0.028
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 1 0.8081 0.62466 0.752 0.248
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.9087 0.47319 0.676 0.324
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.9580 0.54843 0.380 0.620
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.79852 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 1 0.8327 0.59632 0.736 0.264
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 1 0.5294 0.76308 0.880 0.120
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.9954 0.35059 0.460 0.540
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.3584 0.71993 0.068 0.932
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.0000 0.71348 0.000 1.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.79852 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 1 0.0000 0.79852 1.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.71348 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 1 0.0938 0.80095 0.988 0.012
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 1 0.7453 0.67480 0.788 0.212
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.9977 0.31022 0.472 0.528
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.79852 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.2948 0.71740 0.052 0.948
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.0000 0.79852 1.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.3431 0.71832 0.064 0.936
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.9954 0.34539 0.460 0.540
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 1 0.8144 0.61657 0.748 0.252
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.0000 0.79852 1.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.3584 0.71993 0.068 0.932
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 1 0.9996 -0.15181 0.512 0.488
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.6973 0.70133 0.812 0.188
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 1 0.0376 0.79945 0.996 0.004
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.9988 0.27614 0.480 0.520
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.9129 0.62077 0.328 0.672
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.8861 0.64386 0.304 0.696
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.7745 0.69357 0.228 0.772
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.0000 0.71348 0.000 1.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.8861 0.64386 0.304 0.696
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.0000 0.71348 0.000 1.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.71348 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.71348 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.9000 0.63433 0.316 0.684
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.9963 0.32680 0.464 0.536
#> 8751D026-849B-44ED-933B-FD9B80DE329E 1 0.9977 -0.07554 0.528 0.472
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 1 0.7453 0.67341 0.788 0.212
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 1 0.8608 0.56344 0.716 0.284
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.4690 0.71607 0.100 0.900
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.71348 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.79852 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 1 0.0376 0.79948 0.996 0.004
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.0672 0.80021 0.992 0.008
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.9996 0.24427 0.488 0.512
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.9944 0.35920 0.456 0.544
#> 2AC38CDA-108E-4553-893F-F36211922BB6 1 0.8081 0.62159 0.752 0.248
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.9661 0.52176 0.392 0.608
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.79852 1.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.1633 0.71836 0.024 0.976
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.71348 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.9963 0.00446 0.536 0.464
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 1 0.5178 0.76575 0.884 0.116
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.9732 0.25435 0.596 0.404
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 1 0.9427 0.38344 0.640 0.360
#> 325F0A64-2E43-473F-B946-D328BF79BE69 2 0.3584 0.71749 0.068 0.932
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.71348 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.79852 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 2 0.0000 0.71348 0.000 1.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.9988 0.26628 0.480 0.520
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.0000 0.71348 0.000 1.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.79852 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 1 0.9996 -0.14651 0.512 0.488
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.9983 -0.05599 0.524 0.476
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 1 0.9580 0.32860 0.620 0.380
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.9170 0.61850 0.332 0.668
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.9988 -0.08112 0.520 0.480
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 1 0.2043 0.80120 0.968 0.032
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.1843 0.80144 0.972 0.028
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0376 0.71472 0.004 0.996
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.9129 0.62111 0.328 0.672
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.9661 0.52365 0.392 0.608
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 1 0.1184 0.80152 0.984 0.016
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.71348 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 2 0.8081 0.67718 0.248 0.752
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 2 0.0672 0.71572 0.008 0.992
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.8813 0.64833 0.300 0.700
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.9933 0.37300 0.452 0.548
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.0000 0.79852 1.000 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 2 0.0672 0.71572 0.008 0.992
#> AF0426B7-7A31-4943-973A-05114783DB32 2 0.3584 0.71749 0.068 0.932
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.9963 0.00446 0.536 0.464
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 1 0.0000 0.79852 1.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.0000 0.71348 0.000 1.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 1 0.3114 0.79637 0.944 0.056
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0376 0.71470 0.004 0.996
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 1 0.0376 0.79940 0.996 0.004
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 1 0.5519 0.75792 0.872 0.128
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 1 0.0000 0.79852 1.000 0.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 1 0.0376 0.79952 0.996 0.004
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 1 0.7674 0.65798 0.776 0.224
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.7883 0.68972 0.236 0.764
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.5737 0.71786 0.136 0.864
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.0000 0.71348 0.000 1.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.9635 0.30861 0.612 0.388
#> B422FFF3-623B-419A-964E-046BAE3578B3 1 0.0000 0.79852 1.000 0.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 2 0.9977 0.26602 0.472 0.528
#> 64BA791A-C418-4507-BF64-B4B473C78834 1 0.1633 0.80153 0.976 0.024
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 1.0000 0.19935 0.500 0.500
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.1843 0.80144 0.972 0.028
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.4298 0.78378 0.912 0.088
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 1 0.3431 0.79406 0.936 0.064
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.6973 0.70794 0.188 0.812
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 1 0.9993 -0.12908 0.516 0.484
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.9087 0.62748 0.324 0.676
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 1 0.2236 0.80058 0.964 0.036
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 2 0.0000 0.71348 0.000 1.000
#> 679EE059-DDD9-4138-9973-51A583941B71 2 0.0000 0.71348 0.000 1.000
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 2 0.0000 0.71348 0.000 1.000
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.9983 -0.05599 0.524 0.476
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#> 50A7A07E-B452-466D-97BF-978C4F9C47DA 1 0.0000 0.79852 1.000 0.000
#> 0E6AE036-64ED-4489-AE40-55F77089A890 2 0.7674 0.69492 0.224 0.776
#> BC9A5294-255F-47A4-8879-11C441093A3D 1 0.1633 0.80153 0.976 0.024
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.8813 0.64753 0.300 0.700
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 1 0.9491 0.36282 0.632 0.368
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 1 0.0672 0.80044 0.992 0.008
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 2 0.0000 0.71348 0.000 1.000
#> 3508F4B0-1ADA-4937-B924-424AC2596341 1 0.5178 0.76890 0.884 0.116
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 1 0.3274 0.79507 0.940 0.060
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 2 0.3431 0.72073 0.064 0.936
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.9963 -0.00065 0.536 0.464
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.9491 0.56448 0.368 0.632
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.1843 0.80144 0.972 0.028
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 1 0.0000 0.79852 1.000 0.000
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 1 0.6247 0.72749 0.844 0.156
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 2 0.0000 0.71348 0.000 1.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0000 0.71348 0.000 1.000
#> A5572139-03CA-4299-98B6-13A2945649D0 1 0.0000 0.79852 1.000 0.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.9954 0.35586 0.460 0.540
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.9710 0.51086 0.400 0.600
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 1 0.0000 0.79852 1.000 0.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.8386 0.67270 0.268 0.732
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 1 0.5294 0.76652 0.880 0.120
#> DCD932D2-B708-487A-93C1-8485FBE9048A 1 0.1633 0.80153 0.976 0.024
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.9998 0.23424 0.492 0.508
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.9996 -0.11319 0.512 0.488
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 2 0.0000 0.71348 0.000 1.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 1 0.0376 0.79948 0.996 0.004
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 1 0.9710 0.24704 0.600 0.400
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.8861 0.64386 0.304 0.696
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.9635 0.53094 0.388 0.612
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.9977 -0.03654 0.528 0.472
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.4562 0.72164 0.096 0.904
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 1 0.0000 0.79852 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 1 0.9775 0.19579 0.588 0.412
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.0376 0.71470 0.004 0.996
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 1 0.2778 0.79869 0.952 0.048
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 1 0.0000 0.79852 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.9909 0.40084 0.444 0.556
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 1 0.1414 0.80184 0.980 0.020
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 2 0.9248 0.59427 0.340 0.660
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 1 0.0000 0.79852 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.9661 0.52271 0.392 0.608
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.8081 0.68311 0.248 0.752
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.6247 0.72691 0.844 0.156
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 1 0.8327 0.59632 0.736 0.264
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.9754 0.49150 0.408 0.592
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 1 0.6148 0.74070 0.848 0.152
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 2 0.0000 0.71348 0.000 1.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 2 0.8955 0.62721 0.312 0.688
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 1 1.0000 -0.18554 0.504 0.496
#> BF128355-3E49-449D-A503-00E678E90DF8 1 0.9358 0.40599 0.648 0.352
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.0938 0.71644 0.012 0.988
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.9815 0.45747 0.420 0.580
#> 1E2B2F45-6629-41B3-8498-321A2E726698 1 0.5294 0.76308 0.880 0.120
#> 44047435-3E87-473A-9231-B61FB0D5045B 1 0.1184 0.80163 0.984 0.016
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 1 0.0000 0.79852 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.7674 0.69553 0.224 0.776
#> 59C375B4-60FB-4598-A146-5B175C2B8079 1 0.1184 0.80127 0.984 0.016
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 1 0.0938 0.80108 0.988 0.012
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.9881 0.42334 0.436 0.564
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 1 0.9427 0.38553 0.640 0.360
#> A65773C1-18D0-4F48-85E1-380338B66C7D 1 0.1414 0.80157 0.980 0.020
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 1 0.0000 0.79852 1.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.9044 0.62958 0.320 0.680
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 2 0.9522 0.54274 0.372 0.628
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.0000 0.71348 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 1 0.1633 0.80180 0.976 0.024
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 1 0.0000 0.79852 1.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 1.0000 -0.15017 0.504 0.496
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.0000 0.71348 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 1 0.8608 0.56389 0.716 0.284
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 2 0.0000 0.71348 0.000 1.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.6343 0.72188 0.840 0.160
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 1 0.3274 0.79544 0.940 0.060
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 1 0.7219 0.68998 0.800 0.200
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 1 0.5408 0.76366 0.876 0.124
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.9460 0.57068 0.364 0.636
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.9933 0.33870 0.452 0.548
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 1 0.7602 0.66618 0.780 0.220
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 1 0.5519 0.75792 0.872 0.128
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 1 0.1633 0.80180 0.976 0.024
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.9608 0.54183 0.384 0.616
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.7602 0.69789 0.220 0.780
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.0000 0.79852 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.9427 0.57717 0.360 0.640
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.9635 0.30861 0.612 0.388
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.2603 0.79910 0.956 0.044
#> 42DCA292-7292-4162-994F-FFBC0102C55E 1 0.9522 0.35601 0.628 0.372
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.8499 0.65898 0.276 0.724
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.6973 0.70794 0.188 0.812
#> E2A25905-7C92-4E43-81C0-D09268014334 1 0.8386 0.59298 0.732 0.268
#> E6901976-2075-463C-828D-8DF924EFC78E 1 0.6148 0.74070 0.848 0.152
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0000 0.79852 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0376 0.71470 0.004 0.996
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.9635 0.52953 0.388 0.612
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.79852 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 1 0.4562 0.77898 0.904 0.096
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.5059 0.77135 0.888 0.112
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.3879 0.78979 0.924 0.076
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 1 0.6343 0.73220 0.840 0.160
#> 29635F4D-3149-49BC-B960-FF863D10F747 1 0.5519 0.75792 0.872 0.128
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.79852 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.79852 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.79852 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.9129 0.62027 0.328 0.672
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.8144 0.68293 0.252 0.748
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.0000 0.71348 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.9795 0.46484 0.416 0.584
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.9129 0.62077 0.328 0.672
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.71348 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 1 0.0000 0.79852 1.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 1.0000 0.20306 0.496 0.504
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 1 0.0000 0.79852 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.9710 0.26803 0.600 0.400
#> D021A258-8713-4383-9DCA-45E2F54A0411 1 0.0000 0.79852 1.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.9881 0.42334 0.436 0.564
#> F5F7B591-062D-4FF0-AB68-73D678574318 1 0.8661 0.55435 0.712 0.288
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.9983 0.29027 0.476 0.524
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.9732 0.49824 0.404 0.596
#> DB7FD043-2A8F-480A-A208-912D99CE8848 1 0.0000 0.79852 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.8499 0.66722 0.276 0.724
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.0000 0.71348 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 1 0.0672 0.80033 0.992 0.008
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.0000 0.71348 0.000 1.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 1 0.0000 0.79852 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.79852 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.0000 0.71348 0.000 1.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.79852 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4022 0.78824 0.920 0.080
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.71348 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 1 0.0000 0.79852 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 1 0.0000 0.79852 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.9993 0.26959 0.484 0.516
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.5408 0.71970 0.124 0.876
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.79852 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 1 0.9993 -0.12616 0.516 0.484
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.8955 0.63836 0.312 0.688
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.9963 -0.00065 0.536 0.464
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.9661 0.52282 0.392 0.608
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 1 0.0000 0.79852 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.9044 0.62979 0.320 0.680
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.0000 0.79852 1.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 1 0.0000 0.79852 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 1 0.3274 0.79492 0.940 0.060
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.9460 0.57068 0.364 0.636
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.9635 0.53172 0.388 0.612
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.0000 0.71348 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.2043 0.80125 0.968 0.032
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 1 0.6247 0.73688 0.844 0.156
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.71348 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.7602 0.69681 0.220 0.780
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.9983 -0.05599 0.524 0.476
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.71348 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.0000 0.71348 0.000 1.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.0000 0.71348 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.9983 0.28087 0.476 0.524
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 1 0.9129 0.46895 0.672 0.328
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.0000 0.71348 0.000 1.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0000 0.71348 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.6140 0.04741 0.000 0.596 0.404
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6235 -0.06267 0.000 0.564 0.436
#> 300D7F74-A627-4738-91A9-62778D98C5AD 3 0.6095 0.53422 0.000 0.392 0.608
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 3 0.6140 0.51959 0.000 0.404 0.596
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.5690 0.48201 0.288 0.708 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.1411 0.84456 0.964 0.036 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.84367 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.71658 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 3 0.6192 0.49086 0.000 0.420 0.580
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0424 0.71982 0.000 0.008 0.992
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.84367 1.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.6225 0.46706 0.000 0.432 0.568
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.5529 0.36034 0.000 0.704 0.296
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.6126 0.27913 0.400 0.600 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.6095 0.53711 0.000 0.392 0.608
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.6079 0.43036 0.612 0.388 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3412 0.81161 0.876 0.124 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.6305 0.34784 0.000 0.484 0.516
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 1 0.6307 0.09554 0.512 0.488 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.6176 0.65712 0.100 0.780 0.120
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.6161 0.39799 0.016 0.696 0.288
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.6045 0.46935 0.620 0.380 0.000
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#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 2 0.3183 0.66938 0.076 0.908 0.016
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 1 0.5098 0.68227 0.752 0.248 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.71658 0.000 0.000 1.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.4838 0.67008 0.076 0.848 0.076
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.1031 0.84570 0.976 0.024 0.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.6489 -0.14537 0.004 0.540 0.456
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0237 0.71839 0.000 0.004 0.996
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.5635 0.64070 0.180 0.784 0.036
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 3 0.6267 0.42060 0.000 0.452 0.548
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 2 0.5098 0.54041 0.248 0.752 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0424 0.71982 0.000 0.008 0.992
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.5595 0.58476 0.228 0.756 0.016
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.6274 0.09945 0.456 0.544 0.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.5268 0.56420 0.012 0.212 0.776
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.4782 0.57098 0.016 0.820 0.164
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.5939 0.59900 0.224 0.748 0.028
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.6750 0.31729 0.024 0.640 0.336
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.3038 0.82221 0.896 0.104 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 2 0.5754 0.46687 0.296 0.700 0.004
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.6034 0.67585 0.152 0.780 0.068
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.4056 0.64281 0.032 0.876 0.092
#> F694D119-BF58-4449-A811-CB7A2165D8C0 1 0.2537 0.83221 0.920 0.080 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.5559 0.62842 0.192 0.780 0.028
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.5678 0.32257 0.000 0.684 0.316
#> 44047435-3E87-473A-9231-B61FB0D5045B 3 0.6299 0.37180 0.000 0.476 0.524
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0237 0.71839 0.000 0.004 0.996
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.6295 0.01346 0.472 0.528 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 3 0.6295 0.38123 0.000 0.472 0.528
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 3 0.6192 0.48784 0.000 0.420 0.580
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.5559 0.63033 0.192 0.780 0.028
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.5020 0.64924 0.056 0.836 0.108
#> A65773C1-18D0-4F48-85E1-380338B66C7D 3 0.6299 0.36875 0.000 0.476 0.524
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.2066 0.71645 0.000 0.060 0.940
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.6033 0.44054 0.336 0.660 0.004
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 2 0.5158 0.55722 0.232 0.764 0.004
#> A4CECC77-3764-4F27-BD37-D7E76E436944 1 0.0000 0.84367 1.000 0.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.6309 -0.29641 0.000 0.504 0.496
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 3 0.6026 0.55409 0.000 0.376 0.624
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 2 0.3213 0.66547 0.092 0.900 0.008
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 1 0.0000 0.84367 1.000 0.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.5119 0.58477 0.028 0.812 0.160
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.84367 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.5072 0.55571 0.012 0.196 0.792
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.6398 0.02084 0.004 0.580 0.416
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.6126 0.43941 0.020 0.712 0.268
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.6047 0.32886 0.008 0.680 0.312
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.5335 0.57049 0.232 0.760 0.008
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.4228 0.63955 0.148 0.844 0.008
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.5551 0.51714 0.020 0.768 0.212
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.5431 0.38053 0.000 0.716 0.284
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.6309 -0.29641 0.000 0.504 0.496
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.6026 0.57085 0.244 0.732 0.024
#> D0920958-B342-4844-9FD6-93F3784CF5A4 1 0.6286 0.20289 0.536 0.464 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.2066 0.71645 0.000 0.060 0.940
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.5698 0.55307 0.252 0.736 0.012
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.4458 0.64173 0.056 0.864 0.080
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.6168 0.02251 0.000 0.588 0.412
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.5931 0.65035 0.084 0.792 0.124
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.5982 0.39026 0.328 0.668 0.004
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.6307 0.15314 0.512 0.488 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4921 0.57664 0.020 0.816 0.164
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.6750 0.31729 0.024 0.640 0.336
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1031 0.71754 0.000 0.024 0.976
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 1 0.1289 0.84532 0.968 0.032 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4883 0.59439 0.208 0.788 0.004
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.71658 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.5988 0.18735 0.000 0.632 0.368
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.5591 0.33179 0.000 0.696 0.304
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.6209 0.18711 0.004 0.628 0.368
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.6172 0.36388 0.012 0.680 0.308
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.5465 0.37350 0.000 0.712 0.288
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1031 0.71754 0.000 0.024 0.976
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1289 0.72055 0.000 0.032 0.968
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.0892 0.71854 0.000 0.020 0.980
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.5529 0.48814 0.296 0.704 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.6302 0.00814 0.480 0.520 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0592 0.84505 0.988 0.012 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.5024 0.60626 0.220 0.776 0.004
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.5621 0.46272 0.308 0.692 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.1529 0.84403 0.960 0.040 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.6008 0.55716 0.000 0.372 0.628
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.5330 0.67363 0.144 0.812 0.044
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 3 0.6168 0.50972 0.000 0.412 0.588
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 2 0.4379 0.64762 0.060 0.868 0.072
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0000 0.71658 0.000 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.5559 0.63033 0.192 0.780 0.028
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4873 0.59077 0.024 0.824 0.152
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.5295 0.66261 0.156 0.808 0.036
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.5220 0.60083 0.208 0.780 0.012
#> DB7FD043-2A8F-480A-A208-912D99CE8848 3 0.6079 0.53946 0.000 0.388 0.612
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6180 0.24000 0.416 0.584 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0747 0.84553 0.984 0.016 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 3 0.6291 0.39616 0.000 0.468 0.532
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0424 0.84489 0.992 0.008 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 3 0.5859 0.57406 0.000 0.344 0.656
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0424 0.71982 0.000 0.008 0.992
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.84367 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0237 0.71871 0.000 0.004 0.996
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.6169 0.20315 0.004 0.636 0.360
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0592 0.84514 0.988 0.012 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 3 0.6168 0.51093 0.000 0.412 0.588
#> 981123DE-D55E-41D1-8850-1A41376F1DED 3 0.6180 0.49684 0.000 0.416 0.584
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.5558 0.66586 0.152 0.800 0.048
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.5363 0.63969 0.724 0.276 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.71658 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.5913 0.67303 0.144 0.788 0.068
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.5926 0.38793 0.356 0.644 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.3461 0.66814 0.076 0.900 0.024
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5597 0.59729 0.216 0.764 0.020
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 3 0.6079 0.53946 0.000 0.388 0.612
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.6026 0.34899 0.376 0.624 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.5988 0.56143 0.000 0.368 0.632
#> 534B9E41-B731-4461-ABEA-30096148A493 3 0.5859 0.57406 0.000 0.344 0.656
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.6244 -0.10464 0.000 0.560 0.440
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5335 0.57049 0.232 0.760 0.008
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.5817 0.57633 0.236 0.744 0.020
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.84367 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.6308 0.31359 0.000 0.492 0.508
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.6750 0.31988 0.024 0.640 0.336
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.84367 1.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 1 0.6244 0.25517 0.560 0.440 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.3272 0.67020 0.080 0.904 0.016
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0237 0.84419 0.996 0.004 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.84367 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0747 0.84553 0.984 0.016 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4748 0.66419 0.144 0.832 0.024
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6119 0.61892 0.064 0.772 0.164
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.84367 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.84367 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4050 0.7075 0.000 0.820 0.036 0.144
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.4849 0.6888 0.000 0.772 0.064 0.164
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.2868 0.6549 0.000 0.864 0.136 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3271 0.6722 0.000 0.856 0.132 0.012
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.6334 0.6404 0.124 0.132 0.032 0.712
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.2345 0.8342 0.900 0.000 0.000 0.100
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.3088 0.8820 0.000 0.128 0.864 0.008
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2741 0.6924 0.000 0.892 0.096 0.012
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3450 0.8807 0.000 0.156 0.836 0.008
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4237 0.6943 0.000 0.808 0.152 0.040
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3945 0.6276 0.000 0.780 0.004 0.216
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.6648 0.6361 0.248 0.140 0.000 0.612
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3105 0.6619 0.000 0.856 0.140 0.004
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.6442 0.0586 0.492 0.068 0.000 0.440
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.4452 0.7323 0.732 0.000 0.008 0.260
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.2983 0.7166 0.000 0.892 0.068 0.040
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.6928 0.4097 0.372 0.116 0.000 0.512
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.5493 0.3347 0.016 0.456 0.000 0.528
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.4661 0.5732 0.004 0.724 0.008 0.264
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.6008 0.0945 0.496 0.040 0.000 0.464
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.5495 0.7202 0.096 0.176 0.000 0.728
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.3311 0.6129 0.000 0.828 0.172 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.2530 0.8355 0.896 0.004 0.000 0.100
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3243 0.7093 0.000 0.876 0.088 0.036
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.5112 0.1158 0.004 0.560 0.000 0.436
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.5728 0.7155 0.104 0.188 0.000 0.708
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.1211 0.8430 0.960 0.000 0.000 0.040
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.6369 0.3496 0.572 0.076 0.000 0.352
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0707 0.8399 0.980 0.000 0.000 0.020
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.6028 0.5628 0.052 0.364 0.000 0.584
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.5663 0.6794 0.060 0.264 0.000 0.676
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 2 0.3311 0.6129 0.000 0.828 0.172 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4485 0.6730 0.000 0.772 0.028 0.200
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3219 0.6223 0.000 0.836 0.164 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.6523 0.6894 0.208 0.156 0.000 0.636
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.6233 0.7095 0.124 0.216 0.000 0.660
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#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 4 0.5570 0.4270 0.016 0.404 0.004 0.576
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.6260 0.6923 0.192 0.144 0.000 0.664
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.5279 0.7135 0.072 0.192 0.000 0.736
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 4 0.5200 0.5589 0.000 0.264 0.036 0.700
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 1 0.5847 0.4914 0.628 0.052 0.000 0.320
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.3217 0.8815 0.000 0.128 0.860 0.012
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 4 0.5326 0.4794 0.016 0.380 0.000 0.604
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.1557 0.8421 0.944 0.000 0.000 0.056
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.3587 0.7219 0.000 0.860 0.052 0.088
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.3401 0.8813 0.000 0.152 0.840 0.008
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.5727 0.6990 0.060 0.248 0.004 0.688
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.3243 0.7093 0.000 0.876 0.088 0.036
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 4 0.5718 0.6842 0.088 0.156 0.016 0.740
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.3450 0.8807 0.000 0.156 0.836 0.008
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 4 0.5511 0.7128 0.084 0.196 0.000 0.720
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.6739 0.5513 0.304 0.120 0.000 0.576
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.5596 0.7014 0.000 0.068 0.696 0.236
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.4888 0.2214 0.000 0.588 0.000 0.412
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.5910 0.7046 0.088 0.236 0.000 0.676
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.4652 0.6311 0.004 0.756 0.020 0.220
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.4262 0.7561 0.756 0.000 0.008 0.236
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 4 0.6285 0.6378 0.128 0.124 0.032 0.716
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 4 0.5672 0.6347 0.036 0.312 0.004 0.648
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.5168 -0.1609 0.004 0.504 0.000 0.492
#> F694D119-BF58-4449-A811-CB7A2165D8C0 1 0.3401 0.8042 0.840 0.008 0.000 0.152
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 4 0.5733 0.7085 0.060 0.216 0.012 0.712
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.3893 0.6469 0.000 0.796 0.008 0.196
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.3370 0.7158 0.000 0.872 0.080 0.048
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.3401 0.8813 0.000 0.152 0.840 0.008
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.6690 0.4377 0.352 0.100 0.000 0.548
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.3216 0.7147 0.000 0.880 0.076 0.044
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.2741 0.6930 0.000 0.892 0.096 0.012
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.5879 0.7004 0.080 0.248 0.000 0.672
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 4 0.5295 0.2164 0.008 0.488 0.000 0.504
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.3439 0.7136 0.000 0.868 0.084 0.048
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.5062 0.7697 0.000 0.284 0.692 0.024
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.6413 0.6991 0.180 0.152 0.004 0.664
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 4 0.6233 0.6477 0.096 0.156 0.032 0.716
#> A4CECC77-3764-4F27-BD37-D7E76E436944 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.2928 0.7187 0.000 0.896 0.052 0.052
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.3266 0.6182 0.000 0.832 0.168 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 4 0.5369 0.5909 0.008 0.244 0.036 0.712
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.5080 0.1899 0.004 0.576 0.000 0.420
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.1022 0.8423 0.968 0.000 0.000 0.032
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.4485 0.7032 0.000 0.012 0.740 0.248
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.4123 0.7122 0.000 0.820 0.044 0.136
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.4799 0.5259 0.008 0.704 0.004 0.284
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.4767 0.6042 0.000 0.724 0.020 0.256
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 4 0.5236 0.7138 0.076 0.164 0.004 0.756
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 4 0.5821 0.6226 0.040 0.212 0.032 0.716
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4761 0.4352 0.004 0.664 0.000 0.332
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.3837 0.6097 0.000 0.776 0.000 0.224
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.2928 0.7187 0.000 0.896 0.052 0.052
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.5910 0.7144 0.104 0.208 0.000 0.688
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.6775 0.2909 0.412 0.096 0.000 0.492
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.5062 0.7697 0.000 0.284 0.692 0.024
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.5702 0.7164 0.100 0.160 0.008 0.732
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 4 0.5897 0.3886 0.000 0.368 0.044 0.588
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.4839 0.6813 0.000 0.764 0.052 0.184
#> 42DCA292-7292-4162-994F-FFBC0102C55E 4 0.5406 0.2413 0.012 0.480 0.000 0.508
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 4 0.6361 0.5895 0.168 0.096 0.032 0.704
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.6399 0.3448 0.364 0.064 0.004 0.568
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.5099 0.2776 0.008 0.612 0.000 0.380
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.4652 0.6311 0.004 0.756 0.020 0.220
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.3243 0.8540 0.000 0.036 0.876 0.088
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 1 0.1940 0.8398 0.924 0.000 0.000 0.076
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 4 0.5170 0.7147 0.060 0.184 0.004 0.752
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.3910 0.8760 0.000 0.156 0.820 0.024
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.3862 0.6939 0.000 0.824 0.024 0.152
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.4737 0.6016 0.000 0.728 0.020 0.252
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.4365 0.6738 0.000 0.784 0.028 0.188
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.4535 0.6144 0.000 0.744 0.016 0.240
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4018 0.6133 0.000 0.772 0.004 0.224
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.3243 0.8540 0.000 0.036 0.876 0.088
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.3873 0.8354 0.000 0.228 0.772 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.3333 0.8560 0.000 0.040 0.872 0.088
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.5483 0.7131 0.136 0.128 0.000 0.736
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.6738 0.4569 0.352 0.104 0.000 0.544
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.2216 0.8376 0.908 0.000 0.000 0.092
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 4 0.6248 0.6942 0.104 0.252 0.000 0.644
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.5990 0.7093 0.164 0.144 0.000 0.692
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.2408 0.8328 0.896 0.000 0.000 0.104
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.3219 0.6206 0.000 0.836 0.164 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.5657 0.6293 0.044 0.312 0.000 0.644
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3217 0.6770 0.000 0.860 0.128 0.012
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 4 0.5855 0.4161 0.000 0.356 0.044 0.600
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.4238 0.8682 0.000 0.176 0.796 0.028
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.5879 0.7004 0.080 0.248 0.000 0.672
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.5070 0.1686 0.004 0.580 0.000 0.416
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.5365 0.6769 0.044 0.264 0.000 0.692
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.5593 0.7109 0.080 0.212 0.000 0.708
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3024 0.6469 0.000 0.852 0.148 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.6637 0.6212 0.260 0.132 0.000 0.608
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.2345 0.8360 0.900 0.000 0.000 0.100
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.2773 0.7094 0.000 0.900 0.072 0.028
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0469 0.8385 0.988 0.000 0.000 0.012
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4086 0.5454 0.000 0.776 0.216 0.008
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.3450 0.8807 0.000 0.156 0.836 0.008
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0707 0.8399 0.980 0.000 0.000 0.020
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.3300 0.8812 0.000 0.144 0.848 0.008
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.4307 0.6695 0.000 0.784 0.024 0.192
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.1118 0.8426 0.964 0.000 0.000 0.036
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3335 0.6805 0.000 0.856 0.128 0.016
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.2799 0.6841 0.000 0.884 0.108 0.008
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.5887 0.6656 0.048 0.284 0.008 0.660
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.6058 0.4200 0.604 0.060 0.000 0.336
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.4238 0.8682 0.000 0.176 0.796 0.028
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.6014 0.5607 0.052 0.360 0.000 0.588
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.6523 0.6894 0.208 0.156 0.000 0.636
#> 671507DB-3949-4A41-9682-644CE8FED3D3 4 0.5195 0.5508 0.000 0.276 0.032 0.692
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.5664 0.7163 0.076 0.192 0.008 0.724
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3024 0.6469 0.000 0.852 0.148 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.6691 0.6676 0.236 0.152 0.000 0.612
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.3311 0.6129 0.000 0.828 0.172 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4086 0.5454 0.000 0.776 0.216 0.008
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.2593 0.7156 0.000 0.904 0.016 0.080
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.5236 0.7138 0.076 0.164 0.004 0.756
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.5535 0.7171 0.088 0.192 0.000 0.720
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.4071 0.7149 0.000 0.832 0.104 0.064
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4886 0.6316 0.004 0.744 0.028 0.224
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.8339 1.000 0.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.6831 0.2731 0.420 0.100 0.000 0.480
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 4 0.5378 0.5633 0.004 0.264 0.036 0.696
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0469 0.8379 0.988 0.000 0.000 0.012
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0336 0.8367 0.992 0.000 0.000 0.008
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.2345 0.8360 0.900 0.000 0.000 0.100
#> BD879832-E177-4FCA-B1EA-D1553518E700 4 0.5847 0.6304 0.052 0.320 0.000 0.628
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5919 -0.1493 0.012 0.488 0.016 0.484
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0707 0.8399 0.980 0.000 0.000 0.020
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.8339 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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.3634 0.74237 0.000 0.820 0.004 0.136 0.040
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.4693 0.69085 0.000 0.752 0.008 0.092 0.148
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3005 0.68264 0.000 0.856 0.012 0.008 0.124
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3107 0.70042 0.000 0.852 0.008 0.016 0.124
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.5703 0.54297 0.076 0.056 0.000 0.692 0.176
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.3098 0.81124 0.836 0.000 0.000 0.148 0.016
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0290 0.80965 0.992 0.000 0.000 0.000 0.008
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.5597 -0.65816 0.000 0.072 0.488 0.000 0.440
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2568 0.71354 0.000 0.888 0.004 0.016 0.092
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 5 0.6019 0.80546 0.000 0.120 0.380 0.000 0.500
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0290 0.80965 0.992 0.000 0.000 0.000 0.008
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.4646 0.71853 0.000 0.780 0.048 0.052 0.120
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3720 0.65578 0.000 0.760 0.000 0.228 0.012
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4525 0.60282 0.172 0.036 0.000 0.764 0.028
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3601 0.69052 0.000 0.832 0.024 0.020 0.124
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.5458 0.05434 0.420 0.020 0.000 0.532 0.028
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.4615 0.71815 0.700 0.000 0.000 0.252 0.048
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3292 0.75637 0.000 0.864 0.016 0.056 0.064
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.5363 0.41301 0.292 0.032 0.000 0.644 0.032
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.4416 0.43205 0.000 0.356 0.000 0.632 0.012
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.4240 0.59193 0.000 0.700 0.004 0.284 0.012
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5305 -0.00591 0.436 0.012 0.000 0.524 0.028
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.3488 0.70232 0.040 0.072 0.000 0.856 0.032
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.3441 0.64727 0.000 0.824 0.024 0.004 0.148
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.2909 0.81821 0.848 0.000 0.000 0.140 0.012
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3105 0.74037 0.000 0.864 0.004 0.044 0.088
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#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3401 0.69854 0.036 0.092 0.004 0.856 0.012
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0290 0.80965 0.992 0.000 0.000 0.000 0.008
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.4276 0.75366 0.000 0.812 0.052 0.064 0.072
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4679 0.63677 0.000 0.700 0.012 0.260 0.028
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0451 0.81085 0.988 0.000 0.000 0.004 0.008
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.5322 0.30758 0.336 0.024 0.000 0.612 0.028
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 4 0.6123 0.48649 0.000 0.188 0.004 0.584 0.224
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.1195 0.81805 0.960 0.000 0.000 0.028 0.012
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0404 0.81633 0.988 0.000 0.000 0.012 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.2674 0.81934 0.868 0.000 0.000 0.120 0.012
#> BD879832-E177-4FCA-B1EA-D1553518E700 4 0.4048 0.63650 0.016 0.208 0.000 0.764 0.012
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.5292 0.22725 0.000 0.416 0.016 0.544 0.024
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0955 0.81981 0.968 0.000 0.000 0.028 0.004
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0290 0.80965 0.992 0.000 0.000 0.000 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.4003 0.707768 0.096 0.104 0.016 0.784 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.5122 0.435714 0.344 0.012 0.056 0.584 0.004 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 4 0.2531 0.665098 0.012 0.000 0.132 0.856 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.2791 0.679756 0.016 0.008 0.124 0.852 0.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.5169 0.634714 0.504 0.432 0.024 0.000 0.000 0.040
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.4199 0.767638 0.048 0.188 0.012 0.000 0.004 0.748
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.4094 0.660616 0.000 0.000 0.652 0.024 0.324 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 4 0.2326 0.693247 0.012 0.008 0.092 0.888 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.4062 0.814531 0.000 0.000 0.736 0.068 0.196 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4603 0.692286 0.032 0.048 0.128 0.764 0.028 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 4 0.4246 0.596112 0.032 0.232 0.004 0.720 0.012 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.3518 0.538149 0.084 0.824 0.004 0.008 0.000 0.080
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3219 0.675701 0.012 0.020 0.148 0.820 0.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.5655 0.221672 0.092 0.552 0.008 0.008 0.004 0.336
#> 2437A516-5312-409E-8679-B85BB60530CD 6 0.5729 0.652821 0.168 0.180 0.036 0.000 0.000 0.616
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3156 0.728081 0.024 0.044 0.080 0.852 0.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.5209 0.405314 0.104 0.664 0.004 0.012 0.004 0.212
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.4660 0.482467 0.048 0.636 0.000 0.308 0.008 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4495 0.538457 0.044 0.284 0.008 0.664 0.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.5515 0.179470 0.088 0.548 0.008 0.008 0.000 0.348
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.2990 0.552317 0.104 0.852 0.000 0.036 0.004 0.004
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2912 0.639628 0.012 0.000 0.172 0.816 0.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.4235 0.784442 0.060 0.160 0.016 0.000 0.004 0.760
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.3075 0.716380 0.016 0.040 0.092 0.852 0.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4863 0.116921 0.040 0.512 0.000 0.440 0.008 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.2339 0.597926 0.028 0.904 0.004 0.056 0.004 0.004
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 6 0.2287 0.822454 0.036 0.048 0.012 0.000 0.000 0.904
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.5582 -0.003039 0.100 0.516 0.008 0.000 0.004 0.372
#> 00F70D11-3B58-4517-82EC-258CCED34A60 6 0.1777 0.819624 0.032 0.024 0.012 0.000 0.000 0.932
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.4081 0.564237 0.040 0.740 0.000 0.208 0.012 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3223 0.599745 0.020 0.824 0.004 0.144 0.008 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.0881 0.813903 0.012 0.008 0.008 0.000 0.000 0.972
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.2912 0.639628 0.012 0.000 0.172 0.816 0.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4682 0.671039 0.108 0.160 0.016 0.716 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.2805 0.649353 0.012 0.000 0.160 0.828 0.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4194 0.559077 0.092 0.796 0.004 0.044 0.004 0.060
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3360 0.603301 0.048 0.856 0.004 0.060 0.016 0.016
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 4 0.5106 0.428270 0.352 0.008 0.060 0.576 0.004 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.4506 0.416735 0.036 0.344 0.000 0.616 0.004 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.6205 -0.034889 0.276 0.380 0.000 0.340 0.004 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.3499 0.537381 0.104 0.824 0.000 0.052 0.000 0.020
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.4062 0.814531 0.000 0.000 0.736 0.068 0.196 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 4 0.5921 0.092012 0.180 0.384 0.000 0.432 0.004 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 4 0.3874 0.619999 0.028 0.208 0.000 0.752 0.012 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.3316 0.597160 0.028 0.812 0.000 0.152 0.008 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.6700 -0.252165 0.300 0.368 0.032 0.000 0.000 0.300
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 6 0.3910 0.792989 0.092 0.100 0.016 0.000 0.000 0.792
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 5 0.6175 -0.001163 0.020 0.004 0.332 0.156 0.488 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.1471 0.737715 0.000 0.000 0.932 0.064 0.004 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.3185 0.707081 0.024 0.024 0.112 0.840 0.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4481 0.444106 0.028 0.336 0.004 0.628 0.004 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3414 0.599782 0.040 0.812 0.000 0.140 0.008 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.4062 0.814531 0.000 0.000 0.736 0.068 0.196 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 6 0.6126 0.558012 0.220 0.192 0.036 0.000 0.000 0.552
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.1471 0.737715 0.000 0.000 0.932 0.064 0.004 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.6767 -0.251752 0.300 0.344 0.036 0.000 0.000 0.320
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.4190 0.477876 0.148 0.740 0.000 0.112 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 4 0.5201 0.241088 0.064 0.392 0.000 0.532 0.012 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.3050 0.600582 0.000 0.000 0.764 0.236 0.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.6700 -0.252165 0.300 0.368 0.032 0.000 0.000 0.300
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.3593 0.575575 0.024 0.764 0.000 0.208 0.004 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.6118 0.377481 0.264 0.208 0.012 0.512 0.004 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.3025 0.689497 0.020 0.016 0.120 0.844 0.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4104 0.579163 0.072 0.760 0.004 0.160 0.004 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.2765 0.565880 0.064 0.876 0.000 0.016 0.000 0.044
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.2985 0.562409 0.076 0.864 0.004 0.012 0.000 0.044
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4820 0.425664 0.092 0.704 0.008 0.004 0.004 0.188
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 6 0.5579 0.677350 0.152 0.176 0.036 0.000 0.000 0.636
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.2816 0.566205 0.064 0.876 0.004 0.012 0.000 0.044
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 6 0.5514 0.685214 0.144 0.176 0.036 0.000 0.000 0.644
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4344 0.507608 0.120 0.776 0.004 0.028 0.004 0.068
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.3941 0.588821 0.060 0.780 0.000 0.148 0.008 0.004
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4109 0.561772 0.040 0.736 0.000 0.212 0.012 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.4419 0.491102 0.040 0.304 0.000 0.652 0.004 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4779 0.053941 0.040 0.468 0.000 0.488 0.004 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.6742 -0.294458 0.336 0.356 0.036 0.000 0.000 0.272
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.4008 0.813987 0.000 0.000 0.740 0.064 0.196 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.2850 0.698668 0.016 0.016 0.112 0.856 0.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 5 0.6742 0.101638 0.048 0.008 0.156 0.388 0.400 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4108 0.567804 0.060 0.752 0.004 0.180 0.004 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4232 0.470846 0.148 0.736 0.000 0.116 0.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.4638 0.362641 0.040 0.368 0.000 0.588 0.004 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4102 0.602436 0.072 0.796 0.004 0.100 0.004 0.024
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.1471 0.737715 0.000 0.000 0.932 0.064 0.004 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 6 0.5550 0.501580 0.100 0.356 0.008 0.000 0.004 0.532
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.0665 0.812250 0.008 0.004 0.008 0.000 0.000 0.980
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.4350 0.807615 0.660 0.292 0.000 0.048 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 4 0.4093 0.630410 0.028 0.204 0.008 0.748 0.012 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.5320 0.747961 0.640 0.232 0.004 0.108 0.016 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.5050 0.397283 0.076 0.572 0.000 0.348 0.004 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 6 0.6767 0.628384 0.224 0.152 0.024 0.000 0.060 0.540
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 5 0.3136 0.598663 0.000 0.000 0.228 0.004 0.768 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 6 0.3910 0.792989 0.092 0.100 0.016 0.000 0.000 0.792
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.3812 0.582705 0.036 0.776 0.000 0.176 0.004 0.008
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 6 0.4092 0.789563 0.080 0.140 0.012 0.000 0.000 0.768
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.4294 0.782675 0.000 0.000 0.692 0.060 0.248 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.3377 0.575227 0.028 0.784 0.000 0.188 0.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.4047 0.817310 0.676 0.296 0.000 0.028 0.000 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.4513 0.458080 0.040 0.628 0.000 0.328 0.004 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.2792 0.583670 0.072 0.876 0.000 0.036 0.004 0.012
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.4347 0.814252 0.668 0.288 0.000 0.040 0.000 0.004
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 4 0.2985 0.734609 0.020 0.068 0.040 0.868 0.004 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 4 0.5425 0.421535 0.324 0.008 0.096 0.568 0.004 0.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 6 0.4834 0.705429 0.076 0.240 0.008 0.000 0.004 0.672
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.4190 0.508623 0.116 0.788 0.004 0.028 0.004 0.060
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.2413 0.600284 0.020 0.896 0.004 0.072 0.004 0.004
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.3059 0.719982 0.020 0.040 0.084 0.856 0.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 6 0.4407 0.753679 0.056 0.200 0.012 0.000 0.004 0.728
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.5940 0.507675 0.480 0.388 0.036 0.000 0.000 0.096
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 6 0.5391 0.696038 0.148 0.164 0.032 0.000 0.000 0.656
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.3317 0.554245 0.076 0.848 0.004 0.012 0.004 0.056
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.3553 0.589990 0.064 0.804 0.000 0.128 0.000 0.004
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 5 0.1838 0.751605 0.016 0.000 0.068 0.000 0.916 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 6 0.5758 0.648434 0.172 0.180 0.036 0.000 0.000 0.612
#> AF0426B7-7A31-4943-973A-05114783DB32 6 0.6767 0.628384 0.224 0.152 0.024 0.000 0.060 0.540
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.4350 0.807615 0.660 0.292 0.000 0.048 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.4339 0.774763 0.000 0.000 0.684 0.060 0.256 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.3303 0.736825 0.020 0.092 0.040 0.844 0.004 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 6 0.4671 0.754789 0.088 0.180 0.012 0.000 0.004 0.716
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#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.4391 0.483956 0.028 0.320 0.008 0.644 0.000 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 4 0.5747 0.493716 0.208 0.212 0.012 0.568 0.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.3558 0.457269 0.168 0.792 0.000 0.028 0.000 0.012
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.4353 0.781314 0.620 0.356 0.008 0.008 0.000 0.008
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 4 0.4649 0.275243 0.036 0.400 0.000 0.560 0.004 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 4 0.4362 0.546126 0.036 0.264 0.000 0.688 0.012 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 4 0.2800 0.731204 0.020 0.052 0.052 0.876 0.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.2490 0.598122 0.044 0.892 0.000 0.052 0.012 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.5212 0.396178 0.092 0.668 0.008 0.012 0.004 0.216
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.2912 0.630208 0.000 0.000 0.784 0.216 0.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.3332 0.516465 0.116 0.836 0.004 0.028 0.004 0.012
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.5389 0.733180 0.636 0.224 0.004 0.120 0.016 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 4 0.4965 0.410351 0.368 0.012 0.040 0.576 0.004 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4710 0.444535 0.040 0.620 0.000 0.328 0.012 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.5626 0.609706 0.484 0.412 0.024 0.000 0.000 0.080
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.5091 0.340674 0.112 0.664 0.004 0.004 0.004 0.212
#> E2A25905-7C92-4E43-81C0-D09268014334 4 0.5067 0.127476 0.056 0.432 0.000 0.504 0.008 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.4808 0.585411 0.040 0.256 0.016 0.676 0.012 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 5 0.1610 0.746499 0.000 0.000 0.084 0.000 0.916 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.4003 0.781482 0.048 0.164 0.012 0.000 0.004 0.772
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3668 0.518794 0.132 0.804 0.000 0.052 0.004 0.008
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.2923 0.784241 0.000 0.000 0.848 0.052 0.100 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 4 0.3831 0.683959 0.024 0.172 0.020 0.780 0.004 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 4 0.5102 0.317715 0.396 0.060 0.004 0.536 0.004 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.5205 0.590174 0.236 0.100 0.020 0.644 0.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.4450 0.613292 0.052 0.236 0.012 0.700 0.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.4500 0.549305 0.036 0.264 0.004 0.684 0.012 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 5 0.1444 0.750507 0.000 0.000 0.072 0.000 0.928 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.5368 0.670610 0.004 0.000 0.592 0.144 0.260 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.1838 0.751605 0.016 0.000 0.068 0.000 0.916 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.3581 0.518059 0.116 0.820 0.000 0.020 0.004 0.040
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4890 0.458728 0.092 0.720 0.008 0.016 0.004 0.160
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 6 0.4024 0.794442 0.084 0.128 0.012 0.000 0.000 0.776
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4085 0.607128 0.056 0.796 0.004 0.116 0.008 0.020
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.2765 0.565880 0.064 0.876 0.000 0.016 0.000 0.044
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.4318 0.763336 0.056 0.188 0.012 0.000 0.004 0.740
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.2805 0.647195 0.012 0.000 0.160 0.828 0.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.3377 0.579615 0.028 0.784 0.000 0.188 0.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 4 0.2748 0.683229 0.016 0.008 0.120 0.856 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.5359 0.744534 0.636 0.232 0.004 0.112 0.016 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.1471 0.737715 0.000 0.000 0.932 0.064 0.004 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.2609 0.602201 0.036 0.868 0.000 0.096 0.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4644 0.093387 0.040 0.504 0.000 0.456 0.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.3641 0.570283 0.072 0.788 0.000 0.140 0.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.2350 0.597781 0.036 0.888 0.000 0.076 0.000 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.2653 0.658734 0.012 0.000 0.144 0.844 0.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4445 0.516968 0.096 0.776 0.008 0.028 0.004 0.088
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 6 0.4092 0.789563 0.080 0.140 0.012 0.000 0.000 0.768
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.2745 0.719078 0.020 0.024 0.072 0.880 0.004 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 6 0.1794 0.819941 0.028 0.024 0.016 0.000 0.000 0.932
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.3342 0.587376 0.012 0.000 0.228 0.760 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.4062 0.814531 0.000 0.000 0.736 0.068 0.196 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 6 0.1777 0.819624 0.032 0.024 0.012 0.000 0.000 0.932
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.3896 0.805309 0.000 0.000 0.744 0.052 0.204 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.5149 0.576374 0.248 0.096 0.016 0.640 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.2830 0.813818 0.024 0.092 0.012 0.000 0.004 0.868
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.2703 0.685884 0.016 0.008 0.116 0.860 0.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.2149 0.686937 0.004 0.004 0.104 0.888 0.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.3942 0.566083 0.084 0.784 0.000 0.120 0.012 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.5646 -0.108092 0.092 0.484 0.012 0.000 0.004 0.408
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1471 0.737715 0.000 0.000 0.932 0.064 0.004 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.4145 0.565351 0.044 0.736 0.000 0.208 0.012 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4194 0.559077 0.092 0.796 0.004 0.044 0.004 0.060
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.4234 0.808075 0.676 0.280 0.000 0.044 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.3821 0.495759 0.144 0.792 0.000 0.048 0.004 0.012
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.2653 0.658734 0.012 0.000 0.144 0.844 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.4132 0.556789 0.076 0.800 0.004 0.036 0.004 0.080
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2912 0.639628 0.012 0.000 0.172 0.816 0.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.3342 0.587376 0.012 0.000 0.228 0.760 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.3459 0.731244 0.024 0.104 0.036 0.832 0.004 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.3523 0.464279 0.164 0.796 0.000 0.028 0.000 0.012
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.2708 0.603321 0.024 0.884 0.004 0.072 0.004 0.012
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.0520 0.809970 0.008 0.000 0.008 0.000 0.000 0.984
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.4346 0.718797 0.044 0.052 0.076 0.796 0.032 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.4846 0.585660 0.036 0.260 0.020 0.672 0.012 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.0665 0.812250 0.008 0.004 0.008 0.000 0.000 0.980
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.5024 0.383741 0.096 0.664 0.004 0.004 0.004 0.228
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.4047 0.817310 0.676 0.296 0.000 0.028 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.1647 0.818875 0.008 0.032 0.016 0.000 0.004 0.940
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.1059 0.819656 0.016 0.016 0.004 0.000 0.000 0.964
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.4092 0.789563 0.080 0.140 0.012 0.000 0.000 0.768
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3777 0.584934 0.040 0.784 0.000 0.164 0.004 0.008
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.5802 0.278621 0.100 0.528 0.008 0.348 0.016 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 6 0.1777 0.819624 0.032 0.024 0.012 0.000 0.000 0.932
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.0622 0.809381 0.012 0.000 0.008 0.000 0.000 0.980
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 17581 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.990 0.959 0.982 0.5000 0.500 0.500
#> 3 3 0.669 0.782 0.895 0.2350 0.632 0.413
#> 4 4 0.625 0.663 0.823 0.1468 0.732 0.427
#> 5 5 0.845 0.841 0.908 0.0796 0.855 0.561
#> 6 6 0.759 0.629 0.796 0.0484 0.974 0.893
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.000 0.9798 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.000 0.9798 1.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 1 0.000 0.9798 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 1 0.000 0.9798 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.000 0.9840 0.000 1.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.000 0.9840 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.000 0.9840 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.000 0.9798 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 1 0.000 0.9798 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.000 0.9798 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.000 0.9840 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.000 0.9798 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 1 0.000 0.9798 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.000 0.9840 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.000 0.9798 1.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.000 0.9840 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.000 0.9840 0.000 1.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.000 0.9798 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.000 0.9840 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.000 0.9798 1.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 1 0.000 0.9798 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.000 0.9840 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.000 0.9840 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.000 0.9798 1.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.000 0.9840 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.000 0.9798 1.000 0.000
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#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 2 0.000 0.9840 0.000 1.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.000 0.9840 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 1 0.402 0.9110 0.920 0.080
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 2 0.000 0.9840 0.000 1.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 1 0.000 0.9798 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 1 0.000 0.9798 1.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 1 0.000 0.9798 1.000 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 1 0.000 0.9798 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.000 0.9840 0.000 1.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.000 0.9840 0.000 1.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 1 0.000 0.9798 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 1 0.000 0.9798 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 1 0.000 0.9798 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 1 0.416 0.9069 0.916 0.084
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.000 0.9840 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.000 0.9798 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.000 0.9840 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.000 0.9798 1.000 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.000 0.9798 1.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 1 0.644 0.8126 0.836 0.164
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.000 0.9840 0.000 1.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.000 0.9840 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 1 0.494 0.8811 0.892 0.108
#> E6901976-2075-463C-828D-8DF924EFC78E 1 0.000 0.9798 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.000 0.9798 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.000 0.9840 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.000 0.9840 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.000 0.9798 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 1 0.000 0.9798 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.000 0.9798 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.000 0.9798 1.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 1 0.000 0.9798 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 1 0.000 0.9798 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.000 0.9798 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.000 0.9798 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.000 0.9798 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.000 0.9840 0.000 1.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.000 0.9840 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.000 0.9840 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.000 0.9840 0.000 1.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.000 0.9840 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.000 0.9840 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 1 0.000 0.9798 1.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 1.000 0.0254 0.488 0.512
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 1 0.000 0.9798 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.000 0.9798 1.000 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 1 0.000 0.9798 1.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.402 0.9057 0.080 0.920
#> F5F7B591-062D-4FF0-AB68-73D678574318 1 0.000 0.9798 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.000 0.9840 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.000 0.9840 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 1 0.000 0.9798 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.000 0.9840 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.000 0.9840 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 1 0.000 0.9798 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.000 0.9840 0.000 1.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 1 0.000 0.9798 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.000 0.9798 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.000 0.9840 0.000 1.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.000 0.9798 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.000 0.9798 1.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.000 0.9840 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 1 0.000 0.9798 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 1 0.000 0.9798 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 1 0.416 0.9069 0.916 0.084
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.000 0.9840 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.000 0.9798 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 1 0.327 0.9303 0.940 0.060
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.000 0.9840 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.260 0.9441 0.044 0.956
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.000 0.9840 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 1 0.000 0.9798 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.000 0.9840 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.000 0.9798 1.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 1 0.000 0.9798 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 1 0.000 0.9798 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.000 0.9840 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.000 0.9840 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.000 0.9840 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.000 0.9798 1.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 1 0.000 0.9798 1.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.000 0.9840 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.000 0.9840 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.000 0.9840 0.000 1.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.000 0.9840 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.000 0.9840 0.000 1.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.000 0.9840 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.000 0.9840 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 1 0.000 0.9798 1.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.000 0.9840 0.000 1.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.000 0.9840 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.5810 0.528 0.000 0.664 0.336
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.5926 0.497 0.000 0.644 0.356
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.5905 0.497 0.000 0.648 0.352
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 3 0.6252 0.182 0.000 0.444 0.556
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3644 0.827 0.872 0.124 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.1643 0.906 0.956 0.044 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.1643 0.906 0.956 0.044 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0237 0.899 0.000 0.004 0.996
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.5835 0.521 0.000 0.660 0.340
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0237 0.899 0.000 0.004 0.996
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.1643 0.906 0.956 0.044 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.5926 0.489 0.000 0.644 0.356
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1411 0.848 0.000 0.964 0.036
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.1860 0.904 0.948 0.052 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.5650 0.551 0.000 0.312 0.688
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.2261 0.895 0.932 0.068 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.893 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.5859 0.513 0.000 0.656 0.344
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 1 0.3482 0.855 0.872 0.128 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.1753 0.843 0.000 0.952 0.048
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.1643 0.845 0.000 0.956 0.044
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.5363 0.722 0.724 0.276 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0237 0.853 0.004 0.996 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0237 0.899 0.000 0.004 0.996
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.1643 0.906 0.956 0.044 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.5835 0.521 0.000 0.660 0.340
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.854 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0424 0.852 0.008 0.992 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0237 0.891 0.996 0.000 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.1643 0.906 0.956 0.044 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.893 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.854 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0237 0.853 0.004 0.996 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.1643 0.906 0.956 0.044 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0237 0.899 0.000 0.004 0.996
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1411 0.848 0.000 0.964 0.036
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.4750 0.709 0.000 0.216 0.784
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1289 0.837 0.032 0.968 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0237 0.853 0.004 0.996 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 3 0.1753 0.871 0.000 0.048 0.952
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.1289 0.849 0.000 0.968 0.032
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.1765 0.843 0.040 0.956 0.004
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.6309 0.234 0.500 0.500 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0237 0.899 0.000 0.004 0.996
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1411 0.848 0.000 0.964 0.036
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2537 0.826 0.000 0.920 0.080
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.854 0.000 1.000 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0237 0.891 0.996 0.000 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.893 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0237 0.899 0.000 0.004 0.996
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.0237 0.899 0.000 0.004 0.996
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.1643 0.906 0.956 0.044 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.5926 0.489 0.000 0.644 0.356
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.854 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.854 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0237 0.899 0.000 0.004 0.996
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.893 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.0237 0.899 0.000 0.004 0.996
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0237 0.891 0.996 0.000 0.004
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0237 0.853 0.000 0.996 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1411 0.848 0.000 0.964 0.036
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.0237 0.899 0.000 0.004 0.996
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.893 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.854 0.000 1.000 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.1753 0.845 0.000 0.952 0.048
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.5905 0.497 0.000 0.648 0.352
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0237 0.853 0.004 0.996 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 1 0.5948 0.598 0.640 0.360 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.6308 -0.214 0.492 0.508 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 1 0.5397 0.717 0.720 0.280 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.893 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0424 0.852 0.008 0.992 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.893 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 1 0.1643 0.906 0.956 0.044 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.1643 0.906 0.956 0.044 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 1 0.5948 0.599 0.640 0.360 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0237 0.853 0.004 0.996 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.854 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1643 0.845 0.000 0.956 0.044
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.854 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0237 0.891 0.996 0.000 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 1 0.1643 0.906 0.956 0.044 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0237 0.899 0.000 0.004 0.996
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.5905 0.497 0.000 0.648 0.352
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0237 0.899 0.000 0.004 0.996
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.854 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0237 0.853 0.000 0.996 0.004
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.854 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0237 0.853 0.004 0.996 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.0237 0.899 0.000 0.004 0.996
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#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.1643 0.906 0.956 0.044 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0237 0.853 0.004 0.996 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.5859 0.627 0.656 0.344 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.1643 0.906 0.956 0.044 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0237 0.899 0.000 0.004 0.996
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.854 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.5905 0.497 0.000 0.648 0.352
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 3 0.7546 0.309 0.044 0.396 0.560
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0237 0.899 0.000 0.004 0.996
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.854 0.000 1.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0892 0.852 0.000 0.980 0.020
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0237 0.853 0.004 0.996 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0237 0.853 0.004 0.996 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 3 0.5988 0.423 0.000 0.368 0.632
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.4702 0.638 0.212 0.788 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.1643 0.906 0.956 0.044 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4702 0.708 0.000 0.788 0.212
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.893 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 3 0.5859 0.481 0.000 0.344 0.656
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0237 0.899 0.000 0.004 0.996
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.893 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0237 0.899 0.000 0.004 0.996
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.5859 0.520 0.000 0.656 0.344
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.1643 0.906 0.956 0.044 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.5905 0.497 0.000 0.648 0.352
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.5905 0.497 0.000 0.648 0.352
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.854 0.000 1.000 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.1643 0.906 0.956 0.044 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0237 0.899 0.000 0.004 0.996
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.854 0.000 1.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6126 0.155 0.400 0.600 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.2772 0.826 0.080 0.916 0.004
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0237 0.853 0.000 0.996 0.004
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 3 0.5988 0.423 0.000 0.368 0.632
#> C3E23136-7190-4D08-991C-93AFACC48E8D 1 0.5835 0.633 0.660 0.340 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0237 0.899 0.000 0.004 0.996
#> 534B9E41-B731-4461-ABEA-30096148A493 3 0.4887 0.692 0.000 0.228 0.772
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4504 0.726 0.000 0.804 0.196
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4121 0.701 0.168 0.832 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.6026 0.232 0.376 0.624 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.893 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.6267 0.221 0.000 0.548 0.452
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.5882 0.505 0.000 0.652 0.348
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.1643 0.906 0.956 0.044 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 1 0.5760 0.651 0.672 0.328 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.5285 0.642 0.244 0.752 0.004
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.1643 0.906 0.956 0.044 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.893 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.1643 0.906 0.956 0.044 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0237 0.853 0.004 0.996 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.1643 0.845 0.000 0.956 0.044
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.893 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.1643 0.906 0.956 0.044 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3217 0.7041 0.000 0.860 0.012 0.128
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.1109 0.6202 0.028 0.004 0.000 0.968
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.4855 0.4938 0.400 0.000 0.000 0.600
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.1637 0.7860 0.000 0.940 0.060 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4790 0.5230 0.380 0.000 0.000 0.620
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3801 0.7708 0.780 0.000 0.000 0.220
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0657 0.8183 0.000 0.984 0.012 0.004
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4790 0.5230 0.380 0.000 0.000 0.620
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0921 0.8018 0.000 0.972 0.000 0.028
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0336 0.8170 0.000 0.992 0.000 0.008
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.5204 0.5303 0.376 0.012 0.000 0.612
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.4103 0.6375 0.000 0.256 0.000 0.744
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.4955 0.0571 0.000 0.556 0.444 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0524 0.8191 0.000 0.988 0.008 0.004
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.4994 0.3503 0.000 0.480 0.000 0.520
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.6340 0.6251 0.096 0.284 0.000 0.620
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.4925 0.5603 0.572 0.000 0.000 0.428
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.1474 0.8673 0.948 0.000 0.000 0.052
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.2704 0.8476 0.876 0.000 0.000 0.124
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4989 0.3711 0.000 0.472 0.000 0.528
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3123 0.6397 0.000 0.844 0.000 0.156
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3801 0.6210 0.000 0.780 0.220 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.5649 0.5890 0.036 0.344 0.000 0.620
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.4830 0.5388 0.000 0.392 0.000 0.608
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 3 0.7728 0.4195 0.000 0.252 0.440 0.308
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4996 -0.2521 0.000 0.516 0.000 0.484
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 4 0.2011 0.6466 0.000 0.080 0.000 0.920
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.1211 0.6379 0.040 0.000 0.000 0.960
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.3837 0.5121 0.000 0.776 0.000 0.224
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.4866 0.5802 0.596 0.000 0.000 0.404
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2469 0.8569 0.892 0.000 0.000 0.108
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.4998 -0.2643 0.000 0.512 0.000 0.488
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.3569 0.7931 0.804 0.000 0.000 0.196
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.4948 0.5446 0.560 0.000 0.000 0.440
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.2408 0.6627 0.000 0.104 0.000 0.896
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.2081 0.7430 0.000 0.916 0.000 0.084
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.3024 0.8030 0.000 0.148 0.852 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.4790 0.6029 0.620 0.000 0.000 0.380
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 12FD30FF-4D3A-4920-BF80-F44132824017 4 0.4643 0.4345 0.000 0.344 0.000 0.656
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.5511 0.5592 0.352 0.028 0.000 0.620
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.5773 0.5768 0.336 0.044 0.000 0.620
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.5174 0.5395 0.368 0.012 0.000 0.620
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2973 0.8366 0.856 0.000 0.000 0.144
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.6521 0.6369 0.124 0.256 0.000 0.620
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2973 0.8366 0.856 0.000 0.000 0.144
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.5343 0.5869 0.316 0.028 0.000 0.656
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.4996 -0.2521 0.000 0.516 0.000 0.484
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.4830 0.5388 0.000 0.392 0.000 0.608
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 4 0.4992 -0.4194 0.476 0.000 0.000 0.524
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0657 0.8183 0.000 0.984 0.012 0.004
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.4925 0.3460 0.000 0.428 0.572 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.4843 0.5320 0.000 0.396 0.000 0.604
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.3172 0.6590 0.000 0.160 0.000 0.840
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4994 -0.2400 0.000 0.520 0.000 0.480
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.4817 0.5130 0.388 0.000 0.000 0.612
#> DBFA1780-4558-436A-A434-05DAFD0F675A 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 4 0.1022 0.6333 0.000 0.032 0.000 0.968
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 4 0.1022 0.6333 0.000 0.032 0.000 0.968
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.4877 -0.0284 0.000 0.592 0.000 0.408
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.1118 0.8828 0.964 0.000 0.000 0.036
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.3801 0.7708 0.780 0.000 0.000 0.220
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4843 0.5320 0.000 0.396 0.000 0.604
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 4 0.1174 0.6285 0.012 0.020 0.000 0.968
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.4972 -0.1690 0.000 0.544 0.000 0.456
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.6477 0.6341 0.116 0.264 0.000 0.620
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 4 0.1109 0.6318 0.004 0.028 0.000 0.968
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 2 0.6423 0.2296 0.000 0.580 0.336 0.084
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 1 0.1474 0.8673 0.948 0.000 0.000 0.052
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.3528 0.6264 0.192 0.000 0.000 0.808
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#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.2647 0.8312 0.000 0.120 0.880 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.1637 0.8945 0.000 0.000 0.940 0.060
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.1716 0.6361 0.064 0.000 0.000 0.936
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.5713 0.5920 0.040 0.340 0.000 0.620
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.5174 0.5395 0.368 0.012 0.000 0.620
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.4985 0.2455 0.000 0.468 0.532 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4866 0.5179 0.000 0.404 0.000 0.596
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 4 0.5184 0.4156 0.000 0.204 0.060 0.736
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.4193 0.6307 0.000 0.268 0.000 0.732
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.1867 0.7793 0.000 0.928 0.072 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.5393 0.6419 0.044 0.268 0.000 0.688
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.1118 0.8828 0.964 0.000 0.000 0.036
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.8192 0.000 1.000 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0707 0.8980 0.980 0.000 0.000 0.020
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3266 0.6938 0.000 0.832 0.168 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.2081 0.8702 0.916 0.000 0.000 0.084
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.4248 0.5958 0.000 0.768 0.012 0.220
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0657 0.8183 0.000 0.984 0.012 0.004
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0469 0.8174 0.000 0.988 0.012 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.4790 0.5565 0.000 0.380 0.000 0.620
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.1637 0.8604 0.940 0.000 0.000 0.060
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9328 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.4998 -0.2644 0.000 0.512 0.000 0.488
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.5458 0.6455 0.236 0.060 0.000 0.704
#> 671507DB-3949-4A41-9682-644CE8FED3D3 4 0.1022 0.6333 0.000 0.032 0.000 0.968
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.4008 0.6391 0.000 0.244 0.000 0.756
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3219 0.6999 0.000 0.836 0.164 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.5174 0.5395 0.368 0.012 0.000 0.620
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.4948 0.3169 0.000 0.440 0.560 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4072 0.5771 0.000 0.748 0.252 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0188 0.8194 0.000 0.996 0.000 0.004
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.2469 0.6633 0.000 0.108 0.000 0.892
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.5623 0.6101 0.292 0.048 0.000 0.660
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0657 0.8183 0.000 0.984 0.012 0.004
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0657 0.8183 0.000 0.984 0.012 0.004
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.5174 0.5395 0.368 0.012 0.000 0.620
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 4 0.1174 0.6285 0.012 0.020 0.000 0.968
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9047 1.000 0.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 4 0.4804 0.5507 0.000 0.384 0.000 0.616
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.4981 -0.2088 0.000 0.536 0.000 0.464
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2081 0.8702 0.916 0.000 0.000 0.084
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9047 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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0865 0.91102 0.004 0.972 0.000 0.024 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.1485 0.89634 0.032 0.948 0.000 0.020 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0671 0.89288 0.004 0.980 0.016 0.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2825 0.86050 0.860 0.000 0.000 0.124 0.016
#> F405CD29-4016-415B-9546-02DA179A97AC 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0932 0.92884 0.020 0.004 0.972 0.000 0.004
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0771 0.93776 0.004 0.020 0.976 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0798 0.90695 0.008 0.976 0.000 0.016 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1211 0.90635 0.016 0.960 0.000 0.024 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1043 0.88261 0.000 0.000 0.000 0.960 0.040
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.1124 0.87923 0.004 0.960 0.036 0.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0963 0.88398 0.000 0.000 0.000 0.964 0.036
#> 2437A516-5312-409E-8679-B85BB60530CD 5 0.3916 0.65909 0.256 0.000 0.000 0.012 0.732
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0794 0.88505 0.000 0.000 0.000 0.972 0.028
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.4100 0.69166 0.044 0.764 0.000 0.192 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.2209 0.87542 0.056 0.912 0.000 0.032 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.1043 0.88261 0.000 0.000 0.000 0.960 0.040
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.1549 0.90428 0.040 0.016 0.000 0.944 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2563 0.80982 0.008 0.872 0.120 0.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.2795 0.88537 0.056 0.064 0.000 0.880 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0609 0.90351 0.000 0.020 0.000 0.980 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3586 0.81696 0.828 0.000 0.000 0.076 0.096
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 5 0.4300 0.08387 0.000 0.000 0.000 0.476 0.524
#> 00F70D11-3B58-4517-82EC-258CCED34A60 5 0.0579 0.92759 0.008 0.000 0.000 0.008 0.984
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.2729 0.88782 0.056 0.060 0.000 0.884 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.1907 0.90498 0.044 0.028 0.000 0.928 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3269 0.81200 0.056 0.848 0.000 0.096 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.1484 0.86966 0.008 0.944 0.048 0.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.0404 0.90231 0.000 0.012 0.000 0.988 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.2067 0.90395 0.048 0.032 0.000 0.920 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.3760 0.65794 0.784 0.028 0.188 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.2408 0.86601 0.892 0.016 0.000 0.092 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.1251 0.87977 0.036 0.000 0.000 0.956 0.008
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0771 0.93776 0.004 0.020 0.976 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2291 0.87193 0.056 0.908 0.000 0.036 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.4581 0.70039 0.732 0.000 0.000 0.072 0.196
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 5 0.0579 0.92759 0.008 0.000 0.000 0.008 0.984
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1518 0.91827 0.048 0.004 0.944 0.000 0.004
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0798 0.90695 0.008 0.976 0.000 0.016 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0771 0.93776 0.004 0.020 0.976 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 5 0.3779 0.69376 0.236 0.000 0.000 0.012 0.752
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.3116 0.84227 0.860 0.000 0.000 0.076 0.064
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.2997 0.82949 0.148 0.012 0.000 0.840 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3269 0.81240 0.056 0.848 0.000 0.096 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4658 0.05239 0.012 0.504 0.484 0.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.5068 0.52169 0.640 0.000 0.000 0.060 0.300
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.4891 0.43857 0.640 0.316 0.000 0.044 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0000 0.89886 0.000 0.000 0.000 1.000 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.0162 0.89889 0.000 0.000 0.000 0.996 0.004
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.0794 0.88961 0.000 0.000 0.000 0.972 0.028
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 5 0.2574 0.85335 0.112 0.000 0.000 0.012 0.876
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.0510 0.90328 0.000 0.016 0.000 0.984 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 5 0.2574 0.85335 0.112 0.000 0.000 0.012 0.876
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.0451 0.89929 0.008 0.004 0.000 0.988 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 4 0.1750 0.90526 0.036 0.028 0.000 0.936 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.2795 0.88537 0.056 0.064 0.000 0.880 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1211 0.90635 0.016 0.960 0.000 0.024 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.3058 0.85274 0.860 0.000 0.000 0.096 0.044
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0609 0.93886 0.000 0.020 0.980 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.4375 0.23142 0.004 0.576 0.420 0.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.1774 0.90227 0.052 0.016 0.000 0.932 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 4 0.2054 0.90311 0.052 0.028 0.000 0.920 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.0771 0.93799 0.004 0.020 0.976 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.1043 0.88261 0.000 0.000 0.000 0.960 0.040
#> DBFA1780-4558-436A-A434-05DAFD0F675A 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.1571 0.87226 0.936 0.004 0.000 0.060 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.1502 0.87162 0.940 0.004 0.000 0.056 0.000
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#> 310F99CB-0837-4869-8B48-28D4B543BE3B 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.1251 0.88174 0.008 0.000 0.000 0.956 0.036
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2612 0.86299 0.868 0.000 0.000 0.124 0.008
#> A4CECC77-3764-4F27-BD37-D7E76E436944 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.1484 0.86966 0.008 0.944 0.048 0.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.1831 0.87814 0.920 0.004 0.000 0.076 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 5 0.0703 0.93429 0.000 0.000 0.000 0.024 0.976
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 5 0.0807 0.92283 0.012 0.000 0.000 0.012 0.976
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.2964 0.82062 0.152 0.004 0.840 0.000 0.004
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0865 0.91094 0.004 0.972 0.000 0.024 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.2036 0.88079 0.056 0.920 0.000 0.024 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.2036 0.88079 0.056 0.920 0.000 0.024 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.2660 0.86018 0.864 0.000 0.000 0.128 0.008
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.2011 0.87776 0.908 0.004 0.000 0.088 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.5008 0.50269 0.056 0.644 0.000 0.300 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0865 0.91094 0.004 0.972 0.000 0.024 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.2729 0.88782 0.056 0.060 0.000 0.884 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.0404 0.89839 0.000 0.000 0.000 0.988 0.012
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0579 0.90051 0.008 0.008 0.000 0.984 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0798 0.84884 0.976 0.016 0.000 0.008 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.4455 0.31492 0.404 0.588 0.000 0.008 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 4 0.2859 0.88264 0.056 0.068 0.000 0.876 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.2825 0.86050 0.860 0.000 0.000 0.124 0.016
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.0703 0.88543 0.000 0.000 0.000 0.976 0.024
#> E2A25905-7C92-4E43-81C0-D09268014334 4 0.5063 0.53507 0.056 0.312 0.000 0.632 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.1893 0.88666 0.048 0.928 0.000 0.024 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.1518 0.91827 0.048 0.004 0.944 0.000 0.004
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 4 0.1701 0.90317 0.048 0.016 0.000 0.936 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0609 0.93886 0.000 0.020 0.980 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.2036 0.88079 0.056 0.920 0.000 0.024 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0865 0.91102 0.004 0.972 0.000 0.024 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0992 0.90961 0.008 0.968 0.000 0.024 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.1518 0.91827 0.048 0.004 0.944 0.000 0.004
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.2852 0.76328 0.000 0.172 0.828 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.4066 0.55840 0.324 0.000 0.672 0.000 0.004
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.0898 0.88936 0.020 0.000 0.000 0.972 0.008
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.0703 0.90369 0.000 0.024 0.000 0.976 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 4 0.1981 0.90434 0.048 0.028 0.000 0.924 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0794 0.88748 0.000 0.000 0.000 0.972 0.028
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.2707 0.79741 0.008 0.860 0.132 0.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.2370 0.89871 0.056 0.040 0.000 0.904 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0798 0.84884 0.976 0.016 0.000 0.008 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0898 0.93689 0.008 0.020 0.972 0.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.2124 0.87821 0.056 0.916 0.000 0.028 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.1626 0.90391 0.044 0.016 0.000 0.940 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.2036 0.90284 0.056 0.024 0.000 0.920 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.1124 0.87923 0.004 0.960 0.036 0.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.0404 0.90231 0.000 0.012 0.000 0.988 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 5 0.1908 0.88047 0.000 0.000 0.000 0.092 0.908
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 5 0.0404 0.93103 0.000 0.000 0.000 0.012 0.988
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.1484 0.86966 0.008 0.944 0.048 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0771 0.93776 0.004 0.020 0.976 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 5 0.0579 0.92759 0.008 0.000 0.000 0.008 0.984
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0609 0.93886 0.000 0.020 0.980 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.4235 0.48298 0.336 0.656 0.000 0.008 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0865 0.91143 0.004 0.972 0.000 0.024 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.4268 0.17612 0.000 0.000 0.000 0.556 0.444
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0771 0.93776 0.004 0.020 0.976 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.2795 0.88537 0.056 0.064 0.000 0.880 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.0404 0.90231 0.000 0.012 0.000 0.988 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.1831 0.87814 0.920 0.004 0.000 0.076 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.3224 0.82729 0.160 0.016 0.000 0.824 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.1205 0.87670 0.004 0.956 0.040 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.0162 0.90054 0.000 0.004 0.000 0.996 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.2929 0.77549 0.008 0.840 0.152 0.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.2470 0.82314 0.012 0.884 0.104 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0703 0.91171 0.000 0.976 0.000 0.024 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.2574 0.82469 0.112 0.012 0.000 0.876 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0290 0.90143 0.000 0.008 0.000 0.992 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 5 0.0404 0.93539 0.000 0.000 0.000 0.012 0.988
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0727 0.90379 0.004 0.980 0.004 0.012 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0865 0.91129 0.004 0.972 0.000 0.024 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.0963 0.88398 0.000 0.000 0.000 0.964 0.036
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1952 0.87805 0.912 0.004 0.000 0.084 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.0290 0.93253 0.000 0.000 0.000 0.008 0.992
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 5 0.1270 0.91346 0.000 0.000 0.000 0.052 0.948
#> BD879832-E177-4FCA-B1EA-D1553518E700 4 0.2124 0.90223 0.056 0.028 0.000 0.916 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.4537 0.70498 0.184 0.740 0.000 0.076 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 5 0.0579 0.92759 0.008 0.000 0.000 0.008 0.984
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.0510 0.93661 0.000 0.000 0.000 0.016 0.984
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.0000 0.79506 0.000 0.000 0.000 1.000 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.4999 0.46562 0.144 0.000 0.000 0.640 0.216 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 4 0.0260 0.79370 0.000 0.000 0.000 0.992 0.008 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.0806 0.78731 0.000 0.000 0.020 0.972 0.008 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3134 0.75551 0.808 0.024 0.000 0.000 0.168 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.1151 0.89993 0.012 0.000 0.956 0.000 0.032 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 4 0.0146 0.79529 0.000 0.000 0.000 0.996 0.004 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0146 0.90795 0.000 0.000 0.996 0.000 0.004 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0260 0.79364 0.000 0.000 0.000 0.992 0.008 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 4 0.3446 0.46521 0.000 0.000 0.000 0.692 0.308 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0713 0.64997 0.000 0.972 0.000 0.000 0.000 0.028
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0891 0.78553 0.000 0.000 0.024 0.968 0.008 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0547 0.66745 0.000 0.980 0.000 0.000 0.020 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 6 0.5753 0.31892 0.364 0.000 0.000 0.000 0.176 0.460
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0260 0.79512 0.000 0.000 0.000 0.992 0.008 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0632 0.65842 0.000 0.976 0.000 0.000 0.024 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.5708 -0.01629 0.000 0.216 0.000 0.520 0.264 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.4384 0.28662 0.000 0.036 0.000 0.616 0.348 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0363 0.65948 0.000 0.988 0.000 0.000 0.000 0.012
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3647 0.53634 0.000 0.640 0.000 0.000 0.360 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2176 0.74238 0.000 0.000 0.080 0.896 0.024 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.1007 0.82739 0.000 0.044 0.000 0.000 0.000 0.956
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0146 0.79447 0.000 0.000 0.000 0.996 0.004 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4449 0.36486 0.000 0.532 0.000 0.028 0.440 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.66458 0.000 1.000 0.000 0.000 0.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3386 0.74372 0.796 0.016 0.000 0.000 0.176 0.012
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.3833 0.25776 0.000 0.648 0.000 0.000 0.008 0.344
#> 00F70D11-3B58-4517-82EC-258CCED34A60 6 0.3352 0.78516 0.032 0.000 0.000 0.000 0.176 0.792
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3707 0.52194 0.000 0.680 0.000 0.008 0.312 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3706 0.51529 0.000 0.620 0.000 0.000 0.380 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.2448 0.85070 0.000 0.000 0.884 0.064 0.052 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.4453 0.01354 0.000 0.028 0.000 0.528 0.444 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.1341 0.77560 0.000 0.000 0.028 0.948 0.024 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.2793 0.63384 0.000 0.800 0.000 0.000 0.200 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3531 0.53039 0.000 0.672 0.000 0.000 0.328 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.6623 0.41048 0.492 0.000 0.064 0.184 0.260 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.4332 0.47014 0.000 0.616 0.000 0.032 0.352 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.5300 0.29800 0.600 0.188 0.000 0.000 0.212 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.1700 0.66897 0.004 0.916 0.000 0.000 0.080 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0146 0.90795 0.000 0.000 0.996 0.000 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 4 0.4157 0.07900 0.000 0.012 0.000 0.544 0.444 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 4 0.2300 0.70461 0.000 0.000 0.000 0.856 0.144 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.3221 0.58025 0.000 0.736 0.000 0.000 0.264 0.000
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#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2872 0.68901 0.000 0.000 0.140 0.836 0.024 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.2837 0.71311 0.000 0.000 0.056 0.856 0.088 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.0790 0.78939 0.000 0.000 0.000 0.968 0.032 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5035 0.51972 0.168 0.640 0.000 0.000 0.192 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.0458 0.66140 0.000 0.984 0.000 0.000 0.016 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0458 0.79140 0.000 0.000 0.000 0.984 0.016 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0790 0.78849 0.000 0.000 0.000 0.968 0.032 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.66458 0.000 1.000 0.000 0.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0717 0.81838 0.976 0.016 0.000 0.000 0.008 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.2848 0.79722 0.008 0.000 0.000 0.000 0.176 0.816
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.3975 0.45248 0.000 0.392 0.000 0.000 0.008 0.600
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3823 0.44059 0.000 0.564 0.000 0.000 0.436 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.6624 -0.28685 0.068 0.140 0.000 0.440 0.352 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 6 0.3279 0.78749 0.028 0.000 0.000 0.000 0.176 0.796
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.0000 0.84863 0.000 0.000 0.000 0.000 0.000 1.000
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 17581 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 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 1.000 0.983 0.994 0.5013 0.499 0.499
#> 3 3 0.898 0.917 0.963 0.3035 0.788 0.599
#> 4 4 0.938 0.908 0.962 0.1357 0.865 0.633
#> 5 5 0.849 0.845 0.923 0.0651 0.860 0.535
#> 6 6 0.840 0.773 0.894 0.0394 0.920 0.653
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.0000 0.99406 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.99406 1.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 1 0.0000 0.99406 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 1 0.0000 0.99406 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.0000 0.99277 0.000 1.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.99277 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.99277 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.99406 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 1 0.0000 0.99406 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.99406 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.99277 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.0000 0.99406 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 1 0.0000 0.99406 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.99277 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.0000 0.99406 1.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.99277 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.0000 0.99277 0.000 1.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.0000 0.99406 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.99277 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.0000 0.99406 1.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 1 0.0000 0.99406 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0000 0.99277 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.99277 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.0000 0.99406 1.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.99277 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.0000 0.99406 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2603 0.94895 0.044 0.956
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.99277 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.0000 0.99277 0.000 1.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.99277 0.000 1.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.0000 0.99277 0.000 1.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 1 0.0000 0.99406 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.99277 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.99277 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.0000 0.99406 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 1 0.0000 0.99406 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 1 0.0000 0.99406 1.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.99277 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.99277 0.000 1.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0000 0.99406 1.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 1 0.0000 0.99406 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.0000 0.99277 0.000 1.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.0000 0.99277 0.000 1.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.99406 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 1 0.0000 0.99406 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 1 0.0000 0.99406 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.99277 0.000 1.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.0000 0.99277 0.000 1.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.0000 0.99277 0.000 1.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.99406 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 1 0.0000 0.99406 1.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0000 0.99277 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 1 0.0000 0.99406 1.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 1 0.0000 0.99406 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0672 0.98526 0.008 0.992
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.99406 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.0000 0.99277 0.000 1.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.0000 0.99406 1.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.0000 0.99277 0.000 1.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.0000 0.99277 0.000 1.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 1 0.0000 0.99406 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.0000 0.99406 1.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.0000 0.99277 0.000 1.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.99277 0.000 1.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0000 0.99406 1.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 1 0.0000 0.99406 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.99277 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.99277 0.000 1.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0000 0.99277 0.000 1.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.99277 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.0000 0.99277 0.000 1.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0000 0.99277 0.000 1.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.0000 0.99277 0.000 1.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.99277 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.99277 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.99277 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.99277 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 1 0.0000 0.99406 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 1 0.0000 0.99406 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.8499 0.61965 0.276 0.724
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.0000 0.99277 0.000 1.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.99277 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.99406 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 1 0.0000 0.99406 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.0000 0.99406 1.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 1 0.9710 0.32947 0.600 0.400
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.99277 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 1 0.0000 0.99406 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.99277 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.0000 0.99406 1.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.99277 0.000 1.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.99277 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 2 0.0376 0.98904 0.004 0.996
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 1 0.0000 0.99406 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.99406 1.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 1 0.0000 0.99406 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 2 0.0000 0.99277 0.000 1.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.99277 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.99406 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 2 0.0000 0.99277 0.000 1.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.99277 0.000 1.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.0000 0.99277 0.000 1.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.99406 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.6623 0.79097 0.172 0.828
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 2 0.0000 0.99277 0.000 1.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 1 0.0000 0.99406 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.0000 0.99277 0.000 1.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 2 0.0000 0.99277 0.000 1.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 1 0.0000 0.99406 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.0000 0.99406 1.000 0.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.99277 0.000 1.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.0000 0.99277 0.000 1.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.0000 0.99277 0.000 1.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 1 0.0000 0.99406 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.0000 0.99277 0.000 1.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 2 0.0000 0.99277 0.000 1.000
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#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0000 0.99277 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.6295 0.1253 0.000 0.528 0.472
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 3 0.0000 0.9482 0.000 0.000 1.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1964 0.9148 0.000 0.944 0.056
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3482 0.8529 0.000 0.872 0.128
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9790 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.0000 0.9790 1.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.9790 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9482 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.4555 0.7675 0.000 0.800 0.200
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9482 0.000 0.000 1.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.9790 1.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.4974 0.6949 0.000 0.236 0.764
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9425 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.0000 0.9790 1.000 0.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.1031 0.9306 0.000 0.024 0.976
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.0000 0.9790 1.000 0.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9790 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.5810 0.5065 0.000 0.336 0.664
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 1 0.0000 0.9790 1.000 0.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.1031 0.9306 0.000 0.024 0.976
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9425 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.0000 0.9790 1.000 0.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.0000 0.9790 1.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0000 0.9482 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.0000 0.9790 1.000 0.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 3 0.5138 0.6691 0.000 0.252 0.748
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9425 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 1 0.0000 0.9790 1.000 0.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9790 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.0000 0.9790 1.000 0.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9790 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9425 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 1 0.6291 0.0951 0.532 0.468 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.0000 0.9790 1.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0000 0.9482 0.000 0.000 1.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.9425 0.000 1.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.3686 0.8183 0.000 0.140 0.860
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 1 0.0000 0.9790 1.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9425 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 3 0.0000 0.9482 0.000 0.000 1.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3116 0.8726 0.000 0.892 0.108
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.5254 0.6304 0.736 0.264 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.0000 0.9790 1.000 0.000 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9482 0.000 0.000 1.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.9425 0.000 1.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9425 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.6309 -0.0223 0.504 0.496 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9790 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9790 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9482 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.0000 0.9482 0.000 0.000 1.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.0000 0.9790 1.000 0.000 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 3 0.5621 0.5659 0.000 0.308 0.692
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9425 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4399 0.7610 0.188 0.812 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9482 0.000 0.000 1.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9790 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.0000 0.9482 0.000 0.000 1.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9790 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.0000 0.9790 1.000 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.9425 0.000 1.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.0000 0.9482 0.000 0.000 1.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9790 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.5968 0.4507 0.364 0.636 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.3941 0.8258 0.000 0.844 0.156
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.2165 0.9093 0.000 0.936 0.064
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.3116 0.8463 0.108 0.892 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 1 0.0000 0.9790 1.000 0.000 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.0000 0.9790 1.000 0.000 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 1 0.0000 0.9790 1.000 0.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9790 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.0000 0.9790 1.000 0.000 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9790 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 1 0.0000 0.9790 1.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.0000 0.9790 1.000 0.000 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 1 0.0000 0.9790 1.000 0.000 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 1 0.5905 0.4442 0.648 0.352 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9425 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9425 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9425 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9790 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 1 0.0000 0.9790 1.000 0.000 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9482 0.000 0.000 1.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.2066 0.9121 0.000 0.940 0.060
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.9482 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9425 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.0000 0.9790 1.000 0.000 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9425 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.5650 0.5594 0.312 0.688 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.0000 0.9482 0.000 0.000 1.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 1 0.0000 0.9790 1.000 0.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 1 0.0000 0.9790 1.000 0.000 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.5560 0.5848 0.700 0.000 0.300
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0000 0.9425 0.000 1.000 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 3 0.0000 0.9482 0.000 0.000 1.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.9425 0.000 1.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.0000 0.9790 1.000 0.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 1 0.0000 0.9790 1.000 0.000 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9482 0.000 0.000 1.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9790 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.4555 0.7408 0.200 0.800 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 1 0.0000 0.9790 1.000 0.000 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9482 0.000 0.000 1.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9425 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 3 0.4974 0.6716 0.236 0.000 0.764
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0000 0.9425 0.000 1.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 1 0.0000 0.9790 1.000 0.000 0.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.4931 0.7036 0.768 0.000 0.232
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0000 0.9425 0.000 1.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 3 0.0000 0.9482 0.000 0.000 1.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 1 0.0000 0.9790 1.000 0.000 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 1 0.0000 0.9790 1.000 0.000 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 1 0.0000 0.9790 1.000 0.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0592 0.9385 0.000 0.988 0.012
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 1 0.0000 0.9790 1.000 0.000 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9790 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9790 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 1 0.0000 0.9790 1.000 0.000 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.6215 0.2736 0.428 0.572 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.0000 0.9482 0.000 0.000 1.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9790 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 1 0.0000 0.9790 1.000 0.000 0.000
#> 95598EDA-BA98-4C1D-951B-131E149989E1 3 0.0000 0.9482 0.000 0.000 1.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9482 0.000 0.000 1.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 1 0.0000 0.9790 1.000 0.000 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0592 0.9385 0.000 0.988 0.012
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 1 0.0000 0.9790 1.000 0.000 0.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.0592 0.9385 0.000 0.988 0.012
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.0000 0.9425 0.000 1.000 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.9482 0.000 0.000 1.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.0000 0.9482 0.000 0.000 1.000
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0592 0.9385 0.000 0.988 0.012
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 1 0.0000 0.9790 1.000 0.000 0.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 1 0.0000 0.9790 1.000 0.000 0.000
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 1 0.0000 0.9790 1.000 0.000 0.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 3 0.0000 0.9482 0.000 0.000 1.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.9482 0.000 0.000 1.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9790 1.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 3 0.4974 0.6949 0.000 0.236 0.764
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.3192 0.8653 0.000 0.888 0.112
#> FAA284CF-ABD4-4405-B847-AD06672BF451 3 0.0000 0.9482 0.000 0.000 1.000
#> 15C85716-4BE3-43A8-9F61-2929C600C828 3 0.0000 0.9482 0.000 0.000 1.000
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.2356 0.9032 0.000 0.928 0.072
#> AF27FD0A-108C-47D2-9F87-665BED408E99 1 0.0000 0.9790 1.000 0.000 0.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0000 0.9425 0.000 1.000 0.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 1 0.0000 0.9790 1.000 0.000 0.000
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.4974 0.7142 0.000 0.764 0.236
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 1 0.0000 0.9790 1.000 0.000 0.000
#> 679EE059-DDD9-4138-9973-51A583941B71 1 0.0000 0.9790 1.000 0.000 0.000
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.0000 0.9790 1.000 0.000 0.000
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0000 0.9790 1.000 0.000 0.000
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 1 0.5882 0.4773 0.652 0.000 0.348
#> 29C63350-F03B-4C65-979C-53AE84E20042 1 0.0000 0.9790 1.000 0.000 0.000
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 1 0.0000 0.9790 1.000 0.000 0.000
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 1 0.0000 0.9790 1.000 0.000 0.000
#> FEF6E287-8F0D-455B-BA19-7C48C2C583D2 2 0.0000 0.9425 0.000 1.000 0.000
#> BC005778-F88D-47B7-8E04-CEB9750F00C2 1 0.0000 0.9790 1.000 0.000 0.000
#> EB3AA089-6C7A-4E61-8DE3-2A59BCA43CC4 1 0.0000 0.9790 1.000 0.000 0.000
#> 601D287E-1F5C-4AC7-A4A4-85BD89AD5327 3 0.4887 0.7067 0.000 0.228 0.772
#> 1BD3C6DA-1DE9-4DFA-B9DA-A69C1840C8F4 1 0.0000 0.9790 1.000 0.000 0.000
#> 04C60003-5D6D-45EA-957C-E54AACAC7485 3 0.0000 0.9482 0.000 0.000 1.000
#> 38FCA0B0-4399-4061-99AA-B886F54CA0DB 3 0.0000 0.9482 0.000 0.000 1.000
#> C0DC6757-E0CD-4615-9543-A348500AAE84 2 0.1643 0.9223 0.000 0.956 0.044
#> 84B05220-4E28-44AE-B6EE-6018C0DBF0D2 2 0.1031 0.9333 0.000 0.976 0.024
#> AE8D8D83-D457-4164-861E-9329DB223561 3 0.0000 0.9482 0.000 0.000 1.000
#> 85853AF3-27B0-49E0-9E71-478019AE1FA6 3 0.0000 0.9482 0.000 0.000 1.000
#> D1B716E8-E4D4-4089-B46A-9892A8BE55F5 1 0.0000 0.9790 1.000 0.000 0.000
#> 4B1A0809-0B28-4993-893D-1B7EF099DE91 3 0.0000 0.9482 0.000 0.000 1.000
#> 842F6668-669F-4E7D-89F6-F6DA627297B8 3 0.0000 0.9482 0.000 0.000 1.000
#> B6E47B05-AFE9-41B5-B040-7FBCC62D4720 3 0.0000 0.9482 0.000 0.000 1.000
#> E43DADE2-3A54-4FC5-A94A-70752288DE94 2 0.0000 0.9425 0.000 1.000 0.000
#> 421C51E1-BA5F-4FFE-B4ED-39303113709B 2 0.0000 0.9425 0.000 1.000 0.000
#> 06820399-3529-412F-B3A7-6714C9DD5F7D 1 0.0000 0.9790 1.000 0.000 0.000
#> 21BFABFE-7C78-4879-BEC0-74C0CFD20529 1 0.0000 0.9790 1.000 0.000 0.000
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#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 3 0.0000 0.9482 0.000 0.000 1.000
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 3 0.0000 0.9482 0.000 0.000 1.000
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.9790 1.000 0.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 1 0.0000 0.9790 1.000 0.000 0.000
#> A5572139-03CA-4299-98B6-13A2945649D0 3 0.0000 0.9482 0.000 0.000 1.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 3 0.0000 0.9482 0.000 0.000 1.000
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 1 0.0000 0.9790 1.000 0.000 0.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 3 0.5058 0.6823 0.000 0.244 0.756
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 1 0.0000 0.9790 1.000 0.000 0.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.2261 0.9063 0.000 0.932 0.068
#> DCD932D2-B708-487A-93C1-8485FBE9048A 3 0.0000 0.9482 0.000 0.000 1.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 1 0.3879 0.8039 0.848 0.000 0.152
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9790 1.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9790 1.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.3816 0.8317 0.000 0.852 0.148
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 1 0.4235 0.7745 0.824 0.176 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 1 0.0000 0.9790 1.000 0.000 0.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 1 0.0000 0.9790 1.000 0.000 0.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 3 0.6062 0.3634 0.384 0.000 0.616
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 1 0.0000 0.9790 1.000 0.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.9482 0.000 0.000 1.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 1 0.0000 0.9790 1.000 0.000 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 1 0.0000 0.9790 1.000 0.000 0.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0892 0.9352 0.000 0.980 0.020
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.9482 0.000 0.000 1.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 1 0.0000 0.9790 1.000 0.000 0.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 3 0.1964 0.9034 0.000 0.056 0.944
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0000 0.9790 1.000 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.9482 0.000 0.000 1.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 1 0.0000 0.9790 1.000 0.000 0.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 1 0.0000 0.9790 1.000 0.000 0.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.0000 0.9482 0.000 0.000 1.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.9425 0.000 1.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 1 0.0000 0.9790 1.000 0.000 0.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 3 0.0747 0.9366 0.000 0.016 0.984
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9790 1.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9790 1.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 3 0.1643 0.9145 0.000 0.044 0.956
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9425 0.000 1.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 1 0.0000 0.9790 1.000 0.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.0000 0.9790 1.000 0.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9425 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.1643 0.9223 0.000 0.956 0.044
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9482 0.000 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 1 0.0000 0.9790 1.000 0.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.2625 0.8935 0.000 0.916 0.084
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9425 0.000 1.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 1 0.0000 0.9790 1.000 0.000 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9425 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0592 0.9385 0.000 0.988 0.012
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0000 0.9482 0.000 0.000 1.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 1 0.0000 0.9790 1.000 0.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9790 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 1 0.0000 0.9790 1.000 0.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9425 0.000 1.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 3 0.0000 0.9482 0.000 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9790 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 1 0.0000 0.9790 1.000 0.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9425 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9790 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9482 0.000 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 3 0.5497 0.5982 0.000 0.292 0.708
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.4605 0.7618 0.000 0.796 0.204
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9425 0.000 1.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9790 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9790 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9425 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9425 0.000 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1860 0.9174 0.000 0.948 0.052
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9425 0.000 1.000 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 1 0.0000 0.9790 1.000 0.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.9482 0.000 0.000 1.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 1 0.0000 0.9790 1.000 0.000 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 3 0.0000 0.9482 0.000 0.000 1.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 3 0.0000 0.9482 0.000 0.000 1.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9425 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9790 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.0000 0.9790 1.000 0.000 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9425 0.000 1.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 3 0.5882 0.4771 0.000 0.348 0.652
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9482 0.000 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 1 0.0000 0.9790 1.000 0.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 1 0.0000 0.9790 1.000 0.000 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9482 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9425 0.000 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9425 0.000 1.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 3 0.4796 0.7179 0.000 0.220 0.780
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1163 0.9312 0.000 0.972 0.028
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9425 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9482 0.000 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9482 0.000 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.0000 0.9482 0.000 0.000 1.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0000 0.9790 1.000 0.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 1 0.5254 0.6304 0.736 0.264 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9790 1.000 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.2448 0.8798 0.076 0.924 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.0000 0.9790 1.000 0.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.0000 0.9790 1.000 0.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.9482 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9425 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3038 0.8760 0.000 0.896 0.104
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 3 0.0000 0.9482 0.000 0.000 1.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0000 0.9482 0.000 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.3816 0.8056 0.148 0.852 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9425 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.0000 0.9790 1.000 0.000 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 1 0.4555 0.7526 0.800 0.200 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3816 0.8317 0.000 0.852 0.148
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 1 0.0000 0.9790 1.000 0.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9790 1.000 0.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9425 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9790 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.5058 0.7010 0.000 0.756 0.244
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9482 0.000 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9790 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9482 0.000 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 3 0.0000 0.9482 0.000 0.000 1.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0000 0.9790 1.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.2066 0.9121 0.000 0.940 0.060
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3551 0.8487 0.000 0.868 0.132
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 3 0.0000 0.9482 0.000 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.0000 0.9790 1.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9482 0.000 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9425 0.000 1.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 1 0.0000 0.9790 1.000 0.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 3 0.3941 0.7738 0.156 0.000 0.844
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 1 0.0000 0.9790 1.000 0.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4062 0.8131 0.000 0.836 0.164
#> C3E23136-7190-4D08-991C-93AFACC48E8D 1 0.0000 0.9790 1.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.9482 0.000 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 3 0.5058 0.6823 0.000 0.244 0.756
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9425 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.0000 0.9790 1.000 0.000 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.0000 0.9790 1.000 0.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9790 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.0000 0.9482 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.9482 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.9790 1.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 1 0.0000 0.9790 1.000 0.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9790 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0000 0.9790 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9790 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9790 1.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9425 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0000 0.9482 0.000 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9790 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9790 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4356 0.5894 0.000 0.708 0.292 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.2530 0.8596 0.000 0.888 0.112 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.1637 0.9140 0.000 0.060 0.940 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0817 0.9482 0.976 0.000 0.000 0.024
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.1474 0.9211 0.000 0.052 0.948 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.3764 0.7372 0.784 0.000 0.000 0.216
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0000 0.9618 0.000 0.000 0.000 1.000
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#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 3 0.2973 0.8255 0.000 0.144 0.856 0.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.1211 0.9401 0.960 0.000 0.000 0.040
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.0817 0.9406 0.000 0.976 0.024 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0592 0.9456 0.000 0.984 0.016 0.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 4 0.0817 0.9427 0.024 0.000 0.000 0.976
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.1211 0.9401 0.960 0.000 0.000 0.040
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 3 0.5856 0.0734 0.464 0.032 0.504 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0592 0.9456 0.000 0.984 0.016 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0469 0.9474 0.000 0.988 0.012 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.4933 0.2082 0.432 0.000 0.000 0.568
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0707 0.9496 0.980 0.000 0.000 0.020
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 3 0.4164 0.6459 0.000 0.264 0.736 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.3837 0.7090 0.000 0.776 0.224 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0469 0.9436 0.000 0.988 0.000 0.012
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 3 0.4981 0.1436 0.464 0.000 0.536 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 3 0.3610 0.7374 0.200 0.000 0.800 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 3 0.3123 0.8110 0.000 0.156 0.844 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 1 0.4972 0.1869 0.544 0.000 0.000 0.456
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 3 0.4250 0.6242 0.000 0.276 0.724 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0592 0.9456 0.000 0.984 0.016 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.1474 0.9321 0.948 0.000 0.000 0.052
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4898 0.3066 0.000 0.584 0.000 0.416
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.4134 0.6476 0.000 0.740 0.000 0.260
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4992 0.0613 0.524 0.000 0.476 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.0188 0.9539 0.996 0.000 0.000 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.0707 0.9447 0.000 0.020 0.000 0.980
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.1389 0.9207 0.000 0.952 0.048 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.4103 0.6317 0.256 0.000 0.000 0.744
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1792 0.9170 0.932 0.000 0.000 0.068
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.2814 0.8368 0.000 0.868 0.132 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.1302 0.9374 0.956 0.000 0.000 0.044
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0707 0.9435 0.000 0.980 0.020 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0817 0.9406 0.000 0.976 0.024 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.4989 0.0828 0.000 0.000 0.472 0.528
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.0188 0.9588 0.004 0.000 0.000 0.996
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.2081 0.8874 0.000 0.916 0.084 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 3 0.4746 0.4252 0.000 0.368 0.632 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.0188 0.9539 0.996 0.000 0.000 0.004
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9545 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.3649 0.7237 0.204 0.000 0.000 0.796
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.0000 0.9618 0.000 0.000 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9517 0.000 1.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0000 0.9632 0.000 0.000 1.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.1389 0.9344 0.952 0.000 0.000 0.048
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0000 0.9618 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 5 0.0000 0.8833 0.000 0.000 0.000 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 5 0.3814 0.6402 0.004 0.000 0.276 0.000 0.720
#> 300D7F74-A627-4738-91A9-62778D98C5AD 5 0.0000 0.8833 0.000 0.000 0.000 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.0000 0.8833 0.000 0.000 0.000 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.8933 1.000 0.000 0.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9532 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 5 0.0000 0.8833 0.000 0.000 0.000 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9532 0.000 0.000 1.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.1270 0.8665 0.000 0.000 0.052 0.000 0.948
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3857 0.6610 0.000 0.688 0.000 0.000 0.312
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.1270 0.9337 0.000 0.052 0.000 0.948 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.1965 0.8423 0.000 0.000 0.096 0.000 0.904
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2966 0.8040 0.816 0.000 0.000 0.184 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.0963 0.8730 0.000 0.000 0.036 0.000 0.964
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.1281 0.9261 0.000 0.032 0.956 0.000 0.012
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#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1043 0.9394 0.000 0.040 0.000 0.960 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.2377 0.8471 0.000 0.000 0.872 0.000 0.128
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.9532 0.000 0.000 1.000 0.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.1410 0.9279 0.000 0.060 0.000 0.940 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.8933 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.0703 0.9457 0.000 0.024 0.000 0.976 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.1121 0.8759 0.000 0.956 0.000 0.000 0.044
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0000 0.9532 0.000 0.000 1.000 0.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.4235 0.4258 0.576 0.000 0.000 0.424 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0000 0.9533 0.000 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.3599 0.674359 0.020 0.000 0.220 0.756 0.004 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1444 0.803659 0.928 0.000 0.000 0.000 0.000 0.072
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.1141 0.899196 0.000 0.000 0.000 0.000 0.052 0.948
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.2346 0.809193 0.000 0.868 0.000 0.124 0.008 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 5 0.0547 0.787155 0.000 0.000 0.000 0.000 0.980 0.020
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.0146 0.911461 0.000 0.000 0.004 0.996 0.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3446 0.649173 0.692 0.000 0.000 0.000 0.000 0.308
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.1141 0.898442 0.000 0.000 0.000 0.000 0.052 0.948
#> A0A07F44-C51B-420C-92E8-65F464DB0442 5 0.4402 0.605553 0.000 0.000 0.184 0.104 0.712 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.0260 0.909048 0.000 0.000 0.000 0.992 0.008 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3527 0.722116 0.008 0.808 0.000 0.000 0.052 0.132
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.2135 0.812255 0.000 0.000 0.128 0.872 0.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.3126 0.686202 0.000 0.000 0.000 0.000 0.248 0.752
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0260 0.863063 0.000 0.992 0.000 0.000 0.008 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3198 0.705168 0.740 0.000 0.000 0.000 0.000 0.260
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 6 0.2178 0.843184 0.000 0.000 0.000 0.000 0.132 0.868
#> 00F70D11-3B58-4517-82EC-258CCED34A60 6 0.3592 0.283236 0.344 0.000 0.000 0.000 0.000 0.656
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 5 0.2854 0.634766 0.000 0.208 0.000 0.000 0.792 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.2941 0.695375 0.000 0.780 0.000 0.000 0.220 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.0146 0.891266 0.000 0.000 0.000 0.000 0.004 0.996
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.2697 0.754867 0.000 0.000 0.812 0.188 0.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3244 0.650834 0.000 0.732 0.000 0.268 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3582 0.651544 0.000 0.768 0.000 0.000 0.036 0.196
#> 682C11E8-099C-466F-BC8A-B09A754205E3 5 0.3634 0.378795 0.000 0.356 0.000 0.000 0.644 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 3 0.3543 0.634068 0.272 0.000 0.720 0.004 0.004 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.1908 0.836450 0.000 0.000 0.004 0.900 0.096 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.1462 0.781113 0.936 0.056 0.000 0.000 0.000 0.008
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 6 0.3464 0.389902 0.312 0.000 0.000 0.000 0.000 0.688
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1141 0.852751 0.000 0.948 0.000 0.052 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2346 0.809193 0.000 0.868 0.000 0.124 0.008 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 5 0.0146 0.785505 0.000 0.004 0.000 0.000 0.996 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.3076 0.721451 0.760 0.000 0.000 0.000 0.000 0.240
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 6 0.1501 0.830933 0.076 0.000 0.000 0.000 0.000 0.924
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.3833 0.187296 0.000 0.000 0.444 0.556 0.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 5 0.3390 0.507809 0.000 0.296 0.000 0.000 0.704 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 5 0.0692 0.782914 0.000 0.020 0.000 0.000 0.976 0.004
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.3607 0.594210 0.652 0.000 0.000 0.000 0.000 0.348
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.3851 0.131937 0.000 0.000 0.460 0.540 0.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1327 0.804856 0.936 0.000 0.000 0.000 0.000 0.064
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.1267 0.805383 0.940 0.000 0.000 0.000 0.000 0.060
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0146 0.864229 0.000 0.996 0.000 0.004 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.3833 0.208598 0.000 0.000 0.556 0.444 0.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.3175 0.708557 0.744 0.000 0.000 0.000 0.000 0.256
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 5 0.0146 0.785505 0.000 0.004 0.000 0.000 0.996 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.3536 0.563438 0.736 0.008 0.000 0.252 0.004 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.863485 0.000 1.000 0.000 0.000 0.000 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 6 0.3782 0.307037 0.000 0.000 0.000 0.000 0.412 0.588
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 5 0.3586 0.569242 0.000 0.012 0.000 0.000 0.720 0.268
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.3838 0.405775 0.552 0.000 0.000 0.000 0.000 0.448
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.3843 0.396158 0.548 0.000 0.000 0.000 0.000 0.452
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 6 0.1204 0.898700 0.000 0.000 0.000 0.000 0.056 0.944
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.1007 0.898711 0.000 0.000 0.000 0.000 0.044 0.956
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 6 0.0000 0.889815 0.000 0.000 0.000 0.000 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1204 0.842754 0.000 0.944 0.000 0.000 0.056 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 5 0.2996 0.609511 0.000 0.228 0.000 0.000 0.772 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 4 0.1219 0.872504 0.000 0.048 0.000 0.948 0.004 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.2706 0.757037 0.000 0.832 0.000 0.008 0.160 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.1327 0.804856 0.936 0.000 0.000 0.000 0.000 0.064
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0146 0.864433 0.000 0.996 0.000 0.004 0.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.2164 0.796829 0.900 0.032 0.000 0.000 0.000 0.068
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.1701 0.838630 0.000 0.920 0.000 0.072 0.008 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0363 0.860038 0.000 0.988 0.000 0.000 0.000 0.012
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.1141 0.897826 0.000 0.000 0.948 0.052 0.000 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 5 0.4141 0.242781 0.000 0.012 0.000 0.000 0.556 0.432
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.0790 0.897832 0.000 0.000 0.000 0.000 0.032 0.968
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0146 0.804320 0.996 0.000 0.000 0.000 0.004 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 4 0.3841 0.292766 0.000 0.380 0.000 0.616 0.004 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0146 0.804320 0.996 0.000 0.000 0.000 0.004 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.863485 0.000 1.000 0.000 0.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 6 0.1500 0.895605 0.000 0.000 0.012 0.000 0.052 0.936
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 6 0.1267 0.897828 0.000 0.000 0.000 0.000 0.060 0.940
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.3634 0.582997 0.644 0.000 0.000 0.000 0.000 0.356
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0937 0.852208 0.000 0.960 0.000 0.000 0.040 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 6 0.1075 0.898820 0.000 0.000 0.000 0.000 0.048 0.952
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 5 0.1501 0.747747 0.000 0.076 0.000 0.000 0.924 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0146 0.804320 0.996 0.000 0.000 0.000 0.004 0.000
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0632 0.861639 0.000 0.976 0.000 0.024 0.000 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 5 0.0260 0.787682 0.000 0.000 0.000 0.000 0.992 0.008
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.805296 1.000 0.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 4 0.1814 0.820667 0.000 0.100 0.000 0.900 0.000 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 3 0.3979 0.165003 0.000 0.000 0.540 0.456 0.004 0.000
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 5 0.3864 0.089090 0.000 0.000 0.000 0.000 0.520 0.480
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 6 0.0146 0.887962 0.004 0.000 0.000 0.000 0.000 0.996
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 6 0.1387 0.894761 0.000 0.000 0.000 0.000 0.068 0.932
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.2883 0.739253 0.788 0.000 0.000 0.000 0.000 0.212
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.3868 0.271908 0.504 0.000 0.000 0.000 0.000 0.496
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 5 0.0146 0.786777 0.000 0.000 0.000 0.000 0.996 0.004
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.2416 0.767432 0.000 0.844 0.000 0.000 0.156 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 3 0.1285 0.900433 0.052 0.000 0.944 0.000 0.004 0.000
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.3838 0.405775 0.552 0.000 0.000 0.000 0.000 0.448
#> AF0426B7-7A31-4943-973A-05114783DB32 6 0.2826 0.827617 0.000 0.000 0.092 0.000 0.052 0.856
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0146 0.804320 0.996 0.000 0.000 0.000 0.004 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 6 0.1204 0.898700 0.000 0.000 0.000 0.000 0.056 0.944
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 6 0.1204 0.897964 0.000 0.000 0.000 0.000 0.056 0.944
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
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#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.805296 1.000 0.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.2778 0.768370 0.000 0.824 0.000 0.168 0.008 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.2070 0.824344 0.000 0.892 0.000 0.100 0.008 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 5 0.1327 0.753698 0.000 0.064 0.000 0.000 0.936 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.4222 0.645776 0.000 0.728 0.000 0.000 0.184 0.088
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.1663 0.865312 0.000 0.000 0.912 0.088 0.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 6 0.0790 0.898062 0.000 0.000 0.000 0.000 0.032 0.968
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.3993 -0.033815 0.520 0.000 0.476 0.000 0.004 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 4 0.5411 0.477541 0.256 0.000 0.152 0.588 0.004 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.3868 -0.048963 0.000 0.508 0.000 0.000 0.492 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.1267 0.805441 0.940 0.000 0.000 0.000 0.000 0.060
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 6 0.0000 0.889815 0.000 0.000 0.000 0.000 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.863485 0.000 1.000 0.000 0.000 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.1267 0.897828 0.000 0.000 0.000 0.000 0.060 0.940
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 6 0.1219 0.863906 0.004 0.048 0.000 0.000 0.000 0.948
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 4 0.3482 0.460507 0.000 0.316 0.000 0.684 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.3189 0.696377 0.004 0.760 0.000 0.236 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 4 0.0146 0.911675 0.000 0.000 0.000 0.996 0.004 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 4 0.1196 0.878197 0.000 0.040 0.000 0.952 0.008 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.0858 0.917544 0.028 0.000 0.968 0.000 0.004 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 6 0.5063 -0.179096 0.432 0.064 0.000 0.000 0.004 0.500
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.2980 0.739883 0.000 0.808 0.000 0.000 0.180 0.012
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 6 0.1204 0.897964 0.000 0.000 0.000 0.000 0.056 0.944
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0458 0.859833 0.000 0.984 0.000 0.000 0.016 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 5 0.3810 0.258767 0.000 0.000 0.000 0.000 0.572 0.428
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.1327 0.896419 0.000 0.000 0.000 0.000 0.064 0.936
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 5 0.1267 0.755571 0.000 0.060 0.000 0.000 0.940 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.3999 -0.101911 0.500 0.000 0.496 0.000 0.004 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.3823 0.213635 0.000 0.000 0.436 0.564 0.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 5 0.0458 0.781059 0.000 0.016 0.000 0.000 0.984 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.3468 0.670550 0.000 0.728 0.000 0.264 0.008 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.5226 0.068039 0.464 0.444 0.000 0.000 0.000 0.092
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.2135 0.789992 0.000 0.872 0.000 0.000 0.128 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.3617 0.598978 0.000 0.736 0.000 0.000 0.020 0.244
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 6 0.1267 0.897337 0.000 0.000 0.000 0.000 0.060 0.940
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 6 0.0363 0.883389 0.012 0.000 0.000 0.000 0.000 0.988
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 6 0.0865 0.867255 0.036 0.000 0.000 0.000 0.000 0.964
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 4 0.5175 0.562934 0.176 0.000 0.184 0.636 0.004 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.1267 0.897828 0.000 0.000 0.000 0.000 0.060 0.940
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 5 0.2416 0.697414 0.000 0.000 0.156 0.000 0.844 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 6 0.1995 0.873045 0.000 0.052 0.000 0.000 0.036 0.912
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1765 0.857661 0.000 0.000 0.904 0.096 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 5 0.1663 0.739390 0.000 0.088 0.000 0.000 0.912 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 6 0.2572 0.779455 0.000 0.136 0.000 0.000 0.012 0.852
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0146 0.804320 0.996 0.000 0.000 0.000 0.004 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 1 0.3944 0.363207 0.568 0.004 0.000 0.000 0.000 0.428
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 6 0.2867 0.820991 0.000 0.112 0.000 0.000 0.040 0.848
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.2454 0.775868 0.000 0.000 0.160 0.840 0.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.0000 0.913692 0.000 0.000 0.000 1.000 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.0146 0.911274 0.000 0.000 0.000 0.996 0.004 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.4444 0.413660 0.536 0.028 0.000 0.000 0.000 0.436
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 5 0.0363 0.788292 0.000 0.000 0.000 0.000 0.988 0.012
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.0000 0.889815 0.000 0.000 0.000 0.000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.3868 0.010363 0.000 0.000 0.504 0.496 0.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.1075 0.898820 0.000 0.000 0.000 0.000 0.048 0.952
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 5 0.3833 0.216788 0.000 0.000 0.000 0.000 0.556 0.444
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.805296 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.1204 0.898700 0.000 0.000 0.000 0.000 0.056 0.944
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.0146 0.887962 0.004 0.000 0.000 0.000 0.000 0.996
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.2219 0.839356 0.000 0.000 0.000 0.000 0.136 0.864
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.863485 0.000 1.000 0.000 0.000 0.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.0000 0.936790 0.000 0.000 1.000 0.000 0.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 6 0.0632 0.876208 0.024 0.000 0.000 0.000 0.000 0.976
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.1204 0.898359 0.000 0.000 0.000 0.000 0.056 0.944
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 17581 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 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 0.661 0.875 0.937 0.4822 0.517 0.517
#> 3 3 0.611 0.680 0.811 0.2466 0.728 0.534
#> 4 4 0.555 0.604 0.806 0.1403 0.672 0.363
#> 5 5 0.618 0.573 0.797 0.0878 0.793 0.472
#> 6 6 0.629 0.503 0.702 0.0629 0.922 0.729
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 1 0.0000 0.9787 1.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.0000 0.9787 1.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 1 0.0000 0.9787 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 1 0.0000 0.9787 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.0000 0.9000 0.000 1.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.9000 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.9000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.9787 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 1 0.0000 0.9787 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.9787 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.9000 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.0000 0.9787 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 1 0.0000 0.9787 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9000 0.000 1.000
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.0000 0.9787 1.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9000 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.0000 0.9000 0.000 1.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.0000 0.9787 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9000 0.000 1.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.0376 0.9747 0.996 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.9988 0.2846 0.480 0.520
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0000 0.9000 0.000 1.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.5408 0.8489 0.124 0.876
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.0000 0.9787 1.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.9000 0.000 1.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.0000 0.9787 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.7745 0.7729 0.228 0.772
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9000 0.000 1.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.0000 0.9000 0.000 1.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9000 0.000 1.000
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#> 2356B998-0930-403F-9B04-57A18A150955 2 0.7745 0.7729 0.228 0.772
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 2 0.0000 0.9000 0.000 1.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 2 0.8661 0.6887 0.288 0.712
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 1 0.0000 0.9787 1.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.9983 0.2965 0.476 0.524
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 1 0.0376 0.9747 0.996 0.004
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 2 0.0000 0.9000 0.000 1.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.5629 0.8449 0.132 0.868
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.9896 0.3979 0.440 0.560
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 1 0.0000 0.9787 1.000 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 1 0.0000 0.9787 1.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.7745 0.7729 0.228 0.772
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9000 0.000 1.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 1 0.0000 0.9787 1.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9000 0.000 1.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.2236 0.9403 0.964 0.036
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9787 1.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.7745 0.7729 0.228 0.772
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 2 0.0000 0.9000 0.000 1.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.0000 0.9000 0.000 1.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.7745 0.7729 0.228 0.772
#> E6901976-2075-463C-828D-8DF924EFC78E 1 0.0000 0.9787 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 1 0.0000 0.9787 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.0000 0.9000 0.000 1.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.0000 0.9000 0.000 1.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 1 0.0000 0.9787 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 1 0.0000 0.9787 1.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.0376 0.9747 0.996 0.004
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 1 0.0000 0.9787 1.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 1 0.0000 0.9787 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 1 0.0000 0.9787 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 1 0.0000 0.9787 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 1 0.0000 0.9787 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.0000 0.9787 1.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.0000 0.9000 0.000 1.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9000 0.000 1.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.0000 0.9000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.5059 0.8546 0.112 0.888
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9000 0.000 1.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.0000 0.9000 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 1 0.0000 0.9787 1.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.7376 0.7925 0.208 0.792
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 1 0.0000 0.9787 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.2778 0.9264 0.952 0.048
#> D021A258-8713-4383-9DCA-45E2F54A0411 1 0.0000 0.9787 1.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.6887 0.8128 0.184 0.816
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.9996 0.2582 0.488 0.512
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.0000 0.9000 0.000 1.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0000 0.9000 0.000 1.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 1 0.0000 0.9787 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0000 0.9000 0.000 1.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.0000 0.9000 0.000 1.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 1 0.0000 0.9787 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 2 0.0000 0.9000 0.000 1.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 1 0.0000 0.9787 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 1 0.0000 0.9787 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 2 0.0000 0.9000 0.000 1.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 1 0.0000 0.9787 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9787 1.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.0000 0.9000 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 1 0.0000 0.9787 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 1 0.0000 0.9787 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.7139 0.8035 0.196 0.804
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.0000 0.9000 0.000 1.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 1 0.0000 0.9787 1.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.7745 0.7729 0.228 0.772
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0000 0.9000 0.000 1.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.6801 0.8159 0.180 0.820
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.6343 0.8297 0.160 0.840
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 1 0.0000 0.9787 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.9000 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.0000 0.9787 1.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 1 0.0000 0.9787 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 1 0.0000 0.9787 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.0000 0.9000 0.000 1.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.0000 0.9000 0.000 1.000
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.0000 0.9000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.0000 0.9787 1.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 1 0.0000 0.9787 1.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.9000 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9000 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.6148 0.8345 0.152 0.848
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.9000 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.0000 0.9000 0.000 1.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.0000 0.9000 0.000 1.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.6343 0.8297 0.160 0.840
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.9896 0.3979 0.440 0.560
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.0000 0.9000 0.000 1.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0000 0.9000 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 3 0.0000 0.7759 0.000 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 3 0.0000 0.7759 0.000 0.000 1.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 3 0.0000 0.7759 0.000 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 3 0.0000 0.7759 0.000 0.000 1.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.6180 0.4624 0.416 0.584 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.0000 0.9466 1.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.9466 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.6180 0.6337 0.000 0.416 0.584
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 3 0.0000 0.7759 0.000 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.6180 0.6337 0.000 0.416 0.584
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.9466 1.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 3 0.0000 0.7759 0.000 0.000 1.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.6180 0.7168 0.000 0.584 0.416
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.6180 0.4624 0.416 0.584 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 3 0.0000 0.7759 0.000 0.000 1.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.6180 0.4624 0.416 0.584 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9466 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 3 0.0000 0.7759 0.000 0.000 1.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.6180 0.4624 0.416 0.584 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.6180 0.7168 0.000 0.584 0.416
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.6180 0.7168 0.000 0.584 0.416
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.6180 0.4624 0.416 0.584 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.8421 0.6925 0.116 0.584 0.300
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 3 0.0000 0.7759 0.000 0.000 1.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.0000 0.9466 1.000 0.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 3 0.0000 0.7759 0.000 0.000 1.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.6180 0.7168 0.000 0.584 0.416
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.6180 0.4624 0.416 0.584 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9466 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.0000 0.9466 1.000 0.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9466 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.6180 0.7168 0.000 0.584 0.416
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.6180 0.4624 0.416 0.584 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.0000 0.9466 1.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.5178 0.7109 0.000 0.256 0.744
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.6180 0.7168 0.000 0.584 0.416
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 3 0.0000 0.7759 0.000 0.000 1.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.6180 0.4624 0.416 0.584 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.6180 0.4624 0.416 0.584 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 3 0.0000 0.7759 0.000 0.000 1.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.6180 0.7168 0.000 0.584 0.416
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.6180 0.7168 0.000 0.584 0.416
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.6180 0.4624 0.416 0.584 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.6180 0.6337 0.000 0.416 0.584
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.6180 0.7168 0.000 0.584 0.416
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.6309 0.5848 0.000 0.504 0.496
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.6180 0.7168 0.000 0.584 0.416
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.5058 0.5756 0.756 0.244 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9466 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.6180 0.6337 0.000 0.416 0.584
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.6180 0.6337 0.000 0.416 0.584
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.0000 0.9466 1.000 0.000 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 3 0.0000 0.7759 0.000 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.6180 0.7168 0.000 0.584 0.416
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.6180 0.7168 0.000 0.584 0.416
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.6180 0.6337 0.000 0.416 0.584
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9466 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.6180 0.6337 0.000 0.416 0.584
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.5968 0.2509 0.636 0.364 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.6180 0.4624 0.416 0.584 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.6180 0.7168 0.000 0.584 0.416
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.1411 0.7670 0.000 0.036 0.964
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.4974 0.5928 0.764 0.236 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.6180 0.7168 0.000 0.584 0.416
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.6180 0.7168 0.000 0.584 0.416
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 3 0.0000 0.7759 0.000 0.000 1.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.6180 0.7168 0.000 0.584 0.416
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.6180 0.4624 0.416 0.584 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.6180 0.4624 0.416 0.584 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.6180 0.4624 0.416 0.584 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9466 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.7379 0.4996 0.376 0.584 0.040
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9466 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 1 0.0000 0.9466 1.000 0.000 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.0000 0.9466 1.000 0.000 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.6180 0.4624 0.416 0.584 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.6540 0.7156 0.008 0.584 0.408
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.6180 0.7168 0.000 0.584 0.416
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.6180 0.7168 0.000 0.584 0.416
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.6180 0.7168 0.000 0.584 0.416
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.6204 0.4454 0.424 0.576 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 1 0.0000 0.9466 1.000 0.000 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.6180 0.6337 0.000 0.416 0.584
#> 10F2C028-06C5-4560-9A52-DD76A227B891 3 0.0000 0.7759 0.000 0.000 1.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.7759 0.000 0.000 1.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.6180 0.7168 0.000 0.584 0.416
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.7379 0.7089 0.040 0.584 0.376
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.6180 0.7168 0.000 0.584 0.416
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.6180 0.7168 0.000 0.584 0.416
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.6180 0.6337 0.000 0.416 0.584
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#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.6302 0.6155 0.000 0.520 0.480
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.6180 0.7168 0.000 0.584 0.416
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 3 0.0000 0.7759 0.000 0.000 1.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.6180 0.7168 0.000 0.584 0.416
#> 29635F4D-3149-49BC-B960-FF863D10F747 3 0.6140 -0.3443 0.000 0.404 0.596
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.6180 0.6337 0.000 0.416 0.584
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.6180 0.6337 0.000 0.416 0.584
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.6180 0.6337 0.000 0.416 0.584
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.6180 0.4624 0.416 0.584 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.6180 0.4624 0.416 0.584 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.9466 1.000 0.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.8226 0.6966 0.096 0.584 0.320
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.6180 0.4624 0.416 0.584 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.0000 0.9466 1.000 0.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 3 0.0000 0.7759 0.000 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.6180 0.7168 0.000 0.584 0.416
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 3 0.0000 0.7759 0.000 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 3 0.4555 0.4120 0.000 0.200 0.800
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.6180 0.6337 0.000 0.416 0.584
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.6180 0.7168 0.000 0.584 0.416
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.6180 0.7168 0.000 0.584 0.416
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.6180 0.4624 0.416 0.584 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.6180 0.4624 0.416 0.584 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 3 0.0000 0.7759 0.000 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.6180 0.4624 0.416 0.584 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.9466 1.000 0.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 3 0.0000 0.7759 0.000 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9466 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 3 0.0000 0.7759 0.000 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.6180 0.6337 0.000 0.416 0.584
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9466 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.6180 0.6337 0.000 0.416 0.584
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 3 0.0000 0.7759 0.000 0.000 1.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0000 0.9466 1.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 3 0.0000 0.7759 0.000 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 3 0.0000 0.7759 0.000 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6180 0.7168 0.000 0.584 0.416
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.6305 -0.2047 0.516 0.484 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.6180 0.6337 0.000 0.416 0.584
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.6180 0.7168 0.000 0.584 0.416
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6180 0.4624 0.416 0.584 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.6180 0.7168 0.000 0.584 0.416
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.6180 0.7168 0.000 0.584 0.416
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 3 0.0000 0.7759 0.000 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.6180 0.4624 0.416 0.584 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 3 0.0424 0.7740 0.000 0.008 0.992
#> 534B9E41-B731-4461-ABEA-30096148A493 3 0.0000 0.7759 0.000 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.6180 0.7168 0.000 0.584 0.416
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6180 0.4624 0.416 0.584 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.6180 0.4624 0.416 0.584 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9466 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.0000 0.7759 0.000 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.0000 0.7759 0.000 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.9466 1.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.6180 0.4624 0.416 0.584 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.6386 0.7163 0.004 0.584 0.412
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0000 0.9466 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.9466 1.000 0.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9466 1.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.6180 0.7168 0.000 0.584 0.416
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6180 0.7168 0.000 0.584 0.416
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9466 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9466 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3837 0.69231 0.000 0.776 0.224 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 4 0.4877 0.32548 0.408 0.000 0.000 0.592
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.3873 0.68884 0.000 0.772 0.228 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.0817 0.68801 0.000 0.024 0.000 0.976
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.4961 -0.09508 0.552 0.000 0.000 0.448
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.4999 -0.08279 0.000 0.508 0.000 0.492
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.4164 0.64963 0.000 0.736 0.264 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.3172 0.65739 0.000 0.160 0.000 0.840
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 4 0.4967 0.24729 0.452 0.000 0.000 0.548
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.4500 0.04441 0.316 0.000 0.000 0.684
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0336 0.57005 0.992 0.000 0.000 0.008
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.3649 0.63001 0.000 0.204 0.000 0.796
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.3907 0.66570 0.000 0.232 0.768 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.3873 0.68884 0.000 0.772 0.228 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.5000 -0.17921 0.000 0.504 0.000 0.496
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.3764 0.69883 0.000 0.784 0.216 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3172 0.67864 0.000 0.840 0.000 0.160
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.4776 0.41859 0.000 0.624 0.000 0.376
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.2996 0.75980 0.000 0.892 0.064 0.044
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.4382 0.48113 0.000 0.704 0.000 0.296
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 4 0.4877 0.32548 0.408 0.000 0.000 0.592
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.1118 0.56227 0.964 0.000 0.000 0.036
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4804 0.28650 0.000 0.616 0.000 0.384
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.4961 -0.09510 0.552 0.000 0.000 0.448
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 4 0.4898 0.31320 0.416 0.000 0.000 0.584
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.2760 0.65525 0.000 0.128 0.000 0.872
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> C8D64135-1B75-428A-8C75-351D32009EAC 3 0.4994 -0.08450 0.000 0.480 0.520 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 4 0.4933 0.30082 0.432 0.000 0.000 0.568
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.2868 0.70539 0.000 0.864 0.000 0.136
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.2647 0.74784 0.000 0.880 0.000 0.120
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.4843 0.25449 0.000 0.604 0.000 0.396
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.3266 0.47773 0.832 0.000 0.000 0.168
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.4008 0.59589 0.000 0.244 0.000 0.756
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.1302 0.55926 0.956 0.000 0.000 0.044
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.4843 0.25449 0.000 0.604 0.000 0.396
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.4981 0.19374 0.000 0.536 0.000 0.464
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 4 0.4877 0.32548 0.408 0.000 0.000 0.592
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.4477 0.59898 0.000 0.688 0.312 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4776 0.30686 0.000 0.624 0.000 0.376
#> 21821B38-6786-4078-9918-EC0E877C1533 4 0.4998 -0.05746 0.000 0.488 0.000 0.512
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.4967 0.20526 0.000 0.548 0.000 0.452
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.1118 0.90104 0.000 0.036 0.964 0.000
#> 8865E079-D8AB-406C-8886-C854F1A26201 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> DBFA1780-4558-436A-A434-05DAFD0F675A 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.7608 -0.00928 0.408 0.392 0.000 0.200
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.4426 0.71657 0.000 0.772 0.204 0.024
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 2 0.7517 0.21457 0.304 0.484 0.000 0.212
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 325F0A64-2E43-473F-B946-D328BF79BE69 4 0.3074 0.57574 0.152 0.000 0.000 0.848
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.5000 -0.19245 0.504 0.000 0.000 0.496
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 4 0.3649 0.63001 0.000 0.204 0.000 0.796
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 4 0.4955 -0.34965 0.444 0.000 0.000 0.556
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#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.0336 0.68063 0.008 0.000 0.000 0.992
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1389 0.76350 0.000 0.952 0.000 0.048
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.1474 0.76321 0.000 0.948 0.000 0.052
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.4989 -0.40415 0.472 0.000 0.000 0.528
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 4 0.2647 0.66027 0.000 0.120 0.000 0.880
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.2500 0.76218 0.000 0.916 0.040 0.044
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4322 0.73968 0.000 0.804 0.152 0.044
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.91031 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0707 0.90447 0.000 0.020 0.980 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.1211 0.88409 0.040 0.000 0.960 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.0817 0.68836 0.000 0.024 0.000 0.976
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.3486 0.64121 0.000 0.188 0.000 0.812
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.4989 -0.00473 0.000 0.528 0.000 0.472
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.4643 0.53040 0.000 0.656 0.344 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.3219 0.67409 0.000 0.836 0.000 0.164
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 2 0.5727 0.50845 0.236 0.688 0.000 0.076
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.4817 0.27613 0.000 0.612 0.000 0.388
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.2760 0.65525 0.000 0.128 0.000 0.872
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.3975 0.59237 0.000 0.240 0.000 0.760
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.3873 0.68884 0.000 0.772 0.228 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.3400 0.64654 0.000 0.180 0.000 0.820
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.1635 0.63832 0.044 0.008 0.000 0.948
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0188 0.57060 0.996 0.000 0.000 0.004
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3873 0.68884 0.000 0.772 0.228 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.57091 1.000 0.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.4985 0.19691 0.000 0.532 0.000 0.468
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.2466 0.67118 0.028 0.056 0.000 0.916
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1302 0.89879 0.000 0.044 0.956 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.7589 -0.20725 0.408 0.196 0.000 0.396
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4989 0.18571 0.000 0.528 0.000 0.472
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.3873 0.68884 0.000 0.772 0.228 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.3649 0.63001 0.000 0.204 0.000 0.796
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4804 0.45076 0.000 0.616 0.384 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.4431 0.59577 0.000 0.696 0.304 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1302 0.76367 0.000 0.956 0.000 0.044
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.0336 0.68568 0.000 0.008 0.000 0.992
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.1940 0.57655 0.924 0.000 0.000 0.076
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3649 0.70815 0.000 0.796 0.204 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.2081 0.67872 0.000 0.084 0.000 0.916
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 4 0.5856 0.32347 0.408 0.036 0.000 0.556
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.4877 0.54830 0.592 0.000 0.000 0.408
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.3801 0.54818 0.780 0.000 0.000 0.220
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.4972 0.48765 0.544 0.000 0.000 0.456
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4843 0.25449 0.000 0.604 0.000 0.396
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.1792 0.76124 0.000 0.932 0.000 0.068
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0921 0.56564 0.972 0.000 0.000 0.028
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.4877 0.54830 0.592 0.000 0.000 0.408
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0963 0.662308 0.964 0.000 0.000 0.036 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.921445 0.000 0.000 1.000 0.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.2852 0.478434 0.172 0.000 0.000 0.828 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3730 0.436872 0.288 0.000 0.000 0.712 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.5752 0.268534 0.620 0.000 0.000 0.208 0.172
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.4161 0.327233 0.392 0.000 0.000 0.608 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.1792 0.811413 0.000 0.916 0.000 0.084 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.2773 0.480518 0.164 0.000 0.000 0.836 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 4 0.3774 0.427518 0.000 0.296 0.000 0.704 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.0566 0.845656 0.012 0.984 0.004 0.000 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 5 0.2690 0.685502 0.000 0.000 0.000 0.156 0.844
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1544 0.519534 0.068 0.000 0.000 0.932 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0880 0.662650 0.968 0.000 0.000 0.032 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.6204 0.022092 0.164 0.000 0.000 0.524 0.312
#> 00F70D11-3B58-4517-82EC-258CCED34A60 5 0.5985 0.370828 0.408 0.000 0.000 0.112 0.480
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.0404 0.531133 0.000 0.012 0.000 0.988 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 5 0.2690 0.685502 0.000 0.000 0.000 0.156 0.844
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.4232 0.576836 0.012 0.312 0.676 0.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.4723 0.176674 0.016 0.536 0.000 0.448 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0566 0.845656 0.012 0.984 0.004 0.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.3816 0.395114 0.304 0.000 0.000 0.696 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.3684 0.416449 0.000 0.280 0.000 0.720 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.3333 0.668202 0.208 0.788 0.004 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.5778 0.258772 0.096 0.376 0.000 0.528 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 4 0.6125 0.289552 0.136 0.364 0.000 0.500 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 4 0.3816 0.385444 0.304 0.000 0.000 0.696 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2930 0.736508 0.004 0.832 0.000 0.164 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1410 0.824871 0.000 0.940 0.000 0.060 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.4074 0.302880 0.000 0.364 0.000 0.636 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0609 0.662575 0.980 0.000 0.000 0.020 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 5 0.6095 0.348242 0.416 0.000 0.000 0.124 0.460
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0566 0.920603 0.012 0.004 0.984 0.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.1732 0.907379 0.000 0.080 0.920 0.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.4587 0.506149 0.096 0.160 0.000 0.744 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.5810 0.275052 0.604 0.000 0.000 0.244 0.152
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.1732 0.907379 0.000 0.080 0.920 0.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0404 0.662001 0.988 0.000 0.000 0.012 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 4 0.3395 0.418378 0.236 0.000 0.000 0.764 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3480 0.630400 0.000 0.752 0.000 0.248 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4482 0.353080 0.012 0.612 0.376 0.000 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.3086 0.568383 0.816 0.000 0.000 0.180 0.004
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.4256 0.125303 0.000 0.436 0.000 0.564 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.6171 0.311253 0.240 0.556 0.000 0.204 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 4 0.4587 0.506377 0.096 0.160 0.000 0.744 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.3730 0.400705 0.288 0.000 0.000 0.712 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2852 0.478434 0.172 0.000 0.000 0.828 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.2773 0.480518 0.164 0.000 0.000 0.836 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.6166 0.100100 0.556 0.000 0.000 0.200 0.244
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.1469 0.538683 0.016 0.036 0.000 0.948 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 5 0.6099 0.335420 0.424 0.000 0.000 0.124 0.452
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.4161 0.327233 0.392 0.000 0.000 0.608 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 4 0.2890 0.529527 0.004 0.160 0.000 0.836 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.5408 0.470944 0.180 0.156 0.000 0.664 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0510 0.661809 0.984 0.000 0.000 0.016 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.1043 0.920615 0.000 0.040 0.960 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
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#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 4 0.6630 0.247876 0.220 0.376 0.000 0.404 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 4 0.4294 0.030321 0.000 0.468 0.000 0.532 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 5 0.5798 0.449800 0.156 0.000 0.000 0.236 0.608
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 4 0.5798 0.437746 0.236 0.156 0.000 0.608 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.1341 0.826653 0.000 0.944 0.000 0.056 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.1043 0.920615 0.000 0.040 0.960 0.000 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.2852 0.478434 0.172 0.000 0.000 0.828 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0290 0.847025 0.008 0.992 0.000 0.000 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.1671 0.816577 0.000 0.924 0.000 0.076 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.1121 0.527902 0.044 0.000 0.000 0.956 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.5232 0.082017 0.044 0.500 0.000 0.456 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 4 0.4235 0.259421 0.424 0.000 0.000 0.576 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.1908 0.619634 0.908 0.000 0.000 0.092 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.2813 0.641628 0.832 0.000 0.000 0.168 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 1 0.5967 0.103939 0.456 0.000 0.000 0.436 0.108
#> 2356B998-0930-403F-9B04-57A18A150955 4 0.4807 0.111631 0.020 0.448 0.000 0.532 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.4035 0.522066 0.784 0.000 0.000 0.156 0.060
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.1626 0.874778 0.044 0.000 0.940 0.016 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.3707 0.450945 0.716 0.000 0.000 0.284 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.2732 0.646042 0.840 0.000 0.000 0.160 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4731 0.154169 0.016 0.528 0.000 0.456 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0162 0.847227 0.004 0.996 0.000 0.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.2773 0.480518 0.164 0.000 0.000 0.836 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.3395 0.418378 0.236 0.000 0.000 0.764 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.5148 0.241395 0.432 0.528 0.000 0.040 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.3039 0.679858 0.192 0.808 0.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.4291 0.170319 0.000 0.536 0.000 0.464 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0510 0.661809 0.984 0.000 0.000 0.016 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.4307 0.037859 0.500 0.000 0.000 0.500 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.5403 0.048620 0.056 0.488 0.000 0.456 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.921445 0.000 0.000 1.000 0.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 5 0.5619 0.488020 0.156 0.000 0.000 0.208 0.636
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 4 0.3480 0.414230 0.248 0.000 0.000 0.752 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.921445 0.000 0.000 1.000 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1671 0.816656 0.000 0.924 0.000 0.076 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.1197 0.829893 0.000 0.952 0.000 0.048 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.921445 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.2329 0.865129 0.000 0.124 0.876 0.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.3366 0.714594 0.212 0.004 0.784 0.000 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 4 0.3534 0.428780 0.256 0.000 0.000 0.744 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.0510 0.528715 0.016 0.000 0.000 0.984 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 4 0.3966 0.360214 0.000 0.336 0.000 0.664 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.2852 0.478434 0.172 0.000 0.000 0.828 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0566 0.845656 0.012 0.984 0.004 0.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.4242 0.147963 0.000 0.428 0.000 0.572 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.4379 0.502627 0.740 0.220 0.008 0.032 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.1732 0.907379 0.000 0.080 0.920 0.000 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.3730 0.445718 0.000 0.288 0.000 0.712 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4283 0.191965 0.000 0.544 0.000 0.456 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 4 0.3274 0.424350 0.220 0.000 0.000 0.780 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 4 0.4768 0.472843 0.096 0.180 0.000 0.724 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.0794 0.525892 0.028 0.000 0.000 0.972 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.4927 0.321671 0.296 0.000 0.000 0.652 0.052
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 5 0.6085 0.365944 0.404 0.000 0.000 0.124 0.472
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 5 0.4182 0.436520 0.400 0.000 0.000 0.000 0.600
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.2130 0.902691 0.012 0.080 0.908 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.0290 0.847025 0.008 0.992 0.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0404 0.846639 0.012 0.988 0.000 0.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.5831 0.437324 0.236 0.160 0.000 0.604 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.3132 0.473553 0.172 0.000 0.000 0.820 0.008
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1732 0.907379 0.000 0.080 0.920 0.000 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4273 0.089463 0.000 0.448 0.000 0.552 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.3774 0.392546 0.296 0.000 0.000 0.704 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.2813 0.641628 0.832 0.000 0.000 0.168 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 4 0.5798 0.437746 0.236 0.156 0.000 0.608 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0566 0.845656 0.012 0.984 0.004 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.0000 0.529260 0.000 0.000 0.000 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.2997 0.740231 0.012 0.840 0.148 0.000 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0807 0.842581 0.012 0.976 0.012 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1732 0.814168 0.000 0.920 0.000 0.080 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 4 0.4161 0.327233 0.392 0.000 0.000 0.608 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3774 0.392546 0.296 0.000 0.000 0.704 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.847220 0.000 1.000 0.000 0.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 5 0.0290 0.747892 0.000 0.000 0.000 0.008 0.992
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.2852 0.478434 0.172 0.000 0.000 0.828 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.1410 0.671625 0.940 0.000 0.000 0.060 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.6416 0.325574 0.372 0.000 0.000 0.176 0.452
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 5 0.4734 0.421934 0.024 0.000 0.000 0.372 0.604
#> BD879832-E177-4FCA-B1EA-D1553518E700 4 0.4587 0.506262 0.096 0.160 0.000 0.744 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.5761 0.154357 0.088 0.420 0.000 0.492 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 5 0.6099 0.335420 0.424 0.000 0.000 0.124 0.452
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 5 0.0000 0.749476 0.000 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 4 0.0713 0.67816 0.000 0.000 0.000 0.972 0.028 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 4 0.2300 0.64995 0.000 0.000 0.000 0.856 0.144 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 4 0.3578 0.57152 0.000 0.000 0.000 0.660 0.340 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.3756 0.51208 0.000 0.000 0.000 0.600 0.400 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.3819 0.28121 0.700 0.020 0.000 0.000 0.280 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0547 0.86612 0.000 0.000 0.980 0.000 0.020 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 4 0.3578 0.57152 0.000 0.000 0.000 0.660 0.340 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.3320 0.79448 0.000 0.000 0.772 0.016 0.212 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.2454 0.64367 0.000 0.000 0.000 0.840 0.160 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 4 0.3088 0.64602 0.000 0.020 0.000 0.808 0.172 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.4707 0.54934 0.204 0.676 0.000 0.000 0.120 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3101 0.58412 0.000 0.000 0.000 0.756 0.244 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.5454 0.54131 0.292 0.552 0.000 0.000 0.156 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2282 0.62214 0.888 0.024 0.000 0.000 0.000 0.088
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.0000 0.67632 0.000 0.000 0.000 1.000 0.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.5982 0.48049 0.288 0.444 0.000 0.000 0.268 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.0547 0.67334 0.000 0.020 0.000 0.980 0.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.0632 0.67269 0.000 0.024 0.000 0.976 0.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.2562 0.53884 0.172 0.828 0.000 0.000 0.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3426 0.28067 0.004 0.720 0.000 0.276 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3617 0.57140 0.000 0.000 0.020 0.736 0.244 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.2647 0.76425 0.044 0.088 0.000 0.000 0.000 0.868
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.0865 0.67534 0.000 0.000 0.000 0.964 0.036 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.3867 0.26951 0.000 0.488 0.000 0.512 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.1663 0.54864 0.088 0.912 0.000 0.000 0.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0713 0.57361 0.972 0.000 0.000 0.000 0.028 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.6494 0.45463 0.180 0.556 0.000 0.000 0.104 0.160
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.3244 0.57681 0.732 0.000 0.000 0.000 0.000 0.268
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.3854 0.30031 0.000 0.464 0.000 0.536 0.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0858 0.51974 0.004 0.968 0.000 0.028 0.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.1663 0.79652 0.000 0.088 0.000 0.000 0.000 0.912
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.5738 0.40807 0.000 0.000 0.516 0.240 0.244 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 4 0.3782 0.38366 0.000 0.412 0.000 0.588 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.4131 0.51727 0.000 0.000 0.020 0.624 0.356 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.4526 0.54423 0.164 0.704 0.000 0.000 0.132 0.000
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#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.4766 0.51593 0.204 0.704 0.000 0.000 0.040 0.052
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.2163 0.86227 0.000 0.000 0.892 0.016 0.092 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3866 0.26648 0.000 0.484 0.000 0.516 0.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.5324 0.53765 0.172 0.592 0.000 0.000 0.236 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 5 0.5223 0.14009 0.436 0.092 0.000 0.000 0.472 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.6718 0.45779 0.144 0.480 0.000 0.088 0.288 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.4289 0.46491 0.000 0.000 0.020 0.556 0.424 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0146 0.53331 0.004 0.996 0.000 0.000 0.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.4215 0.54273 0.000 0.000 0.056 0.700 0.244 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.4361 0.46132 0.000 0.000 0.024 0.552 0.424 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.3156 0.64157 0.000 0.020 0.000 0.800 0.180 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5971 0.47639 0.264 0.448 0.000 0.000 0.288 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.5464 0.52190 0.204 0.572 0.000 0.000 0.224 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.0000 0.67632 0.000 0.000 0.000 1.000 0.000 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.0146 0.67624 0.000 0.004 0.000 0.996 0.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.0146 0.84950 0.000 0.004 0.000 0.000 0.000 0.996
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.4707 0.54934 0.204 0.676 0.000 0.000 0.120 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.4152 0.26608 0.664 0.032 0.000 0.000 0.304 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.5655 0.43897 0.548 0.180 0.000 0.000 0.004 0.268
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.6287 0.05381 0.064 0.384 0.000 0.000 0.096 0.456
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.4575 0.43443 0.100 0.756 0.000 0.080 0.064 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.4584 0.27049 0.000 0.404 0.000 0.556 0.040 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.3076 0.60092 0.760 0.000 0.000 0.000 0.000 0.240
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.0000 0.85131 0.000 0.000 0.000 0.000 0.000 1.000
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 17581 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 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 0.424 0.789 0.892 0.4179 0.591 0.591
#> 3 3 0.812 0.898 0.953 0.2084 0.582 0.449
#> 4 4 0.672 0.721 0.865 0.2624 0.798 0.615
#> 5 5 0.561 0.592 0.807 0.1254 0.813 0.535
#> 6 6 0.608 0.595 0.755 0.0569 0.921 0.742
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
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.8842 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6343 0.8146 0.160 0.840
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.8842 0.000 1.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4431 0.8207 0.092 0.908
#> A03BDA91-0936-4C67-9508-4903F84C980F 2 0.6343 0.8146 0.160 0.840
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.0000 0.8842 0.000 1.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.0000 0.8842 0.000 1.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 1 0.0000 0.8246 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.8842 0.000 1.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 1 0.0000 0.8246 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.0000 0.8842 0.000 1.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 1 0.9922 0.4600 0.552 0.448
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.1843 0.8722 0.028 0.972
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 1.0000 -0.3031 0.496 0.504
#> 46563983-2B05-4EB7-9E15-07487565158F 1 0.6973 0.8229 0.812 0.188
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.8842 0.000 1.000
#> 2437A516-5312-409E-8679-B85BB60530CD 2 0.6343 0.8146 0.160 0.840
#> F9135D0D-6447-4452-8EA8-98DEE4610226 1 0.6973 0.8229 0.812 0.188
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.2603 0.8615 0.044 0.956
#> A0A07F44-C51B-420C-92E8-65F464DB0442 1 0.6973 0.8229 0.812 0.188
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.9983 -0.2335 0.476 0.524
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.9129 0.6996 0.672 0.328
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.8842 0.000 1.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 1 0.6887 0.8227 0.816 0.184
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.4815 0.8086 0.104 0.896
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 1 0.8713 0.7458 0.708 0.292
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.1843 0.8731 0.028 0.972
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.9933 -0.1353 0.452 0.548
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 2 0.6343 0.8146 0.160 0.840
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.1843 0.8729 0.028 0.972
#> 00F70D11-3B58-4517-82EC-258CCED34A60 2 0.6343 0.8146 0.160 0.840
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 1 0.9427 0.6495 0.640 0.360
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.8842 0.000 1.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.0000 0.8842 0.000 1.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 1 0.0000 0.8246 1.000 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.8842 0.000 1.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 1 0.6973 0.8229 0.812 0.188
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.8842 0.000 1.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0938 0.8804 0.012 0.988
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.6343 0.8146 0.160 0.840
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 1 0.6973 0.8229 0.812 0.188
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.6343 0.8146 0.160 0.840
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.0000 0.8842 0.000 1.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 1 0.0000 0.8246 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.8842 0.000 1.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4562 0.8178 0.096 0.904
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.8016 0.7902 0.756 0.244
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 2 0.6343 0.8146 0.160 0.840
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 2 0.6343 0.8146 0.160 0.840
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 1 0.0000 0.8246 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 1 0.0000 0.8246 1.000 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.3114 0.8525 0.056 0.944
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.8842 0.000 1.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.9286 0.3093 0.344 0.656
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 1 0.9970 0.4118 0.532 0.468
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 1 0.0000 0.8246 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 2 0.6343 0.8146 0.160 0.840
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 1 0.0000 0.8246 1.000 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 2 0.6343 0.8146 0.160 0.840
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.2043 0.8756 0.032 0.968
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.8842 0.000 1.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.8267 0.7256 0.260 0.740
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 2 0.6343 0.8146 0.160 0.840
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.9983 -0.2319 0.476 0.524
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.5737 0.8275 0.136 0.864
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0672 0.8818 0.008 0.992
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0000 0.8842 0.000 1.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.5519 0.7751 0.128 0.872
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.9866 0.5000 0.568 0.432
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.8842 0.000 1.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 2 0.6343 0.8146 0.160 0.840
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 1 0.8555 0.7572 0.720 0.280
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 2 0.6343 0.8146 0.160 0.840
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.0000 0.8842 0.000 1.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.0000 0.8842 0.000 1.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.0000 0.8842 0.000 1.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.8842 0.000 1.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.8661 0.4707 0.288 0.712
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.2236 0.8675 0.036 0.964
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.6343 0.7306 0.160 0.840
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 2 0.6343 0.8146 0.160 0.840
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.0000 0.8842 0.000 1.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 1 0.0000 0.8246 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 1 0.9775 0.5481 0.588 0.412
#> EB9FCAC4-2937-46BC-A560-E506412F8966 1 0.0000 0.8246 1.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.2236 0.8674 0.036 0.964
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.0000 0.8842 0.000 1.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.8842 0.000 1.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.8842 0.000 1.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 1 0.7299 0.6813 0.796 0.204
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0376 0.8831 0.004 0.996
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.0000 0.8842 0.000 1.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 2 0.6343 0.8146 0.160 0.840
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3114 0.8539 0.056 0.944
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 2 0.6343 0.8146 0.160 0.840
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.8842 0.000 1.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 1 0.0000 0.8246 1.000 0.000
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.0000 0.8842 0.000 1.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 1 0.0000 0.8246 1.000 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 2 0.6343 0.8146 0.160 0.840
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0938 0.8804 0.012 0.988
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.0376 0.8833 0.004 0.996
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 1 0.0000 0.8246 1.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.9358 0.2797 0.352 0.648
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#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0000 0.8842 0.000 1.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 1 0.6343 0.8189 0.840 0.160
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.8842 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.1184 0.8785 0.016 0.984
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.2423 0.8726 0.040 0.960
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.6973 0.8229 0.812 0.188
#> D182D919-C57F-4004-93DB-FB1723A82072 2 0.5946 0.8234 0.144 0.856
#> A52CC981-4203-4027-B978-383BFBEB5F75 1 0.6973 0.8229 0.812 0.188
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 1 0.6887 0.8239 0.816 0.184
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.0000 0.8842 0.000 1.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.8842 0.000 1.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.6343 0.8146 0.160 0.840
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.0000 0.8842 0.000 1.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 2 0.6438 0.8129 0.164 0.836
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.7056 0.8217 0.808 0.192
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.8842 0.000 1.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.9996 -0.1561 0.488 0.512
#> C90142D8-F939-4FEA-BC48-073D2814F54E 2 0.6343 0.8146 0.160 0.840
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.2778 0.8589 0.048 0.952
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1163 0.9437 0.028 0.972 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.2165 0.8504 0.936 0.064 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1163 0.9437 0.028 0.972 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9524 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9372 1.000 0.000 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 2 0.3482 0.8596 0.128 0.872 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 2 0.4291 0.8128 0.180 0.820 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9099 0.000 0.000 1.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1860 0.9306 0.052 0.948 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.1031 0.9047 0.000 0.024 0.976
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 2 0.3619 0.8522 0.136 0.864 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.0000 0.9524 0.000 1.000 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9524 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 2 0.0000 0.9524 0.000 1.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.1031 0.9383 0.000 0.976 0.024
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.0000 0.9524 0.000 1.000 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.9372 1.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9524 0.000 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 2 0.0000 0.9524 0.000 1.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 2 0.0000 0.9524 0.000 1.000 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9524 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 2 0.0000 0.9524 0.000 1.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.3482 0.8694 0.128 0.872 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2261 0.9002 0.000 0.932 0.068
#> B013FB96-A517-46EC-8877-4AE84C01AE27 2 0.0000 0.9524 0.000 1.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9524 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9524 0.000 1.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 2 0.0000 0.9524 0.000 1.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0000 0.9372 1.000 0.000 0.000
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 2 0.0000 0.9524 0.000 1.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.0000 0.9372 1.000 0.000 0.000
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9524 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.0000 0.9524 0.000 1.000 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 2 0.4555 0.7956 0.200 0.800 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.6180 0.2992 0.000 0.416 0.584
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1163 0.9437 0.028 0.972 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0424 0.9484 0.000 0.992 0.008
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1031 0.9453 0.024 0.976 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.0000 0.9524 0.000 1.000 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1031 0.9175 0.976 0.000 0.024
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9524 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.4931 0.5725 0.768 0.232 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.4346 0.8150 0.184 0.816 0.000
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.1031 0.9047 0.000 0.024 0.976
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1411 0.9399 0.036 0.964 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.1031 0.9453 0.024 0.976 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 2 0.0000 0.9524 0.000 1.000 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0000 0.9372 1.000 0.000 0.000
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.0000 0.9372 1.000 0.000 0.000
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9099 0.000 0.000 1.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 3 0.3619 0.7893 0.000 0.136 0.864
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 2 0.0747 0.9467 0.016 0.984 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0424 0.9504 0.008 0.992 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9524 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.0000 0.9524 0.000 1.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.1031 0.9047 0.000 0.024 0.976
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0000 0.9372 1.000 0.000 0.000
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 3 0.2537 0.8543 0.000 0.080 0.920
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.9372 1.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5835 0.5654 0.340 0.660 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1163 0.9437 0.028 0.972 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 1 0.8259 0.4646 0.632 0.216 0.152
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0000 0.9372 1.000 0.000 0.000
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 2 0.0000 0.9524 0.000 1.000 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.6111 0.2860 0.604 0.396 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.1163 0.9437 0.028 0.972 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0892 0.9467 0.020 0.980 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 2 0.0000 0.9524 0.000 1.000 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 2 0.0000 0.9524 0.000 1.000 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.0000 0.9524 0.000 1.000 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0000 0.9372 1.000 0.000 0.000
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 2 0.0000 0.9524 0.000 1.000 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.0000 0.9372 1.000 0.000 0.000
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 2 0.4178 0.8179 0.172 0.828 0.000
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 2 0.4346 0.8101 0.184 0.816 0.000
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4062 0.8355 0.164 0.836 0.000
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1163 0.9437 0.028 0.972 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.0000 0.9524 0.000 1.000 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9524 0.000 1.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.0000 0.9524 0.000 1.000 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0000 0.9372 1.000 0.000 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 2 0.3941 0.8346 0.156 0.844 0.000
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0237 0.9100 0.000 0.004 0.996
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9524 0.000 1.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 2 0.6045 0.3386 0.000 0.620 0.380
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0000 0.9524 0.000 1.000 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.4504 0.8003 0.196 0.804 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0000 0.9524 0.000 1.000 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1163 0.9437 0.028 0.972 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 3 0.6168 0.2823 0.412 0.000 0.588
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.0000 0.9524 0.000 1.000 0.000
#> DBFA1780-4558-436A-A434-05DAFD0F675A 2 0.4452 0.8026 0.192 0.808 0.000
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.9372 1.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.0892 0.9466 0.020 0.980 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.9372 1.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1163 0.9437 0.028 0.972 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.3816 0.7842 0.000 0.148 0.852
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 2 0.4178 0.8197 0.172 0.828 0.000
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0000 0.9099 0.000 0.000 1.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.0000 0.9372 1.000 0.000 0.000
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.0000 0.9524 0.000 1.000 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 2 0.1289 0.9377 0.032 0.968 0.000
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0237 0.9100 0.000 0.004 0.996
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 2 0.0000 0.9524 0.000 1.000 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.0424 0.9310 0.992 0.000 0.008
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.0892 0.9467 0.020 0.980 0.000
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 2 0.0000 0.9524 0.000 1.000 0.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.9372 1.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.0892 0.9466 0.020 0.980 0.000
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.1860 0.8948 0.948 0.000 0.052
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 2 0.0000 0.9524 0.000 1.000 0.000
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 2 0.4887 0.7592 0.228 0.772 0.000
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 2 0.0000 0.9524 0.000 1.000 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.0000 0.9524 0.000 1.000 0.000
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 2 0.1163 0.9405 0.028 0.972 0.000
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0000 0.9372 1.000 0.000 0.000
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.0000 0.9372 1.000 0.000 0.000
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 2 0.0000 0.9524 0.000 1.000 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1163 0.9437 0.028 0.972 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.3879 0.7766 0.848 0.000 0.152
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.0000 0.9372 1.000 0.000 0.000
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.3816 0.7842 0.000 0.148 0.852
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.9372 1.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0237 0.9100 0.000 0.004 0.996
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 2 0.4235 0.8153 0.176 0.824 0.000
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.0000 0.9524 0.000 1.000 0.000
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 2 0.0000 0.9524 0.000 1.000 0.000
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.1163 0.9437 0.028 0.972 0.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.1163 0.9437 0.028 0.972 0.000
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0000 0.9099 0.000 0.000 1.000
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.1031 0.9047 0.000 0.024 0.976
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.0000 0.9524 0.000 1.000 0.000
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 2 0.0000 0.9524 0.000 1.000 0.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 2 0.0000 0.9524 0.000 1.000 0.000
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 2 0.1163 0.9404 0.028 0.972 0.000
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.9372 1.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0000 0.9099 0.000 0.000 1.000
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.9372 1.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 2 0.0000 0.9524 0.000 1.000 0.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 2 0.0000 0.9524 0.000 1.000 0.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.1163 0.9138 0.972 0.000 0.028
#> 15C85716-4BE3-43A8-9F61-2929C600C828 1 0.7517 0.3283 0.588 0.364 0.048
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.6008 0.4919 0.372 0.628 0.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.4002 0.8395 0.160 0.840 0.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 2 0.0000 0.9524 0.000 1.000 0.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 2 0.0000 0.9524 0.000 1.000 0.000
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 2 0.0000 0.9524 0.000 1.000 0.000
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.5016 0.6646 0.000 0.240 0.760
#> 679EE059-DDD9-4138-9973-51A583941B71 1 0.0237 0.9329 0.996 0.004 0.000
#> 05CD67DF-CFB3-40D8-A787-3D09886291EA 1 0.0000 0.9372 1.000 0.000 0.000
#> D92AEF7C-FA39-4D0A-B003-9067A7F2D14A 1 0.0000 0.9372 1.000 0.000 0.000
#> F8571DD8-DB9D-448A-AA30-01D56EE892EF 2 0.0000 0.9524 0.000 1.000 0.000
#> 29C63350-F03B-4C65-979C-53AE84E20042 2 0.0000 0.9524 0.000 1.000 0.000
#> FCA0DB35-708A-45A5-8F18-CC0B0A123F42 2 0.0000 0.9524 0.000 1.000 0.000
#> 09CEF733-7623-44A0-816E-5668D0D8EDAE 2 0.1031 0.9452 0.024 0.976 0.000
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#> 795D478D-E1FE-49EB-92AD-8B1B145F944B 2 0.0000 0.9524 0.000 1.000 0.000
#> 6203B63E-6D3F-4399-B524-9573A9BD1E11 2 0.4555 0.7956 0.200 0.800 0.000
#> BDD03456-777B-4E94-8240-CD6B1D4EAC51 2 0.1163 0.9437 0.028 0.972 0.000
#> DE32121C-B7F5-4A94-9977-8F4B2D3BE976 2 0.0000 0.9524 0.000 1.000 0.000
#> 27C0EEBE-589F-41D9-8BF7-C7DA0ED87A3B 2 0.4062 0.8355 0.164 0.836 0.000
#> EE24DCB8-2927-42D4-AD8C-588EA01A64C7 2 0.0000 0.9524 0.000 1.000 0.000
#> A86D241D-FE25-40B7-A61C-B919D30FA545 2 0.0000 0.9524 0.000 1.000 0.000
#> 50A7A07E-B452-466D-97BF-978C4F9C47DA 2 0.0000 0.9524 0.000 1.000 0.000
#> 0E6AE036-64ED-4489-AE40-55F77089A890 2 0.0000 0.9524 0.000 1.000 0.000
#> BC9A5294-255F-47A4-8879-11C441093A3D 2 0.0000 0.9524 0.000 1.000 0.000
#> 658F68D0-AE74-4D23-9A8C-146E9A53FC77 2 0.0000 0.9524 0.000 1.000 0.000
#> 1EF1159E-DDAA-4673-8115-D8F356E51FF8 2 0.1163 0.9437 0.028 0.972 0.000
#> 596736FB-5FB7-446A-B8CA-53F0129F41CF 2 0.2066 0.9256 0.060 0.940 0.000
#> 97765ED1-5E02-49D3-A96B-A20C8CCA3BEE 1 0.4974 0.5674 0.764 0.236 0.000
#> 3508F4B0-1ADA-4937-B924-424AC2596341 2 0.0000 0.9524 0.000 1.000 0.000
#> 13EF5323-EAD9-4BC7-8AC4-33875BF12E17 2 0.0000 0.9524 0.000 1.000 0.000
#> A1F8A4CA-7598-498B-9BC4-95A1B6111ACE 1 0.0000 0.9372 1.000 0.000 0.000
#> 10D5BC48-F79A-4487-B5D0-2D6C98A9F4DD 1 0.0000 0.9372 1.000 0.000 0.000
#> 75F1E6B3-B296-49AE-B065-B4E39A986790 2 0.2625 0.9073 0.084 0.916 0.000
#> 0AC5F4B6-C269-4DAC-9F84-8DDCB5227823 1 0.0237 0.9342 0.996 0.000 0.004
#> D66124FE-E1C5-4D3B-8C95-CFB2E013E924 3 0.0000 0.9099 0.000 0.000 1.000
#> CF1267F2-A3E9-446A-AE7F-9C8B9FD67CA5 3 0.6956 0.5161 0.300 0.040 0.660
#> 6A193B2E-EA8D-4CBE-8EAE-B2486E65C920 1 0.0000 0.9372 1.000 0.000 0.000
#> CAC793EE-A0FC-4FAD-88B4-593205694EC0 2 0.0000 0.9524 0.000 1.000 0.000
#> A5572139-03CA-4299-98B6-13A2945649D0 3 0.0000 0.9099 0.000 0.000 1.000
#> 00F5F2E4-2971-46E4-AE00-35FE31AF4E59 2 0.0000 0.9524 0.000 1.000 0.000
#> CEC3C875-A8E8-434F-8DE4-7C0627D1B074 2 0.0000 0.9524 0.000 1.000 0.000
#> 85380A2D-9951-4D4B-A2A4-6F5F2AFC54E3 2 0.0000 0.9524 0.000 1.000 0.000
#> 992A7083-28CE-4857-898E-9D4B4FBF2FA1 2 0.0000 0.9524 0.000 1.000 0.000
#> 6EAF8148-9EF1-4172-A7FE-B9FE7D747796 2 0.0000 0.9524 0.000 1.000 0.000
#> DCD932D2-B708-487A-93C1-8485FBE9048A 2 0.0237 0.9505 0.000 0.996 0.004
#> 8731F05E-B6AF-4930-97DD-6C933DC91361 2 0.2448 0.9136 0.076 0.924 0.000
#> E6281A02-850B-405E-AF4D-E79967552F0A 1 0.0000 0.9372 1.000 0.000 0.000
#> E2CFC7B2-7C64-4776-BFB8-9682F745078B 1 0.0000 0.9372 1.000 0.000 0.000
#> 8607F343-5C54-4112-A8C3-EC1F0A48F4F4 2 0.1163 0.9437 0.028 0.972 0.000
#> AE43FF42-0266-4CD1-8C27-C3A2DB9C4F55 1 0.2261 0.8442 0.932 0.068 0.000
#> 0C5866D5-41E9-4A62-A84E-5AD63879E249 2 0.0000 0.9524 0.000 1.000 0.000
#> 7FAE9EBB-0821-4077-ABBC-BCFE3B139C9D 2 0.0000 0.9524 0.000 1.000 0.000
#> 8782807A-E8EE-4469-AFEE-966224F6FDD4 1 0.0000 0.9372 1.000 0.000 0.000
#> 4411941F-9A7C-4BFF-86F3-26C959ED849B 2 0.0000 0.9524 0.000 1.000 0.000
#> 65CD49C8-F7D4-403C-9DCD-3A2AC936DD10 3 0.0000 0.9099 0.000 0.000 1.000
#> BF0969AB-4A2E-4890-A215-3A636E6E7731 2 0.5138 0.7238 0.252 0.748 0.000
#> E09CD286-229E-4DCA-9B8C-CA2340AE1FE5 2 0.4504 0.8003 0.196 0.804 0.000
#> E0F3FE37-09BD-4BE1-8CA9-EA1870F6F1B0 2 0.0000 0.9524 0.000 1.000 0.000
#> D925CAC2-BBC5-4160-9DC7-898C3FB28BE3 3 0.0747 0.9079 0.000 0.016 0.984
#> EC9F355E-90FA-42DE-A35E-EC6A2D5EA1BE 2 0.0000 0.9524 0.000 1.000 0.000
#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.0000 0.9524 0.000 1.000 0.000
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.0000 0.9372 1.000 0.000 0.000
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.0892 0.9064 0.000 0.020 0.980
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 2 0.0892 0.9467 0.020 0.980 0.000
#> C6F4EF8F-353C-463E-8069-FDEACF556176 2 0.0000 0.9524 0.000 1.000 0.000
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 1 0.5465 0.5740 0.712 0.000 0.288
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.1411 0.9399 0.036 0.964 0.000
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 2 0.0000 0.9524 0.000 1.000 0.000
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.0000 0.9524 0.000 1.000 0.000
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.9372 1.000 0.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.9372 1.000 0.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.1964 0.9277 0.056 0.944 0.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.1163 0.9437 0.028 0.972 0.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 2 0.3619 0.8553 0.136 0.864 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.5706 0.4319 0.680 0.320 0.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.9524 0.000 1.000 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.1163 0.9437 0.028 0.972 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0747 0.9079 0.000 0.016 0.984
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 2 0.0000 0.9524 0.000 1.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.1163 0.9437 0.028 0.972 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0592 0.9493 0.012 0.988 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 2 0.0000 0.9524 0.000 1.000 0.000
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.9524 0.000 1.000 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.9524 0.000 1.000 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.2448 0.8502 0.000 0.076 0.924
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.5138 0.7237 0.252 0.748 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.9372 1.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 2 0.4121 0.8222 0.168 0.832 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0237 0.9514 0.004 0.996 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.9524 0.000 1.000 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.9372 1.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.6252 0.2990 0.444 0.556 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.9524 0.000 1.000 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.9372 1.000 0.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0000 0.9099 0.000 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.9524 0.000 1.000 0.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.9524 0.000 1.000 0.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.1964 0.9276 0.056 0.944 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0000 0.9372 1.000 0.000 0.000
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9372 1.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.9524 0.000 1.000 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.1163 0.9437 0.028 0.972 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.1163 0.9437 0.028 0.972 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.9524 0.000 1.000 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.0000 0.9524 0.000 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.7603 0.5583 0.096 0.236 0.668
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.0000 0.9524 0.000 1.000 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.1031 0.9175 0.976 0.000 0.024
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0000 0.9372 1.000 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9524 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.9372 1.000 0.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4504 0.8003 0.196 0.804 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1163 0.9437 0.028 0.972 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9524 0.000 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9099 0.000 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 2 0.3619 0.8571 0.136 0.864 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.3412 0.8737 0.124 0.876 0.000
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9099 0.000 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1163 0.9437 0.028 0.972 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.1163 0.9437 0.028 0.972 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.1163 0.9437 0.028 0.972 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0592 0.9494 0.012 0.988 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9524 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9099 0.000 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.4178 0.7556 0.000 0.172 0.828
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.3879 0.7766 0.848 0.000 0.152
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.4504 0.8003 0.196 0.804 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.0000 0.9524 0.000 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 2 0.1031 0.9381 0.000 0.976 0.024
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.0000 0.9524 0.000 1.000 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 2 0.0000 0.9524 0.000 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 2 0.4178 0.8197 0.172 0.828 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.5678 0.5057 0.000 0.684 0.316
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9524 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9524 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.1163 0.9138 0.972 0.000 0.028
#> D021A258-8713-4383-9DCA-45E2F54A0411 3 0.3551 0.7945 0.000 0.132 0.868
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.9524 0.000 1.000 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9524 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.4062 0.8355 0.164 0.836 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1031 0.9452 0.024 0.976 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9524 0.000 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.2261 0.9194 0.068 0.932 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 2 0.0000 0.9524 0.000 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0747 0.9479 0.016 0.984 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.9372 1.000 0.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9524 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.1031 0.9047 0.000 0.024 0.976
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.9372 1.000 0.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1031 0.9047 0.000 0.024 0.976
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.0000 0.9372 1.000 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 2 0.3879 0.8401 0.152 0.848 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9524 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9524 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.9524 0.000 1.000 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.3816 0.8455 0.148 0.852 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.1031 0.9047 0.000 0.024 0.976
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.9524 0.000 1.000 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.4121 0.8314 0.168 0.832 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.9372 1.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.5706 0.6044 0.320 0.680 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9524 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.3116 0.8870 0.108 0.892 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4842 0.6906 0.000 0.776 0.224
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1163 0.9437 0.028 0.972 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9524 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6235 0.3244 0.436 0.564 0.000
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 2 0.0000 0.9524 0.000 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.2448 0.8325 0.924 0.076 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.1529 0.9256 0.000 0.960 0.040
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.9524 0.000 1.000 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 2 0.2356 0.9091 0.072 0.928 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 2 0.0000 0.9524 0.000 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9372 1.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 2 0.4178 0.8197 0.172 0.828 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.1529 0.8887 0.960 0.040 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 2 0.0000 0.9524 0.000 1.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0000 0.9524 0.000 1.000 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.9524 0.000 1.000 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9372 1.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 2 0.0892 0.9447 0.020 0.980 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1211 0.8500 0.000 0.960 0.000 0.040
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.6074 0.3841 0.600 0.340 0.000 0.060
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0921 0.8554 0.000 0.972 0.000 0.028
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0188 0.8598 0.000 0.996 0.000 0.004
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0000 0.9091 1.000 0.000 0.000 0.000
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#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.9091 1.000 0.000 0.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.3105 0.6326 0.004 0.140 0.000 0.856
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0290 0.7699 0.000 0.992 0.000 0.008 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.6766 0.0020 0.412 0.452 0.000 0.060 0.076
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0404 0.7720 0.000 0.988 0.000 0.012 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0880 0.8768 0.968 0.000 0.000 0.000 0.032
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.5002 0.1687 0.000 0.160 0.000 0.708 0.132
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 5 0.4590 0.7643 0.000 0.012 0.000 0.420 0.568
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.2329 0.8600 0.000 0.000 0.876 0.000 0.124
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0898 0.7745 0.008 0.972 0.000 0.020 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0290 0.9107 0.000 0.000 0.992 0.008 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.4152 -0.1369 0.000 0.012 0.000 0.692 0.296
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4420 0.2025 0.000 0.448 0.000 0.548 0.004
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.3013 0.7518 0.000 0.832 0.000 0.160 0.008
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0703 0.5338 0.000 0.024 0.000 0.976 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.3934 0.5862 0.000 0.244 0.016 0.740 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.3999 0.3334 0.000 0.344 0.000 0.656 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1965 0.8641 0.904 0.000 0.000 0.000 0.096
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.3774 0.5235 0.000 0.296 0.000 0.704 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.1106 0.5333 0.000 0.024 0.000 0.964 0.012
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.1908 0.5817 0.000 0.092 0.000 0.908 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.4302 0.0155 0.000 0.520 0.000 0.480 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.1082 0.5386 0.000 0.028 0.000 0.964 0.008
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3970 0.5915 0.000 0.236 0.020 0.744 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0290 0.4985 0.000 0.000 0.000 0.992 0.008
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.4060 0.4166 0.000 0.360 0.000 0.640 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.3013 0.7518 0.000 0.832 0.000 0.160 0.008
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.1478 0.5696 0.000 0.064 0.000 0.936 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2516 0.8504 0.860 0.000 0.000 0.000 0.140
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0671 0.5240 0.000 0.016 0.000 0.980 0.004
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.3932 0.7145 0.672 0.000 0.000 0.000 0.328
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.4045 0.4377 0.000 0.356 0.000 0.644 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.3013 0.7518 0.000 0.832 0.000 0.160 0.008
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.7669 -0.4182 0.064 0.228 0.000 0.424 0.284
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.5330 0.5594 0.000 0.168 0.064 0.720 0.048
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.3988 0.5777 0.000 0.252 0.016 0.732 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3053 0.7489 0.000 0.828 0.000 0.164 0.008
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.0609 0.8731 0.980 0.000 0.000 0.000 0.020
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2929 0.5988 0.000 0.180 0.000 0.820 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.5003 0.2138 0.572 0.400 0.000 0.016 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.5800 0.3867 0.048 0.664 0.000 0.220 0.068
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0510 0.9036 0.000 0.000 0.984 0.016 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1544 0.5714 0.000 0.068 0.000 0.932 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0609 0.8785 0.980 0.000 0.000 0.000 0.020
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2471 0.8499 0.864 0.000 0.000 0.000 0.136
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2439 0.8358 0.000 0.000 0.876 0.004 0.120
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.7430 0.3031 0.000 0.140 0.260 0.504 0.096
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.3910 -0.0290 0.000 0.008 0.000 0.720 0.272
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0955 0.7752 0.000 0.968 0.000 0.028 0.004
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.4448 0.1183 0.000 0.480 0.000 0.516 0.004
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.3039 0.5989 0.000 0.192 0.000 0.808 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9157 0.000 0.000 1.000 0.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2424 0.8517 0.868 0.000 0.000 0.000 0.132
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.7593 0.2870 0.000 0.136 0.252 0.492 0.120
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5269 0.4718 0.224 0.688 0.000 0.072 0.016
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 4 0.8764 0.0750 0.156 0.276 0.016 0.332 0.220
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1851 0.8665 0.912 0.000 0.000 0.000 0.088
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.3452 0.5943 0.000 0.244 0.000 0.756 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.4333 0.5456 0.212 0.740 0.000 0.048 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.1638 0.7769 0.000 0.932 0.000 0.064 0.004
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1043 0.7774 0.000 0.960 0.000 0.040 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.1341 0.5637 0.000 0.056 0.000 0.944 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.0963 0.5479 0.000 0.036 0.000 0.964 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 2 0.4151 0.5150 0.000 0.652 0.000 0.344 0.004
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2424 0.8517 0.868 0.000 0.000 0.000 0.132
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.1197 0.5587 0.000 0.048 0.000 0.952 0.000
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2424 0.8517 0.868 0.000 0.000 0.000 0.132
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 5 0.4590 0.7643 0.000 0.012 0.000 0.420 0.568
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 5 0.4590 0.7643 0.000 0.012 0.000 0.420 0.568
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.5452 0.4755 0.080 0.704 0.000 0.180 0.036
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4227 0.2896 0.000 0.420 0.000 0.580 0.000
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.3013 0.7518 0.000 0.832 0.000 0.160 0.008
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.4443 0.0455 0.000 0.524 0.000 0.472 0.004
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0162 0.8793 0.996 0.000 0.000 0.000 0.004
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.4644 -0.6031 0.000 0.012 0.000 0.528 0.460
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9157 0.000 0.000 1.000 0.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.4249 0.1982 0.000 0.568 0.000 0.432 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.5394 0.4798 0.000 0.064 0.116 0.732 0.088
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.3607 0.6588 0.000 0.752 0.000 0.244 0.004
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.3169 0.6788 0.084 0.856 0.000 0.060 0.000
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.2971 0.7538 0.000 0.836 0.000 0.156 0.008
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 4 0.9639 -0.2152 0.116 0.128 0.220 0.280 0.256
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.4288 0.4396 0.000 0.612 0.000 0.384 0.004
#> DBFA1780-4558-436A-A434-05DAFD0F675A 4 0.7233 -0.4551 0.052 0.156 0.000 0.468 0.324
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.0000 0.7707 0.000 1.000 0.000 0.000 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.4632 0.5165 0.000 0.000 0.540 0.012 0.448
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 5 0.4627 0.7372 0.000 0.012 0.000 0.444 0.544
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.0794 0.9137 0.000 0.000 0.972 0.000 0.028
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.1965 0.8641 0.904 0.000 0.000 0.000 0.096
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.3013 0.7518 0.000 0.832 0.000 0.160 0.008
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 4 0.2462 0.3813 0.000 0.008 0.000 0.880 0.112
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0000 0.9157 0.000 0.000 1.000 0.000 0.000
#> 2F86D512-9177-45AC-B724-BBC31D83CDB7 4 0.4287 0.1877 0.000 0.460 0.000 0.540 0.000
#> 76AF5ABA-5A99-4C9B-8AC0-19F902FD887D 1 0.2471 0.8016 0.864 0.000 0.000 0.000 0.136
#> 29D55F13-D78D-45F1-8FDF-65733C69F1BC 2 0.1571 0.7772 0.000 0.936 0.000 0.060 0.004
#> 4FF799D9-202C-4F5A-BD58-495A23B3C39C 4 0.1121 0.5553 0.000 0.044 0.000 0.956 0.000
#> 45C2CEF7-58B5-4E76-ABF6-8B88088C6C82 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> F39FF3E3-0636-4949-A0A1-9B6163158BC6 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> B8042E2C-B5C3-42BC-9149-E56E952E5A56 1 0.7108 0.3282 0.572 0.152 0.000 0.104 0.172
#> 896A84A3-F8A2-44C6-B48A-DBF887F8F5AC 4 0.0566 0.5181 0.000 0.012 0.000 0.984 0.004
#> 48023DF3-770B-4C9E-9EBA-AC5586EDA57F 4 0.7945 0.0186 0.148 0.224 0.000 0.456 0.172
#> 7FF75F50-B61C-4230-96B0-F711FBC27834 4 0.1270 0.5618 0.000 0.052 0.000 0.948 0.000
#> B178A8CB-B28C-4FED-A8AE-D4E37AE39261 2 0.3093 0.7494 0.000 0.824 0.000 0.168 0.008
#> 89A77489-F3C1-438A-8A9F-9AFACCDC47E0 4 0.5565 0.1490 0.000 0.240 0.000 0.632 0.128
#> 7804F23A-10F9-4AC1-A0FA-B1370FC68C09 1 0.0162 0.8793 0.996 0.000 0.000 0.000 0.004
#> 9F992BE8-400E-4230-AC42-E5483B4A5F7F 1 0.2424 0.8517 0.868 0.000 0.000 0.000 0.132
#> BA3E03EF-663F-437A-BEED-897A2FD80DAF 4 0.2230 0.5646 0.000 0.116 0.000 0.884 0.000
#> BDB30060-C2CF-4C66-AB80-3DA009A1161F 2 0.1043 0.7755 0.000 0.960 0.000 0.040 0.000
#> 47DF52C0-562A-4163-8B56-69F09BE7DEC6 1 0.4466 0.6724 0.728 0.000 0.032 0.008 0.232
#> 9065DBEF-8BEA-4E06-A4E5-F4C422B47A56 1 0.2424 0.8517 0.868 0.000 0.000 0.000 0.132
#> AF0426B7-7A31-4943-973A-05114783DB32 3 0.4632 0.5165 0.000 0.000 0.540 0.012 0.448
#> 95598EDA-BA98-4C1D-951B-131E149989E1 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> A5FD7D09-E2A0-49D0-B976-8BEF7B0E38E5 3 0.0000 0.9157 0.000 0.000 1.000 0.000 0.000
#> 6F54F9C0-5687-4A07-BF75-B506752B4A52 5 0.4590 0.7643 0.000 0.012 0.000 0.420 0.568
#> 879F6C9B-B821-47D8-85F0-3965C0B16289 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> E65D0B66-B1D6-40E2-916E-990522AD7E7B 4 0.1386 0.5131 0.000 0.016 0.000 0.952 0.032
#> 4BB7A412-9471-41B0-8974-140D5A2C1750 2 0.1121 0.7780 0.000 0.956 0.000 0.044 0.000
#> 118B6525-67D8-4BF1-9B6B-6D22D52E06B6 2 0.3048 0.7407 0.000 0.820 0.000 0.176 0.004
#> A8099400-B1DC-471C-8C6A-95CEADB6869A 3 0.0794 0.9137 0.000 0.000 0.972 0.000 0.028
#> 6F0DF420-9BA6-48D7-91A0-7AA2CC5B5E80 3 0.6330 0.0639 0.000 0.000 0.472 0.364 0.164
#> C63B843A-E3B3-4714-A0A2-AB93DA5A4C67 2 0.2890 0.7528 0.000 0.836 0.000 0.160 0.004
#> 10FCDD7E-8103-423D-9B4D-85223D9DB75E 4 0.0880 0.5420 0.000 0.032 0.000 0.968 0.000
#> 766E0D2F-123B-474A-901C-F3CB25A92D95 4 0.0671 0.5240 0.000 0.016 0.000 0.980 0.004
#> 6985560F-33FE-435F-83E0-CBD9E0C20413 4 0.3885 -0.0364 0.000 0.008 0.000 0.724 0.268
#> 5B527FB2-9DE2-419A-9F62-989333449F6C 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> B422FFF3-623B-419A-964E-046BAE3578B3 3 0.0794 0.9137 0.000 0.000 0.972 0.000 0.028
#> 64D0958D-EF53-43EC-8167-390D957485C4 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> 64BA791A-C418-4507-BF64-B4B473C78834 4 0.4242 0.2640 0.000 0.428 0.000 0.572 0.000
#> 79641836-8684-4E1E-A8B1-935A6760CD6F 4 0.2561 0.5954 0.000 0.144 0.000 0.856 0.000
#> FAA284CF-ABD4-4405-B847-AD06672BF451 1 0.0671 0.8730 0.980 0.000 0.000 0.004 0.016
#> 15C85716-4BE3-43A8-9F61-2929C600C828 4 0.8773 0.1270 0.084 0.228 0.052 0.388 0.248
#> B1DF468D-306D-4483-87A2-F5022E0D31CD 2 0.2763 0.6602 0.148 0.848 0.000 0.004 0.000
#> AF27FD0A-108C-47D2-9F87-665BED408E99 2 0.1282 0.7520 0.004 0.952 0.000 0.044 0.000
#> A8D8311C-73C4-4806-A8CA-D275905FC1AE 4 0.4291 0.1777 0.000 0.464 0.000 0.536 0.000
#> A1EB28F4-2621-492D-9E0C-FDE3749D464A 4 0.4305 -0.0413 0.000 0.488 0.000 0.512 0.000
#> 8F30F0E6-CE60-480F-B69D-8CD9655BA6F2 4 0.4302 0.1129 0.000 0.480 0.000 0.520 0.000
#> 27E456AE-A15F-41E4-B595-BE55E11A4CE1 3 0.5818 0.3364 0.000 0.000 0.464 0.092 0.444
#> 679EE059-DDD9-4138-9973-51A583941B71 1 0.5072 0.6788 0.696 0.000 0.000 0.116 0.188
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#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.1168 0.7561 0.008 0.960 0.000 0.032 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.0794 0.7762 0.000 0.972 0.000 0.028 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.4622 0.2312 0.000 0.440 0.012 0.548 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.0451 0.7676 0.008 0.988 0.000 0.004 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.2130 0.4839 0.000 0.012 0.000 0.908 0.080
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.2516 0.8480 0.860 0.000 0.000 0.000 0.140
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.3013 0.7540 0.000 0.832 0.000 0.160 0.008
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0162 0.9137 0.000 0.000 0.996 0.004 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.3857 0.7305 0.688 0.000 0.000 0.000 0.312
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9157 0.000 0.000 1.000 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4065 0.6867 0.812 0.116 0.000 0.024 0.048
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.6711 -0.3874 0.004 0.216 0.000 0.444 0.336
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3013 0.7540 0.000 0.832 0.000 0.160 0.008
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.1608 0.5742 0.000 0.072 0.000 0.928 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.1270 0.7454 0.000 0.948 0.000 0.052 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.5544 0.5929 0.000 0.044 0.712 0.128 0.116
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3796 0.5198 0.000 0.300 0.000 0.700 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.0771 0.7652 0.004 0.976 0.000 0.020 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.6473 0.3666 0.224 0.612 0.000 0.100 0.064
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.4538 0.1284 0.000 0.540 0.008 0.452 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.0162 0.7704 0.000 0.996 0.000 0.004 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.4348 0.5885 0.000 0.216 0.032 0.744 0.008
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1386 0.7590 0.000 0.952 0.000 0.032 0.016
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.3053 0.7519 0.000 0.828 0.000 0.164 0.008
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5615 0.4126 0.260 0.648 0.000 0.068 0.024
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.1485 0.5222 0.000 0.020 0.000 0.948 0.032
#> D182D919-C57F-4004-93DB-FB1723A82072 5 0.4973 0.5943 0.092 0.004 0.000 0.192 0.712
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3909 0.5946 0.000 0.216 0.024 0.760 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.3628 0.5966 0.000 0.216 0.012 0.772 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.4590 -0.4924 0.000 0.012 0.000 0.568 0.420
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.4211 0.3186 0.000 0.360 0.000 0.636 0.004
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.8793 1.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.6835 -0.3349 0.004 0.276 0.000 0.428 0.292
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 5 0.6616 0.4173 0.200 0.000 0.052 0.148 0.600
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.0912 0.5144 0.000 0.012 0.000 0.972 0.016
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0162 0.7724 0.000 0.996 0.000 0.004 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.5170 0.4240 0.008 0.412 0.000 0.552 0.028
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2561 0.8469 0.856 0.000 0.000 0.000 0.144
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.4481 -0.4895 0.000 0.008 0.000 0.576 0.416
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.1398 0.65609 0.000 0.940 0.000 0.008 0.052 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.5607 -0.09214 0.496 0.408 0.000 0.000 0.052 0.044
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.1845 0.67224 0.000 0.920 0.000 0.028 0.052 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.4814 0.63060 0.000 0.644 0.000 0.256 0.100 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2201 0.83576 0.900 0.000 0.000 0.000 0.048 0.052
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.6298 0.45155 0.000 0.044 0.000 0.280 0.160 0.516
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.2257 0.75326 0.000 0.008 0.000 0.116 0.000 0.876
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.2402 0.87594 0.000 0.000 0.856 0.004 0.140 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.1053 0.67053 0.004 0.964 0.000 0.012 0.020 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.5800 0.41846 0.000 0.008 0.000 0.320 0.160 0.512
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.4209 0.21810 0.000 0.384 0.000 0.596 0.020 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4705 0.63320 0.000 0.652 0.000 0.260 0.088 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.3268 0.56451 0.000 0.008 0.000 0.808 0.164 0.020
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.4131 0.59849 0.000 0.168 0.020 0.760 0.052 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.4513 0.05565 0.000 0.396 0.000 0.572 0.004 0.028
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.2882 0.59299 0.000 0.180 0.000 0.812 0.008 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.3176 0.60760 0.000 0.048 0.000 0.856 0.040 0.056
#> A0A07F44-C51B-420C-92E8-65F464DB0442 4 0.2851 0.60697 0.000 0.020 0.000 0.844 0.132 0.004
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.3830 0.24724 0.000 0.376 0.000 0.620 0.004 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3268 0.56451 0.000 0.008 0.000 0.808 0.164 0.020
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3728 0.56892 0.000 0.152 0.060 0.784 0.004 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.4286 0.49224 0.000 0.000 0.000 0.728 0.164 0.108
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 4 0.2969 0.56449 0.000 0.224 0.000 0.776 0.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.4663 0.63693 0.000 0.660 0.000 0.252 0.088 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2401 0.62257 0.000 0.028 0.000 0.892 0.072 0.008
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.3698 0.81045 0.788 0.000 0.000 0.000 0.096 0.116
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.3502 0.57016 0.000 0.016 0.000 0.800 0.160 0.024
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.3748 0.80915 0.784 0.000 0.000 0.000 0.108 0.108
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 4 0.3248 0.61904 0.000 0.164 0.000 0.804 0.032 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4751 0.59773 0.000 0.624 0.000 0.300 0.076 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 6 0.3509 0.74044 0.024 0.032 0.000 0.128 0.000 0.816
#> 8236A77B-E07E-4859-86C4-C154F706C239 4 0.4720 0.38456 0.000 0.076 0.228 0.684 0.012 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 4 0.3515 0.57771 0.000 0.192 0.016 0.780 0.012 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.1007 0.65727 0.000 0.956 0.000 0.000 0.044 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.4798 0.58273 0.000 0.612 0.000 0.312 0.076 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1267 0.81654 0.940 0.000 0.000 0.000 0.060 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 4 0.2965 0.62996 0.000 0.080 0.000 0.848 0.072 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.2854 0.55529 0.792 0.208 0.000 0.000 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 2 0.3271 0.58799 0.020 0.844 0.000 0.060 0.000 0.076
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0405 0.88497 0.000 0.000 0.988 0.008 0.004 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.4934 0.62456 0.000 0.632 0.000 0.256 0.112 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2996 0.59190 0.000 0.016 0.000 0.832 0.144 0.008
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.2070 0.83708 0.908 0.000 0.000 0.000 0.044 0.048
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0458 0.88647 0.000 0.000 0.984 0.000 0.016 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 4 0.6622 -0.13655 0.000 0.056 0.284 0.492 0.164 0.004
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.5454 0.29550 0.000 0.008 0.000 0.600 0.160 0.232
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.2308 0.67965 0.000 0.892 0.000 0.068 0.040 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 4 0.3797 0.12793 0.000 0.420 0.000 0.580 0.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.2178 0.62078 0.000 0.132 0.000 0.868 0.000 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 4 0.6715 -0.20319 0.000 0.056 0.292 0.472 0.176 0.004
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0363 0.84423 0.988 0.000 0.000 0.000 0.012 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.3142 0.57507 0.096 0.848 0.000 0.008 0.044 0.004
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1682 0.66874 0.000 0.928 0.000 0.020 0.052 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 5 0.8616 0.60062 0.152 0.244 0.044 0.092 0.396 0.072
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.3464 0.81694 0.808 0.000 0.000 0.000 0.084 0.108
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.2092 0.62448 0.000 0.124 0.000 0.876 0.000 0.000
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.4059 0.30560 0.228 0.720 0.000 0.000 0.052 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.4549 0.65091 0.000 0.680 0.000 0.232 0.088 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2560 0.68933 0.000 0.872 0.000 0.092 0.036 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.2478 0.62346 0.000 0.076 0.000 0.888 0.012 0.024
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.3421 0.57278 0.000 0.016 0.000 0.804 0.160 0.020
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.4725 -0.19380 0.000 0.456 0.000 0.508 0.020 0.016
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.3331 0.56969 0.000 0.012 0.000 0.808 0.160 0.020
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 6 0.2257 0.75326 0.000 0.008 0.000 0.116 0.000 0.876
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 6 0.2257 0.75326 0.000 0.008 0.000 0.116 0.000 0.876
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 2 0.4305 0.51709 0.052 0.776 0.000 0.076 0.000 0.096
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.1007 0.65727 0.000 0.956 0.000 0.000 0.044 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 4 0.4780 0.61358 0.000 0.148 0.000 0.696 0.148 0.008
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.4745 0.62667 0.000 0.644 0.000 0.268 0.088 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 4 0.3899 0.15371 0.000 0.404 0.000 0.592 0.004 0.000
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0547 0.84429 0.980 0.000 0.000 0.000 0.020 0.000
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 6 0.3445 0.62895 0.000 0.008 0.000 0.260 0.000 0.732
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 4 0.3728 0.32956 0.000 0.344 0.000 0.652 0.004 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 4 0.3755 0.47568 0.000 0.012 0.192 0.768 0.028 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.4121 0.49185 0.000 0.604 0.000 0.380 0.016 0.000
#> 21821B38-6786-4078-9918-EC0E877C1533 2 0.1857 0.64016 0.028 0.924 0.000 0.000 0.044 0.004
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.4659 0.63307 0.000 0.656 0.000 0.260 0.084 0.000
#> C559D965-1125-4CF6-8205-4286AB6AA3B9 2 0.1007 0.65727 0.000 0.956 0.000 0.000 0.044 0.000
#> F1099B84-FE2A-419C-9948-D0754C1AF902 5 0.8807 0.66905 0.052 0.160 0.260 0.100 0.360 0.068
#> 8865E079-D8AB-406C-8886-C854F1A26201 2 0.5610 0.13209 0.000 0.464 0.000 0.432 0.084 0.020
#> DBFA1780-4558-436A-A434-05DAFD0F675A 6 0.3031 0.72056 0.032 0.016 0.000 0.100 0.000 0.852
#> 1463039D-7953-4216-9E8B-97F681332EFF 1 0.0146 0.84226 0.996 0.004 0.000 0.000 0.000 0.000
#> 06B39BB2-3381-4452-8000-ECAAE10C1734 2 0.4707 0.63765 0.000 0.656 0.000 0.252 0.092 0.000
#> CC684AEE-6D8A-4074-8474-1C4A48DBC8C7 1 0.0000 0.84313 1.000 0.000 0.000 0.000 0.000 0.000
#> 14B4BCFA-5B10-4AED-AB47-EDF73B252D0B 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> 325F0A64-2E43-473F-B946-D328BF79BE69 3 0.3735 0.83538 0.000 0.000 0.780 0.012 0.172 0.036
#> 7FC6CF7D-67BD-452F-B55E-3ADFD7FDA590 6 0.2553 0.74758 0.000 0.008 0.000 0.144 0.000 0.848
#> CFA5FC5F-4381-415C-B244-C1FE9D992FFB 3 0.2558 0.87023 0.000 0.000 0.840 0.004 0.156 0.000
#> 417CB3FA-2125-42CE-A638-51952C81DC2B 1 0.3834 0.80639 0.776 0.000 0.000 0.000 0.108 0.116
#> 4EDE70FE-C7CF-4CAA-B180-01C5035ECEE4 2 0.4819 0.60981 0.000 0.628 0.000 0.284 0.088 0.000
#> 0AB7F76D-F87D-449B-BA39-73DEE4F032FC 4 0.5637 0.35899 0.004 0.020 0.000 0.620 0.164 0.192
#> 9B3467F3-41E9-4517-BDF5-8CB910A36F1E 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
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#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.4875 0.62590 0.000 0.636 0.000 0.260 0.104 0.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.1285 0.65352 0.000 0.944 0.000 0.004 0.052 0.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.3148 0.61279 0.000 0.116 0.000 0.840 0.024 0.020
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.1285 0.65352 0.000 0.944 0.000 0.004 0.052 0.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4473 0.64251 0.000 0.676 0.000 0.252 0.072 0.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.2251 0.62852 0.000 0.052 0.000 0.904 0.036 0.008
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.4092 0.55122 0.000 0.636 0.000 0.344 0.020 0.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.4895 0.62188 0.000 0.632 0.000 0.264 0.104 0.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 5 0.7822 0.47987 0.000 0.084 0.248 0.312 0.320 0.036
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.6753 -0.15825 0.252 0.500 0.000 0.008 0.060 0.180
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.3552 0.81563 0.800 0.000 0.000 0.000 0.084 0.116
#> A4CECC77-3764-4F27-BD37-D7E76E436944 6 0.2389 0.75149 0.000 0.008 0.000 0.128 0.000 0.864
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.4663 0.63797 0.000 0.660 0.000 0.252 0.088 0.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 4 0.3073 0.57325 0.000 0.204 0.000 0.788 0.008 0.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0000 0.84313 1.000 0.000 0.000 0.000 0.000 0.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 2 0.7562 -0.40082 0.268 0.324 0.000 0.016 0.084 0.308
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.4719 0.62187 0.000 0.644 0.000 0.272 0.084 0.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.5845 0.55864 0.552 0.000 0.024 0.000 0.136 0.288
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.2703 0.86463 0.000 0.000 0.824 0.004 0.172 0.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.3938 0.51806 0.000 0.672 0.000 0.312 0.012 0.004
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 4 0.3999 -0.19447 0.000 0.496 0.000 0.500 0.000 0.004
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.3469 0.81682 0.808 0.000 0.000 0.000 0.088 0.104
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.84313 1.000 0.000 0.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.4725 0.62833 0.000 0.648 0.000 0.264 0.088 0.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.4934 0.62035 0.000 0.628 0.000 0.264 0.108 0.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.4046 0.67980 0.000 0.748 0.000 0.168 0.084 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.3828 0.59962 0.000 0.048 0.000 0.780 0.160 0.012
#> D0920958-B342-4844-9FD6-93F3784CF5A4 2 0.5142 0.56522 0.000 0.596 0.000 0.316 0.076 0.012
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.8328 0.69610 0.000 0.224 0.216 0.148 0.348 0.064
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.5025 0.29719 0.000 0.276 0.000 0.632 0.012 0.080
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0547 0.83698 0.980 0.000 0.000 0.000 0.020 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.0291 0.84143 0.992 0.004 0.000 0.000 0.004 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 4 0.4977 0.58602 0.000 0.236 0.000 0.636 0.128 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.3650 0.81173 0.792 0.000 0.000 0.000 0.092 0.116
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.3545 0.58331 0.036 0.844 0.000 0.016 0.044 0.060
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1700 0.66949 0.000 0.928 0.000 0.024 0.048 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 4 0.3823 0.05208 0.000 0.436 0.000 0.564 0.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2558 0.87023 0.000 0.000 0.840 0.004 0.156 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 6 0.5846 0.29838 0.000 0.248 0.000 0.264 0.000 0.488
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.2953 0.62641 0.000 0.864 0.000 0.076 0.040 0.020
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0146 0.89411 0.000 0.000 0.996 0.004 0.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.4200 0.66742 0.000 0.720 0.000 0.208 0.072 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.1141 0.65366 0.000 0.948 0.000 0.000 0.052 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.1500 0.65605 0.000 0.936 0.000 0.012 0.052 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.2956 0.68164 0.000 0.840 0.000 0.120 0.040 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.4931 0.55208 0.000 0.592 0.000 0.324 0.084 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2558 0.87023 0.000 0.000 0.840 0.004 0.156 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1082 0.84542 0.000 0.000 0.956 0.040 0.004 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 1 0.5170 0.19002 0.544 0.000 0.016 0.000 0.384 0.056
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 2 0.1726 0.64362 0.012 0.932 0.000 0.000 0.044 0.012
#> 5324E01D-69F5-4979-903B-7644F3236EE0 2 0.4861 0.63761 0.000 0.660 0.000 0.244 0.088 0.008
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 4 0.6858 0.17902 0.000 0.000 0.144 0.508 0.196 0.152
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3680 0.69106 0.000 0.784 0.000 0.144 0.072 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.3541 0.62195 0.000 0.088 0.000 0.824 0.068 0.020
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 6 0.3377 0.72195 0.000 0.028 0.000 0.188 0.000 0.784
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 4 0.3658 0.58030 0.000 0.188 0.020 0.776 0.016 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 4 0.3837 0.61029 0.000 0.060 0.000 0.780 0.152 0.008
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4663 0.63797 0.000 0.660 0.000 0.252 0.088 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.1444 0.81080 0.928 0.000 0.000 0.000 0.072 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 4 0.6693 -0.16283 0.000 0.060 0.284 0.484 0.168 0.004
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.2214 0.63190 0.000 0.096 0.000 0.888 0.016 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.4725 0.62745 0.000 0.648 0.000 0.264 0.088 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.1152 0.65628 0.004 0.952 0.000 0.000 0.044 0.000
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.2265 0.68357 0.000 0.900 0.000 0.068 0.024 0.008
#> DB7FD043-2A8F-480A-A208-912D99CE8848 4 0.3510 0.57172 0.000 0.204 0.016 0.772 0.008 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.1398 0.64755 0.000 0.940 0.000 0.000 0.052 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.4247 0.50194 0.000 0.004 0.000 0.740 0.164 0.092
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.4684 0.63541 0.000 0.656 0.000 0.256 0.088 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.4613 0.63571 0.000 0.660 0.000 0.260 0.080 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.3748 0.80915 0.784 0.000 0.000 0.000 0.108 0.108
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0146 0.89309 0.000 0.000 0.996 0.000 0.004 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1176 0.82455 0.956 0.024 0.000 0.000 0.020 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.4075 0.68671 0.000 0.076 0.000 0.184 0.000 0.740
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.4869 0.61397 0.000 0.628 0.000 0.276 0.096 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.4663 0.63797 0.000 0.660 0.000 0.252 0.088 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 4 0.0972 0.62248 0.000 0.028 0.000 0.964 0.008 0.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 2 0.2078 0.63657 0.000 0.912 0.000 0.004 0.044 0.040
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0891 0.87613 0.000 0.000 0.968 0.008 0.024 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.3756 0.60623 0.000 0.052 0.000 0.784 0.156 0.008
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.1265 0.65303 0.000 0.948 0.000 0.000 0.044 0.008
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0000 0.84313 1.000 0.000 0.000 0.000 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.4644 0.38595 0.184 0.720 0.000 0.016 0.004 0.076
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.3673 0.52922 0.000 0.244 0.016 0.736 0.004 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.1265 0.65303 0.000 0.948 0.000 0.000 0.044 0.008
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.3818 0.56055 0.000 0.128 0.084 0.784 0.004 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1890 0.65679 0.000 0.924 0.000 0.024 0.008 0.044
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.4771 0.63265 0.000 0.648 0.000 0.256 0.096 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.5192 0.27479 0.208 0.672 0.000 0.000 0.052 0.068
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 4 0.3349 0.56201 0.000 0.008 0.000 0.804 0.164 0.024
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.2846 0.53410 0.100 0.004 0.000 0.012 0.020 0.864
#> A52CC981-4203-4027-B978-383BFBEB5F75 4 0.3618 0.58211 0.000 0.084 0.084 0.816 0.016 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 4 0.3375 0.59233 0.000 0.104 0.060 0.828 0.004 0.004
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.4093 0.37772 0.004 0.004 0.000 0.440 0.000 0.552
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.5935 0.35441 0.000 0.340 0.000 0.508 0.128 0.024
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.84313 1.000 0.000 0.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.4026 0.68741 0.000 0.088 0.000 0.160 0.000 0.752
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.6793 0.21364 0.108 0.000 0.020 0.096 0.236 0.540
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.4382 0.49950 0.000 0.004 0.000 0.728 0.164 0.104
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2237 0.68262 0.000 0.896 0.000 0.068 0.036 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 4 0.5498 0.19380 0.000 0.452 0.000 0.460 0.028 0.060
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.3878 0.80502 0.772 0.000 0.000 0.000 0.112 0.116
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.5496 0.29054 0.000 0.008 0.000 0.592 0.160 0.240
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 17581 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 0.967 0.950 0.979 0.4613 0.541 0.541
#> 3 3 0.828 0.869 0.928 0.3819 0.739 0.553
#> 4 4 0.821 0.844 0.925 0.1431 0.837 0.592
#> 5 5 0.609 0.618 0.784 0.0696 0.841 0.502
#> 6 6 0.630 0.516 0.707 0.0508 0.928 0.694
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0000 0.980 0.000 1.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.0000 0.980 0.000 1.000
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#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.0000 0.976 1.000 0.000
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0000 0.976 1.000 0.000
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.0000 0.980 0.000 1.000
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.0000 0.980 0.000 1.000
#> F694D119-BF58-4449-A811-CB7A2165D8C0 1 0.0000 0.976 1.000 0.000
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 2 0.0000 0.980 0.000 1.000
#> 1E2B2F45-6629-41B3-8498-321A2E726698 2 0.0000 0.980 0.000 1.000
#> 44047435-3E87-473A-9231-B61FB0D5045B 2 0.0000 0.980 0.000 1.000
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 2 0.0000 0.980 0.000 1.000
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 1 0.0000 0.976 1.000 0.000
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.0000 0.980 0.000 1.000
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.0000 0.980 0.000 1.000
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 1 0.2236 0.948 0.964 0.036
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.0000 0.980 0.000 1.000
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.0000 0.980 0.000 1.000
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 2 0.0000 0.980 0.000 1.000
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 1 0.0000 0.976 1.000 0.000
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.2423 0.944 0.960 0.040
#> A4CECC77-3764-4F27-BD37-D7E76E436944 1 0.0000 0.976 1.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 2 0.0000 0.980 0.000 1.000
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 2 0.0000 0.980 0.000 1.000
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 2 0.0000 0.980 0.000 1.000
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 1 0.0000 0.976 1.000 0.000
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.0000 0.980 0.000 1.000
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.0000 0.976 1.000 0.000
#> 5F284542-900E-4FAC-A1E6-4F267502D845 2 0.0000 0.980 0.000 1.000
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 2 0.0000 0.980 0.000 1.000
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.0000 0.980 0.000 1.000
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.0000 0.980 0.000 1.000
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.0672 0.970 0.992 0.008
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 2 0.7745 0.704 0.228 0.772
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0000 0.980 0.000 1.000
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0000 0.980 0.000 1.000
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0000 0.980 0.000 1.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.0000 0.980 0.000 1.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 1 0.0000 0.976 1.000 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 2 0.0000 0.980 0.000 1.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.6148 0.815 0.152 0.848
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 2 0.0000 0.980 0.000 1.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.0000 0.980 0.000 1.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.980 0.000 1.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0000 0.976 1.000 0.000
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.0000 0.976 1.000 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0000 0.980 0.000 1.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.980 0.000 1.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 2 0.0000 0.980 0.000 1.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 1 0.0000 0.976 1.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.7139 0.752 0.196 0.804
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 2 0.0000 0.980 0.000 1.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0000 0.980 0.000 1.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.0000 0.980 0.000 1.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.0000 0.980 0.000 1.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.980 0.000 1.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.980 0.000 1.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 2 0.0000 0.980 0.000 1.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 2 0.0000 0.980 0.000 1.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 2 0.0000 0.980 0.000 1.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.0000 0.976 1.000 0.000
#> 5324E01D-69F5-4979-903B-7644F3236EE0 1 0.0000 0.976 1.000 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0000 0.976 1.000 0.000
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 1 0.0376 0.973 0.996 0.004
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.0000 0.976 1.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.0000 0.976 1.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0000 0.980 0.000 1.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.980 0.000 1.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.980 0.000 1.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 2 0.0000 0.980 0.000 1.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.0000 0.980 0.000 1.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.0000 0.980 0.000 1.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.980 0.000 1.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.9909 0.196 0.444 0.556
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.8909 0.553 0.308 0.692
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.980 0.000 1.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 1 0.0000 0.976 1.000 0.000
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.0000 0.976 1.000 0.000
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.980 0.000 1.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.0000 0.976 1.000 0.000
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.980 0.000 1.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 2 0.0000 0.980 0.000 1.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0000 0.976 1.000 0.000
#> 8B3B9337-038A-4385-AF58-D285A3706234 2 0.0000 0.980 0.000 1.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.0000 0.980 0.000 1.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0000 0.976 1.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.980 0.000 1.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.980 0.000 1.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.0000 0.980 0.000 1.000
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.0000 0.976 1.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 2 0.0000 0.980 0.000 1.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.0000 0.980 0.000 1.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 1 0.0000 0.976 1.000 0.000
#> 671507DB-3949-4A41-9682-644CE8FED3D3 2 0.0000 0.980 0.000 1.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0000 0.980 0.000 1.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.980 0.000 1.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 1 0.0000 0.976 1.000 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.0000 0.980 0.000 1.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.980 0.000 1.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.980 0.000 1.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.3274 0.926 0.940 0.060
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 1 0.9909 0.211 0.556 0.444
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.976 1.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 2 0.0000 0.980 0.000 1.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.0000 0.980 0.000 1.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.976 1.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 1 0.0000 0.976 1.000 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 2 0.0376 0.977 0.004 0.996
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0000 0.976 1.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0000 0.976 1.000 0.000
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.976 1.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 1 0.9087 0.533 0.676 0.324
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.0000 0.980 0.000 1.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.0000 0.976 1.000 0.000
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.976 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.0747 0.9171 0.000 0.984 0.016
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.2261 0.8977 0.000 0.932 0.068
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0000 0.9208 0.000 1.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0000 0.9208 0.000 1.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.2356 0.9170 0.928 0.000 0.072
#> F405CD29-4016-415B-9546-02DA179A97AC 1 0.0000 0.9387 1.000 0.000 0.000
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 1 0.0000 0.9387 1.000 0.000 0.000
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.2356 0.9321 0.000 0.072 0.928
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0000 0.9208 0.000 1.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.2448 0.9305 0.000 0.076 0.924
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 1 0.0000 0.9387 1.000 0.000 0.000
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.1031 0.9097 0.000 0.976 0.024
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9208 0.000 1.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 1 0.0000 0.9387 1.000 0.000 0.000
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.2537 0.8679 0.000 0.920 0.080
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 1 0.0424 0.9364 0.992 0.008 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.2356 0.9170 0.928 0.000 0.072
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0000 0.9208 0.000 1.000 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 1 0.0000 0.9387 1.000 0.000 0.000
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.2711 0.9233 0.000 0.088 0.912
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9208 0.000 1.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 1 0.0000 0.9387 1.000 0.000 0.000
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.7259 0.6119 0.248 0.680 0.072
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2537 0.8679 0.000 0.920 0.080
#> B013FB96-A517-46EC-8877-4AE84C01AE27 1 0.0000 0.9387 1.000 0.000 0.000
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0000 0.9208 0.000 1.000 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.2066 0.8894 0.060 0.940 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 1 0.0000 0.9387 1.000 0.000 0.000
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2448 0.9157 0.924 0.000 0.076
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 1 0.0000 0.9387 1.000 0.000 0.000
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.1753 0.9264 0.952 0.000 0.048
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.0000 0.9208 0.000 1.000 0.000
#> 839EC959-1497-45DC-8E46-B5C285215603 1 0.5016 0.6795 0.760 0.240 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 1 0.0000 0.9387 1.000 0.000 0.000
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.3192 0.9051 0.000 0.112 0.888
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.1860 0.9009 0.000 0.948 0.052
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9208 0.000 1.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 1 0.3752 0.8137 0.856 0.144 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.2448 0.8769 0.076 0.924 0.000
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 2 0.6111 0.4602 0.000 0.604 0.396
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.0000 0.9208 0.000 1.000 0.000
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 2 0.2356 0.8876 0.000 0.928 0.072
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.2356 0.9170 0.928 0.000 0.072
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.2448 0.9305 0.000 0.076 0.924
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.2066 0.8960 0.000 0.940 0.060
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9208 0.000 1.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 1 0.2356 0.8913 0.928 0.072 0.000
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.2356 0.9170 0.928 0.000 0.072
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2261 0.9187 0.932 0.000 0.068
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.2356 0.9321 0.000 0.072 0.928
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.4178 0.7654 0.000 0.828 0.172
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 1 0.0000 0.9387 1.000 0.000 0.000
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.0000 0.9208 0.000 1.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0000 0.9208 0.000 1.000 0.000
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.3879 0.7901 0.152 0.848 0.000
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.2356 0.9321 0.000 0.072 0.928
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2356 0.9170 0.928 0.000 0.072
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.4291 0.7544 0.000 0.820 0.180
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.2356 0.9170 0.928 0.000 0.072
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5588 0.7836 0.124 0.808 0.068
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1860 0.9009 0.000 0.948 0.052
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.2959 0.8492 0.000 0.900 0.100
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.2356 0.9170 0.928 0.000 0.072
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 1 0.3043 0.8775 0.908 0.084 0.008
#> 12FD30FF-4D3A-4920-BF80-F44132824017 2 0.2356 0.8876 0.000 0.928 0.072
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0000 0.9208 0.000 1.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.2165 0.8875 0.064 0.936 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 1 0.0000 0.9387 1.000 0.000 0.000
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 1 0.0000 0.9387 1.000 0.000 0.000
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 1 0.0592 0.9348 0.988 0.012 0.000
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2356 0.9170 0.928 0.000 0.072
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#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 2 0.4291 0.7434 0.180 0.820 0.000
#> D0920958-B342-4844-9FD6-93F3784CF5A4 1 0.2356 0.8912 0.928 0.072 0.000
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.6295 0.2048 0.000 0.472 0.528
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 1 0.1289 0.9238 0.968 0.032 0.000
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 3 0.0000 0.8871 0.000 0.000 1.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 2 0.2448 0.8872 0.000 0.924 0.076
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0000 0.9208 0.000 1.000 0.000
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.4654 0.7924 0.792 0.000 0.208
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 1 0.0237 0.9377 0.996 0.004 0.000
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.1529 0.9074 0.000 0.960 0.040
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0000 0.9208 0.000 1.000 0.000
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.2356 0.9321 0.000 0.072 0.928
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 1 0.0000 0.9387 1.000 0.000 0.000
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 1 0.7040 0.6226 0.688 0.252 0.060
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.2356 0.9321 0.000 0.072 0.928
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0237 0.9201 0.000 0.996 0.004
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 2 0.2261 0.8906 0.000 0.932 0.068
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.1411 0.9093 0.000 0.964 0.036
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0000 0.9208 0.000 1.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0000 0.9208 0.000 1.000 0.000
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.2356 0.9321 0.000 0.072 0.928
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.2356 0.9321 0.000 0.072 0.928
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.2356 0.9321 0.000 0.072 0.928
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.2356 0.9170 0.928 0.000 0.072
#> 5324E01D-69F5-4979-903B-7644F3236EE0 1 0.6140 0.3230 0.596 0.404 0.000
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 1 0.0237 0.9376 0.996 0.000 0.004
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.2711 0.8686 0.088 0.912 0.000
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 1 0.0000 0.9387 1.000 0.000 0.000
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 1 0.0000 0.9387 1.000 0.000 0.000
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0000 0.9208 0.000 1.000 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.0000 0.9208 0.000 1.000 0.000
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0000 0.9208 0.000 1.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 3 0.0000 0.8871 0.000 0.000 1.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.3752 0.8007 0.000 0.856 0.144
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 2 0.2625 0.8643 0.084 0.916 0.000
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0000 0.9208 0.000 1.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.7962 0.3851 0.352 0.576 0.072
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.3340 0.8434 0.120 0.880 0.000
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9208 0.000 1.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 1 0.5588 0.8138 0.808 0.124 0.068
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 1 0.1031 0.9288 0.976 0.000 0.024
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0000 0.9208 0.000 1.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.1753 0.9264 0.952 0.000 0.048
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0000 0.9208 0.000 1.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.2448 0.9305 0.000 0.076 0.924
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 1 0.0892 0.9348 0.980 0.000 0.020
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.2448 0.9305 0.000 0.076 0.924
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 2 0.2796 0.8839 0.000 0.908 0.092
#> 3C032234-C350-4170-B8F7-F8DE8269E713 1 0.0000 0.9387 1.000 0.000 0.000
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0000 0.9208 0.000 1.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0000 0.9208 0.000 1.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.5285 0.7885 0.064 0.824 0.112
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 1 0.0000 0.9387 1.000 0.000 0.000
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.2711 0.9233 0.000 0.088 0.912
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.1289 0.9064 0.032 0.968 0.000
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 1 0.2066 0.9215 0.940 0.000 0.060
#> 671507DB-3949-4A41-9682-644CE8FED3D3 3 0.0000 0.8871 0.000 0.000 1.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0829 0.9183 0.004 0.984 0.012
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0000 0.9208 0.000 1.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 1 0.1860 0.9090 0.948 0.052 0.000
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4291 0.7557 0.000 0.820 0.180
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.0000 0.9208 0.000 1.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9208 0.000 1.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.7820 0.4473 0.604 0.324 0.072
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.2496 0.8775 0.068 0.004 0.928
#> D182D919-C57F-4004-93DB-FB1723A82072 1 0.0000 0.9387 1.000 0.000 0.000
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.4887 0.7724 0.000 0.228 0.772
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.3941 0.7876 0.000 0.844 0.156
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 1 0.0000 0.9387 1.000 0.000 0.000
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 1 0.0424 0.9364 0.992 0.008 0.000
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.3826 0.8793 0.868 0.008 0.124
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 1 0.0000 0.9387 1.000 0.000 0.000
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 1 0.0424 0.9363 0.992 0.000 0.008
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 1 0.0000 0.9387 1.000 0.000 0.000
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2261 0.8830 0.068 0.932 0.000
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6244 0.1401 0.000 0.560 0.440
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.2261 0.9187 0.932 0.000 0.068
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 1 0.0000 0.9387 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.2149 0.8887 0.088 0.912 0.000 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 1 0.4761 0.3693 0.628 0.372 0.000 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.0592 0.9283 0.016 0.984 0.000 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 2 0.0469 0.9294 0.012 0.988 0.000 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.1211 0.8968 0.960 0.000 0.000 0.040
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.0469 0.9029 0.012 0.000 0.000 0.988
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.0469 0.9029 0.012 0.000 0.000 0.988
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 2 0.1677 0.9124 0.012 0.948 0.040 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.0188 0.9030 0.000 0.004 0.000 0.996
#> 46563983-2B05-4EB7-9E15-07487565158F 2 0.2704 0.8462 0.000 0.876 0.124 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 4 0.1557 0.8829 0.000 0.056 0.000 0.944
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.1867 0.8861 0.928 0.000 0.000 0.072
#> F9135D0D-6447-4452-8EA8-98DEE4610226 2 0.0672 0.9274 0.000 0.984 0.008 0.008
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.0188 0.9034 0.004 0.000 0.000 0.996
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.0188 0.9261 0.000 0.004 0.996 0.000
#> A4967738-7FC2-4270-A149-56E459EDB875 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.0469 0.9021 0.000 0.012 0.000 0.988
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.1510 0.8962 0.956 0.028 0.000 0.016
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 2 0.2868 0.8345 0.000 0.864 0.136 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.0188 0.9034 0.004 0.000 0.000 0.996
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.0188 0.9296 0.000 0.996 0.000 0.004
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.0707 0.9001 0.000 0.020 0.000 0.980
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.2011 0.8821 0.920 0.000 0.000 0.080
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.0469 0.9021 0.000 0.012 0.000 0.988
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.4804 0.4386 0.616 0.000 0.000 0.384
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 2 0.3610 0.7374 0.000 0.800 0.000 0.200
#> 839EC959-1497-45DC-8E46-B5C285215603 4 0.2760 0.8272 0.000 0.128 0.000 0.872
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> 8236A77B-E07E-4859-86C4-C154F706C239 3 0.0469 0.9208 0.000 0.012 0.988 0.000
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.2081 0.8916 0.084 0.916 0.000 0.000
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 4 0.2469 0.8462 0.000 0.108 0.000 0.892
#> 682C11E8-099C-466F-BC8A-B09A754205E3 2 0.3444 0.7596 0.000 0.816 0.000 0.184
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.1637 0.8720 0.940 0.060 0.000 0.000
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.1398 0.9094 0.000 0.956 0.004 0.040
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.0707 0.8961 0.980 0.020 0.000 0.000
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.3266 0.8089 0.832 0.000 0.000 0.168
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4040 0.7086 0.248 0.752 0.000 0.000
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.1356 0.8932 0.000 0.032 0.008 0.960
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.1474 0.8939 0.948 0.000 0.000 0.052
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.3266 0.8083 0.832 0.000 0.000 0.168
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 2 0.3908 0.7381 0.004 0.784 0.212 0.000
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.0469 0.9029 0.012 0.000 0.000 0.988
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.1867 0.8996 0.072 0.928 0.000 0.000
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.0817 0.9214 0.000 0.976 0.000 0.024
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 4 0.5229 0.2781 0.000 0.428 0.008 0.564
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.2011 0.8821 0.920 0.000 0.000 0.080
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 2 0.3908 0.7381 0.004 0.784 0.212 0.000
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.1211 0.8966 0.960 0.000 0.000 0.040
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 1 0.1792 0.8656 0.932 0.068 0.000 0.000
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.1022 0.9223 0.032 0.968 0.000 0.000
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.4542 0.8019 0.088 0.804 0.108 0.000
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.1557 0.8927 0.944 0.000 0.000 0.056
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.1114 0.9033 0.008 0.016 0.004 0.972
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.0817 0.8946 0.976 0.024 0.000 0.000
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 2 0.0921 0.9239 0.028 0.972 0.000 0.000
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.0469 0.9273 0.000 0.988 0.000 0.012
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.0336 0.9027 0.000 0.008 0.000 0.992
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.0188 0.9030 0.000 0.004 0.000 0.996
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.2081 0.8641 0.000 0.084 0.000 0.916
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.2281 0.8725 0.904 0.000 0.000 0.096
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.0817 0.8987 0.000 0.024 0.000 0.976
#> 1CA20860-4A2E-4D34-A479-5B56FACC2C0A 1 0.2408 0.8671 0.896 0.000 0.000 0.104
#> 55A3AFE4-8F9F-4FAF-92F1-D15A9A562DD8 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> A1AD6E6B-270D-4C2D-9092-B18099EE1783 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> 79A8F606-9A9B-45F4-99E2-61B8498AB4BD 4 0.1389 0.8877 0.000 0.048 0.000 0.952
#> 4A47B575-D714-42DE-991A-E4841DA0BF67 2 0.0188 0.9305 0.004 0.996 0.000 0.000
#> 8751D026-849B-44ED-933B-FD9B80DE329E 2 0.3649 0.7304 0.000 0.796 0.000 0.204
#> D0213FF6-3B56-440A-8D5D-53F6E6C70F11 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> B8757A4B-548E-41BD-B0B0-F7A8658AAFE6 2 0.1211 0.9103 0.000 0.960 0.000 0.040
#> 073C074D-A9DF-4547-9BFA-1F46C27650D7 1 0.0921 0.8989 0.972 0.000 0.000 0.028
#> 989000D0-FBA6-4AF0-9FBB-1A0949A29425 4 0.0592 0.9022 0.016 0.000 0.000 0.984
#> D67DB58D-2971-4B11-8A95-49EA7E0028D3 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 10F2C028-06C5-4560-9A52-DD76A227B891 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> EB9FCAC4-2937-46BC-A560-E506412F8966 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> B5F328DB-3D7D-4B9A-A5E1-639F07865F23 2 0.0817 0.9209 0.000 0.976 0.000 0.024
#> 21821B38-6786-4078-9918-EC0E877C1533 1 0.0921 0.9002 0.972 0.000 0.000 0.028
#> 2AC38CDA-108E-4553-893F-F36211922BB6 2 0.0188 0.9296 0.000 0.996 0.000 0.004
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#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.1474 0.8937 0.948 0.000 0.000 0.052
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0000 0.9003 1.000 0.000 0.000 0.000
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 2 0.0336 0.9285 0.000 0.992 0.000 0.008
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 2 0.0336 0.9283 0.000 0.992 0.000 0.008
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 2 0.0707 0.9270 0.020 0.980 0.000 0.000
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 4 0.4776 0.4368 0.000 0.376 0.000 0.624
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.2868 0.8190 0.000 0.136 0.000 0.864
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 3 0.5250 0.1804 0.008 0.440 0.552 0.000
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 4 0.1406 0.8937 0.000 0.024 0.016 0.960
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.0779 0.8965 0.980 0.016 0.004 0.000
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.1716 0.8684 0.936 0.064 0.000 0.000
#> 42DCA292-7292-4162-994F-FFBC0102C55E 2 0.0921 0.9184 0.000 0.972 0.000 0.028
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.1474 0.8937 0.948 0.000 0.000 0.052
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 4 0.0804 0.9039 0.008 0.012 0.000 0.980
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.0188 0.9305 0.004 0.996 0.000 0.000
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.0188 0.9298 0.000 0.996 0.000 0.004
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 1 0.6148 0.3055 0.540 0.052 0.000 0.408
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.3764 0.7043 0.784 0.216 0.000 0.000
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.4406 0.6225 0.300 0.700 0.000 0.000
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> 29635F4D-3149-49BC-B960-FF863D10F747 2 0.0188 0.9296 0.000 0.996 0.000 0.004
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 3 0.0469 0.9219 0.012 0.000 0.988 0.000
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.1557 0.8926 0.944 0.000 0.000 0.056
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.3649 0.7456 0.000 0.204 0.000 0.796
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 4 0.0592 0.9022 0.016 0.000 0.000 0.984
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.2345 0.8599 0.000 0.900 0.000 0.100
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0188 0.9030 0.000 0.004 0.000 0.996
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.0592 0.9022 0.016 0.000 0.000 0.984
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 2 0.0707 0.9261 0.000 0.980 0.020 0.000
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 2 0.3444 0.7632 0.000 0.816 0.000 0.184
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0817 0.8918 0.976 0.000 0.024 0.000
#> D021A258-8713-4383-9DCA-45E2F54A0411 2 0.3539 0.7863 0.004 0.820 0.176 0.000
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.4961 0.2333 0.000 0.448 0.000 0.552
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.0188 0.9305 0.004 0.996 0.000 0.000
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 1 0.1661 0.8797 0.944 0.052 0.000 0.004
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.1677 0.9118 0.012 0.948 0.000 0.040
#> DB7FD043-2A8F-480A-A208-912D99CE8848 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 4 0.3587 0.8203 0.052 0.088 0.000 0.860
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.0804 0.9016 0.012 0.000 0.008 0.980
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.4277 0.6511 0.720 0.000 0.000 0.280
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 2 0.0707 0.9270 0.020 0.980 0.000 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 4 0.4605 0.4560 0.336 0.000 0.000 0.664
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.1389 0.8808 0.952 0.048 0.000 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.0469 0.9029 0.012 0.000 0.000 0.988
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.0336 0.9302 0.008 0.992 0.000 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.7269 0.0779 0.000 0.456 0.148 0.396
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.0707 0.9007 0.020 0.000 0.000 0.980
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 3 0.0188 0.9261 0.000 0.004 0.996 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 2 0.4907 0.2447 0.000 0.580 0.000 0.420
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 4 0.2814 0.8051 0.132 0.000 0.000 0.868
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0188 0.9000 0.996 0.004 0.000 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.0921 0.9251 0.028 0.972 0.000 0.000
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 2 0.0188 0.9305 0.004 0.996 0.000 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.2216 0.8583 0.000 0.092 0.000 0.908
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 2 0.4103 0.6762 0.000 0.744 0.256 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 2 0.1792 0.9021 0.068 0.932 0.000 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 2 0.0000 0.9304 0.000 1.000 0.000 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 1 0.7082 0.5395 0.564 0.252 0.000 0.184
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.0000 0.9282 0.000 0.000 1.000 0.000
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.0817 0.8988 0.024 0.000 0.000 0.976
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.1474 0.8869 0.000 0.052 0.948 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 2 0.4193 0.6543 0.000 0.732 0.268 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0469 0.9029 0.012 0.000 0.000 0.988
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.1557 0.8828 0.000 0.056 0.000 0.944
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0000 0.9003 1.000 0.000 0.000 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.0336 0.9033 0.008 0.000 0.000 0.992
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.1211 0.8892 0.040 0.000 0.000 0.960
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.0188 0.9034 0.004 0.000 0.000 0.996
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.0707 0.9228 0.000 0.980 0.000 0.020
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 3 0.4936 0.3818 0.004 0.372 0.624 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.4730 0.4854 0.636 0.000 0.000 0.364
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0592 0.9022 0.016 0.000 0.000 0.984
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.4594 0.32900 0.036 0.680 0.000 0.000 0.284
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.5492 0.24749 0.396 0.536 0.000 0.000 0.068
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.3895 0.14624 0.000 0.680 0.000 0.000 0.320
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 5 0.4307 0.48308 0.000 0.496 0.000 0.000 0.504
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0162 0.87017 0.996 0.000 0.000 0.000 0.004
#> F405CD29-4016-415B-9546-02DA179A97AC 4 0.1043 0.83875 0.000 0.000 0.000 0.960 0.040
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 4 0.0290 0.83504 0.000 0.000 0.000 0.992 0.008
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.0609 0.86869 0.000 0.000 0.980 0.000 0.020
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 5 0.4262 0.58582 0.000 0.440 0.000 0.000 0.560
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.4256 0.47612 0.000 0.000 0.564 0.000 0.436
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 4 0.0771 0.83844 0.000 0.004 0.000 0.976 0.020
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 5 0.3884 0.65341 0.000 0.288 0.004 0.000 0.708
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 2 0.4192 -0.17225 0.000 0.596 0.000 0.000 0.404
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 4 0.2377 0.82249 0.000 0.000 0.000 0.872 0.128
#> 46563983-2B05-4EB7-9E15-07487565158F 5 0.3242 0.63796 0.000 0.116 0.040 0.000 0.844
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4235 0.24157 0.000 0.576 0.000 0.424 0.000
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0162 0.87048 0.996 0.000 0.000 0.004 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 5 0.3491 0.68491 0.000 0.228 0.004 0.000 0.768
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 4 0.1372 0.83251 0.004 0.024 0.000 0.956 0.016
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.4122 0.70480 0.000 0.004 0.688 0.004 0.304
#> A4967738-7FC2-4270-A149-56E459EDB875 5 0.4549 0.47967 0.000 0.464 0.000 0.008 0.528
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 4 0.3132 0.80202 0.000 0.000 0.008 0.820 0.172
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 1 0.6186 0.37035 0.552 0.320 0.000 0.116 0.012
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 5 0.4522 0.65820 0.000 0.176 0.080 0.000 0.744
#> B013FB96-A517-46EC-8877-4AE84C01AE27 4 0.1410 0.83734 0.000 0.000 0.000 0.940 0.060
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.2690 0.50685 0.000 0.844 0.000 0.000 0.156
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 5 0.4589 0.61935 0.000 0.212 0.000 0.064 0.724
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 4 0.2813 0.80678 0.000 0.000 0.000 0.832 0.168
#> 2D82BAF3-62A1-4B94-A806-F044B8595DB6 1 0.0324 0.86969 0.992 0.000 0.000 0.004 0.004
#> 8CAD119D-652E-4D43-BB99-49F90FE5CBF3 4 0.2424 0.82050 0.000 0.000 0.000 0.868 0.132
#> 00F70D11-3B58-4517-82EC-258CCED34A60 1 0.4746 0.37642 0.600 0.000 0.000 0.376 0.024
#> B9F42E36-78E1-4BB8-93A8-18264A48E8E2 5 0.5428 0.34688 0.000 0.064 0.008 0.308 0.620
#> 839EC959-1497-45DC-8E46-B5C285215603 2 0.4219 0.30695 0.000 0.584 0.000 0.416 0.000
#> 59E0DEB0-C771-4FB9-A823-6FB7B5CBA876 4 0.0981 0.83229 0.008 0.012 0.000 0.972 0.008
#> 8236A77B-E07E-4859-86C4-C154F706C239 5 0.4546 -0.22145 0.000 0.008 0.460 0.000 0.532
#> 775E9758-CBA2-4B87-844A-120E56FE2141 2 0.3416 0.58333 0.088 0.840 0.000 0.000 0.072
#> 90EFD0B1-6CBA-4860-92DB-6CD6F04C8422 5 0.4138 0.69032 0.000 0.276 0.016 0.000 0.708
#> 71B6CAEF-331D-4331-A42B-4F83DCA777D5 2 0.3177 0.56402 0.000 0.792 0.000 0.208 0.000
#> 682C11E8-099C-466F-BC8A-B09A754205E3 4 0.6066 0.15776 0.000 0.120 0.000 0.456 0.424
#> 59705C6B-02F5-4E49-AE4C-F2510112FE67 1 0.4995 0.70695 0.704 0.084 0.004 0.000 0.208
#> 072BAC5F-4E09-4831-9C32-F42B94C4B30D 2 0.3394 0.55195 0.000 0.824 0.004 0.020 0.152
#> CB8E1E32-91DB-4B35-9556-F6537F64BCBE 1 0.2674 0.80281 0.868 0.120 0.000 0.000 0.012
#> A81E5EF5-C201-410D-BE73-63F273DFF6E7 1 0.3500 0.75886 0.808 0.004 0.000 0.172 0.016
#> EC24A121-D2CE-4CC3-8D70-033B9AF36EFC 5 0.4201 -0.01780 0.000 0.000 0.408 0.000 0.592
#> 9C7554E5-AECC-4F41-9B1A-5F82541BB4DF 2 0.4348 0.42966 0.316 0.668 0.000 0.000 0.016
#> D330B86E-5373-49B2-87C6-DC5ED2021B45 5 0.4088 0.64313 0.000 0.368 0.000 0.000 0.632
#> 6B131704-D54C-4E0E-9D01-BFEE2C59BE88 4 0.2737 0.83459 0.000 0.032 0.020 0.896 0.052
#> 54F8F899-DF83-42DD-BBF4-51D7583E5652 1 0.0162 0.87101 0.996 0.000 0.000 0.000 0.004
#> E08283CA-68E0-4171-B8B9-51AEE0B1E0EF 1 0.2077 0.83210 0.908 0.000 0.000 0.084 0.008
#> 1B04B428-7C0D-49A2-B08A-072FA715AD1B 3 0.1121 0.86457 0.000 0.000 0.956 0.000 0.044
#> F436FB5B-FC23-4F57-BF88-48468B201DA6 5 0.3944 0.63492 0.000 0.160 0.052 0.000 0.788
#> 7E87CD79-D38C-448B-8D02-018B1E7EFE9F 4 0.0290 0.83726 0.000 0.000 0.000 0.992 0.008
#> C07800C1-91B6-4612-9831-F4F6FC6CF318 2 0.4232 0.22231 0.012 0.676 0.000 0.000 0.312
#> 42202AF1-6414-4509-995B-21EDCD2CC2CF 2 0.3934 0.54966 0.000 0.800 0.000 0.124 0.076
#> 5C1BC8CE-63BC-4151-A9C7-7929D399EABE 2 0.4134 0.57162 0.000 0.760 0.000 0.196 0.044
#> 348C6DA2-7AFB-4FE1-9AFC-5839111BD0A3 3 0.3707 0.70977 0.000 0.000 0.716 0.000 0.284
#> 30774CD0-6F55-4E04-AE96-DBD729702499 1 0.0798 0.86691 0.976 0.000 0.000 0.016 0.008
#> 1A258EE7-6BBC-4FA0-BC26-9C5243D7B04B 5 0.3875 0.63275 0.000 0.160 0.048 0.000 0.792
#> 0F8369F0-A35F-4327-8F7E-CC089C899FC8 1 0.0000 0.87071 1.000 0.000 0.000 0.000 0.000
#> BFEEA30B-9DF7-46BC-BC83-3BF1EDE95EB2 2 0.5461 0.23140 0.408 0.528 0.000 0.000 0.064
#> EC9DD1B9-15AA-441D-8D80-D32F663B3A5C 2 0.3661 0.27541 0.000 0.724 0.000 0.000 0.276
#> C8D64135-1B75-428A-8C75-351D32009EAC 2 0.5104 0.29134 0.000 0.648 0.068 0.000 0.284
#> 8A9C0B95-4830-45C3-A596-75C2F22CFA14 1 0.0324 0.87121 0.992 0.000 0.000 0.004 0.004
#> 0A4B2A06-3603-42F6-9E6D-E5595E86D1EA 4 0.3554 0.77782 0.000 0.004 0.004 0.776 0.216
#> 12FD30FF-4D3A-4920-BF80-F44132824017 1 0.4691 0.54741 0.680 0.276 0.000 0.000 0.044
#> 6559039D-B6F2-4BBB-B10C-DFBF22DBFCAA 5 0.4227 0.61136 0.000 0.420 0.000 0.000 0.580
#> C6FB2026-B740-459E-9831-93279BBF354E 2 0.1478 0.61699 0.000 0.936 0.000 0.064 0.000
#> 9F6360E2-1DF2-4459-9103-5073926E93BA 4 0.1485 0.83600 0.000 0.032 0.000 0.948 0.020
#> 12D8F871-C919-44A0-96BC-C95F4FECE8CD 4 0.2179 0.82810 0.000 0.000 0.000 0.888 0.112
#> 419D0065-52AA-4340-9FDD-9B2B15F44412 4 0.3370 0.80404 0.000 0.028 0.000 0.824 0.148
#> 7A532AB7-001D-4B99-9D30-DC67B7D847DB 1 0.0955 0.86306 0.968 0.000 0.000 0.028 0.004
#> 74707DAA-FE40-4D28-AD49-0D1C5465C253 4 0.2806 0.81256 0.000 0.004 0.000 0.844 0.152
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#> DD138FF8-D54F-4A77-AAF7-DBFEA3BEB17D 2 0.1168 0.61358 0.000 0.960 0.008 0.000 0.032
#> 421E2607-50FA-4260-BD10-C37FCB7D063F 1 0.2130 0.83612 0.908 0.080 0.000 0.000 0.012
#> 5311BB33-72C7-4287-8D56-998477D7E3FB 3 0.2929 0.80363 0.000 0.000 0.820 0.000 0.180
#> 88B6F48A-95D0-4EA7-86EF-52EFCF82DED6 4 0.3606 0.72650 0.004 0.164 0.000 0.808 0.024
#> C6F4EF8F-353C-463E-8069-FDEACF556176 4 0.2852 0.80450 0.000 0.000 0.000 0.828 0.172
#> A451CA06-E1BF-478B-9A50-A0D8C3D4A2AC 3 0.2930 0.82012 0.000 0.004 0.832 0.000 0.164
#> 4378B8BB-C513-4CC2-B06E-8270FED24576 2 0.3563 0.53674 0.208 0.780 0.000 0.000 0.012
#> E26E2897-1B92-47A7-959C-53D6BFDD16FF 4 0.2745 0.83423 0.000 0.024 0.028 0.896 0.052
#> BB5A5553-B4F9-4C63-B9B3-22A928250C97 2 0.3039 0.51793 0.000 0.808 0.000 0.000 0.192
#> 3F2D803B-FED0-4EB7-9058-D67D10CB3532 1 0.2110 0.83672 0.912 0.000 0.000 0.072 0.016
#> 483BEB1B-6EDD-4954-8324-BA2E7CB8A9E8 1 0.0324 0.86969 0.992 0.000 0.000 0.004 0.004
#> CDC7DF8C-4E6C-4F00-AE33-F3EAB6F1D08F 2 0.3827 0.57783 0.112 0.816 0.000 0.004 0.068
#> BF128355-3E49-449D-A503-00E678E90DF8 2 0.2074 0.56036 0.000 0.896 0.000 0.000 0.104
#> F694D119-BF58-4449-A811-CB7A2165D8C0 4 0.1597 0.82728 0.020 0.024 0.000 0.948 0.008
#> E5635AF5-62DE-4C8A-9DA7-93832EE14564 1 0.5876 0.29843 0.544 0.364 0.000 0.008 0.084
#> 1E2B2F45-6629-41B3-8498-321A2E726698 5 0.3730 0.67914 0.000 0.288 0.000 0.000 0.712
#> 44047435-3E87-473A-9231-B61FB0D5045B 5 0.4283 0.56472 0.000 0.456 0.000 0.000 0.544
#> 424C7DA7-1E1F-4B2B-9743-5996BD163573 3 0.2852 0.81601 0.000 0.000 0.828 0.000 0.172
#> B38CE2EB-7610-45C6-A83E-BBC16A341F79 4 0.3282 0.70307 0.000 0.188 0.000 0.804 0.008
#> 59C375B4-60FB-4598-A146-5B175C2B8079 2 0.1403 0.60630 0.024 0.952 0.000 0.000 0.024
#> EF51ED0E-46ED-4AB0-9504-9F3B8FCD36F2 2 0.4015 0.01851 0.000 0.652 0.000 0.000 0.348
#> 9AABE7F6-9EA3-41E9-B763-418BADA1CF4F 4 0.4305 0.70935 0.000 0.200 0.000 0.748 0.052
#> 310F99CB-0837-4869-8B48-28D4B543BE3B 2 0.1251 0.61533 0.000 0.956 0.000 0.036 0.008
#> A65773C1-18D0-4F48-85E1-380338B66C7D 2 0.3837 0.22067 0.000 0.692 0.000 0.000 0.308
#> DD20D507-013B-4E54-9B1B-0D3B82A3C9CA 3 0.5847 0.24886 0.000 0.096 0.480 0.000 0.424
#> 10848C09-8257-426B-AAB6-EEDCAB1274B1 2 0.6987 0.16046 0.288 0.404 0.000 0.300 0.008
#> A340E38D-AF36-4B13-ADD3-50BE6819D4FE 1 0.0000 0.87071 1.000 0.000 0.000 0.000 0.000
#> A4CECC77-3764-4F27-BD37-D7E76E436944 4 0.0000 0.83634 0.000 0.000 0.000 1.000 0.000
#> C079CC60-A420-4F66-8B9C-32DC51C49986 5 0.4138 0.63960 0.000 0.384 0.000 0.000 0.616
#> 0783FF5E-F78D-49AC-8F8E-FC27C3673F81 5 0.4108 0.66364 0.000 0.308 0.008 0.000 0.684
#> 508C73D0-3A7E-47E6-934C-2CC68E00ED53 1 0.0609 0.87096 0.980 0.000 0.000 0.000 0.020
#> 67D1EA12-766F-4EB9-AF7E-4545975B076C 4 0.5128 0.28994 0.028 0.392 0.000 0.572 0.008
#> 2356B998-0930-403F-9B04-57A18A150955 2 0.2929 0.48903 0.000 0.820 0.000 0.000 0.180
#> 72EF685A-00BB-42C5-BB4F-4CB52B798DB2 1 0.6379 0.30763 0.528 0.000 0.064 0.360 0.048
#> 5F284542-900E-4FAC-A1E6-4F267502D845 3 0.0290 0.86215 0.000 0.000 0.992 0.000 0.008
#> 48BD0E00-BE54-47A2-9AED-73C0C863FD39 5 0.4491 0.56405 0.008 0.364 0.004 0.000 0.624
#> 42AAAE48-01CC-4010-BEF6-CCD49202E816 2 0.2074 0.59083 0.000 0.896 0.000 0.000 0.104
#> A664B550-4B77-4B1E-BD11-62C4F73073DF 2 0.3551 0.56386 0.136 0.820 0.000 0.000 0.044
#> 1324C50E-3D79-48BB-BCDE-28A0E5B73F68 1 0.3528 0.80762 0.848 0.084 0.000 0.052 0.016
#> AAA54A0C-F437-4E0E-AE39-977BEBD517BF 1 0.0609 0.87096 0.980 0.000 0.000 0.000 0.020
#> 88CD8F3F-5158-4E98-ABA0-1ABFFCEA5FF5 5 0.4262 0.55839 0.000 0.440 0.000 0.000 0.560
#> 91382C7F-7FEC-4369-B1A4-60911A47C56A 5 0.3636 0.66406 0.000 0.272 0.000 0.000 0.728
#> E0B3C5D3-A6B3-4516-97E4-AE8796C8B12F 5 0.4304 0.52788 0.000 0.484 0.000 0.000 0.516
#> CD86EEAF-D99B-4BD6-96CC-C44A4263CDD7 5 0.5539 -0.14110 0.000 0.048 0.008 0.444 0.500
#> D0920958-B342-4844-9FD6-93F3784CF5A4 4 0.5799 0.58035 0.000 0.220 0.000 0.612 0.168
#> E6C48482-0AD8-4B4C-9FB9-C3594E198024 5 0.6439 0.14518 0.000 0.184 0.356 0.000 0.460
#> 627CEEEC-42C0-4104-A134-A6E4A7738BF8 2 0.4678 0.53466 0.004 0.716 0.004 0.236 0.040
#> 1BC37328-9C24-40D3-BB7B-000E0F562CB5 1 0.1121 0.86597 0.956 0.000 0.000 0.000 0.044
#> 150FEEB1-7643-4B1C-A77C-CFD97D301D37 1 0.3409 0.79653 0.836 0.112 0.000 0.000 0.052
#> 42DCA292-7292-4162-994F-FFBC0102C55E 5 0.4444 0.60325 0.000 0.180 0.000 0.072 0.748
#> A9237A7A-3C6C-44E7-B2A9-B2E4B1A45B07 1 0.0404 0.87149 0.988 0.000 0.000 0.000 0.012
#> D63FFCFC-A31F-4281-AD8D-2FEE7439ABE4 2 0.4829 0.34211 0.016 0.604 0.000 0.372 0.008
#> E2A25905-7C92-4E43-81C0-D09268014334 2 0.4088 -0.04778 0.000 0.632 0.000 0.000 0.368
#> E6901976-2075-463C-828D-8DF924EFC78E 2 0.1671 0.60462 0.000 0.924 0.000 0.000 0.076
#> 89D22C35-AE69-4596-99BA-3B33CF66846F 3 0.0162 0.86380 0.000 0.000 0.996 0.000 0.004
#> F7B0D141-4D33-4A6E-8E05-08F7CF325459 4 0.0807 0.83347 0.012 0.000 0.000 0.976 0.012
#> B63EDF98-ED66-485D-BEA8-9EBB5666D030 2 0.4888 0.55773 0.080 0.760 0.008 0.136 0.016
#> CDE9046D-3C7B-4B08-90C8-FF0A6BB585C7 3 0.1732 0.86014 0.000 0.000 0.920 0.000 0.080
#> FD1BC717-18D7-47AF-820D-7A8C6FDD4ED5 2 0.1197 0.59883 0.000 0.952 0.000 0.000 0.048
#> C2E78287-F440-4BCB-B9DC-C8CDA71760B1 1 0.3825 0.75116 0.804 0.060 0.000 0.000 0.136
#> CB75FB62-E6E9-4763-A97C-1A2B919ADC5A 2 0.5631 0.37789 0.292 0.600 0.000 0.000 0.108
#> 84314004-2EE2-4AA9-B9DE-B6EF7DB3FE82 2 0.0162 0.61158 0.000 0.996 0.000 0.000 0.004
#> 29635F4D-3149-49BC-B960-FF863D10F747 5 0.4126 0.62528 0.000 0.380 0.000 0.000 0.620
#> 42B438C3-DF9D-4BE6-9798-43935C5F0B66 3 0.0000 0.86480 0.000 0.000 1.000 0.000 0.000
#> F79245C7-064D-4C8A-87F2-6DB02585C395 3 0.1732 0.85441 0.000 0.000 0.920 0.000 0.080
#> 6AA999CB-5D78-463B-9068-720C09EB9D34 5 0.4800 -0.07623 0.028 0.000 0.368 0.000 0.604
#> 3676FF64-9F37-4EE8-84FD-84131DAE04A2 1 0.3604 0.79891 0.836 0.056 0.000 0.100 0.008
#> 5324E01D-69F5-4979-903B-7644F3236EE0 4 0.5960 0.35398 0.000 0.352 0.000 0.528 0.120
#> E6AAFCE7-B2CF-4D73-9796-152051122A1A 4 0.1124 0.83834 0.000 0.000 0.004 0.960 0.036
#> 8A1C823B-62DF-4C1F-9D0F-BBF4D93E3245 2 0.3492 0.55753 0.000 0.796 0.000 0.188 0.016
#> BA714D2C-C88F-44C8-85CB-DE57055BAB1D 4 0.0566 0.83855 0.000 0.004 0.000 0.984 0.012
#> FD476524-E22C-44A1-8F91-2A8A0519AA7D 4 0.0290 0.83628 0.000 0.000 0.000 0.992 0.008
#> A8304BF0-EC4E-41C2-8FC8-90949C7A4F38 5 0.4524 0.67203 0.000 0.336 0.020 0.000 0.644
#> BD2081D7-90DD-4F9A-89C1-76D4322A1C8E 5 0.6462 0.10321 0.000 0.188 0.000 0.356 0.456
#> 808C3B2A-4B4D-49E6-B60E-2E05F7E9CA04 2 0.4030 0.04287 0.000 0.648 0.000 0.000 0.352
#> 0EECC108-EAA0-4723-8342-DDC7F91710F9 1 0.0794 0.86999 0.972 0.000 0.000 0.000 0.028
#> D021A258-8713-4383-9DCA-45E2F54A0411 5 0.3875 0.63275 0.000 0.160 0.048 0.000 0.792
#> AE5E85D4-0B93-44CC-B846-7E893CA67B21 4 0.6367 0.30024 0.000 0.372 0.000 0.460 0.168
#> F5F7B591-062D-4FF0-AB68-73D678574318 2 0.2230 0.57307 0.000 0.884 0.000 0.000 0.116
#> E4673254-C59F-4C2D-BF1D-DE6F7464A287 2 0.5755 0.18582 0.416 0.516 0.000 0.052 0.016
#> EC6F630A-8F81-4170-B41B-97D9E4582B68 2 0.3425 0.60662 0.004 0.840 0.000 0.112 0.044
#> DB7FD043-2A8F-480A-A208-912D99CE8848 5 0.3491 0.68541 0.000 0.228 0.004 0.000 0.768
#> 18C5BB3B-FC3B-472C-BE3E-4348704BEFA4 2 0.5649 0.51396 0.100 0.632 0.000 0.260 0.008
#> 3DB28A6F-C3B3-4E71-BDCB-8F19F1599695 4 0.3532 0.77581 0.000 0.000 0.128 0.824 0.048
#> FA5BCA6C-A84E-4BAA-9AF4-3304F6364440 2 0.3636 0.28230 0.000 0.728 0.000 0.000 0.272
#> 79A4EA16-B871-4932-B1F4-169004233CBA 1 0.4436 0.37252 0.596 0.000 0.000 0.396 0.008
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 5 0.4304 0.51671 0.000 0.484 0.000 0.000 0.516
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.4030 0.60393 0.000 0.000 0.648 0.000 0.352
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 4 0.4846 0.29828 0.384 0.000 0.000 0.588 0.028
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.1732 0.85479 0.000 0.000 0.920 0.000 0.080
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.4849 0.69171 0.724 0.136 0.000 0.000 0.140
#> 3C032234-C350-4170-B8F7-F8DE8269E713 4 0.0798 0.83293 0.000 0.016 0.000 0.976 0.008
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 5 0.3774 0.68681 0.000 0.296 0.000 0.000 0.704
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.1732 0.58301 0.000 0.920 0.000 0.000 0.080
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.5162 0.51989 0.000 0.704 0.140 0.152 0.004
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 4 0.2283 0.81671 0.040 0.036 0.000 0.916 0.008
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 5 0.4542 -0.15340 0.000 0.008 0.456 0.000 0.536
#> 05127463-A69A-42B3-9635-575A08EB980A 5 0.5533 0.41430 0.000 0.096 0.008 0.248 0.648
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.6005 0.46281 0.152 0.608 0.000 0.232 0.008
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.1043 0.86688 0.960 0.000 0.000 0.000 0.040
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2513 0.61068 0.016 0.904 0.000 0.020 0.060
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 5 0.3508 0.68926 0.000 0.252 0.000 0.000 0.748
#> C3E23136-7190-4D08-991C-93AFACC48E8D 4 0.4867 0.19359 0.000 0.432 0.000 0.544 0.024
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 5 0.5444 0.60281 0.000 0.160 0.180 0.000 0.660
#> 534B9E41-B731-4461-ABEA-30096148A493 5 0.4101 0.61357 0.000 0.372 0.000 0.000 0.628
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 5 0.3999 0.66543 0.000 0.344 0.000 0.000 0.656
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.6118 0.47444 0.240 0.592 0.000 0.160 0.008
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.3327 0.76336 0.000 0.000 0.828 0.144 0.028
#> D182D919-C57F-4004-93DB-FB1723A82072 4 0.1403 0.83084 0.024 0.000 0.000 0.952 0.024
#> A52CC981-4203-4027-B978-383BFBEB5F75 3 0.4066 0.74628 0.000 0.044 0.768 0.000 0.188
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 3 0.6399 0.15859 0.000 0.196 0.496 0.000 0.308
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 4 0.0963 0.83858 0.000 0.000 0.000 0.964 0.036
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 4 0.3132 0.79945 0.000 0.008 0.000 0.820 0.172
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0609 0.87096 0.980 0.000 0.000 0.000 0.020
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 4 0.0992 0.83119 0.000 0.024 0.000 0.968 0.008
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 4 0.2665 0.82116 0.032 0.000 0.020 0.900 0.048
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 4 0.2338 0.82706 0.000 0.000 0.004 0.884 0.112
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.2193 0.60904 0.000 0.912 0.000 0.060 0.028
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 2 0.6536 0.07359 0.004 0.420 0.408 0.000 0.168
#> C90142D8-F939-4FEA-BC48-073D2814F54E 1 0.4436 0.36187 0.596 0.000 0.000 0.396 0.008
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 4 0.0609 0.83726 0.000 0.000 0.000 0.980 0.020
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> F9E194A1-E5C1-4A1A-840B-4E0246640D09 2 0.6148 0.31094 0.032 0.464 0.000 0.132 0.372 0.000
#> BB329D2F-C41D-4147-92D9-C7B971CAD0DC 2 0.5971 0.40630 0.088 0.544 0.000 0.056 0.312 0.000
#> 300D7F74-A627-4738-91A9-62778D98C5AD 2 0.4574 0.17501 0.000 0.524 0.000 0.440 0.036 0.000
#> 727911B5-45AA-42A6-8D32-4D131C8B0824 4 0.4972 0.41571 0.000 0.288 0.004 0.620 0.088 0.000
#> A03BDA91-0936-4C67-9508-4903F84C980F 1 0.0891 0.85634 0.968 0.024 0.000 0.000 0.008 0.000
#> F405CD29-4016-415B-9546-02DA179A97AC 6 0.0632 0.70077 0.000 0.000 0.000 0.000 0.024 0.976
#> F86BCE61-6748-4F0D-B56A-C30BD71EB2FE 6 0.0146 0.69855 0.000 0.000 0.000 0.000 0.004 0.996
#> 7D119F66-6ACB-4A78-A0F7-D90ED6D1FA50 3 0.1682 0.83399 0.000 0.000 0.928 0.052 0.020 0.000
#> 9657C56C-0A9D-4C0B-9039-9DC26FEEF5C4 4 0.3259 0.55619 0.000 0.216 0.000 0.772 0.012 0.000
#> 37CC38B2-2C87-4ADD-B8C7-A0D2343448AD 3 0.5310 0.30317 0.000 0.004 0.512 0.392 0.092 0.000
#> 9D4E55F2-FCD1-4523-8879-44F95BC3DA35 6 0.1075 0.69837 0.000 0.000 0.000 0.000 0.048 0.952
#> A72B96C5-2ECE-463E-A6CC-4598901A9BEF 4 0.5200 0.33081 0.000 0.088 0.004 0.552 0.356 0.000
#> 7B7DBEA3-DF47-4051-8A58-548705A21035 4 0.4118 0.37126 0.000 0.352 0.000 0.628 0.020 0.000
#> 00E9CCE0-2367-4963-A72F-2A08B143B0B8 6 0.4203 0.52230 0.000 0.000 0.000 0.032 0.316 0.652
#> 46563983-2B05-4EB7-9E15-07487565158F 4 0.2905 0.53290 0.000 0.008 0.012 0.836 0.144 0.000
#> FDBD24ED-A293-4F84-A418-8AB531750E9A 2 0.4947 0.37581 0.000 0.596 0.000 0.000 0.088 0.316
#> 2437A516-5312-409E-8679-B85BB60530CD 1 0.0000 0.85713 1.000 0.000 0.000 0.000 0.000 0.000
#> F9135D0D-6447-4452-8EA8-98DEE4610226 4 0.4791 0.36964 0.000 0.048 0.004 0.564 0.384 0.000
#> DC75C731-6DBA-4DCA-B8B2-AF97DB11CEAC 6 0.3344 0.64687 0.000 0.044 0.000 0.000 0.152 0.804
#> A0A07F44-C51B-420C-92E8-65F464DB0442 3 0.6353 0.01157 0.000 0.000 0.400 0.312 0.276 0.012
#> A4967738-7FC2-4270-A149-56E459EDB875 4 0.6502 0.10896 0.000 0.152 0.000 0.408 0.392 0.048
#> 17E8321E-7265-486E-8EC8-A5EBB547892D 6 0.5629 0.21369 0.000 0.000 0.000 0.148 0.404 0.448
#> A9DA8022-CE84-4C1F-A483-C2EF6F085505 2 0.6084 0.43377 0.192 0.560 0.000 0.000 0.036 0.212
#> DB4D15E2-063B-4BDF-A410-F574B73509B9 4 0.3880 0.49906 0.000 0.028 0.024 0.772 0.176 0.000
#> B013FB96-A517-46EC-8877-4AE84C01AE27 6 0.2631 0.65345 0.000 0.000 0.000 0.000 0.180 0.820
#> 39BF9FE5-0385-44CD-A45E-29D432784BDE 2 0.4555 0.38248 0.000 0.628 0.008 0.328 0.036 0.000
#> 1CBCD09F-2824-4E99-B657-F9565E9C9372 4 0.3219 0.52075 0.000 0.020 0.000 0.820 0.148 0.012
#> 71F8A28D-077A-4A91-B56E-B035E4861E9C 6 0.5108 0.29949 0.000 0.000 0.000 0.080 0.436 0.484
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#> 79A4EA16-B871-4932-B1F4-169004233CBA 6 0.4051 0.05818 0.432 0.000 0.000 0.000 0.008 0.560
#> 1B75BBE2-56C5-4979-B6F3-2E79C7642057 4 0.3992 0.56353 0.000 0.180 0.000 0.748 0.072 0.000
#> 217CC90E-771C-4136-9F6E-BF1DA0555A15 3 0.4278 0.51787 0.000 0.000 0.632 0.336 0.032 0.000
#> CFD5C33B-C102-4F62-B34D-C178342CEB4D 6 0.4330 0.31551 0.332 0.000 0.000 0.000 0.036 0.632
#> 8B3B9337-038A-4385-AF58-D285A3706234 3 0.2300 0.78499 0.000 0.000 0.856 0.144 0.000 0.000
#> 5C811B7B-0457-448E-B170-7ABB4BB63CAB 1 0.6626 0.11260 0.408 0.136 0.000 0.068 0.388 0.000
#> 3C032234-C350-4170-B8F7-F8DE8269E713 6 0.0717 0.69723 0.000 0.016 0.000 0.000 0.008 0.976
#> 0915DDE6-5839-4705-8D9B-B01A6450FEB6 4 0.1429 0.57877 0.000 0.052 0.004 0.940 0.004 0.000
#> 981123DE-D55E-41D1-8850-1A41376F1DED 2 0.3088 0.61867 0.000 0.808 0.000 0.172 0.020 0.000
#> EFA7715F-AA27-4C5C-88B2-0C6B838DE496 2 0.6506 0.29777 0.000 0.524 0.128 0.008 0.280 0.060
#> 039D56DA-2740-4FAE-BEE7-AB7F5BBA8A20 6 0.3123 0.64822 0.040 0.072 0.000 0.004 0.024 0.860
#> 6BE57D47-2006-4FE6-A5AE-6954D0E60E96 4 0.5607 0.21919 0.000 0.004 0.316 0.532 0.148 0.000
#> 05127463-A69A-42B3-9635-575A08EB980A 4 0.4870 0.28455 0.000 0.000 0.008 0.612 0.320 0.060
#> 36F63B8A-5F8D-41AE-958F-8B142FEB1A3D 2 0.3386 0.62892 0.032 0.824 0.000 0.000 0.020 0.124
#> 671507DB-3949-4A41-9682-644CE8FED3D3 1 0.0458 0.85720 0.984 0.000 0.000 0.000 0.016 0.000
#> 6418884F-19D9-4101-A35C-6F1F43A4690A 2 0.2504 0.63997 0.000 0.856 0.000 0.004 0.136 0.004
#> FA17E3DC-118F-4CD8-A79B-236A3776CCA5 4 0.1483 0.56429 0.000 0.012 0.008 0.944 0.036 0.000
#> C3E23136-7190-4D08-991C-93AFACC48E8D 2 0.6700 0.23929 0.000 0.448 0.000 0.120 0.092 0.340
#> D8E7120B-A46C-4581-A4D5-B8C25857BD37 4 0.5721 0.42405 0.000 0.048 0.128 0.624 0.200 0.000
#> 534B9E41-B731-4461-ABEA-30096148A493 4 0.5032 0.45157 0.000 0.132 0.004 0.648 0.216 0.000
#> 1835A17A-8710-47C8-B5B3-986CFD50C8B8 4 0.2965 0.56732 0.000 0.072 0.000 0.848 0.080 0.000
#> 5B565B8A-68A0-42DA-9010-A7F00B638F7D 2 0.4519 0.61923 0.068 0.760 0.000 0.004 0.124 0.044
#> E01CA3E0-BEB0-46B7-BB7C-F5B16F966918 3 0.2507 0.77588 0.000 0.000 0.884 0.004 0.040 0.072
#> D182D919-C57F-4004-93DB-FB1723A82072 6 0.0603 0.69553 0.004 0.000 0.000 0.000 0.016 0.980
#> A52CC981-4203-4027-B978-383BFBEB5F75 5 0.5986 0.04255 0.000 0.096 0.308 0.052 0.544 0.000
#> 03C22FB8-0643-48FB-A09A-6119F722C09A 5 0.7132 0.13190 0.000 0.184 0.220 0.140 0.456 0.000
#> C4EC541D-8BEA-4B1D-8E7D-83B04E349944 6 0.0790 0.70103 0.000 0.000 0.000 0.000 0.032 0.968
#> BE4C9AE8-0B45-410A-BB06-746B10CDAAEC 6 0.5751 0.22527 0.000 0.000 0.000 0.180 0.348 0.472
#> 17CA0DC6-8FF2-4D03-ADF7-B12AC8C5DA44 1 0.0146 0.85719 0.996 0.000 0.000 0.000 0.004 0.000
#> BD351D39-883A-47E8-AF88-DB0C77A888C8 6 0.1594 0.68206 0.000 0.052 0.000 0.000 0.016 0.932
#> FBB65B75-A831-4616-8D6B-ADBA825A228D 6 0.2275 0.66526 0.008 0.000 0.008 0.000 0.096 0.888
#> 4EF663A1-721E-4417-89B4-F201C2C3901D 6 0.3606 0.60990 0.000 0.000 0.000 0.016 0.256 0.728
#> BD879832-E177-4FCA-B1EA-D1553518E700 2 0.3508 0.64870 0.000 0.828 0.000 0.088 0.024 0.060
#> B11EDD8F-C129-455E-AD2D-491F80F36A60 5 0.6474 -0.18743 0.008 0.384 0.108 0.052 0.448 0.000
#> C90142D8-F939-4FEA-BC48-073D2814F54E 6 0.4469 -0.10689 0.468 0.000 0.000 0.000 0.028 0.504
#> CDEC90EC-016B-4C68-82AA-7EE297188B03 6 0.0458 0.69956 0.000 0.000 0.000 0.000 0.016 0.984
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